ims accesspoint - november 2012

THE MAGAZINE OF IMS HEOR & REAL-WORLD EVIDENCE SOLUTIONS

Volume 3, Issue 5 • November 2012

AccessPointNews, views and insights from leading experts in HEOR and RWE

IMS HEALTH ECONOMICS AND OUTCOMES RESEARCHOUTCOMES - Issue 1 Page 1

Murray Aitken revealssavings of half atrillion dollars, whileoutcomes are improvedPage 50

Renée Arnold findsnew demands forHEOR models inAsian marketsPage 30

Phil McEwan showskey role of IMS COREDiabetes Model in HTA submissionsPage 37

Real-world evidenceaccelerates research

Rising to the uniquechallenges of oncology

Collaborating withstakeholders to enhance outcomes

IMS HEOR & REAL-WORLD EVIDENCE SOLUTIONS

Volume 3, Issue 5 • November 2012

AccessPointNews, views and insights from leading experts in HEOR and RWE

Understanding global trends in HTAHow to leverage HTA data for an optimal HEOR strategypage 42

Sample size in real-world researchWhy observational studies require special considerationpage 21

Measuring quality for improved outcomesShift in focus to quality metrics brings potential for enhanced relationshipspage 16

Seamless integration of patient-level dataIndustry and academic experts discuss the new opportunities

with IMS PharMetrics Plus™ - the largest US claims database

page 6

ACCESSPOINT • VOLUME 3 ISSUE 5 PAGE 1

CONTENTS

NEWS

2 HTA task force optimizes data

3 Diabetes Cohort supports access in France

4 IMS/CPRD target critical linkage in England

5 Largest US dataset expands outcomes research

INSIGHTS

6 REAL-WORLD EVIDENCE Sizing up IMS PharMetrics Plus™

11 EVIDENCE NEEDS IN ONCOLOGYDemanding new approaches

16 QUALITY MEASUREMENTImproving patient outcomes

21 OBSERVATIONAL METHODOLOGYDetermining correct sample size

26 COST-EFFECTIVENESS MODELING IN CANCEREnhancing accuracy and appeal

30 MODEL ADAPTATIONS IN ASIAEnsuring credibility and relevance

37 IMS CORE DIABETES MODELDriving new HTA insights

42 IMS SYMPOSIUM: HTA STRATEGYLearning from past submissions

50 HEALTHCARE SPENDINGSavings from responsible drug use

PROJECT FOCUS

58 ORPHAN DISEASE Achieving market access in Europe

60 GLAUCOMA Demonstrating cost-effectiveness in Asia

IMS HEOR & RWE SOLUTIONS OVERVIEW

62 ENABLING YOUR REAL-WORLD SUCCESS Solutions, locations and expertise

AccessPoint is published twice yearly by the IMS HEOR and Real-World Evidence Solutions team. VOLUME 3 ISSUE 5. PUBLISHED NOVEMBER 2012.

IMS HEALTH 210 Pentonville Road, London N1 9JY, UK Tel: +44 (0) 20 3075 4800 • www.imshealth.com/[email protected]

©2012 IMS Health Incorporated and its affiliates. All rights reserved.Trademarks are registered in the United States and in various other countries.

WELCOME

Welcome to the latest issue of ACCESSPOINT, a twice-yearlyresource of news, views and insights from IMS Health – offeringa current perspective on the changes and exciting advances thatare driving more and better health economics and outcomes research.

Today, more than ever, countries and healthcare systemsworldwide need to focus on strategies to raise efficiency, qualityand value against the real pressures of constrained budgets. We arebeginning to observe and forecast a significant shift towardsincentive-aligned programs (eg, pay-for-performance), rewardingoutcomes on the basis of quality metrics and signaling a new rolefor HEOR in establishing the benchmarks and measures that willdeliver the greatest benefits (page 16). We see policy makers,regulators, providers and payers increasingly dependent on real-world evidence (RWE) in optimizing spending and improvingpatient outcomes (page 50). And, globally, we see growing use ofHTAs, bringing fresh challenges for outcomes research (page 30)but also opportunities to leverage a growing body of RWE (page 42).

The expanding utility of RWE across the spectrum of healthcaredelivery continues to drive new levels of achievement in themethodologies and technologies that allow its more sophisticatedanalysis and management. At the same time, there is growingrecognition that commonality in measurements and increasedcollaboration will be key to achieving their potential.

With a global team of more than 200 experts in HEOR andRWE, IMS is committed to investing in advanced informatics andtechnical platforms to increase the coverage, depth and integrityof available data - through partnerships and proprietary tools thatleverage seamless integration of multiple datasets (page 4 & 5),new patient cohorts that bring deeper insights in support ofmarket access (page 3) and enhancements that maintain our coredata assets at the forefront of decision support (page 37). Ourrecent expansion of IMS LifeLink PharMetrics PlusTM has createdthe largest, most diverse integrated US claims database, informingthe complete patient journey, with tremendous new potential foroutcomes research (page 6).

As we look through the lens of 2013 to a future of ever greaterchallenges for healthcare, we see a marketplace moving closer togreater consensus and partnership - a marketplace that isincreasingly empowered to realize opportunities for advancinghealth through efficiency and quality improvements.

I hope you will enjoy this issue of ACCESSPOINT.

“We see a marketplace moving closerto greater consensus and partnership.”

Jon ResnickVICE PRESIDENT, HEOR & REAL-WORLD EVIDENCE SOLUTIONS, IMS [email protected]


ENCePP/EUnetHTA collaboration marks a major step forward in optimizing the use ofrelevant data for effectiveness assessments – and an exciting appointment for IMS.

HTA task force leads guideline development to optimize real-world data

A recent collaboration between two of Europe’sleading scientific networks - the European Networkof Centres for Pharmacoepidemiology andPharmacovigilance (ENCePP) and the Europeannetwork for Health Technology Assessment(EUnetHTA) - brings a new role for IMS Health inthe region’s evolving drug safety and HTAenvironment. The collaboration is targeting theimproved availability and best use of data relevantto effectiveness assessment.

The ENCePP is coordinated by the European Medicines Agency(EMA) and developed in collaboration with European expertsin the fields of pharmacoepidemiology and pharmacovigilance.The goal of the network is to further strengthen the post-authorization monitoring of medicinal products in Europeby facilitating the conduct of multi-center, independent, post-authorization studies focusing on safety and benefit:risk, usingavailable expertise and research experience across the region.

The EUnetHTA focuses on HTA in Europe to facilitate efficientuse of resources available for HTA, to create a sustainablesystem of HTA knowledge sharing and to promote good practicein HTA methods and processes.

IMS partners with the ENCePP in the development anddissemination of methodological and ethical standards for conducting pharmacoepidemiological studies andpharmacovigilance evaluations, reflecting its continueddedication to excellence in research. IMS LifeLink patient-level databases are part of the ENCePP Database of ResearchResources, an electronic index of EU research organizations andavailable data sources in pharmacoepidemiology andpharmacovigilance. The company adheres to the ENCePP Guideon Methodological Standards and Code of Conduct on promotingscientific independence and transparency.

Through the recent establishment of an HTA task force, theENCePP and EUnetHTA aim to lead the development ofmethodological guidelines on comparative effectivenessstudies. As part of this task force, IMS has reaffirmed itscommitment to advancing healthcare as an active scientificstakeholder in the safety/HTA arena.

For further information on ENCePP visit:

Organization:http://www.encepp.eu/

Methodological standards:http://www.encepp.eu/standards_and_guidances/index.html

Code of conduct:http://www.encepp.eu/code_of_conduct/index.html

Database listing:http://www.encepp.eu/encepp/resourcesDatabase.jsp

NEWS | HTA TASK FORCE

Visit us onlineIMS HEOR and Real-World Evidence Solutions has a new, enhanced website with improved access to information, including links to our onlinebibliography and previous issues of AccessPoint.Please visit us at www.imshealth.com/heor


IMS DIABETES COHORT | NEWS

Drug reform has brought new stipulations for monitoring real-world use in France,especially in diabetes. An innovative IMS patient database facilitates fulfillment of key requirements for more sustainable market access.

New Diabetes Cohort drives RWE for effective market access in France

IMS recently announced a new enhancement toits existing LifeLink Electronic Medical Records(EMR) offering in France with the launch of IMSLifeLink Diabetes Cohort. The move comes inresponse to the increasing demand for real-worldevidence in the country, following drug reformtriggered by the high-profile withdrawal of a number of anti-diabetes drugs. The provision of safety and appropriate-use data is nowcompulsory in France to ensure continued marketaccess, particularly for diabetes drugs.

RICH RESOURCE

Diabetes Cohort is a comprehensive and clinically rich resourceon diabetes patients and treatment strategies in France. Bycollecting detailed information from a representative sampleof patients with diabetes type 1 and type 2 and combiningelectronic case-report forms with EMRs for all medicalconsultations, the dataset can help manufacturers fulfil keyrequirements for post-registration studies in this country. Thecohort includes detail on patient profiles, therapeutic regimen,treatment duration, persistence and compliance, reasons fortreatment changes, and patient journey through primary andsecondary care.

FULLY VALIDATED AND GROWING

Based on the input of more than 200 physicians who regularlyprovide longitudinal information on more than 5,500 diabetespatients, Diabetes Cohort continues to grow. Validation againstthe Echantillon National Témoin Représentatif des personnesDiabétiques (ENTRED) 2007-2010 study, endorsed by the FrenchHaute Autorité de Santé (HAS), confirms the excellence andreliability of this study (Figure 1).

FUTURE DEVELOPMENTS

IMS continues to invest in enhancing our patient-level dataassets in Europe to meet the growing demand for real-worldevidence (RWE) and establish prerequisites for developing validand reliable databases.

For further information on the insights enabled by IMSDiabetes Cohort and the way in which it can help to fulfilRWE requirements in France, please email Nathalie Grandfils at [email protected]

FIGURE 1: COMPARISON BETWEEN ENTRED STUDY AND IMS DIABETES COHORT (DIABETES TYPE 2 PATIENTS)

Entred (2007) IMS Diabetes Cohort (2012) N=3,894 N=4,185

AgeMean 66 years 66.2 years < 45 years 3% 4% 45-54 years 13% 12% 55-64 years 28% 29% 65-74 years 31% 30% 75-84 years 21% 21% ≥ 85 years 4% 4%

Time from first diagnosis Mean 11 years 10 years0-4 years 29% 41%5-9 years 23% 22%10-19 years 28% 27%≥ 20 years 19% 10%

BMI ≥ 30 kg/m2

Patients not on insulin 40% 48%Patients on insulin 45% 55%

HbA1cMean 7.1% 7.2%Median 6.9% 6.9%≤ 6.5% 35.8% 33.4%6.5-7% 21.1% 21.0%7-8% 27.4% 24.1%> 8% 15.8% 16.5%

Blood Pressure Mean 134/77 mmHg 133.9/76.3 mmHg


At a time of increasing focus on outcomes-based measures in healthcare, a new IMS partnership is set to shed light on the entire patient journey in England.

IMS/CPRD agreement heralds critical linkageof GP and hospital patient data

The extension of an established relationshipbetween IMS and GPRD – the world’s largestdatabase of anonymized longitudinal GP medicalrecords – is paving the way for the unique linkageof patient-level primary and secondary care data inEngland. This will make it possible for the first timeever to capture the full patient pathway for a largepopulation in this country.

Since 2008, the partnership between IMS and GPRD hasenabled HEOR teams around the world to access significantlyincreased patient populations in England, for more powerful,robust analytic studies. The agreement to continue andextend the relationship follows the recent evolution of GPRDinto CPRD (Clinical Practice Research Datalink), and includesthe direct linking of IMS Hospital Treatment Insights (HTI)data with CPRD.

HOSPITAL TREATMENT INSIGHTS

Hospital Treatment Insights is a unique dataset launched in2012. Integrating IMS proprietary Hospital Pharmacy Audit(HPA) information with patient-level Hospital Episode Statistics(HES) outcome data, HTI enables detailed exploration of thedynamics between drug, patient and associated outcomeswithin the hospital environment in England.

Today, the number of patients within the dataset has reached1.2 million across 90 hospitals in England and it continuesto grow.

The longitudinal patient data, in the form of a retrospectivedataset, can be interrogated to answer critical questionsaround patient treatments and outcomes (Figure 1).

Going forward, studies based on the linkage of HTI and CPRDwill enable research across the spectrum of patient care inthe GP and hospital setting in England, supporting clinicalinnovation, stronger evidence of effectiveness and improvedhealth outcomes and public health.

For further information on the IMS/CPRD partnership orHospital Treatment Insights, please email Josh Hiller [email protected]

NEWS | PATIENT PATHWAY

Diagnosis Re-admissionDischarged Operation

Drug dispensed

Dosage titration

Change indrug regimen

Discharged Outpatient visit

• Which drugs are used for which diagnoses, andfor which patient profile?

• How big is theaddressable market?

• What are the treatment pathwaysand how do they vary?

• How often are patients re-admitted for the originaldiagnoses, or side effects?

• What procedures areassociated with thepatient pathways?

• How does the treatmentregimen change over time?

• How can we start tomeasure patient outcomes?

FIGURE 1: HTI PROVIDES UNDERSTANDING ACROSS THE PATIENT PATHWAY

Hospital Treatment Insights Example patient countsOncology: >75,000

Mental health: >150,000

Respiratory conditions: >240,000

Heart disease: >375,000


DATABASE EXPANSION | NEWS

Landmark IMS/HIC agreement creates industry’s largest integrated US health claimsdatabase to inform the improvement of healthcare efficiency.

Enhanced dataset dramatically expandscapabilities for outcomes research

In early September 2012, IMS announced anagreement with Health Intelligence Company (HIC)in the US, operating as Blue Health Intelligence,to leverage HIC’s secure healthcare claims databasein IMS solutions.

Offered as part of IMS LifeLink PharMetrics Plus™, thisenhanced dataset builds on the IMS health plan asset knownas PharMetrics, creating the largest, most diverse, integratedUS claims database available. It spans geographies, caresettings and industry types to bring significant gains overexisting data offerings in the market:

• Insight into health plan claims for more than 150 million US patients (or 1 in 3 Americans) - almost twice the size ofexisting claims databases

• Complete provider details for improved granularity

• Access to detailed information on benefit design (eg, co-paysand coinsurance amounts) and expanded details on inpatientstays (admission type, admitting diagnosis, discharge status)

• Patented HIPAA-compliant de-identification and linkagetechnology enabling integration with other IMS assets,including Electronic Medical Records, laboratory and hospitalinpatient data, as well as unique client data (eg, fromregistries)

KEY STEP TO IMPROVING HEALTHCARE EFFICIENCY

IMS and HIC see their agreement as an important step inproviding the HEOR community with increased capability forrigorous assessment of disease outcomes. Says Swati Abbott,CEO of Blue Health Intelligence, “We are very pleased to enterthis agreement with IMS and accelerate our mission to leveragehealthcare informatics to identify and drive gains in efficienciesand effective solutions across the healthcare system.”

A key feature of IMS PharMetrics Plus is the expansive coverageof more than 50% of the US population, with IMS tools allowingextensibility across data assets. Says Jon Resnick, VP HEOR andReal-World Evidence Solutions at IMS, “Too often, study needsrequire insight that spans outside a single data source. In thepast, this has required assumptions and projections that have

questioned the integrity of the output. With IMS PharMetricsPlus and IMS LifeLink we can leverage de-identification andencryption technology to connect disparate assets in anefficient manner.”

IMS continues to invest to support the increasing marketdemand for RWE. As Jon Resnick states, “The growing trend fortechnology assessments, CER and formation of bodies such asPCORI, is dramatically increasing the need for RWE solutionssuch as IMS PharMetrics Plus that provide insight into thequality of healthcare at a very granular level of detail.”

For further information on IMS PharMetrics Plus, themost comprehensive, integrated database available in the US market, please email Jovan Willford [email protected]

IMS PharMetrics Plus Example patient countsHypertension: >4.5 million

Asthma: >1.3 million

Breast cancer: >0.25 million

Counts are for 2011 only and include patients with both pharmacy and medical coverage

An inside perspective on IMS PharMetrics Plus

See our Insights feature on page 6 for an industry and academic expertview on the benefits and applicationsof IMS PharMetrics Plus.

INSIGHTS | REAL-WORLD EVIDENCE

The recent expansion of IMS LifeLink PharMetrics Plus™ has

created the industry’s most comprehensive US claims asset

(see News, page 5) with the capacity for seamless

integration with multiple patient-level datasets.

To explore its practical implications for advancing outcomes

research, we ask two leading experts from industry and

science for their take on its potential in enabling more

proactive management of real-world evidence requirements.

PAGE 6 IMS HEOR & REAL-WORLD EVIDENCE SOLUTIONS

Jovan Willford, MBA is Principal RWE Solutions, IMS [email protected]

Shibani M. Pokras, MPH is Director HEOR, IMS [email protected]

The interviewers

An inside perspective on IMS LifeLink PharMetrics Plus™How will the largest US integrated claims database make a difference to the world ofpharma and science? We investigate with two key users from industry and academia.

INTERVIEW WITH DAVID LAITINEN, MPHDavid Laitinen is Associate Director, Global HEOR at Abbott Laboratories. He previously worked forProcter & Gamble Pharmaceuticals and Pfizer and has more than 20 years experience in HEOR anddisease management. David holds an MPH in Epidemiology from the University of Minnesota Schoolof Public Health and is currently in his 6th year at Abbott. Here, he shares his views on the importanceof patient-level data and the opportunities enabled by PharMetrics Plus, in discussion with Jovan Willford,Principal RWE Solutions at IMS Health.

Jovan Willford: How do you view the importance of patient-level data, especially given thegrowing trend of comparative effectiveness research (CER)?

David Laitinen: This is a tough question because CER has been around for many years in someform, at least among epidemiologists and biostatisticians. However, the accessibility of the dataand supporting tools available now allow other scientists to perform these types of studies. Forexample, websites such as SAS and SUJI provide individuals who have a propensity for researchto do it themselves in a way that was not available 20 years ago.

JW: In terms of utility for your research, what do you see as challenges that can’t be met withexisting data today?

DL: We have 7 or 8 data resources in-house including medical claims databases, electronicmedical record (EMR) databases and survey databases. None of these provide the entirety ofwhat we need and each has strengths and weaknesses. Claims databases, for example, lackinformation like family history, diet, height and weight for obesity which is increasinglyimportant for our research. EMRs, on the other hand, don’t provide the entire health historyfor these patients and typically don’t include hospitalizations or cost information but they havesome of the patient characteristics that we lack in the claims data.

In the case of survey data, we are asking patients at a single point in time and hoping they canremember what has happened to them, what they were prescribed, whether they werecompliant and how they felt about the drug. This requires a lot of memory and recall on theirpart and it’s on a relatively small population. The strength of medical claims and EMRs is thepower of tens of millions of patients against an average of around two thousand patients in oursurvey data in-house.

REAL-WORLD EVIDENCE | INSIGHTS

New connections for RWE

continued on next page


“We have 7 or 8 data resources in-house and none of these provide the entirety of what we need.Each has strengths and weaknesses.”


JW: Given the challenges you’ve mentioned above, I imagine some of the planned benefits forPharMetrics Plus around the de-identification, encryption and linkages would be able to addresssome of these asset-specific gaps and allow you to maximize the value of each of your datasources in a more comprehensive way.

DL: Yes, I’m excited about PharMetrics Plus. The ability to take the core claims dataset and linkthat back to existing IMS datasets to obtain socio-demographic information, linkage to deathand mortality index, and linkages to things like oncology registries, will fill holes that wehaven’t been able to fill before. We have a large oncology franchise with several products indevelopment and when I try to address some of the questions they have, it’s often difficult dueto lack of staging information, for example, which we can’t get from claims or EMR data. So,linking to registries will fill a big gap.

Given what I understand about PharMetrics Plus, there is potential to dramatically streamlinemy data management. I have a relatively small shop with a handful of programmers and wecan’t adequately cover 7 or 8 assets, particularly when we’re only using an asset once or twice ayear. Anything that will allow me to have a core of data assets that will help us to become moreefficient and improve the integrity of our underlying research is a gain relative to the currentenvironment.

JW: In addition to the de-identification and linkage, what are the other benefits that interestyou with PharMetrics Plus? Some of the additional elements we consider unique are size,provider identification, geographic granularity and richness of benefit information.

DL: PharMetrics Plus is as close to a complete dataset as I’d want, relative to anything in themarket today. Size is certainly important to an extent but I think we’ve achieved scale. You have150 million patients in the US in PharMetrics Plus which is plenty, even for orphan productsand rare diseases. Outside of OMAP and some of the government solutions, private vendorswill have difficulty going much beyond this level. Thankfully, we are now at a scale wheresample, size and power are no longer really an issue. •


“The ability to take the core claims dataset and link that back to existing IMS datasets to obtainsocio-demographic information, linkage to death and mortality index, and linkages to things likeoncology registries, will fill holes that we haven’t been able to fill before.”

“Given what I understand about PharMetrics Plus, there is potential to dramatically streamlinemy data management. It is as close to a complete dataset as I’d want, relative to anything in themarket today.”


INTERVIEW WITH ERNST BERNDT, MS, PHDErnst Berndt is Louis E. Seley Professor in Applied Economics and Professor of Applied Economics at theMIT Sloan School of Management. He is also co-director of the Biomedical Enterprise Program and waspreviously director of the National Bureau of Economic Research Program on Technological Progress andProductivity Measurement. His recent research has focused on the changing dynamics of the healthcareindustries. Ernst holds an MS and a PhD from the University of Wisconsin. Here he shares his views onthe importance of patient-level data and the opportunities enabled by PharMetrics Plus, in discussion withShibani Pokras, Director HEOR at IMS Health.

Shibani Pokras: How do you view the importance of patient-level data, especially given thegrowing trend of comparative effectiveness research (CER)?

Ernst Berndt: The use of patient-level data is very critical because we want to be able to followpatients over time to track the dynamics of treatment and re-admission and longer term effects.Secondly, one of the things that CER is really grappling with is around different sub-populations, where treatments may be very effective for one sub-population but not for anotherand in order to determine that, you really need patient-level data. So, I think that both forPCORI-type purposes and more generally for CER, and cost-effectiveness research for thatmatter, it is really critical to have data for individuals that you can follow over time, that you canlink across pharmacy benefits, medical procedures, and possible lab test results, and so forth. Ithink it is a very important tool that will have tremendous value in future medical and costresearch and CER.

SP: In terms of utility for your research, what do you see as challenges that can’t be met withexisting data? What types of analyses have you tried to conduct, or have thought ofconducting, but couldn’t, given the current limitations of patient-level data available today?

EB: One of the things that we’d like to do is take a look at the effects of various medicines andprocedures on lab test results, be it for CD4 load factor issues or HbA1c tests for diabetes. Sofar, unless you work with specific hospital networks databases or provider databases, you cannotgain access to lab test data. And so, to the extent that IMS can merge the new PharMetrics Plusdata with lab data, it will be a really important leg up, particularly for very significant, costlydiseases like diabetes, where having lab test results is really valuable.

Having lab tests may also allow you to work backwards and ask: If I have certain test results canI then say that certain subpopulations are responding differentially? Can I use that to movetowards a more personalized medicine sort of treatment - which you might be able to do onceyou have a humongous database.

SP: Yes, at IMS we’re really excited about the size and ability to link several datasets withPharMetrics Plus. There are lots of pockets of local lab datasets that you can work with fromhospital or providers, but they are very small. IMS works with one of the largest US nationalproviders of lab data services so we anticipate that the overlap between this and our greatlyenlarged PharMetrics Plus database will be much bigger than datasets currently available today.

REAL-WORLD EVIDENCE | INSIGHTS


“For PCORI-type purposes and more generally for CER and cost-effectiveness research, it isreally critical to have data for individuals that you can follow over time and link across pharmacybenefits, medical procedures, possible lab test results, and so forth.”


What are the possibilities and opportunities with PharMetrics Plus relative to what you’re usingtoday? We’ve talked about lab data, but are there other areas where you see it might be usefulin your research?

EB: One area of research that’s been developed rather well for Medicare patients is the way inwhich treatments differ across geographic areas, ie, the Dartmouth Atlas project. It’s not beennearly as widely done for commercially-insured populations. Indeed, some of the preliminaryfindings are quite different for commercial vs. Medicare populations. We see considerably lessgeographic variability and I think with the PharMetrics Plus data that you have at the 3-digitzip code level and at the MSA level (Metropolitan Statistical Area) you’ll be able to look atgeographic variations in care for populations other than Medicare much more carefully. I wouldsee that as a real opportunity for important additional work on costs, outcomes and treatmentutilization at the detailed geographic level.

We know now that drug utilization varies much less than does utilization of certain medicalprocedures like C-sections and lower back pain treatments, but we still don’t have goodexplanations for this variability. By linking these procedures not only with very detailedgeographic data but also with provider networks and hospitals, you can explore this in muchgreater detail.

One of the trends in applied economic research today is figuring out new ways to integratedifferent databases and link them to each other. Having access to PharMetrics Plus would reallyfacilitate that. In the healthcare context, it’s particularly valuable because you have providernetworks attempting to constrain treatment variability by developing treatment protocols and sothere is much more that you can model and measure to see just how effective these attempts areto control costs.

SP: Where do you see the significantly enhanced sample size offered by PharMetrics Plushaving utility in your research?

EB: I’m now getting into the economics of personalized medicine and that gets you into smallsub-populations. For rather small population or orphan diseases, any sort of information ongeographic diversity at all is very difficult to obtain. In personalized medicine what you’d likebe able to say, for example, is “what percentage of patients on Herceptin have tested positive ona HER2 test?”, and by looking at historical retrospective claims data, “how do survival ratesdiffer based on those HER2 tests scores?” With a longitudinal claims database, and with somegenetic testing results from cancer registries, you really have a very rich possibility to look atlonger term outcomes for important diseases like breast cancer.

I’m very excited about this data in the long term, particularly the geographic detail and insightinto hospital stay, because that has been a bit of a black box so far. Keep me posted on theprogress made with PharMetrics Plus! •


“I’m very excited about this data in the long term, particularly the geographic detail and insightinto hospital stay, because that has been a bit of a black box so far.”

“With a longitudinal claims database and with some genetic testing results from cancer registries, you have a very rich possibility to look at longer-term outcomes for important diseases like breast cancer.”


EVIDENCE NEEDS IN ONCOLOGY | INSIGHTS

Karin Berger, MBA is Principal HEOR, IMS [email protected]

The author

Oncology growth drives new evidence needsOncology is one of the fastest growing sectors in

healthcare. With its rising incidence and a significant

number of new molecules in development across a range

of cancer indications, ensuring access to optimal

treatment is an increasing challenge.


INSIGHTS | EVIDENCE NEEDS IN ONCOLOGY

The special demands on cancer treatmentsThe current reality of healthcare suggests that payer/budget holder influence willcontinue to escalate, limiting physician prescribing autonomy and subsequently patientaccess to innovative medicines.

Oncology medications are amongst the most expensive specialty drugs available. With years ofresearch finally bearing fruit, an influx of innovative treatments for cancer, including newmolecular targeted therapies, along with developments in diagnostics, genomics andproteomics, have driven tremendous growth in this sector. As more treatment options becomeavailable and their costs continue to rise, there is increasing scrutiny of the value they bringand demand for proof of their benefits in terms of patient-relevant outcomes.

A range of access hurdles are already in use by payers/budget holders to curb physicianprescribing. At their heart is the goal of improving effectiveness and value in healthcare as away of balancing growing costs and increasingly limited resources. Equal and effective for alldiagnostics and treatments (including those for rare and orphan diseases), their use has becomeincreasingly applicable to drugs being developed for cancer. After many years away from thespotlight, new oncology treatments must now compete with technologies in other indications,in terms of the benefits they bring and the proof points required to support them. With everhigher levels of performance demanded in terms of key patient outcomes, the need forevidence of their effectiveness and cost-effectiveness, based on real-world data, is imperative.

OPTIMIZING DECISION-MAKING PROCESSES Playing a key role in the desire of healthcare systems to optimize decision-making processesare evidence-based medicine (EBM), health technology assessment (HTA) and comparativeeffectiveness research (CER).1,2While separate, these are critically linked and interdependent,with HTAs evaluating literature according to evidence-based criteria and CER leveragingHTA reports for analyses.

1. Evidence-based medicine

The principle article on EBM by David Sackett and colleagues3 gives the followingcomprehensive description: “EBM is the conscientious, explicit, and judicious use of currentbest evidence in making decisions about the care of individual patients. The practice of EBMmeans integrating individual clinical expertise with the best available external clinical evidencefrom systematic research”.

EBM has the goal of achieving better value and improving health outcomes for patients.However, cost containment in healthcare will not be assured. On the contrary, in most cases,EBM will probably reveal a better evidence base for more expensive therapeutic options.

Oncology growth drives new evidence needs


In the EU, the use of EBM is perhaps most apparent in Germany, where benefit/effectivenessdata form the basis of reimbursement decisions. Recent regulations in the country stipulatethat randomized controlled trials (RCTs) provide the highest level of evidence possible.4Outcome endpoints focus on: improved state of health (morbidity), shortening of diseaseduration, prolongation of life (mortality), decrease of adverse events, and improved quality oflife. The new benefit dossier which is statutory for drug reimbursement and pricing discussionshas a primary focus on informing therapeutic benefits compared to standard therapy oralternative therapy options.

2. Health technology assessment

HTA is used to give a high-quality scientific synthesis of the available evidence regardingclinical benefits, harms, economic consequences, and ethical or social issues of a therapeuticconcept or a health technology. HTAs are increasingly leveraged in markets around the worldas the basis for healthcare decision making. However, the results of this synthesis can often becontroversial or uncertain with respect to the availability of evidence.1

3. Comparative effectiveness research

The purpose of CER is to directly compare active treatments, generate information onpatients, caregivers, diagnostic and therapeutic methods during daily routine, and helpconsumers, caregivers and policy makers come to reasonable decisions concerning the bestmedical care for the individual patient.5,6 The concept of CER includes various researchmethods, observational research, RCTs and decision analysis to explore the evidence fordiagnostic tests or therapies.5 However, clinical evidence has become closely linked to healtheconomics. Therefore, CER has to consider both benefits and costs and estimate the remaininguncertainty.1,5

Within the context of CER, the informative value and significance of observational studiesand real-world data in comparison to RCTs is the subject of ongoing debate.5,7 Proposals havebeen put forward to explore in a scientifically rigorous manner the huge amount of availabledata from healthcare service and/or payer databases before starting costly RCTs. Evaluation ofroutine data in health service databases has thus far been challenging due to the limitations ofavailable datasets, particularly in terms of reported outcomes measures. However, withincreasing awareness of the need for RWE this may change in the future; already, keyadvancements, including sophisticated database linkage and integration, are opening up new possibilities.

UNIQUE CHALLENGES OF ONCOLOGYAs noted by Mulvey in 2006, oncology is more dependent on an evidence-based approach totreatment than perhaps any other medical specialty8. Yet, certainly more than most, its clinicalattributes brings particular challenges for demonstrating and understanding the value ofcompeting therapeutic interventions. The mainstays of treatment, for example, may often beeffective in halting tumor progression, reducing associated cancer pain, prolonging life andsometimes even curing the disease, but not without the risk of significant side effects9 – whichvary in frequency, duration and toxicity.


Going forward, as decision makers demand ever higher levels of performance for reimbursementand market access in oncology, the ability to generate and access RWE will be essential.



INSIGHTS | EVIDENCE NEEDS IN ONCOLOGY

Furthermore, many cancer drugs require combination with one or more other agents, withinthe context of intricate treatment protocols, adding to both the complexity as well as the costof therapy.

The use of multiple lines of treatment brings further complications and uncertainty for valueassessments in oncology, compounded by endemic off-label prescribing of approved drugs; inthe US, more than 50% of drug use in this area is estimated to be outside approvedindications10, often on the basis of unclear evidence of benefit.

Against this background is a powerful patient voice in oncology that has witnessed agroundswell of lobbying and media pressure for access to the latest medical innovations. This particularly implies a need to learn more about patients’ perception of their treatment forcancer, with a special focus on quality of life - one of the most relevant patient-relatedoutcomes in this area.

A key point too, is that many cancers are rare diseases, creating issues for proving an effectthrough double-blind RCTs which often demand higher patient numbers than is feasible.Ethical reasons, also, frequently stand against the realization of an RCT in oncology.

Thus, with a clinical profile that challenges best efforts to understand the relative benefits ofnew technologies, and an emotional attachment that increases the pressure for treatment accessand coverage, there is a need for healthcare providers, manufacturers and patient groups togallvanize action for data collection in real-life in order to generate the proof they need on theeffectiveness of alternative treatment options.

A KEY ROLE FOR RWE With many targeted therapies in development, expectations for progress in cancer treatmentsuccess are high among clinicians and patients. Data that is sufficient to fulfil both medical andpatient needs, with efficiency measured in terms of hard clinical endpoints, cannot feasibly becollected in oncology RCTs. Especially in this case, RWE has a key role to play in informingaspects of care, including patient demographics, clinical and patient-relevant outcomes, toxicityprofiles in real-life practice, patient treatment preferences, impact of off-label usage, etc, and toidentify the right patient groups and measure the benefits in these often very small patientpopulations. Going forward, as decision makers demand ever higher levels of performance forreimbursement and market access in oncology, the ability to generate and access RWE will be essential.

Oncology is more dependent on an evidence-based approach to treatment than perhaps any othermedical specialty.8 Yet, certainly more than most, its clinical attributes brings particular challengesfor demonstrating and understanding the value of competing therapeutic interventions.

With many targeted therapies in development, expectations for progress in cancer treatmentsuccess are high among clinicians and patients. RWE has a key role to play in informing aspects of care.



Achieving this goal will be contingent on:

• Connecting currently fragmented information through the use of enablingtechnologies and methodologies which allow the linkage and integration of multiplepatient-level datasets for deeper insights into patient care across the entire treatment journey.EMRs, health plan, claims and other healthcare databases have been used increasingly inrecent years as single datasets for generating RWE, but are currently not typically joinedacross service provision.

• Moving closer towards achieving data interoperability, at a national and ultimatelyinternational level, by leveraging alliances and technical platforms for the sharing of data.

• Increasing the focus on standardized approaches to data collection, privacy and evaluation.

• Engaging with stakeholders across the healthcare sector to facilitate the application,understanding and interpretation of RWE.

• Overcoming the difficulties of data generation by engendering a spirit of opencollaboration in data exchange.

While RCTs remain the cornerstone for demonstrating the efficacy of medical technologies,the key challenge for reimbursement and market access in oncology will be in developingapproaches that embrace the use of data from multiple sources and reduce the uncertainty forpayers and other decision makers in this sector. •

1Walley T. Translating comparative effectiveness research into clinical practice: The UK experience. Drugs, 2012; 72: 163-702 Drummond MF, Schwartz JS, Jonsson B, Luce BR, Neumann PJ, Siebert U, et al. Key principles for the improved conduct ofhealth technology assessments for resource allocation decisions. Int J Technol Assess Health Care, 2008; 24: 244-58; discussion 362-8

3 Sackett DL, Rosenberg WM, Gray JA, Haynes RB, Richardson WS. Evidence based medicine: What it is and what it isn't. BMJ,1996; 312: 71-2

4 Gesetz zur Neuordnung des Arzneimittelmarktes in der gesetzlichen Krankenversicherung (Arzneimittelmarktneuordnungsgesetz- AMNOG) vom 22. December, 2010. Bundesgesetzblatt, 2010; Teil 1 Nr. 67: 2262-77

5 «Sox HC, Goodman SN. The methods of comparative effectiveness research. Annu Rev Public Health, 2012; 33: 425-456« Tunis SR, Benner J, McClellan M. Comparative effectiveness research: Policy context, methods development and researchinfrastructure. Stat Med, 2010; 29: 1963-76

7 Greenfield S, Platt R. Can observational studies approximate RCTs? Value Health, 2012; 15: 215-68 Mulvey TM, Preserving evidence-based oncology: We can't jeopardize clinical trials. J Oncol Pract, 2006, Sept; 2(5): 2049 Lipscomb J, Gotay CC, Synder CF. Patient-reported outcomes in cancer: A review of recent research and policy initiatives. CACanc J Clin, 2007; 57:278-300

10 The off-label use of drugs in oncology: A position paper by the European Society for Medical Oncology (ESMO). Annals ofOncology, 2007, 18; 2:1923-25


A concerted focus on improving health outcomes is

increasing the use of pay-for-performance and other

programs to raise the quality of care. Opportunities exist

for industry to partner with stakeholders to develop and

implement quality measures that will derive the greatest

economic and clinical benefits.

INSIGHTS | QUALITY MEASUREMENT

Renée JG Arnold, PHARM D, RPHis Principal HEOR, IMS [email protected]

The author


QUALITY MEASUREMENT | INSIGHTS

Quality measurement brings new opportunitiesImproved health outcomes are one of the central tenets of the US Patient Protection andAffordable Health Care Act (PPACA). Health plans and insurance issuers are required toshow the effects of quality reporting, effective case management, care coordination andchronic disease management on this measure. For example, PPACA requires the creationof Accountable Care Organizations (ACOs) - voluntary groupings of healthcare providerswho are accountable for “quality, cost and overall care of the Medicare fee-for-service(FFS) beneficiaries assigned to it.”

An ACO will provide the bulk of beneficiaries’ primary care services, must have at least 5,000Medicare FFS beneficiaries assigned to it and, importantly, providers may benefit financially ifthey meet federal quality and efficiency thresholds. Thus, pay-for-performance (P4P) and otherquality improvement programs are becoming increasingly important to providers and insurersas these groups attempt to improve patient outcomes.

Many P4P programs are based on quality metrics established by groups such as the NationalCommittee for Quality Assurance (NCQA), Centers for Medicare and Medicaid Services(CMS) and URAC (Figure 1). Health insurance plans often develop their own, customizedstandards, typically using these metrics, for incentive programs to financially reward clinicianswho have demonstrated improved patient outcomes in disease-specific measures.

Enhancing stakeholder relationshipswith quality metrics programs

Group Standards

National Committee for Quality Assurance(NCQA)

Healthcare Effectiveness Data and InformationSet (HEDIS®)

Centers for Medicare and Medicaid Services(CMS)

• Physician Quality Reporting System (PQRS) • Nursing Home Value-Based Purchasing

Measures• Medicare Stars Measures

URAC Individual standards, such as Diabetes Long-Term Complications Event Rate

FIGURE 1: QUALITY METRICS THAT FORM THE BASIS OF MANY P4P PROGRAMS


These programs include, for example, mental health antidepressant medication management(eg, percentage of members aged 18 years and older, diagnosed with a new episode of majordepression and treated with antidepressant medication and who remained on an antidepressantmedication for at least 6 months); pharmacologic therapy for persistent asthma (eg, percentageof patients aged 5 through 50 years with a diagnosis of persistent asthma and at least onemedical encounter for asthma during the measurement year, who were prescribed long-termcontrol medication); or for coronary artery disease (CAD) (eg, percentage of patients with adiagnosis of CAD who were prescribed oral anti-platelet therapy).

PROCESS METRICS DOMINATE The majority of the measures are typically process metrics, such as percentage of patientsmeeting a certain criterion (eg, percentage with diabetes mellitus who had an HbA1c testperformed over a one-year period) rather than outcomes measures (eg, percentage of patientswho had a HbA1c test <8mg/dl over a one-year period). This is because process metrics areoften easier to measure (available as counts in medical claims data, for example) and less opento interpretation and confounding by factors that have nothing to do with programimplementation designed to positively influence the outcome. For example, if a health plandevelops a web-based dietary program to reduce HbA1c, there are multiple factors, bothmeasured and unmeasured, that could influence a more beneficial outcome in one patient thananother, eg, amount of exercise, family support, co-morbid conditions and plan incentives.

LEVERAGING QUALITY MEASUREMENTSBecause of the desire to positively influence patient experience, as well as enactment of thehealthcare reform legislation and its associated financial incentives, medical groups, ACOs,managed care organizations and Integrated Delivery Networks are very interested inimproving health outcomes. Pharmaceutical companies can leverage quality metrics with thesestakeholders (their customers) in a number of ways:

1. A consensus-based approach to evaluating the feasibility, reliability, validity, and usability ofquality performance measures

2. Development of care management programs around this stable of quality performancemeasures that positively influence health outcomes

3. Establishment of shared-risk programs whereby companies that cannot help lower costswhile improving health outcomes from use of their drugs, will subsequently reduce the costof these agents and reimburse the health plan for the lack of improved outcomes.

Each of these methods establishes pathways for companies to partner with their customers tohelp them in evaluating, measuring and implementing programs that will reward thesestakeholders under the terms of P4P environments.

1. Consensus-based approach: For this method, it is essential to use existing data toestablish a baseline of quality measures to be further explored, based on relevant therapeuticareas that reflect a company’s likely economic value proposition. In other words, aretrospective analysis should be used to establish quality measure benchmarks that willsupport customer (eg, health plan) targeting and segmentation and also identify areas ofgreatest opportunity for the company with their customers. Ultimately, such a program canserve as the basis for an ongoing partnership and collaboration with customers byencouraging stakeholders to share their data with the company so that the hypothesesgenerated with the proxy data can be tested using advanced analytic methods. In addition toidentifying appropriate quality metrics for a particular plan, such analytic methods can



support predictive models, which would identify customer programs that are more likely todeliver good health outcomes and allow the customer to target their programs moreeffectively.

2. Care management programs:This method engenders partnerships between a companyand its customers through use of wellness and disease management programs developed toaddress specific constituencies within a health plan’s populace. Such programs can be builtaround the benchmarks established by the consensus-based approach. The company can actas a strategic operational partner, jointly developing the programs and methods ofmeasuring outcomes in advance of program implementation to enable timely evaluationand modification of these programs. Indeed, the company can provide health informationtechnology (HIT) tools that will aid their stakeholders in compiling claims and paymentdata of participating providers, aggregating data from electronic medical records, identifyingpatient or group risk and opportunity areas, and providing clinical decision-making support.

3. Shared-risk programs:Through the establishment of shared-risk programs, ACOs, forexample, can benefit from a company’s vast knowledge of analytic database methods toproduce the reports necessary to comply with CMS reporting mandates, and thus enablingthe ACO to benefit monetarily from P4P programs. It is essential to efficiently link acustomer’s multiple data sources to be able to evaluate the effectiveness of these programsfrom a real-world evidence (RWE) perspective. Furthermore, the company can help theACO in establishing an appropriate incentive structure for participating providers aroundadherence to these quality metrics.

BASIS OF THE APPROACH IMS has partnered with pharmaceutical companies to help them understand the economicvalue proposition for their products and establish outcomes-based metrics for their patientpopulations. These can serve as a baseline for their performance and allow them tobenchmark vs. their peer set. Based on our experience, we recommend the followingapproach:

• Retrospective analysis using secondary patient-level data, such as IMS PharMetrics Plus, tobuild a RWE value proposition. The retrospective analysis allows the establishment ofbaseline quality measure benchmarks that will support customer (eg, health plan) targetingand segmentation and also identifies areas of greatest opportunity for the company withtheir customers.

• The establishment of an ongoing partnership and collaboration with customers byacquiring and integrating customer data for retrospective/prospective analytics. This allowsthe company to demonstrate the brand value proposition among the customer’s patientpopulation and establish new contracting models. It further provides a platform for qualitymeasure performance tracking to help the customer maximize financial incentives, whileoptimizing opportunities for the company.

The company can also offer programs designed to improve outcomes and measure theimpact of these programs. In addition, data can also be leveraged to support predictivemodels which would identify customer programs that are more likely to deliver good healthoutcomes. These models allow the customer to target their programs more effectively.

QUALITY MEASUREMENT | INSIGHTS




Step 1Definition

Step 2Development

Step 3Targeting

Step 4Implementation

Market definitionCreation of qualitybenchmarks

Economic evaluation

Segmentation

Segmentation appliedto patient-level data

Identification ofcustomers performingabove/below nationalbenchmarks

Identification of customers withpoor/strong economicoutcomes

Company buildscustomer partnership & negotiates for receipt of data

Integration of customer data forprospective RWA

Analysis of fullcustomer dataset

Data procurement

Metric finalization

Sample size estimation

Methodology agreement

FIGURE 2: FOUR-STEP PROCESS TO ESTABLISH PARTNERSHIPS

FOUR-STEP PROCESS The specific steps involved are shown in Figure 2 and principally focus on:

1. Defining the market and metrics to be measured

2. Establishing quality benchmarks and performing simultaneous economic analysis usingretrospective evaluation of real-world data around the metrics identified in Step 1thereby allowing identification of customer segments

3. Applying segmentation from Step 2 to patient-level data to build target files and identifycustomers performing above and below the outcomes benchmarks

4. Building a partnership with customers and negotiating for receipt of their data toperform real-world analytics using the full customer dataset

In these ways, companies can establish partnerships with their key customers, helping toidentify which of their P4P programs can provide the greatest economic benefit for thecustomer. This is based on effective profiling of its population, and establishing programs (egdisease management) around the company’s therapeutic areas that will support improvementsin the customer’s quality outcomes measurement and reporting.

While the post-reform environment asks healthcare stakeholders to share more of the qualityand cost-risk, it also offers aligned interests between pharmaceutical companies, payers andproviders. In this environment, patient satisfaction, treatment outcomes and total cost of carewill receive greater scrutiny and attention, implying a stronger, more relevant role for theindustry in medication adherence, population wellness and patient education than in previous years. •


Observational studies are increasingly valid for informing

the real-world use of a drug but have their own challenges

in design and execution that are different from RCTs.

Here we explore the critical issue of determining required

sample size and the key considerations for ensuring subject

numbers that will achieve the desired research goals.

Sonia Rojas Farreras, MSC is Statistician HEOR, IMS [email protected]

Núria Lara Surinach, MD, MSC is Principal HEOR, IMS [email protected]

Montse Roset Gamisans, BSC is Director HEOR, IMS [email protected]

OBSERVATIONAL METHODOLOGY | INSIGHTS

Sample size requirements inobservational studies

The authors

Considerations for the right calculation Sample size determination is defined as the mathematical process of deciding, before astudy begins, how many subjects should be studied1 to ensure that the number of patientsincluded will allow assessment of the desired objective(s).

Observational studies have certain characteristics that are quite distinct from randomizedcontrolled trials (RCTs), most of them impacting on sample size requirements:

• Address multiple & more general objectives rather than a specific hypothesis

• Need a sample size that ensures generalizability of findings to the population (external validity) in order to yield reliable results

• Require expected missing data & selection bias to be addressed in sample size

• Perform multiple comparisons requiring larger sample size

• Require more assumptions & larger sample size for subgroup analyses or modeling

• Owing to the absence of previous data, sample size can be re-estimated during the study, based on interim analysis

CALCULATING REQUIRED SAMPLE SIZE To calculate the sample size for an observational study there are various concepts which needto be defined, as shown in Figure 1.

Firstly, the overall objective of the observational study will determine its design and thenumber of patients to be included. A key step in calculating sample size is to first ask thequestion “What kind of statement do we want to be able to make from the results of thestudy?” Depending on the answer, different sample sizes will be required. The study designwill also determine the process for calculating the appropriate number of patients for inclusion.

Outcomes are the assessments that enable answers to the study questions which have beenraised to address the objectives. The nature of the outcomes (continuous, categorical, onepopulation, two populations, etc…) will influence the process to obtain the correct sample size.

The statistical analysis needs to be defined in the study protocol according to studyobjectives, design and outcomes. The statistical techniques to be used (paired data, multivariatemodel, covariance adjustment, etc) must also be taken into account when defining therequired sample size.

In addition to the general concepts defined above, there are some further specific parametersto be considered in the sample size determination process, such as level of precision, level ofconfidence, statistical power and degree of variability:

• Level of precision (LOP) corresponds to the exactitude in which the specific value orresult is estimated in the study sample, providing a confidence interval. The definition of theLOP depends on the study design: in a single cohort study it will be defined as the range ofthe confidence interval obtained in the estimation; in a study comparing two cohorts ofpatients, it will be defined through the difference the investigator wishes to obtain betweentwo study groups.


INSIGHTS | OBSERVATIONAL METHODOLOGY

Sample size requirements inobservational studies




• Level of confidence provides information about the confidence of the estimation. It isexpressed as a percentage and represents how often the true value of the outcome picks ananswer that lies within the confidence interval defined by the LOP.

• Statistical power corresponds to the probability of rejecting that there are statisticallysignificant differences between two groups, when differences exist. Statistical power can beonly defined when a specific test is defined, not when the need is to estimate a specificparameter (mean, proportion) with pre-defined precision. Any sample size can estimate theoutcome of a study; the problem is the statistical power that this sample size owns.

• Degree of variability will define the size of the sample to be examined since it refers tothe distribution of the attributes being measured in the population. The more heterogeneousa population, the larger the sample size required to obtain a given level of precision.

CONSIDERATIONS AND ADDITIONAL ADJUSTMENTS As noted earlier, many of the attributes that distinguish observational studies from RCTsdirectly impact requirements for sample size, specifically: the nature of the study objectives; theneed to be able to generalize findings to the broader population; the issue of missing data andselection bias; the use of sub-group analysis and monitoring; and potential for interim analysis.The impact of each of these elements is discussed in turn below.

1. General and multiple objectives

The objectives of observational studies are usually quite general, ie, to estimate the burden of aspecific disease, define the clinical management of a disease, assess patient-reported outcomes(PROs) in patients with a specific disease, assess the use of a particular treatment, etc.

Each general objective includes a list of specific objectives. For example, a study aimed atestimating the burden of a disease will need to assess different specific objectives, such as theclinical and therapeutic management of the disease, healthcare resource use, productivity loss,symptoms and quality of life. In this case, sample size calculation is based on one or more ofthese specific objectives, depending on the available information. If previous data exists related

FIGURE 1: REQUIRED SAMPLE SIZE IS DEPENDENT ON SEVERAL CONCEPTS

Study objective Study design

Statistical power Sample sizerequired

Outcomes

Significance/confidence level Precision

Statistical analysis


INSIGHTS | OBSERVATIONAL METHODOLOGY

to different study objectives, the required sample size should be considered for each aspect andthen the highest one selected. This approach will assure the sample size needed to assess all thestudy objectives or sub-objectives.

2. Generalizability of results

The generalizability of results to the broader population is related to the systematic error orbias. This occurs when the characteristics of the selected sample are different from those in thepopulation. Bias is related to the patient selection process but not to the sample sizecalculation. In this case, no matter how large the sample size, the results obtained will always bebiased and therefore the study will have no validity. As shown in Figure 2, a higher sample sizewill allow a lower variability, but not a higher generalizability.

3. Missing data & selection bias

Two common characteristics of observational studies are missing data and selection bias. In thereal world, data gaps appear in all observational studies and must therefore be taken intoaccount in estimating sample size. Once the sample size has been calculated, based on thestandard statistical approach, it must then be increased in order to cope with the expectedpercentage of missing data.

In observational studies comparing two or more groups, patients are not randomly assignedwith equal probability. Therefore, the probability of assignment can be related to patientbaseline characteristics, often resulting in non-comparable groups due to the absence ofhomogeneity. To address this, adjustments are applied in the statistical analysis. When completeadjusted analysis is applied, only those patients with available data in all variables will be usedin the analysis.

The use of propensity scores (PS), applied in the statistical analysis, is a sophisticated approachto solving this issue. The technique attempts to estimate the effect of a treatment, or otherinterventions, by accounting for the covariates that predict receiving the treatment.2 PSattempts to reduce the bias that could be found in an estimate of treatment effect from simplycomparing outcomes among patients from each group. The possibility of bias arises becausethe apparent difference between these two groups of patients may depend on characteristicsthat impact whether or not a patient received a given treatment, rather than being due to theeffect of the treatment per se.

FIGURE 2: HIGHER SAMPLE SIZE REDUCES VARIABILITY BUT DOES NOT INCREASE GENERALIZABILITY

Higher sample size will allow a lower variability...

...but not a highergeneralizability



1 Last JM (Ed.). A Dictionary of Epidemiology. Oxford: Oxford University Press, 19952 Yue LQ. Statistical and regulatory issues with the application of propensity score analysis to non-randomized medical deviceclinical studies. J Biopharm Stat. 2007; 17(1):1-13

3 Gurka MJ, Coffey CS, Gurka KK. Internal pilots for observational studies. Biom J. 2010 Oct; 52(5):590-603

In terms of sample size, the percentage of overlap in PS must be considered. The requiredsample size estimated using standard statistical techniques needs to represent the percentage ofoverlap regarding the final sample size.

In RCTs, the randomization enables unbiased estimation of treatment effects; for eachcovariate, randomization implies that treatment groups will be balanced on average, by the lawof large numbers. Unfortunately, for observational studies, the assignment of treatments is notrandomized. PS attempts to mimic randomization by creating a sample of patients whoreceived the treatment that is comparable on all observed covariates to a sample of patientswho did not receive the treatment.

4. Subgroup analysis & modeling

In observational studies, it is quite common to compare different subgroups of patientsaccording to site, country or clinical condition. Calculations of sample size need to take intoaccount these kinds of subgroup analyses to ensure the minimum sample size necessary forsuch comparisons. If modeling is planned, the required sample size must be increased in orderto obtain the minimum number of patients needed based on the characteristics of thedependent variable to be analyzed and the expected number of predictors.

5. Interim analysis

In the clinical trial setting, where allocation to treatment groups is pre-determined, interimanalysis allows achievement of the targeted power with the minimum sample of patientsrequired and without introducing substantial inflation of the type I error rate. It has not beendemonstrated whether the same general conclusions hold in observational studies, whereexposure-group membership cannot be controlled by the investigator.

In observational studies, different parameters considered in sample size calculation can be re-estimated at an interim stage, which helps to ensure optimal power for observational researchwith little inflation of the type I error associated with the final analysis.3 Interim analysis canprovide better estimation of assumptions (treatment/covariance distribution, estimatepropensity scores overlap, drop-out rates and missing data), appropriate assumptions, andpotential for revising study design (exclude treatment groups, differential recruitment intosmall groups, etc).

In long-term longitudinal studies or when the initial numbers used to estimate the sample sizeare unknown (no bibliography found or hypotheses pre-determined) sometimes there is theneed to have a sample size re-estimation. For example, plan to re-estimate the sample size after10% and 20% of patients enrolled. In this case any adjustment in p-values is not required.

CONCLUSIONEstimating sample size for observational studies requires careful consideration of several keyparameters, including study objective, design, population characteristics, outcomes, level ofprecision and errors. Various adjustments related to the planned statistical analysis must also betaken into account to ensure a subject cohort that will meet the desired study objectives. •


INSIGHTS | COST-EFFECTIVENESS MODELING

When demonstrating the value of new cancer treatments,

well-designed cost-effectiveness models are paramount to

achieve reimbursement. However, the trade-off between

clinical accuracy and simplicity of the model to increase

transparency is a slippery slope. It is no surprise that the

ability to model cost-effectiveness with greater accuracy,

relevance and decision-maker appeal is key in achieving

reimbursement – as the recent use of an 8-state model

illustrates in a hematological cancer.

Mark Lamotte, MD is Principal HEOR, IMS [email protected]

Stijn Vandekerckhove, MSC is Analyst HEOR, IMS [email protected]

The authors


COST-EFFECTIVENESS MODELING | INSIGHTS

A better cost-effectiveness model?From a model structure perspective, cost–effectiveness analysis in cancer treatments canbe quite straightforward: often times, modelers opt for a 3-health state structure to modeldisease progression - progression-free, progression, and death.

This is in line with the guidelines on good practice for decision analytic modeling outlined byWeinstein, et al, in 2003: “The structure of the model should be as simple as possible, whilecapturing underlying essentials of the disease process and interventions”.1 Indeed, a 3-statestructure is relatively intuitive and can be populated based on clinical trial data (given thenecessary assumptions and calculations).

However, clinicians may well disagree and find this structure unintuitive. It could be argued,for example, that disease progression and the treatment pathways are over-simplified. It was thissense that drove the underlying rationale for the model described below, aimed at achievingreimbursement for a novel treatment in a hematological cancer.

CLINICAL SETTING The cancer is characterized by a slow and abnormal build up of lymphocytes and istraditionally considered a chronic disease of the elderly. Patients with early-stage cancer have agood prognosis with a life expectancy of more than 10 years. However, for patients with moreadvanced or progressive disease, the overall survival is much shorter.

Clinical trials had been conducted to prove that patients with a worse prognosis could benefitfrom the new treatment. Up to this point, a single randomized controlled trial had beenpublished. Over a median observation period of 35.5 months, two first-line treatments werecompared. The new drug demonstrated a significantly better progression-free survival (PFS).

In real-life practice, patients who progress after first-line treatment can have a second course ofthe same treatment or become eligible for second and third treatment lines. This means thatthese additional lines of treatment will further postpone progression and as such mortality dueto the disease. In other words, additional quality-adjusted life years could be gained.

Other ways to model diseaseprogression in cancer treatments

The approach used aimed to provide a closer and country-specific reflection of the diseaseprogression without introducing unnecessary complexity and assumptions.


GATHERING RESOURCE USE FOR COSTS IN THE MODELThe resource-use data for costs for the most used treatment alternatives was not available in thetwo foreseen base case countries. Additionally, it was unclear which would be the most usedsecond- and third-line treatment alternatives in the countries of interest. Therefore, a Delphipanel with key opinion leaders was organized in each country. The purpose of this was to:

• Clarify the treatment path for this cancer in both countries• Confirm that the current standard of care for first-line treatment matched the comparator used in the trial

• Gather information on resource use per treatment (including those after first-line)

The findings from this expert panel confirmed that the chosen first-line comparator wasappropriate in both countries, but that the second-line and third-line treatments differedbetween them. Thus, in the model, it was necessary to use within the same structure other PFSand mortality data (as well as cost data) for the second and third lines of treatment.

AN ALTERNATIVE MODELING APPROACH Despite the need for this approach, the collected data combined with the results from theclinical trial provided sufficient information to populate a Markov model with 8 health states.This is depicted in the bubble diagram in Figure 1.

In a Markov model, the progression of patients is modeled over time by following them overthe health states. In fact, the treatment pathway determined the flow of arrows shown inFigure 1. A returning arrow indicated that patients could remain in the same health state.


INSIGHTS | COST-EFFECTIVENESS MODELING

First linetreatment

Second-linetreatment

Third-linetreatment

PFS after

treatment

PFS afterSecond-linetreatment

PFS afterthird-linetreatment

Death

BSC

-

FIGURE 1: STRUCTURE OF THE MARKOV MODEL


COST-EFFECTIVENESS MODELING | INSIGHTS

Consequently, the disease flow is modeled over lifetime as follows:

In the model, patients are assigned a probability for each arrow (transition probabilities). Forclarity of the diagram in Figure 1 the arrow for patients moving to the Death state from anystate due to progression or natural mortality has been omitted. However, in the model itself,the Death state is accessed from all states.

In contrast to a 3-health state model, where typically one treatment line is examined, theadditional states in this model had two important implications:

1. First of all, the Markov model was country-specific. In the 3-health state model, all data forevents occurring after progression are drawn from the multi-country clinical trial and do notanswer the local treatment pathways.

2. Secondly, quality of life during and after each treatment line was also modeled. As patientsprogressed to a second treatment line and PFS after second-line, the quality of life score waslower than PFS after first-line. Similarly, the quality of life of patients in PFS after third-linetreatment was lower than after first- and second-line.

MORE APPEALING, ACCURATE AND APPLICABLE The approach taken in this analysis aimed to provide a more appealing model from a clinicalperspective. Adherence to the natural flow of the disease was increased, while from a healtheconomic perspective costs could be assigned to patients in more health states for a higherdegree of accuracy.

From a payer perspective, this model can be appreciated for the same reasons. Additionally, theresults provided lifelong projections of the health effects. This clinical information wascomplementary to the trial data of 35.5 months and thus useful for the decision maker.

However, this model was not the first of its kind. The concept had already been used inoncology in health technology assessments2 and various other publications.3,4

Although the model was subject to a number of limitations, due to the Delphi panel data andtreatment data for second- and third-line options, these limitations are also present in a 3-statemodel. In this type of model, other assumptions will have to be made to project the treatmentoutcomes beyond the first-line treatment.

In summary, the approach used aimed to provide a closer and country-specific reflection of thedisease progression without introducing unnecessary complexity and assumptions. The resultsof it paid off with reimbursement being granted. Future research and submissions may furthervalidate and increase the awareness of this type of model. •

1 Weinstein MC, O’Brien B, Hornberger J, Jackson J, Johannesson M, McCabe C, Luce BR. Principles of good practice fordecision analytic modeling in health-care evaluation: Report of the ISPOR task force on good research practices – Modelingstudies. Value in Health, 2003;6(1):9-17

2 Takeda AL, Jones J, Loveman E, Tan SC, Clegg AJ. The clinical effectiveness and cost-effectiveness of gemcitabine for metastaticbreast cancer: A systematic review and economic evaluation. Health Technol Assess, 2007;11(19)

3 Campbell HE, Epstein D, Bloomfield D, Griffin S, Manca A, Yarnold J, Bliss J, Johnson L, Earl H, Poole C, Hiller L, Dunn J,Hopwood P, Barrett-Lee P, Ellis P, Cameron D, Harris AL, Gray AM, Sculpher MJ. The cost-effectiveness of adjuvantchemotherapy for early breast cancer: A comparison of no chemotherapy and first, second, and third generation regimens forpatients with differing prognoses. Eur J Cancer, 2011 Nov;47(17):2517-30

4 Lux MP, Hartmann M, Jackisch C, Raab G, Schneeweiss A, Possinger K, Oyee J, Harbeck N. Cost-utility analysis for advancedbreast cancer therapy in Germany: Results of the fulvestrant sequencing model. Breast Cancer Res Treat, 2009 Sep;117(2):305-17

1. First-line treatment2. PFS after first line3. Second-line treatment4. PFS after second line

5. Third-line treatment6. PFS after third line7. Best supportive care (no active treatment)8. Death


Growing emphasis on HTAs in countries across Asia

Pacific is driving new challenges for HEOR in translating

global models to the needs of local markets.

An IMS Workshop at the ISPOR 5th Annual Asia-Pacific

Conference in Taipei drew on input from health

authorities, industry and consultants in the region to

consider the evolving landscape.

INSIGHTS | MODEL ADAPTATIONS IN ASIA

Renée JG Arnold, PHARM D, RPH is Principal HEOR, IMS [email protected]

The author


MODEL ADAPTATIONS IN ASIA | INSIGHTS

Key considerations for Asia Pacific Although there is probably no specific differential issue for modeling in emerging versusdeveloped markets, the primary concern is availability of information and usually havingglobal models designed for settings with more data. When is it acceptable to use globaltrial data versus a requirement for local trial data? And what if there is no officialwillingness-to-pay threshold, but multiple implicit thresholds based on word-of-mouth,challenging direct interpretation of the results?

WHY MODEL? Taking a step back, it is helpful to first consider what we mean by health economic (HE)models. They are a visual framework used typically to establish the cost-effectiveness and/orbudget impact of a new therapy.1-11 Models are also useful in helping to determine appropriatehealth system (eg, hospital, region, country) reimbursement levels as well as in guiding thedevelopment of therapeutic guidelines and formulary decision making for populations andindividuals.

An example of a cost-effectiveness model could be where we assess whether it is cost-effectiveto drink coffee in the morning (Figure 1). In this model, we use the probability and cost ofdrinking coffee to stay awake, requiring an antacid (Gaviscon) due to gastric distress (from thecaffeine), or falling asleep in a meeting, losing one’s job and needing to advertise for a newone. Although somewhat “tongue-in-cheek”, the model serves to illustrate and quantify themultiple factors associated with decision pathways.

An example of an interactive budget impact model (BIM)4,5,10 is shown in Figure 2 for thedrug argatroban in heparin-induced thrombocytopenia (HIT). The model allows end users tochange assumptions, including probabilities and costs, to determine the impact on therapeuticoutcomes, eg, comparative cost or cost-effectiveness of two or more pathways.

Adapting global health economicmodels to emerging markets

The primary concern for modeling in emerging markets is availability of information and usuallyhaving global models designed for settings with more data.




FIGURE 1: DECISION-ANALYTIC MODEL FOR COFFEE DRINKING

FIGURE 2: SCREENSHOT FROM BUDGET IMPACT MODEL FOR ARGATROBAN

Yes

No

MorningCoffee?

Stay Awake80%

Doze Off20%

Stay Awake40%

Doze Off inMeeting60%

$2 + $3

$2

$2 + $300

$0

$300

Lose Job100%

Success!100%

Lose Job100%

Success!90%

Gaviscon10%

0.72

0.08

0.20

0.40

0.60



What is lacking in a number of emerging markets, not just those in Asia Pacific, is data. And, without the right data inputs, we have no chance of generating credible numbers. So, how can we fill in the gaps? Although none is ideal, there are multiple ways to approachthis, including:

• Use of global data

• Adaptation of global data to local circumstances

• Collection of local data, either pre-existing or de novo

HTA REQUIREMENTS IN ASIA PACIFICA number of countries have developed health technology assessment (HTA) guidelines thatmay require use of HE models (Figure 3). However, these guidelines have evolved withvarying levels of complexity and in different formats.

For example, in South Korea, Taiwan, Thailand and China, HTA is merged with policydevelopment. Although recommended, HTA assessment is not compulsory for formularyinclusion and reimbursement decision processes. Guideline development took place in threestages: development of HTA units (1994), promotion of HTA (1994) and merging HTA withpolicy development (1999). The responsible organization is the Ministry of Health and HTAsinvolve mainly new, high-technology products. Agents are assessed on safety, efficacy,effectiveness, cost-effectiveness and social impact, and local data is usually preferred.

Diversity in evaluation requirements exists among the few Asian jurisdictions that haveestablished HTA processes (Figure 4). Although their respective approaches to implementingHTA are different, a single top-down method or combination seems to be the norm. Lack ofrelevant expertise often restricts capacity and capability development.

FIGURE 3: FORMAL REQUIREMENT FOR ECONOMIC EVALUATION OF NEW TECHNOLOGIES AROUND THE WORLD (AS OF 2012)


On, Canada, 1996

US, 1994

Netherlands, 1998

Italy, 1998

Portugal, 1999

UK, 1999

S. Africa, 2004

Brazil, 2004

Norway, 2000

S. Korea, 2007

Malaysia, 2013

France, 1997

Denmark, 1997

Australia,1993

New Zealand, 1993

BC, Canada 1995

Sweden, 2002

Poland, 2003

1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013

Thailand, 2009

Taiwan, 2008



CHALLENGES OF HE MODELING IN CHINAIn China, the sorts of questions that health policy makers typically raise in assessing aninnovative health technology include:

• Were there Chinese patients in the international multi-center clinical trial as reported in the literature?

• What is the efficacy and effectiveness of the drug in the clinical trial (Phase II or III) inChina or in the Chinese population in Hong Kong, Singapore, Taiwan?

• Has a systematic review of the Chinese literature been completed?

• Has the drug been approved by FDA or NICE?

Although HE modeling has been widely applied internationally in the evaluation ofpharmaceuticals, it is seldom used in China due to lack of both internal and external countryresources. This includes lack of data, internal trained staff, capable contract researchorganizations (CROs) and trained academicians able to carry out the necessary evaluations.Nevertheless, modeling analysis is mentioned in the 2011 version of the China Guidelines forPharmacoeconomic Evaluations (Figure 5).

Policy makers and government agencies face challenges when outcomes data are adapted fromthe literature and cost data are collected from the local setting. Cost data can be collected inChina from: clinical trials; medical insurance claims data; case records in hospitals; healthstatistics and information data from health authorities (30 diseases); and field study andhousehold health surveys (every five years).

An example of an analysis completed in China to estimate factors that contribute to theeffectiveness of pneumococcal vaccines (PCVs) and the impact of Prevenar in the country is amodel to inform treatment patterns and understand the burden of pneumonia and meningitis

FIGURE 4: COMPARISON OF HTA GUIDELINES

Key Features

Type of guideline

Year

Purpose of thedocument

ICER

Total C/E

Threshold

Submissionguidelines

2008

Methods ofHTA & appraisal

Yes

Yes

GBP 20,000 - 30,000

PE guidelines

2011

Economicanalysis forpricing &reimbursement

Yes

Yes

None but WHOthresholdnoted

PE guidelines

2006

Guide toconduct,evaluate &report PEstudy

Yes

Yes

None

PE guidelines

2006

Not stated

Not stated

Not stated

<GDP percapita

Submissionguidelines

2008

For economicevaluation ofhealthtechnology

Yes

Yes

<3xGDP per capita (THB 300,000)

PE Guidelines

2012

Guidelines forPE analysis

Yes

Yes

None

UK China Taiwan SouthKorea Thailand Malaysia



caused by streptococcus pneumoniae. This analysis used a systematic literature review as theprimary data source, supplemented by local collection of epidemiological data.

Although a field study might have been preferable to inform the model, there are manyhurdles to this approach in China. These include: the low diagnostic rate of invasivepneumococcal disease (IPD); overuse or misuse of antibiotics leading to low isolate rates; lackof microbiological laboratory facilities to perform serotyping; lack of a surveillance system forstreptococcus pneumoniae infection; the fact that PCV belongs to second category vaccines inChina (thereby requiring out-of-pocket payment); and PCV having a very low coverage rate.

RECOMMENDATIONS FOR COUNTRY ADAPTATIONIn adapting a global HE model to a particular country it is important to consider the policyenvironment, whether the model will meet local requirements, and whether it will reflect localdrug price and direct/indirect cost, clinical practice, disease progression, mortality and resourceutilization data. It is essential to use evidence-based principles for data inputs (avoiding reliancesolely on expert opinion for cost data) as well as utilities from other, representative countries iflocal data are not available. Obstacles that exist for adapting models from global to localinclude:

• Lack of solid data, especially local utility data and cost data (real hospitalization cost andreimbursement cost)

• Absence of information about local treatment patterns

Ensuring credibility and relevance

What innovative solutions can assure that local adaptation will be credible and applicable? Themodel should be validated/accepted by local key opinion leaders (KOLs) in the local language.Being able to model local practice, using local treatment guidelines/clinical practices, is helpfuland local cost and clinical data should be employed.

Guideline 6: Modeling Analysis

Introduction

6.1 Decision Tree Models

6.1.1 Model hypothesis

6.1.2 Model structure

6.1.3 Source of parameters

6.2 Econometric models

6.2.1 Total cost estimation & impact factor analysis

6.2.2 ICER estimation

6.2.3 Net bene�t framework

FIGURE 5: CHINA GUIDELINES FOR PHARMACOECONOMIC EVALUATIONS 2011




Lessons learned from experience in adapting global models to emerging markets underscorethe importance of:

• Creating as sophisticated a model as country level, budget and timeframe will allow, takinginto consideration:

• Country level: Relative complexity of relevant PE/HTA guidelines

• Budget: Consider using local labor?

• Timeframe: Prepare KOLs in advance

• Collecting local literature (both in English and translate from local language if not a nativespeaker) about practice patterns in country of interest

• Retrieving and translating international disease treatment guidelines, if available

• Applying local cost sources (depending on model perspective: country, region, largehospital, local KOLs)

• For BIMs, using local market access (market share) figures for the baseline (often availablefrom the sponsor)

Above all, success will be contingent on developing a model that is as sophisticated as is necessaryto include all relevant components and pathways, using local, credible data whenever available,but also taking into consideration the level of sophistication of the audience and KOLs. •

This article draws on debate from the IMS Workshop “Issues in adapting global health economicmodels to emerging markets: A conversation with health authorities, pharmaceutical industry andconsultants in Asia Pacific” held during the ISPOR 5th Asia-Pacific Conference in Taipei, September,2012 to consider issues around HTA development in emerging Asia-Pacific markets and engender dialogamongst the various stakeholders in the region. Leaders: Dr Renée JG Arnold (IMS Health & MountSinai School of Medicine, NY), Dr KKC Lee (Monash University, Malaysia), Dr J Xuan (Pfizer, NY,Fudan University, Shanghai, & University of Florida) and Dr S Hu (Fudan University & ShanghaiBureau of Health).

• See Project Focus on page 60 for a further example of cost-effectiveness modeling in Asia Pacific.

1 Annemans L. Budget Impact Analysis. In: Pharmacoeconomics: From theory to practice, ed. R Arnold, pp. 109-18. Boca Raton: CRC Press (Taylor &Francis Group LLC), 2010

2 Arnold R. Cost-effectiveness analyses throughout the drug development life cycle. In: Burger’s Medicinal Chemistry, Drug Discovery and Development,ed. D Abraham. Hoboken, NJ: John Wiley & Sons, 2010

3 Arnold R, Frishman W. Health economic considerations in cardiovascular drug utilization. In: Cardiovascular Pharmacotherapeutics, ed. W Frishman, DSica. Minneapolis: Cardiotext Publishing, 2011

4 Arnold R, Kim R, Zhou Y, Tang B. Budgetary impact of heparin-induced thrombocytopenia with thrombosis and treatment with the direct thrombininhibitor Argatroban (P401E). Presented at the ASHP 39th Midyear Clinical Meeting, Orlando, FL, 2004

5 Arnold R, Kim R, Zhou Y, Tang B. Temporal effect of argatroban administration on cost of treatment of heparin-induced thrombocytopenia. Presented atthe Annual Meeting of the American College of Clinical Pharmacy, Dallas, Texas, 2004

6 Arnold R, Pettit K, DiCesare J, Canafax D, Lewis R, Kaniecki D. Application of Medicare databases to a theoretical renal transplant Markov model. ClinicalTher, 1996; 18:28

7 Arnold R, Pettit K, DiCesare J, Fastenau J, Kaniecki D. Prospective economic evaluation in a Phase IIIb renal transplant clinical trial. Value in Health, 1998; 1:368 Arnold RJ. Cost-effectiveness analysis: Should it be required for drug registration and beyond? Drug Discov Today, 2007; 12:960-59 Arnold RJ, Ekins S. Time for cooperation in health economics among the modelling community. Pharmacoeconomics, 2010; 28: 609-1310Arnold RJ, Kim R, Tang B. The cost-effectiveness of argatroban treatment in heparin-induced thrombocytopenia: The effect of early versus delayedtreatment. Cardiol Rev, 2006; 14:7-13

11Bree RL, Arnold RJ, Pettit KG, Kaniecki DJ, O'Haeri C, LaFrance ND, Toaff AL. Use of a decision-analytic model to support the use of a new oral UScontrast agent in patients with abdominal pain. Acad Radiol, 2001; 8:234-42

IMS CORE DIABETES MODEL | INSIGHTS

Proving rigor and market relevance is increasingly

important in diabetes modeling. Building on its record

of robust validation, the IMS CORE Diabetes Model

continues to demonstrate expanded applications that

underscore the importance of more insightful HTA analyses.

Understanding the importance ofmore insightful HTA submissions

Phil McEwan, PHDis an independent researcher with IMS HEOR, IMS [email protected]

David Grant, MBA is Senior Principal HEOR, IMS [email protected]

The authors



INSIGHTS | IMS CORE DIABETES MODEL

Opportunities for the IMS CORE Diabetes ModelThe relevance of the adage 'garbage in, garbage out' is well understood by diseasemodelers and those undertaking a health technology assessment (HTA). In HTAsubmission guidelines, it is common to find considerable emphasis on justifying datainput values as well as the choice of modeling approach and assumptions applied to long-term projections. The latter is particularly important in models with a lifetime perspectiveand presents both challenges and opportunities for the IMS CORE Diabetes Model (CDM).

THE CHALLENGESDespite adherence to the principles of Occam's Razor, diabetes is a complex disease and,therefore, the CDM is a complex model. Furthermore, the choice of sub-populations tomodel, the product positioning, choice of comparators, choice of underlying equations anddisease progression parameters all contribute additional complexity. It is thus unsurprising that,despite input values derived from systematic reviews and the presentation of extensivesensitivity analysis, uncertainty exists around the credibility of diabetes-specific HTAsubmissions.

To some extent, such skepticism is understandable; it is rare to find an economic evaluation ofa novel diabetes drug that isn't cost-effective. Consequently, when reviewing a new technologysubmission that utilizes the CDM, concerns regarding the validity of the model and its clinicalpredictions are inevitable.

THE OPPORTUNITIESIMS understands diabetes and how to model the disease. This is particularly relevant todaybecause the value argument associated with novel therapeutic technologies for themanagement of diabetes is primarily linked to their side-effect profile; specifically, theavoidance of hypoglycemia and weight gain. This is noteworthy given the preoccupation inevaluations of diabetes models with assessing their validity in terms of cardiovascular (CV) riskprediction.

The CDM has presented at all six Mount Hood Challenge meetings where comparison of CVrisk prediction is a central feature. Furthermore, the recent validation work of the CDMVersion 8.5 has focused on validating the CDM to contemporary outcomes trials in diabetes.

Applying UKPDS equations

To be clear, CDM's predictive validity to contemporary outcomes studies remains veryfavorable, despite the use of the UKPDS risk and outcomes equations1,2,3 which have beensubject to criticism regarding their ongoing relevance.4,5 Querying the justification forcontinued use of equations derived from UKPDS data to drive CV endpoints within theCDM, is both a common and relevant question.

Understanding the importance ofmore insightful HTA submissions



While the UKPDS equations are subject to criticism they also have been the most studied,being externally validated in nine published articles. The choice of validating population isimportant as studies that use split sample, or v-fold cross-validation are likely to show superiorpredictive capabilities compared to equations validated to very different populations.6 Morerecently, published equations such as the DCS7, DARTS8 or Freemantle9 equations havedemonstrated improved external validation although they have been validated only once.

Studies reporting a lack of fit, particularly those associated with the UKPDS equations, mainlyreport poor calibration with a tendency to overestimate risk. When interpreting the results ofrisk equation validation studies, it is important to distinguish between assessing thegeneralizability of a risk equation and the generalizability of a diabetes model that uses thatequation. This is because disease models typically calibrate and adjust risk estimates. TheCDM, for example, adjusts risk prediction to accommodate use of aspirin, antihypertensiveand lipid-lowering therapy. This is a form of evidence-based calibration designed toacknowledge that different levels of CV risk factor management within a population willimpact upon overall CV risk.

Tracking mortality

As part of the recent CDM validation work, the decline in early mortality shown in UKclinical practice10 and attributed to more effective control of lipids, blood glucose and bloodpressure, has been shown to be reproducible within the CDM using only the model's clinicalmanagement settings (via the percentage prescribed aspirin, statins and ACE inhibitors). Thismortality validation demonstrates how time dependent risk equation calibration enables theCDM to track declining levels of mortality in male and female type 2 diabetes patients.Matching levels of risk factor management is an important component in setting up eachvalidation simulation and explains how the CDM is able to consistently predict both relativeand absolute diabetes-specific events.

MAINTAINING VALIDITY AND EXPANDING APPLICATIONSIMS has made a substantial investment over the last year in both validating Version 8.5 of theCDM and in supporting non product-specific applications of the model. These applicationshave a particular relevance to HTA as they demonstrate functional relationship within themodel and the importance of insightful analysis.

1. Quantifying relationships

Figure 1 is taken from recent work presented at the 48th European Association for the Studyof Diabetes Meeting in Berlin, quantifying the relationship between HbA1c reduction, non-severe hypoglycemia risk reduction and quality-adjusted life expectancy (QALE). For a rangeof published disutilities associated with non-severe hypoglycemia events (NSHE), the graphshows that the equivalent HbA1c reduction required to generate the same QALE difference isbetween 0.33% and 1.84%. This is because incrementally, even relatively large HbA1cdifferences have only a modest impact on future CV event rates; furthermore, the compoundeffect of discounting these future events is substantial. Contrast this with the impact ofhypoglycemia, which is therapy-specific and therefore its effects begin to accrue immediatelywithin the model; the impact of discounting on the impact of hypoglycemia is far lesspronounced. A similar finding occurs when modeling the avoidance of weight gain.


2. Analyzing linked input/output patient-level data

Another illustration of the capabilities of CDM 8.5 is the analysis of linked input/outputpatient-level data (PLD) to provide insight into the inner workings of the model. For example,Figure 2 shows simulated cost-effectiveness pairs output by the CDM linked to input baselineHbA1c and stratified into groups. In this example, high baseline HbA1c is more cost-effectivebecause simulated patients escalate to the next line of therapy sooner, thereby incurring lessadditional cost.

These examples illustrate how the CDM's functionality can be used to provide insight intowhat drives cost-effectiveness. Technology assessments that take this approach are more likelyto present compelling cases that have face validity. It is those who best understand the model,and how it works, who are most likely to achieve this. •


INSIGHTS | IMS CORE DIABETES MODEL

FIGURE 1: ILLUSTRATING THE HBA1C REDUCTIONREQUIRED TO ACHIEVE EQUAL LIFETIMEQALE BENEFIT VERSUS THE AVOIDANCEOF 1 NON-SEVERE HYPOGLYCEMIAEPISODE PER YEAR FOR A RANGE OFPUBLISHED HYPOGLYCEMIA-RELATED DISUTILITIES.

2

1.8

1.6

1.4

1.2

1

0.8

0.6

0.4

0.2

0-0.02 -0.015 -0.01 -0.005 0

Disutility for 1 NSHE

HbA1

c redu

ction (%

)

FIGURE 2: COST-EFFECTIVENESS PLANE SHOWINGINCREMENTAL COSTS AND QALYS FOR ASECOND-LINE DPP4 COMPARED TO ASULPHONYLUREA STRATIFIED BYBASELINE HBA1C

8000

6000

4000

2000

0

-2000

-4000

-0.4 0.0 0.4 0.8

Delta QALY

Delta

Cost

0.60.2-0.2



1 Stevens RJ, Kothari V, Adler AI, Stratton IM. United Kingdom Prospective Diabetes Study (UKPDS) Group. The UKPDS riskengine: A model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clinical Science (Lond), 2001 Dec;101(6):671-9

2 Kothari V, Stevens RJ, Adler AI, Stratton IM, Manley SE, Neil HA, et al. UKPDS 60: Risk of stroke in type 2 diabetes estimated by theUK Prospective Diabetes Study risk engine. Stroke, 2002 Jul;33(7): 1776-81

3 Clarke PM, Gray AM, Briggs A, Farmer AJ, Fenn P, Stevens RJ, et al. A model to estimate the lifetime health outcomes of patientswith type 2 diabetes: The United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68). Diabetologia,2004 Oct;47(10): 1747-59

4 Kengne AP, Patel A, Colagiuri S, Heller S, Hamet P, Marre M, et al. The Framingham and UK Prospective Diabetes Study (UKPDS)risk equations do not reliably estimate the probability of cardiovascular events in a large ethnically diverse sample of patients withdiabetes: The Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation (ADVANCE) Study.Diabetologia, 2010 May;53(5): 821-31

5 van Dieren S, Peelen LM, Nothlings U, van der Schouw YT, Rutten GEHM, Spijkerman AMW, et al. External validation of the UKProspective Diabetes Study (UKPDS) risk engine in patients with type 2 diabetes. Diabetologia, 2011 Feb;54(2): 264-70

6 Chamnan P, Simmons RK, Sharp SJ, Griffin SJ, Wareham NJ. Cardiovascular risk assessment scores for people with diabetes: A systematic review. Diabetologia, 2009 Oct;52(10): 2001-14

7 Elley CR, Robinson E, Kenealy T, Bramley D, Drury PL. Derivation and validation of a new cardiovascular risk score for people withtype 2 diabetes: The New Zealand diabetes cohort study. Diabetes Care, 2010 Jun;33(6):1347-52

8 Donnan PT, Donnelly L, New JP, Morris AD. Derivation and validation of a prediction score for major coronary heart disease eventsin a U.K. type 2 diabetic population. Diabetes Care, 2006 Jun;29(6): 1231-6

9 Davis WA, Knuiman MW, Davis TME. An Australian cardiovascular risk equation for type 2 diabetes:the Fremantle Diabetes Study.Intern Med J, 2010 Apr;40(4): 286-92

10Charlton J, Latinovic R, Gulliford MC. Explaining the decline in early mortality in men and women with type 2 diabetes: A population-based cohort study. Diabetes Care, 2008 Sep;31(9): 1761-6

New version of CORE Diabetes Model releasedAffirming a strong commitment to ensuring thatthe IMS CORE Diabetes Model remains the leadingnon-product-specific, subscription-based model ofdiabetes mellitus and its complications, IMS hasrecently introduced the new Version 8.5. Therelease follows a rigorous update of the modelduring 2012.

KEY ENHANCEMENTS While retaining the solid epidemiological data sources (eg, UKProspective Diabetes Study) and leading-edge modelingmethodologies (eg, non-parametric bootstrapping) of previousversions, the CORE Diabetes Model V8.5 includes a number ofspecific data updates and user-friendly enhancements:

1. The ability to share simulation results online with teamusers, reducing duplication of effort. Previously, it was onlypossible to share simulation input settings (eg, a diseasemanagement setting).

2. The display of cumulative incidence plots over time for eachdiabetes complication in the model. This provides a goodindication of patient complication status during progressionthrough the simulation. The new feature is displayed alongsidethe standard survival curve output, which is carried over fromprevious versions.

3. Adjustments to the default physiological parameterprogression approaches (eg, HbA1c), in response to feedbackfrom HTA groups and cross-validation with UK Prospective

Diabetes Model-based tools. The updated HbA1c progressionapproach is more conservative, in terms of between-treatmentdifferences, which may lead to greater acceptance of the modelby payers.

4. A review of default clinical settings, including recent datafrom the US Renal Data System for renal replacement modalitiesand subsequent survival. The CDC WONDER online database hasbeen queried to inform the latest non-diabetes-specificmortality rates. In all complication sub-models, post-eventmortality risks are appropriately adjusted for competing risks,leading to greater overall life expectancy and more accuratecause of death attribution in the model.

5. Better granularity of BMI-associated quality of lifedisutilities from the CODE-2 study is enabled; this enhancementwill be particularly relevant for cost-utility analyses wheredifferences in BMI between two treatments is a keydifferentiator of the clinical profile.

In line with the latest updates, the CDM User Guide has beenfully revised to include all the model’s features up to andincluding V8.5. This can be downloaded as a PDF file from theCDM Help Center accessed from the main menu.

IMS is confident that the changes and new features of themodel and its output will enhance diabetes economic modelingwork. Feedback is welcomed as users become familiar with thelatest update.

For further information on the V8.5 update of the IMSCORE Diabetes Model, please email: David Grant at [email protected]

REFERENCESfor article, pages 37-40


As the use of HTAs for determining market access continues

to grow worldwide, an IMS Symposium at the ISPOR 17th

Annual International Meeting explored the value of

monitoring data on past submissions to inform and improve

the development of future indications and compounds.

Analysis of recent HTA decisions in oncology offered some

intriguing insights.

INSIGHTS | IMS SYMPOSIUM

Michael Nelson, PHARM D is Senior Principal HEOR, IMS [email protected]

Won Chan Lee, PHD is Principal HEOR, IMS [email protected]

The authors


IMS SYMPOSIUM | INSIGHTS

Lessons for an optimal HEOR strategy

Today, there are a growing number of health technology assessment (HTA) agencies incountries around the world, some more prominent and systematic in their approach, butall undertaking some form of HTA evaluation. Their approval and reimbursement decisionsvary considerably, even when reviewing similar efficacy, safety and economic data, witha consequent variable impact on a drug’s market access profile. And the situationcontinues to evolve; even countries with more mature processes are still searching forthe optimal HTA model.

For health economics and outcomes researchers, the diversity and heterogeneity of HTAagencies create enormous challenges, including constantly changing evidence requirements,inconsistent availability of appropriate data, variability in methodology and interpretation ofthat data, and ultimately demonstrating product value across disparate markets. Real-worldevidence, for example, is one data element that is used increasingly in decision making but todifferent degrees in different countries (Figure 1).

Learning from global trends in HTA


FIGURE 1: COUNTRIES ARE AT DIFFERENT STAGES IN ADOPTING RWE IN DECISION MAKING

Geographical examples Label Price Access Use

Observational data used in post‐launchdecision making

AMNOG ruling speci�es that prices areto be re-assessed post‐launch

Drug utilization studies speci�ed as acondition of market access

Phase IV studies potentially in�uencingregional payer decisions

Value‐based pricing consultation willpotentially re-assess price post‐launch

Private payer attention to PCORI,private CER, FDAMA Sec 114

ApplicationLimited applicationNo application


The extent to which HTA outcomes and guidance vary across countries can be seen in thecase of sunitinib for renal cell carcinoma (RCC), which received very different ratings fromfour independent European HTA agencies focused on cost-effectiveness. As shown in Figure 2,the rulings ranged from full (conditional) reimbursement by the TLV (Tand-ochLakemedelsformansverket) in Sweden to complete denial of access in Scotland followingreview by the SMC (Scottish Medicines Consortium), reflecting their very differentperceptions of the drug’s “value”.

GROWING NEED FOR A NEW UNDERSTANDING Understanding the diverse international HTA environment and the nature of individualagency decisions is thus of growing importance for the development of an optimal healtheconomic research strategy. The challenge is being able to use the prior learnings andincorporate them as far as possible into the clinical trial program to ensure a positive earlyreimbursement decision from each of the respective HTA bodies. For manufacturersdeveloping a market access strategy, this requires answers to a number of key questions:

• Did the HTA agency evaluate similar products previously – either a clinical comparator orpricing comparators? If so:

• Did they interpret the clinical data in the same way?

• What were the key drivers of negative/positive appraisal decisions?

• How likely is it that an appraisal by one HTA will impact appraisals by others?

• How can the learnings from previous appraisals be used strategically to maximize thelikelihood of a positive reimbursement decision?

• If the new product is first-in-class, is there another disease state that could be used as aproxy to assess how HTA agencies are likely to appraise it?

FIGURE 2: HTA DECISIONS ON SUNITINIB VARIED WIDELY IN FOUR EUROPEAN COUNTRIES

SMC(Scotland)

HTA rationale

HTAdecision

Impact on marketaccess

NICE (UK)

CVZ(Netherlands)

TLV(Sweden)

Insufficientinformation on overallsurvival, and lack ofrobust economic

argument

Benefit in overallsurvival vs INF-α aloneonly for patients whohave not been treatedwith other products

Benefit unclear due tolack of experience.

Concerns over unknownlong-term side effects

High need for treatmentsand orphan drug, even though

cost-effectiveness has ahigh level of uncertainty

Should not be used

Should only be usedin patient

population whereeffectiveness isdemonstrated

Should be restrictedfor use when othertreatments have

failed

Recommended forinclusion forconditional

reimbursement

Access denied byScottish healthauthorities

Restricted to first-lineuse only by PCTs

Restricted to patientswho have failed on INF-α or ILK-2

Fully reimbursed aslabel indication

(conditional – to bereassessed when moredata is available)


SMC: Scottish Medicines Consortium NICE: National Institute for Health and Clinical Excellence CVZ: College Voor Zorgverzekeringen TLV: Tand-och Lakemedelsformansverket

Relative market access:

✘ No access ✔✔ Full access

✘ ✔ ✔ ✔✔


To address these issues, there is a clear need within HEOR to monitor the influence of theinformation being provided to HTA agencies and leverage it for the improvement of researchover time. This knowledge can serve as the basis for:

1. Discussions with clinical development to determine the design of the Phase II/IIIprogram in relation to: the comparator or comparators that are likely to be faced inreimbursement decisions across multiple jurisdictions, the endpoints (primary and secondary)and effect size.

2. Discussions with commercial functions to inform decisions around pricing, launchsequencing and the access level that is likely to be achieved, for forecasting and otherfunctional purposes.

3. Formulary and reimbursement submissions as the basis for designing economicevaluations, modeling assumptions, cross-country communication and pricing negotiations.

SYSTEMATIC APPROACH TO DATA COLLECTION The optimal approach to collecting HTA data will vary by organization size, level ofsophistication and the involvement of local affiliates. Responsibility may be assigned to a globalHEOR group, local operating companies or an external vendor, depending on availability ofmanpower, resources and budget. In terms of timing, monitoring ideally should begin prior tothe design of pivotal Phase II/III studies by engaging payers or advisors at HTA agencies earlyin development to establish key endpoints, continually appraise them, and update as decisionsare made.

The collection process should give consideration to HTA reviews on competitors but also dataon the new compound itself which can serve as an important internal resource for applyingkey learnings across the organization’s portfolio of products. Addressing future launches and/orindications that may be planned for the same compound is also important. The ultimate goalshould be a systematic process that includes: regular updates as decisions are made by HTAagencies; details of discussions leading to decisions (where available); and provision for trackingfuture reviews to anticipate competitor activity.

A key issue from a company perspective is to ensure that the collection of data is combinedwith systematic analysis – ie, understanding not only the decision that was reached but also therationale or discussions around it – to facilitate forward planning for the type of challenges thecompound might face in reimbursement.

The value of systematic collection lies in the immediate access to the data which is sharedacross all functional areas within the company and resonates in a way that can influencedecisions at key points during R&D. Done well, such a process can enable:

• Avoidance of potential pitfalls in future submissions and a better understanding of datarequirements in each market

• Identification of possible data gaps within the clinical trial program and other targetedHEOR projects

• Understanding of the methodologies (accepted/rejected) around health economic modelsthat should be implemented early on or at the time of submission

• Development of more innovative tactics in price negotiations with theHTA/reimbursement authorities by learning from competitor successes and failures




APPLICATION OF HTA DATA IN ONCOLOGY Oncology is one key therapy area which has attracted increasing attention from payers inrecent years following major scientific breakthroughs and strong growth in sales. Based onHTA decisions, product uptake rates vary from one country to another. Analysis ofsubmissions in six countries (France, Spain, England, Scotland, Australia and Canada) between2004 and 2010 shows that approval rates across four different tumor types (lung, breast, RCCand hematological malignancies) averaged close to 60%.

For RCC only, the approval rate was 32% - the lowest among the four cancers. From acountry perspective, France had the highest percent of HTA approvals for RCC whileAustralia and Canada had the highest number of rejections. This variation among countriesremains true for other tumor types.

Also evident is the growing number of submissions for lung cancer in recent years. In general,positive reviews have also been on the rise, reflecting advancements in treatment for thisdisease. However, in breast cancer, where medical progress has been more pronounced, themarket is somewhat crowded compared to other tumor types. Thus, while the number ofsubmissions is also similarly on the rise, there is no clear trend regarding positive and negativeapprovals by these agencies. However, in the case of hematological malignancies, almost allsubmissions were approved, reflecting the unmet needs in this area.

STUDY METHODOLOGY These findings are drawn from an IMS analysis of historic HTA data collected through acombination of stakeholder interviews by in-market IMS experts, and secondary desk researchacross HTA agency and national reimbursement websites. This approach enabled a wide rangeof data to be collected, including local information, record information, molecular order,regulatory and reimbursement status, HTA decision (clinical and economic assessments),pricing, and risk-sharing/commercial agreements.

FIGURE 3: DATA EXTRACTION FORM - HTA DETAILS: CLINICAL ASSESSMENT SECTION



In total, more than 100 fields were captured and used to populate a searchable Excel-basedtool, with hyperlinks to key documents where available. An example of a data extraction formis shown in Figure 3.

One of the main utilities of the database is the multiplicity of data points, enabling a detailedunderstanding of recent trends in HTA decisions and their implications for market access indifferent markets. Some examples of the insights it has been possible to glean from the datasetare outlined below.

1. Drivers of negative outcomes

Most HTA rejections in RCC were the result of unacceptable economic analysis, specifically“unacceptable ICERs” - a label that is open to wide interpretation. More granular analysis of HTAdecisions for RCC in Australia, Canada and the UK shows that most of the ICERs exceeded a$50K willingness-to-pay threshold, resulting in a negative outcome (Figure 4). However, in two caseswhere the ICER was also above this level (Australia, UK) sunitinib was approved for use. Why?

• Australia: In 2007, the manufacturer of sunitinib approached the Australian PBAC threetimes for feedback. On the first occasion, there was no economic model included in thedossier so the submission was rejected outright. The second time, the cost/utility for adverseevents had been omitted and progression-free survival proxied for overall survival. Finally,on the third attempt, the manufacturer was able to address all the previous requests and,through price negotiations, reduce the ICER to an acceptable level and ultimately gainaccess in the country.

• UK: Also in 2007, several submissions were made for sunitinib in the UK, where potentialdenial of access to the drug had triggered a public outcry. Through the ensuing negotiationprocess, NICE began to rethink its framework for determining reimbursement, particularlyin relation to the issue of prolonging life for patients with few therapy options. Sunitinibwas eventually approved for a subset of patients where the drug had proven survival benefitscompared to immunotherapy. NICE has since been giving more consideration to equityissues and the possibility of applying some form of weighted threshold for different diseases.

FIGURE 4: MOST HTA ICERS EXCEEDED $50K WILLINGNESS TO PAY WITH A NEGATIVE OUTCOME

UK

Sunitinib

UK

Sorafenib

$200k

$175k

$150k

$125k

$100k

$75k

$50k

$25k

UK

EverolimusUK

UK UKUKUK

AUS

Temsirolimus

AUS

N

AUS

AUS

CAN


Manufacturer estimate of cost/QALY (US dollars)

Impact of manufacturer ICER* values on HTA outcomes

Negative HTA outcome Positive HTA outcome** * All values represent ICERsthat were reported bymanufacturers in the HTAreports

** Positive HTA decision =recommendation for full orsubset of licensed indication



2. Impact of survival data

A further interesting and very relevant analysis is the degree to which overall survival (OS)versus progression-free survival (PFS) has impacted HTA decisions. On the basis of the datacollected, there is no discernible salient association between OS and PFS and HTA impact inthis particular tumor type. However, it is of note that all trials using PFS without OS wererejected.

3. ICER differentials

Historical HTA data for RCC reveals significant disparities between the ICER estimatessubmitted by manufacturers and those developed by the agencies themselves, due largely todifferent assumptions in economic models. This signals potentially protracted negotiations toadjust the numbers during a period when time is of the essence and pricing discussions wouldalso be ongoing. The key message here is that by ensuring robust data and a reasonable pricebehind the ICER, there is an opportunity for manufacturers to reduce the negotiation periodfrom approval to reimbursement/access, and by doing so, also minimize the opportunity costsof time lost during that process.

TAKE-HOME LEARNINGS What we can see from the data is that every situation is different; the lessons vary from onetumor type to another and each approach must be tailored. Knowledge of emergingcomparators, products in the pipeline and other developments that will shape the future mustalso be drawn into the mix. However, purely based on the historic data, there are some keylessons to be learned in this area:

• Robust evidence from well-designed trials: Clinical trials must be flawlessly designedand trial data used appropriately when submitting to HTA agencies, especially in terms ofthe patient group, line of therapy, outcome measures, and increasingly in the case of RCC,as well as in other tumor types, treatment sequencing and use in combination.

• ICERs: Price negotiations are increasingly based on ICERs. The ICER is essentially ananalytical tool employed by HTA agencies for price reductions, re-negotiations andcommercial arrangements. The fact than an ICER is high does not necessarily implyautomatic rejection. Even if a drug is deemed not cost-effective, there are other vehicles bywhich manufacturers can gain access in those countries.

• Value-based pricing and risk-sharing agreements: In 2014 the UK will move intovalue-based pricing, signaling the need for even greater consideration of volume/pricetrade-offs between sub-populations, and a premium price versus broader indications and alower price; in Italy and a number of other countries, the use of risk-sharing andcommercial arrangements is growing. Future performance is thus becoming just as relevantas data from clinical trials for price and volume negotiations - and increasing theimportance of RWE. Value-based pricing will be more common in future and payermanagement is likely to increase, despite the low budget impact of RCC.

• Country implications: In Canada, the UK and Australia, few products were reimbursedand approved, especially in RCC. The access opportunity for new products in RCC will be similar to current therapies in the near future, with the greatest payer hurdles inthese countries.



• Survival endpoints: All trials using PFS without OS as an endpoint were rejected. Trialendpoints must be carefully chosen: traditionally challenging markets demand both OS andPFS; in other markets, PFS may be sufficient for access and uptake as second-linepositioning. Purely basing trials on OS is lengthy, difficult and financially burdensome butthese are areas that need to be considered more carefully.

• Quality of life: Although most quality of life data favored the products under assessment,most corresponding HTA outcomes were negative (apart from France). It is possible that iffuture products for RCC are able to avoid or reduce certain toxicities, especially Grade 3/4adverse events that require suspension of treatment and therefore risk compromisingefficacy, then those products are likely to be heralded by these agencies.

FUTURE IMPACT OF HTA ON NEW PRODUCTS HTA decisions are becoming increasingly influential in the success of new compounds asmore countries establish HTAs and require formal submission, impacting not only HEOR butall functional areas involved in the drug development process, including pricing, market accessand government affairs. As HTA engagements grow ever more complex, with greater emphasison RWE, a coherent strategy is imperative to maximize the likelihood of positivereimbursement.

In order to manage the evolving trends, monitoring HTA data has a valid and growing role toplay in informing HEOR and reimbursement strategies. There is a greater need not only forreal-time access to HTA data in different countries but also for the intelligence behind thedecisions and the way they are made so that this can be leveraged in internal decision making.With a growing number of NMEs in the pipeline there will be more and more HTAengagements and a greater number to consider for their impact on development. At a time ofimmense constraints on resources, finding the most efficient and expeditious way of doing thiswill be key. •

This article summarizes presentations from the IMS Symposium “International HTA trends andimplications for an optimal health economic research strategy”, held during the ISPOR 17th AnnualInternational Meeting in Washington, DC, in June 2012. Chair: Michael Nelson, Pharm D, SeniorPrincipal HEOR, IMS Health. Speakers: Kasem S. Akhras, Pharm D, Director Global HEOR andTherapeutic Area Leader CNS, Takeda Pharmaceuticals Inc, and Won Chan Lee, PhD, PrincipalHEOR, IMS Heath.

IMS acknowledges the support and guidance of Pfizer Inc, in the development of the HTA databasedescribed in this article.



INSIGHTS | HEALTHCARE SPENDING

More responsible use of medicine by health system

stakeholders and stronger alignment of their capabilities,

resources and activities, could avoid half a trillion dollars in

annual global health spending, according to a new study

from the IMS Institute for Healthcare Informatics.

This represents 8 percent of total annual health

expenditures worldwide.

Lyudmila Gorokhovich, MSC is Project Leader, IMS Institute for Healthcare Informatics [email protected]

Murray Aitken, MBA is Executive Director, IMS Institute for Healthcare [email protected]

The authors


HEALTHCARE SPENDING | INSIGHTS

A half trillion dollar opportunity Improving the responsible use of medicines is an urgent health policy priority. Bettermedicine use can improve health outcomes and alter the way health systems operate tooptimize overall spending. At a time of intensified efforts to contain medicine spendingand overall health system costs, it should be a critical goal for any health system leader.

• Medicines improve quality of life and survival in the context of the larger healthsystem: Medicines have had an unprecedented positive effect on health, leading to reducedmortality and improved quality of life. They are a key component of efficient health systems,both as a means of prevention and avoidance of costlier, more severe conditions.Unfortunately, medicines are often overused, misused or underused, leading to avoidableand costly adverse events and inferior health outcomes.

• Higher volumes of pharmaceuticals are being consumed globally: The increasedavailability of necessary medicines along with expanded access by patients have drivenpharmaceutical volume growth in recent years. This volume growth is the primary cause ofthe rise in overall pharmaceutical costs across most countries. Injectable and infusionformulations have been leading volume growth over the past ten years with an 85%increase, followed by orals and other formulations, including nasals (based on IMS Midasdata for 70 countries).

• Healthcare policy is often focused on managing elements of a health system inisolation: Medicine policy that focuses on access or cost containment through pricereduction is often separated from the health system’s ability to ensure appropriate use ofmedicines. Approaches such as health technology assessments attempt to link the value ofmedicines in the context of the broader health system by measuring indicators such asavoidable hospitalizations. However, these assessments are in limited use worldwide.

SIX PRIMARY LEVERS CAN IMPROVE THE RESPONSIBLE USE OF MEDICINES WORLDWIDE Our research identified six levers of opportunity which any health system leader can apply toimprove the responsible use of medicines and contain overall health system costs:

1. Non-adherence to medicines occurs when patients do not take their medicinesappropriately or at all. This results in avoidable and costly complications which are oftenmore expensive than medicines and worsen health outcomes. This research includes fivefocus disease areas: hypertension, hypercholesterolemia, asthma, diabetes type 2 andcongestive heart failure.

The responsible use of medicines

At a time of intensified efforts to contain medicine spending and overall health system costs,improving the responsible use of medicines should be a critical goal for any health system leader.




2. Untimely or delayed medicine use occurs when patients do not obtain medicines at theright time, leading to avoidable, relatively expensive complications downstream. In thisresearch, the focus is on hepatitis B and C and diabetes type 2 as examples.

3. Antibiotic misuse/overuse occurs due to the perception by many that antibiotics cantreat any kind of infection. Their availability and low price combined with thismisperception drives misuse and overuse. Misuse results in downstream avoidable coststhrough hospitalizations and more expensive treatment.

4. Medication errors occur along the following processes: Prescribing, preparing anddispensing, administration and monitoring. Within each process, errors by stakeholders resultin avoidable hospitalizations and additional medicine use.

5. Suboptimal generics use occurs if there is an unexploited opportunity to save costs dueto greater use of safe, low-cost generics in the unprotected market. This opportunitydepends on price and volume differences between off-patent and never protectedmedicines. The mix of these medicines can be adjusted to reduce health system costs,provided health outcomes are not undermined.

6. Mismanaged polypharmacy occurs when there is limited oversight by healthcareprofessionals of patients taking multiple medicines concurrently. The risk of costly andadverse events increases with age, particularly when patients are more than 60 years old andwhen patients take more than five medicines concurrently.

SECONDARY LEVERS In addition, we have identified three secondary levers of opportunity which apply moreselectively in some countries:

1. Supply disruptions through medicine shortages and substandard medicines.Medicine shortages occur when suppliers are unable to meet the demand for medicines,causing a disruption in patients’ ability to use the right medicines at the right time.Substandard medicines refer to counterfeits, falsified, and/or spurious medicines that do notwork appropriately in patients and/or delay quality treatment, potentially leading to adversedrug events.

2. Excessive use of expensive therapies occurs when costly medicines are provided topatients with limited or no consideration for their likelihood of improving health outcomes.This lever is more relevant in countries with increasing access to innovative and expensivetherapies in disease areas such as oncology. In this context, it is increasingly important toensure that expensive medicines are not provided to patients who will not respond or areineligible.

3. Medicine abuse of prescriptions occurs when legal medicines are taken by patients for apurpose different from their intended prescription use. Patients also abuse over-the-countermedicines through overdose and/or addiction. In these situations, patients are not taking theright medicines, contributing to avoidable adverse events and costs.

HALF A TRILLION DOLLARS OF ANNUAL COSTS CAN BE AVOIDEDOur research estimates that approximately $500 billion in avoidable costs, or about 8% ofannual total health expenditure worldwide, could have been realized in 2011 throughoptimized use of medicines (Figure 1).



These figures were derived from a global modeling analysis based on best available data from186 countries. The model assumes that health outcomes will be at minimum maintained orimproved. Factors considered for country variation in the analysis include demographics, non-communicable disease risk factors, healthcare access, health system infrastructure and medicineintensity, including antibiotic use in the system and availability of new chemical entities.

With cost containment a key concern of health ministers, the primary focus of thisopportunity analysis is on cost avoidance. The opportunity should be assessed in the context ofoptimizing overall healthcare and reallocating avoidable costs to address other healthcareneeds. The estimates shown are likely to be understated since some of the analysis focused on alimited number of disease areas.

This global quantification effort is intended to trigger a meaningful discussion not on theexact figures but rather on how to assess the impact of responsible medicine use.

HEALTH SYSTEM LEADERS CAN LEVERAGE EXISTING, PRAGMATIC EVIDENCEAll healthcare stakeholders in the private and public sectors can implement recommendationsleveraging existing, pragmatic evidence from around the world. The IMS Institute identifiedmore than 50 recommendations for health ministers. Most apply to a number of private andpublic sector stakeholders also, including payers, prescribers, dispensers, patients and the industry.More than a third of the recommendations require a collaborative, multi-stakeholder approach.

Each recommendation has been assessed for time to impact (maximum being five years), level ofhealth outcome improvement and initial spending level. Prioritized recommendations with thelowest time to impact, greatest health outcome improvement and lowest spending level, primarilyrely on dispensers, policymakers/payers and a collaborative effort among all stakeholders.

The five key recommendations that health system leaders can implement to drive improvement are:

1. Strengthen the role of pharmacists in medicines management

2. Invest in medical audits focused on elderly patients

3. Implement mandatory reporting of antibiotic use

4. Encourage a “no blame” culture towards error reporting

5. Support targeted disease management programs for prevalent non-communicable diseases

BREAKDOWN OF THE HALF A TRILLION DOLLARS

Avoidable cost opportunity (Billions USD)

Improve adherence$269 $62 $54 $42 $30

$18

TOTAL$475

Ensure timelymedicine use

Optimizeantibiotic

use

Prevent medication errorsManage polypharmacy

Use low-cost generics where available

FIGURE 1: ESTIMATED AVOIDABLE COSTS FROM SUBOPTIMAL USE OF MEDICINES



FIVE SUCCESS FACTORS TO CONSIDER PRIOR TO IMPLEMENTATIONBefore implementing recommendations, health system leaders must consider a combination offive success factors:

1. Policy: Regulations or laws that support improvements in medicine use downstreamamong prescribers, dispensers and patients

2. Collaboration: Engagement between healthcare professionals and patients in the publicand private sectors

3. Education and capacity-building efforts: Education efforts directed to healthcareprofessionals and patients through training and/or public awareness campaigns

4. Informatics:Applied data collection or medicine use monitoring to inform decisionmaking, including the application of information technology (IT) and non-IT basedmethods

5. Incentives:Alignment of incentives among healthcare professionals to drive change inclinical and/or dispensing practice

Implementing policies to support the responsible use of medicines may be challenging, but isessential. Health system leaders should not let the perfect stand in the way of the good. Whilean overall shift to improved policies will take time, each leader can take initial, necessary stepsto advance the responsible use of medicines in the near term.

RECOMMENDATIONS FOR ACTION HAVE BEEN IDENTIFIED ACROSS ALL SIX PRIMARY LEVERS Our research offers recommendations across all six levers of opportunity based on provenexisting efforts with positive impact. Below are selected highlights prepared for Ministers ofHealth:

• Improve adherence: Adopt cross-disease learnings, apply a patient-centered approach,support data collection efforts to enable targeted interventions and strengthen the role ofhealthcare professionals, particularly the pharmacists, to improve adherence. Apply lessonsfrom Uganda’s efforts to improve adherence and outcomes for HIV positive patients andfrom Ipsos Marketing’s approach in the US that tracks attitudinal and behavioral drivers ofpersistence to identify targeted interventions with the best return on investment.

• Ensure timely medicine use: Support a national focus on early diagnosis, leverageeconomic evaluations and ensure targeted disease management programs for diseases likediabetes type 2 and hepatitis B and C to prevent delayed medicine use and costlycomplications. Using an economic evaluation process, Thailand included first-line andsecond-line treatment on the national medicines list, developed a free screening programand negotiated a 50% reduction in treatment prices with the industry.

• Optimize antibiotic use: Apply a combination of strategic and operational interventionsto improve the use of antibiotics. For example, national treatment guidelines, patienteducation programs and public campaigns, and mandatory reporting of antibiotic use canmake a difference as long as incentives are aligned. In China, a nationally led policy whichdisincentivized providers from over prescribing led to a 15% reduction in antibioticconsumption over a six-month period.




• Prevent medication errors: Leverage low and high resource-intensive options to reducethe likelihood of medication errors during the medicine provision process. However,technology-based efforts such as computerized decision support systems will becounterproductive without a “no blame” culture to error reporting. In the UK, such aculture driven by payer and provider management systems across the country has led to ayear-on-year increase in the reporting of medication incidents at the national level.

• Use low-cost generics where available: Reassess competition policies as well as supply-side measures and adopt cross-country learnings to ensure that the savings opportunity fromthe use of safe and low-cost generics is galvanized. Each country in the world differs ontheir starting point to harness the opportunity for cost savings on medicines after patentexpiry. Recommended actions depend on price differentials between unbranded andbranded generics, as well as volume penetration of unbranded medicines.

• Manage polypharmacy: Implement medical audits targeting the elderly, strengthen thepharmacists’ role in the auditing process, and invest in risk stratification processes to identifypatients at risk of mismanaged polypharmacy. The Health Alliance Plan in the US hasdifferent medicine management programs for patients taking eight to 19 medicines and forpatients taking 20 or more. Over a three-year period the program led to a 16% reductionin prescription costs, a 21% reduction in medical costs, improved adherence and health goals(eg, HbA1c levels).

UNLEASHING THE POWER OF INFORMATION Today, more information on patients and healthcare provision is available than ever before.Payers and providers are increasingly aware of the extent to which informatics and incentivescan impact behavior to realize gains from health outcome and cost savings perspectives. Weoffer three observations to help health system leaders understand different dimensions ofeffective health informatics:

1. Advanced technology platforms are not always necessary. There are various lowresource-intensive ways to collect information for decision making. Mobile health solutionsand paper-based data collection systems can provide value where electronic prescribingsystems and other technology-heavy systems are not possible due to resource constraints.

2. Health informatics capabilities will only deliver their full value whenaccompanied by efforts to drive data-driven behavior change amongstakeholders. Many countries have created systems for reporting error data but must workto create a climate and culture conducive to error reporting and learning.

3. Privacy concerns, centralization vs. fragmentation and data interoperability arebottlenecks which can be overcome. Policies in the EU, Canada, Australia and Japanensure that patients decide whether information collected about them can be disclosed toany third party. The FDA Sentinel Initiative in the US analyzes available data from multiplesources to track adverse events from medicines and medicine device use. To addresschallenges with data interoperability, the Continua Health Alliance, a membership-based,non-profit organization, establishes guidelines for combining and applying existing standardsacross patient-connected health products such as inhalers.


The feasibility of the recommendations put forward in the IMS Institute report varies bycountry and a Minister’s corresponding spheres of influence to drive change. Successfulimplementation depends on a blend of: policies to trigger improvements in medicine use;stakeholder collaboration; education of health professionals and patients; availability of healthinformatics for informed decision making; and alignment of incentives to optimize clinicaland/or dispensing practices. •



BACKGROUND AND SCOPEIn 2012, the IMS Institute for Healthcare Informatics and the World HealthOrganization were invited to contribute preparatory material for a Health Ministerssummit hosted by the Dutch Ministry of Health, Welfare and Sport. As part of thiseffort, the IMS Institute developed a technical report, “The responsible use of medicines:Applying levers for change,” as a public service without funding from any public or privatesector entity. To download the full report or individual chapters, please visitwww.responsibleuseofmedicines.org

The IMS Institute applied three guiding principles in preparing the report and in therecommendations to health ministers:

• Use all available and relevant information

• Quantify findings so that progress or setbacks can be measured and assessed

• Draw conclusions that are pragmatic: do not let perfect be the enemy of the good

The following working description of the responsible use of medicines was applied:

The responsible use of medicines implies that the activities, capabilities and existing resources ofhealth system stakeholders are aligned to ensure patients receive the right medicines at the righttime, use them appropriately and benefit from them.

The key emphasis in this description is on the role of stakeholders in ensuring thatmedicines are used appropriately. When each stakeholder within the health systembehaves responsibly given the best available information, medicine use can deliver veryhigh value to the entire health system. This differs from rational medicine use which hasan implicit or explicit cost implication.

The analysis draws from the World Health Organization (WHO), the World Bank, theOrganisation for Economic Co-operation and Development (OECD) and IMS datasources. Details of the methodology used, together with a complete bibliography, can befound in the full report.

The IMS Institute is committed to leveraging this research as part of a broader initiative tobuild on and strengthen existing healthcare efforts. It is actively seeking collaborationopportunities through research and projects with different stakeholders to advanceunderstanding of this space. Please contact [email protected] for further information.

Pharmaceutical companies worldwide rely on IMS LifeLink™ to power patient-centereddecisions – from the first exploratory questions that drive clinical development,through evidence generation to tactical sales planning for mature brands.

IMS LifeLink PharMetrics Plus™ is the largest, most diverse integrated US health plan databaseavailable. With the broadest coverage of geographies, care settings and industries, it provides dataon more than 150 million US patients. Through the global IMS LifeLink program, we provide apowerful patient lens to drive focus and alignment across your business, deepening yourunderstanding of critical patient, physician and payer dynamics. LifeLink allows you to identify theright patient segments early on, in order to gain competitive advantage in today’s complex environment.

We make a patient-centered perspective easy – by integrating patient-level intelligence into ourindustry leading offerings and giving you expert consultants who apply it to your key issues.

LifeLink provides the insights of primary research with the benefits of secondary: lower cost,repeatable, faster, larger sample size.

IMS LifeLink has everything you need to succeed in a patient-centered universe.

Powering a patient perspective

They are recognizing significant benefits, such as:• Better global decision making through consistent insights across all brands and across theproduct lifecycle

• Improved internal alignment with consistent patient segments defined across Research &Development and Commercial functions

• Enhanced communication with healthcare payers and other stakeholders through the use of aconsistent patient view and common language

• Faster and more accurate views across three key dimensions: patients, payers and prescribers• Confidence working with a partner who is committed to driving new metrics for new business models

IMS has made extensive investments in anonymized patient-level data in markets around the world.Today, we capture information for more than 300 million patient lives - for unparalleled real-worldtreatment insights.

AN UNPARALLELED ARRAY OF ANONYMIZED PATIENT-LEVEL DATA WORLDWIDE

CANADA• Longitudinal Rx• Drug Plan Claims(Oncology, hospital)

EUROPE• Longitudinal Rx(Belgium, France, Germany, Italy,Netherlands, Sweden, UK)

• Electronic Medical Records(France, Germany, Italy, UK)

• Oncology Analyzer(France, Germany, Italy, Netherlands,Spain, Turkey, UK)

• Hospital Disease Database(Belgium)

• Longitudinal Patient Database(Sweden)

ASIA PACIFIC• Oncology Analyzer(China, Japan, South Korea,Taiwan)

• Longitudinal Rx(Japan, South Korea)

AUSTRALIA• Longitudinal Rx

UNITED STATES• Longitudinal Rx• Health Plan Claims• Electronic Medical Records(Oncology, ambulatory)

• PharMetrics Plus• Hospital Charge Detail Master


PATIENT-LEVEL DATA | IMS


PROJECT FOCUS | ORPHAN DISEASE

At a time of growing emphasis on value demonstration and morerestrictive conditions for market access in countries around theworld, drugs to treat orphan diseases – defined as those with aprevalence of less than 200,000 affected individuals (US) or lessthan 5 per 10,000 of the population (EU) – have traditionally facedlower payer pressure than technologies in other therapeutic areas.More recently, however, with increasing numbers of highly-pricedtreatments for these rare conditions being submitted forreimbursement, scrutiny of this class of drugs has risen – along withdemand for stronger, real-world evidence of the clinical, economicand societal benefits they bring.

Faced with this shift in the market landscape, a small biotechcompany came to IMS for help with the European launch of its neworphan product which had just received EMA marketingauthorization. The drug was the first medicine to be licensed forthe treatment of an orphan disease which had an estimated mediansurvival time of just a few years from diagnosis.

With a small employee base and only months to go until the productwas due to reach the market, the company was in urgent need ofexpert support for its pricing and market access activities. In IMSthey found a partner that had the skills and capabilities to coverand coordinate multiple EU mid-size markets, with extensive multi-disciplinary expertise, in-market presence, up-to-date country-specific insight, established relationships with regional and localhealth authorities, and a proven track record of projects deliveredin orphan diseases in all the focus countries.

TARGETING FORMULARY LISTING

In order to meet the goal of national formulary listing in tenEuropean markets, the IMS team defined and followed a rigorousthree-step process (Figure 1). This firstly involved detaileddelineation of the PMA landscape by country to determine keystakeholders, ascertain their views and expectations in this area,and explore the feasibility of establishing innovative agreements.Drawing on the findings of this in-depth analysis, IMS thendeveloped a comprehensive market access plan for addressing thepricing and reimbursement requirements as they applied in eachmarket. Leveraging their longstanding relationships with localconsultants and liaison with clinical and payer key opinion leaders(KOLs), the team then completed the third and final step ofpreparing and submitting a compelling value dossier incorporatingall the necessary documentation for each individual market.

Comprehensive

approaches,

transparent

methodologies and

the ability to enter

open dialog in support

of value arguments

can facilitate

formulary listing in

increasingly

pressurized markets

Achieving market access for a novel orphan drug in Europe

The authorManuela Gschwend, PHD is Senior Consultant HEOR, IMS [email protected]


OVERCOMING INITIAL PUSHBACK

The application was not without its challenges, includingmethodological issues within the clinical trial program,uncertainty around the magnitude of the clinical benefit andan ICER that exceeded accepted thresholds. IMS continuedto work with the relevant authorities to follow up andmanage their queries. Through a process of open discussionand transparency concerning cost-effectiveness and budgetimpact model assumptions, they were able to overcome someinitial payer pushback that was encountered in a number ofmarkets. Their ability to bring on board clinical KOLs toexplain the disease gravity and unmet need was key tofacilitating the application of a different value to healthgain: the importance of the (small) budgetary impact andequity considerations over cost-effectiveness alone.

REIMBURSEMENT SUCCESS

Clear definition of criteria for patient eligibility, prescribingand treatment cessation, together with the development ofa multinational patient registry to monitor use, safety andefficacy of the product, were further important parametersleading to a successful result. Through its work with the IMSteam, the company has been able to achieve reimbursementfor its orphan drug in the majority of markets at theenvisaged price, with additional approvals anticipated in thenear future. •

ORPHAN DISEASE | PROJECT FOCUS

FIGURE 1: THREE-STEP PROCESS TO NATIONAL FORMULARY LISTING

• Who are the main stakeholders? • How are they organized?• What are their needs and requirements? • What is their general view of this kind of product, comparators?• How is this type of drug reimbursed and funded? • What technical data are required and how should they be presented? • What is the best way to address and educate stakeholders andcommunicate information?

• What are the likely timelines? • What potential restrictions may be imposed? • What cost-effectiveness arguments are expected? • What agreements are feasible?

PMAlandscape

Marketaccess plan

Preparationandsubmissionof dossier

• Recommendations based on the alternatives available in each country• Summary of the information required to apply for reimbursement andprice in each country

• Preparation of the necessary documentation in each country• Submission to the relevant authorities and follow-up of eventual queries• Work with local independent consultants who have specific expertise• Involvement of clinical and payer KOLs

Product onnational list of reimburseddrugs

PROJECT FOCUS | GLAUCOMA

The increasingly global scale of product launches is driving newchallenges for pharmaceutical manufacturers in generating a coherentvalue proposition across multiple diverse markets. More countries areformalizing an HTA process and strengthening their focus ontreatment cost-effectiveness but, importantly, their requirementsdiffer. Approaches that enable core evidence for a product to bemodeled and adapted to individual healthcare settings play a key rolein ensuring value messages that are locally relevant but consistentwith global positioning. For one leading manufacturer of eye care products, the ability to demonstrate improved long-term outcomesleveraging rigorous, best-practice model adaptations proved criticalto supporting preferential product use across ten Asia-Pacific markets.

IDENTIFYING LONG-TERM VALUE

The company had recently launched a new treatment for primaryopen angle glaucoma (POAG) - a chronic eye disease characterizedby damage to the optic nerve associated with increased intra-ocularpressure. The condition progresses through three stages of severity:ocular hypertension (OHT); early, moderate and advanced glaucoma; and blindness. Glaucoma is the second leading cause ofblindness after cataract1 and is estimated to affect more than 60 million people worldwide.2

Although the loss of visual fields is irreversible, the progression ofglaucoma can be slowed with medication, usually in the form of eyedrops. These are typically preserved to allow multiple dosing from asingle bottle. However, exposure to the commonly-used preservativebenzalkonium chloride (BAK) has been linked to a higher incidenceof ocular surface disease (OSD) as well as issues with post-surgicaloutcome in glaucoma. Marking an important step forward intreatment, the company had developed an alternative BAK-freeformulation. This was expected to lower the risk of OSD, translatinginto fewer treatment changes, improved quality of life (QoL), bettercompliance and potentially reduced progression of disease.

The company was keen to complement existing data on the product’sclinical benefits with evidence of its health economic implications,particularly in terms of long-term cost and patient outcomes. Thisinformation would be pivotal for HTA submissions, reimbursement,and pricing negotiations during the planned launch roll-out in Europeand Asia Pacific, but would require advanced capabilities in modelingoutcomes across countries with very different healthcare systemsand HTA requirements. In IMS HEOR they found a coordinated, globalteam of in-market experts with extensive experience in developingcore models and seamlessly adapting them to multiple geographicsettings, supported by access to a strong network of local contactsand relevant patient-level data.

Country adaptations

of economic models

leveraging rigorous,

best-practice

methodologies are

key to generating

value arguments in

diverse local settings

Modeling cost-effectivenessin glaucoma across multipleAsia-Pacific markets

The authors Laetitia Gerlier, MSC is Senior Consultant HEOR, IMS [email protected]

Joe Caputo, BSC is Regional Principal HEOR, Asia Pacific,IMS Health [email protected]

PAGE 60 IMS HEOR AND REAL-WORLD EVIDENCE SOLUTIONS

FROM GLOBAL TO LOCAL

The key goal was to estimate the modeled effectiveness andcost-effectiveness of treating OHT/POAG patients with thenew product compared to the original brand as well as aleading BAK-preserved competitor. A core model wasdeveloped in Europe and adapted to a cross-section ofcountries in Asia Pacific.

Leveraging the findings of a patient chart review which hadbeen previously undertaken by IMS HEOR in Europe, andfollowing a systematic literature search, IMS designed atransition-state Markov model so as to capture the effects ofOSD on both the risk of treatment change and diseaseprogression.

Country-specific data included mortality, discount rates, typeand frequency of medical resources used and correspondingunit costs. Resource use and glaucoma costs from a cost-of-illness study were applied to populate the core model. Unitcost data for the country settings was collected by local IMSexperts in each of the markets, with microcosting allowingfor adaptation of the core model. Interviews with key opinionleaders (KOLs) were conducted in each of the focus Asia-Pacific countries to account for local practice in terms of typeand frequency of medical resource use.

Outcomes were measured over a 10-year horizon, enablingdisease progression to be followed from OHT through to moreadvanced stages of glaucoma. These included:

• Percentage of patients with OSD: reaching second- orthird-line treatment; remaining in first-line treatment atmodel end; requiring eye surgery/laser

• Drug cost

• Total cost of glaucoma management

• Final visual field defect

• Quality-adjusted life years (QALYs) gained

Extensive sensitivity analyses were conducted on all keyparameters of the model.

SIGNIFICANT COST SAVINGS REVEALED

The IMS analysis showed that despite its higher unit cost, useof the new formulation was consistently associated with lowertotal costs, better clinical outcomes and a modest but positive impact on QoL. Both the cost savings and clinical/QoL improvements were directly attributable to a significantlyreduced incidence of OSD (Figure 1) and higher rate ofcompliance and persistence observed with the product versusthe comparators.

Probabilistic sensitivity analysis confirmed the significance ofthe clinical results when using distributions around the keymodel parameters. The findings paved the way for furthercomparative studies to more closely examine the effect of theBAK-free formulation on treatment persistence and on rate ofdisease progression.

IMPORTANT VALUE MESSAGES FOR KEY STAKEHOLDERS

Through its work with IMS, the company gained a deepunderstanding of the real-world value of its new formulation interms of long-term benefits and economic consequences withinthe context of disparate healthcare systems in Asia Pacific. Inaddition to informing market access decision making and servingas a vital tool for affiliate dialogue with local payers, the clinicaland cost outcomes of the model were presented at a number ofspecialist international conferences. At a time of continuedgrowth in the prevalence of glaucoma they have also enabledimportant value messages to physicians and KOLs, serving toincrease prescriber awareness of the long-term impact of BAKon the rate of OSD in glaucoma. They continue to inform pricenegotiations in this rapidly expanding region and justify thepresence of the product on formulary listings. •

GLAUCOMA | PROJECT FOCUS


1Resnikoff S, Pascolini D, Etya’ale D, et al. Global data on visual impairment in the year 2002. Bulletin of the World Health Organization, 2004; 82:844-512Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmology, 2006; 90: 262-267

FIGURE 1: OSD DEVELOPMENT OVER TIME

34.4%

50.7%

0%

10%

20%

30%

40%

50%

60%

70%

0 1 2 3 4 5 6 7 8 9 10Year

% p

atie

nts

wit

h O

SD

BAK-free product

BAK-preserved productNatural OSD

Development of OSD in patients receiving the BAK-free formulationwas slower than for the BAK-preserved product and similar to OSDprogression expected in a normal aging population without glaucoma.


Enabling your real-world successIMS offers a spectrum of world-class expertise in health economics and outcomesresearch (HEOR) and real-world evidence (RWE) to deliver the local excellence you need.

IMS is a leading independent provider of RWE, outcomes research, economic modelingand market access solutions, and value communication, leveraging relevant IMSproprietary and other key external, third-party data assets.

IMS HEOR & RWE SOLUTIONS | OVERVIEW

In a future where healthcare efficiency and quality are measured through the lens of ‘real-world’insights, external validity demands a focus on the right data sources, scientifically credible researchand actionable communication.

IMS is committed to helping you succeed:

• Largest multi-disciplinary team of HEOR experts, based in 18 countries worldwide

• Credible scientific voice and deep therapy area knowledge, captured in 200+ publications each year

• Market leadership in developing and adapting robust economic models

• Most advanced capabilities in RWE management and analysis

• Proven expertise in generating and communicating RWE to advance stakeholder engagement at all levels

Technology• Platform engines• Data warehouse/data marts• Encryption systems & linking technology• Meta-data repository• User interface & sophisticated analytics library

• Electronic data capture

IMS LifeLinkTM

Largest collection of scientifically validated,anonymized patient-level data assets: • Health plan claims• Longitudinal Rx• Electronic medical records• Hospital disease• Oncology• Diabetes

Outcomes Research• Evidence generation• Late-phase studies• Patient-Reported Outcomes (PROs)• Database studies• Epidemiology • Risk management

Real-World Evidence Solutions• Data sourcing & validation• Data integration & linking• Data management & curation • Platform development• Customized analytics & reporting• Evidence planning

Health Economic Modeling• Health economic evaluations• Core models & local adaptations• Budget impact• Meta-analyses• Indirect comparisons• IMS CORE Diabetes Model

Market Access• Value development planning• Market access strategy• Core value dossiers & local adaptations• HTA readiness• Value communication• Reimbursement submissions

Our unique, data-agnostic market position can help you develop and support the evidence requiredto engage global and local healthcare stakeholders, with deep insights into product safety, efficacy,cost, value for money and affordability.


Global scope, local expertiseIMS HEOR and RWE experts are located in 18 countries worldwide and they have publishedon projects completed in more than 50 countries on all continents.

Dr. Michael NelsonSenior Principal HEORIMS Health1725 Duke Street, Suite 510Alexandria, VA 22314USATel: +1 703 837 [email protected]

Dr. Jacco KejaSenior Principal HEORIMS Health210 Pentonville RoadLondon N1 9JYUnited KingdomTel: +31 (0) 631 693 [email protected]

Dr. Xavier BadiaSenior Principal HEORIMS HealthDoctor Ferran 25-2708034 Barcelona SpainTel: +34 93 749 63 [email protected]

Adam LloydSenior Principal HEORIMS Health210 Pentonville RoadLondon N1 9JYUnited KingdomTel: +44 (0)20 3075 [email protected]

YOUR PRIMARY CONTACTS

NORTH AMERICAREGIONAL HEADQUARTERS11 Waterview BoulevardParsippany, NJ 07054USATel: +1 973 316 4000

UNITED STATES1725 Duke StreetSuite 510Alexandria, VA 22314USATel: +1 703 837 5150

One IMS DrivePlymouth MeetingPA 19462USATel: +1 610 834 0800

CANADA16720 Route TranscanadienneKirkland, Québec H9H 5M3CanadaTel: +1 514 428 6000

LATIN AMERICAREGIONAL HEADQUARTERSInsurgentes Sur # 23755th Floor, Col. TizapanMexico City D.F. - C.P. 01090 MexicoTel: +52 (55) 5062 5239 or +1 917 542 5844

EUROPEREGIONAL HEADQUARTERS210 Pentonville RoadLondon N1 9JYUnited KingdomTel: +44 (0)20 3075 4800

BELGIUMMedialaan 381800 VilvoordeBelgiumTel: +32 2 627 3211

FRANCE29ème EtageTour Ariane5-7 Place de la Pyramide92088 La Défense CedexFranceTel: +33 1 41 35 1000

GERMANYErika-Mann-Str. 580636 MünchenGermanyTel: +49 89 457912 6400

ITALYViale Certosa 220155 MilanoItalyTel: +39 02 69 78 6721

SPAINDr Ferran, 25-2708034 BarcelonaSpainTel: +34 93 749 63 00

SWEDENSveavägen 155/Plan911346 StockholmSwedenTel: +46 8 508 842 00

SWITZERLANDTheaterstr. 44051 BasleSwitzerlandTel: +41 61 204 5071

UNITED KINGDOM210 Pentonville RoadLondon N1 9JYUnited KingdomTel: +44 (0)20 3075 4800

ASIA PACIFICREGIONAL HEADQUARTERS

10 Hoe Chiang Road Keppel Towers #23-01/02Singapore 089315 Tel: +65 6412 7365

AUSTRALIALevel 5, Charter Grove29-57 Christie StreetSt Leonards, NSW 2065AustraliaTelephone: +61 2 9805 6800

CHINA7/F Central TowerChina Overseas PlazaJianguomenwai Avenue, Chaoyang DistrictBeijing 100001ChinaTel: +86 10 8567 4255

SOUTH KOREA9F Handok Building735 Yeoksam1-dongKangnam-ku Seoul135-755S. KoreaTel: +82 2 3459 7307

TAIWAN8th FloorNo 2, Tun Hwa South RoadSection 1Taipei 10506TaiwanROCTel: +886 2 2721 5337

FOR FURTHER INFORMATION: email [email protected] or visit www.imshealth.com/heor

LOCATIONS | IMS

IMS HEOR & RWE Solutions office locations


Expertise in depthIMS has one of the largest global teams of experts in HEOR, RWE and market access ofany organization in the world.

IMS | EXPERTISE


We apply unrivalled experience and specialist expertise to help our clients meet the demands of an increasingly complexglobal, regional and local pharmaceutical landscape. Our highly qualified, multi-disciplinary consultants and researchershave proven skills and capabilities across all key therapy areas. Spanning industry, consulting, government and academia,their expertise reflects a global grasp, local experience and a unique, inside market perspective.

Renée J. G. Arnold, PHARM D• Dr. Renée Arnold is Principal HEOR at IMS Health with particular expertise in the use of technology to collectand/or model real-world data to facilitate rational decision making by healthcare practitioners and policy makers.

• Renée was previously President and CEO, Arnold Consultancy & Technology where she developed and oversawoutcomes research for the pharmaceutical, biotech and device industries as well as federal government programs.Her distinguished career in health economics and outcomes research includes roles as President and co-founder ofPharmacon International, Center for Health Outcomes Excellence and Senior VP and Medical Director at William JBologna International.

• Founding member and former Chair of the Education Committee of ISPOR, Renée has several adjunctappointments and is the author of numerous articles on pharmacoeconomics and cost-containment strategies. She holds a Doctor of Pharmacy degree from the University of Southern California in Los Angeles.

Xavier Badia, MD, MPH, PHD• Dr. Xavier Badia is Senior Principal HEOR at IMS Health with extensive experience in all areas of outcomes research.• A founder of Health Outcomes Research Europe, Xavier has extensive experience in consulting and researchoutcomes, patient-reported outcomes, and effectiveness and cost-effectiveness evaluations. A respectedscientific speaker and member of EuroQol since 1993, he serves on several international advisory and editorialboards and has published over 150 peer-reviewed papers.

• Xavier holds an MD, a PhD in Medicine, and a Master’s in Public Health and Health Economics from theUniversity of Barcelona.

Our senior team

Karin Berger, MBA• Karin Berger is Principal HEOR at IMS Health with a particular focus on real-world evidence, patient- reportedoutcomes, and cost-effectiveness evaluation analyses at a national and international level.

• Formerly Managing Director of MERG (Medical Economics Research Group), an independent German organizationproviding health economics services to the pharmaceutical industry, university hospitals and EuropeanCommission, Karin has more than 14 years experience in the health economics arena. She lectures at severaluniversities, has published extensively in peer-reviewed journals, and regularly presents at economic andmedical conferences around the world.

• Karin graduated as Diplom-Kaufmann (German MBA equivalent) from the Bayreuth University, Germany, with aspecial focus on health economics.

Christopher M. Blanchette, PHD, MS, MA• Dr. Chris Blanchette is Principal HEOR at IMS Health, with extensive experience in retrospective database research andobservational studies with particular emphasis on respiratory diseases.

• Chris was previously Director of Clinical & Outcomes Research at the Lovelace Respiratory Research Institute,where he led a team of 50 people conducting clinical research, biostatistics, and outcomes research programs.He also spent time in market access and R&D health economics at GlaxoSmithKline, most recently as Directorfor Health Data Analytics, and was formerly a researcher at the Premier Hospital Alliance and Agency forHealthcare Research and Quality.

• In addition to serving in leadership positions for ISPOR and several respiratory disease associations,Christopher is on the editorial board of the Journal of Medical Economics and advisory board of Current MedicalResearch and Opinion. He holds a PhD in Pharmaceutical Health Services Research and an MS in Epidemiologyfrom the University of Maryland, and an MA in Medical Sociology from the University of North Carolina.


EXPERTISE | IMS


Nevzeta Bosnic, BA• Nevzeta Bosnic is Principal at IMS Brogan, where she manages projects to meet the broad spectrum of clientneeds in the Canadian pharmaceutical market.

• Formerly Director of Economic Consulting at Brogan Inc, Nev has led many strategic consulting, policy and dataanalyses for pharmaceutical clients, government bodies and academic institutions in Canada. She has extensiveknowledge of public and private drug plans across the country and in-depth expertise and experience on the drug reimbursement process.

• Nev holds a Bachelor’s degree in Business Economics from the School of Economics and Business at theUniversity of Sarajevo, Bosnia-Herzegovina.

Frank-Ulrich Fricke, PHD, MSC• Dr. Frank-Ulrich Fricke is Principal HEOR at IMS Health and Professor for Health Economics, Georg-Simon-OhmUniversity of Applied Sciences, Nuremberg in Germany, with a focus on health economic evaluations, market accessstrategies and health policy.

• Formerly a Managing Director of Fricke & Pirk GmbH, and previously Head of Health Economics at NovartisPharmaceuticals, Frank-Ulrich has conducted health economic evaluations across a wide range of therapeuticareas, developing a wealth of experience in pricing, health affairs and health policy. As a co-founder of the NIG21 association, he has forged strong relationships with health economists, physicians and related researchersworking in the German healthcare system.

• Frank-Ulrich holds a PhD in Economics from the Bayreuth University, and an MBA equivalent from the Christian-Albrechts-University, Kiel.

Joe Caputo, BSC• Joe Caputo is Regional Principal HEOR, Asia Pacific at IMS Health leveraging more than 20 years experience inthe pharmaceutical sector to help clients address the challenges of global reimbursement and market accessthroughout the drug development program. He has led numerous projects involving payer research, valuedossiers, local market access models and HTA submissions.

• With a background that spans industry roles in drug development, sales & marketing and UK & global healthoutcomes, and consulting in health economics, Joe has wide-ranging knowledge of the drug developmentprocess at both local and international level and a unique understanding of evidence gaps in light ofreimbursement and market access requirements.

• Joe holds a BSc in Applied Statistics and Operational Research from Sheffield Hallam University, UK.

David Grant, MBA• David Grant is Senior Principal HEOR at IMS Health, specializing in reimbursement and market access,environmental analysis, prospective and retrospective data collection and communications for productsupport.

• A co-founder and former Director of Fourth Hurdle, David’s experience spans 10 years in health economicsand outcomes research consulting, and 15 years in the pharmaceutical industry, including roles in clinicalresearch, new product marketing and health economics in the UK and Japan.

• David holds a degree in Microbiology and an MBA from the London Business School.

Joshua Hiller, MBA• Joshua Hiller is Principal Real-World Evidence Solutions at IMS Health, supporting the strategic planning anddevelopment of IMS capabilities for data sourcing, integration, analytics and studies. He is also currently serving asAlliance Director in the IMS collaboration with AstraZeneca for the advancement of RWE.

• During a career that includes roles in market analytics, government and healthcare consulting in both the US andUK, Joshua has led a wide range of projects for clients in the pharmaceutical and biotech sector as well as industryassociations. He has extensive experience in pharmaceutical pricing, contracting, market landscape development,supply management, cross border trade, lifecycle management, competitive defense, generics market drivers andaccount management, with expertise across US and European markets.

• Joshua holds an MBA (Beta Gamma Sigma) from Columbia Business School, New York, and a BS in Mathematics fromJames Madison University, Virginia.

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IMS | EXPERTISE

Mark Lamotte, MD• Dr. Mark Lamotte is Principal HEOR at IMS Health with responsibility for the content and quality of allhealth economic evaluations conducted by his team.

• A physician by training (cardiology), Mark spent a number of years in medical practice before joiningRhône-Poulenc Rorer as Cardiovascular Medical Advisor and later becoming Scientific Director at theBelgian research organization, HEDM. He has since worked on more than 150 projects, involving expertinterviews, patient record reviews, extensive modeling and report writing across a wide range of therapyareas, and authored many peer-reviewed publications.

• Mark holds an MD from the Free University of Brussels (Vrije Univeristeit Brussel, Belgium) and is fluent inDutch, French, English and Spanish.

Won Chan Lee, PHD• Dr. Won Chan Lee is Principal HEOR at IMS Health, specializing in prospective and retrospective healtheconomics research.

• Over the course of his career, Won has completed numerous international economic evaluations employing avariety of analytical methods across a range of diseases and geographies. His expertise includes econometricdatabase analysis, quality of life assessment and advanced economic modeling to establish the economic andhumanistic value of new and existing therapeutic interventions.

• Won holds a Master’s in Economics from the University of Grenoble II, and a PhD in Economics from theGraduate Center of the City University of New York.

Claude Le Pen, PHD• Dr. Claude Le Pen is a member of the strategic committee of IMS Health and Professor of Health Economicsat Paris-Dauphine University, providing expert economic advisory services to the consulting practice.

• A renowned economist, leading academic, and respected public commentator, Claude has served as anappointed senior member of several state commissions in the French Ministry of Health and is an expert for anumber of parliamentary bodies, bringing a unique perspective and unparalleled insights into the economicevaluation of pharmaceutical technologies at the highest level.

• Claude studied Business Administration in HEC Business School in Paris and holds a PhD in Economicsfrom Panthéon-Sorbonne University.

Adam Lloyd, MPHIL, BA• Adam Lloyd is Senior Principal HEOR at IMS Health, with a particular focus on economic modeling and theglobal application of economic tools to support the needs of local markets.

• A former founder and Director of Fourth Hurdle, and previously Senior Manager of Global Health Outcomes atGlaxoWellcome, Adam has extensive experience leading economic evaluations of pre-launched and marketedproducts, developing submissions to NICE and the SMC, decision-analytic and Markov modeling, and in the useof health economics in reimbursement and marketing in continental Europe.

• Adam holds an MPhil in Economics, and a BA (Hons) in Philosophy, Politics and Economics from the Universityof Oxford.

Jacco Keja, PHD• Dr. Jacco Keja is Senior Principal HEOR at IMS Health, drawing on deep expertise in global market access,operational and strategic pricing, and health economics and outcomes research.

• Jacco’s background includes four years as global head of pricing, reimbursement, health outcomes and marketaccess consulting services at a large clinical research organization and more than 13 years experience in the pharmaceutical industry, including senior-level international and global roles instrategic marketing, pricing and reimbursement and health economics.

• Jacco holds a PhD in Biology (Neurophysiology) from Vrije Universiteit in Amsterdam, a Masters in MedicalBiology, and an undergraduate degree in Biology, both from Utrecht. He is also visiting Professor at theInstitute of Health Policy & Management at Erasmus University, Rotterdam.


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EXPERTISE | IMS

Frédérique Maurel, MS, MPH• Frédérique Maurel is Principal HEOR at IMS Health, with a particular focus on observational research and healtheconomics studies.

• A skilled consultant and project manager, Frédérique has extensive experience in the economic evaluation ofmedical technologies gained in roles at ANDEM, Medicoeconomie, and AREMIS Consultants.

• Frédérique holds a Masters degree in Economics – equivalent to an MS – and completed a post-graduate degreeequivalent to an MPH with a specialization in Health Economics at the University of Paris-Dauphine (Paris IX)as well as a degree in Industrial Strategies at the Pantheon-Sorbonne University (Paris I).

Joan McCormick, MBA• Joan McCormick is Principal at IMS Brogan, leading a team providing strategic advice to companies withnew products coming to market and ongoing consultation on the rules for existing drugs post launch.

• Formerly Head of Price Regulation Consulting at Brogan Inc, Joan has supported many majorpharmaceutical companies with the preparation of pricing submissions to the Patented Medicine PricesReview Board (PMPRB), gaining extensive insights into the operation of the Canadian pharmaceuticalmarket.

• Joan holds a Bachelor’s degree in Life Sciences from Queen’s University in Kingston, Canada, and an MBAfrom the University of Ottawa, Canada.

Charles Makin, MS, MBA, MM, BS• Charles Makin is Principal HEOR at IMS Health, focusing on naturalistic trials, adherence interventions,chart abstractions, patient-reported outcomes and other studies involving primary data collection.

• During a career that includes senior roles at the UnitedHealth Group and Wellpoint, Charles has lednumerous studies involving database analyses, economic modeling, multi-country patient registries,systematic literature reviews and survey-based research.

• Charles holds a BS in Pharmacy from the University of Pune, India, an MS in Pharmacy Administration fromPurdue University, Indiana, U.S. and an MBA in Marketing Management and a Master’s in Management,both from Goldey Beacom College, Delaware, U.S.


Dana Morlet-Vigier, MD• Dr. Dana Morlet-Vigier is Principal HEOR at IMS Health, applying in-depth expertise and extensive experience inpharmaceutical pricing, reimbursement and market access to help clients meet the growing challenges oftoday’s increasingly complex product launch process.

• A medical doctor and INSEAD executive, Dana’s background spans 15 years in pharmaceuticals and includesroles in R&D, commercial, market access, strategy and government affairs at GlaxoSmithKline, Organon and 3MPharma. She has worked on numerous pricing and reimbursement negotiations and designed and implementednational and international Phase II, III and IV studies across a wide range of therapy areas.

• Dana holds an MD from Bucharest Medical University, Romania and the Paris-Cochin Faculty, Paris, France.

Julie Munakata, MS• Julie Munakata is Principal HEOR at IMS Health, with a particular focus on global economic modeling, valuedevelopment planning, and survey data analysis.

• An accomplished researcher and author of more than 25 original articles, Julie has extensive experience inmanaging clinical trials, health economic studies and decision analytic modeling work, gained in senior roles atValueMedics Research LLC, the VA Health Economics Resource Center and Stanford Center for Primary Care &Outcomes Research, and Wyeth Pharmaceuticals.

• Julie holds an MS in Health Policy and Management from the Harvard School of Public Health and a BS inPsychobiology from the University of California, Los Angeles.

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IMS | EXPERTISE


Vernon Schabert, PHD• Dr. Vernon Schabert is Senior Principal HEOR at IMS Health, with a particular focus on the assessment andvalidation of patient-reported outcomes (PRO) instruments, retrospective analyses of claims and surveydatabases, and primary data collection surveys.

• A founder and former President of Integral Health Decisions, Inc, Vernon has extensive experience inconducting claims analyses, creating custom administrative databases, developing business intelligencesoftware, and leading national quality research projects, gained in roles with Thomson Reuters, StrategicHealthcare Programs LLC, and CIGNA HealthCare. His expertise spans numerous disease areas and diversetopics including medication adherence, in-patient safety and outcomes in post-acute care.

• Vernon holds a PhD in Personality and Social Psychology from Stanford University and a BA in Psychologyfrom Princeton University.

Jon Resnick, MBA• Jon Resnick is Vice President HEOR and Real-World Evidence Solutions at IMS Health, leading thecompany’s global real-world evidence (RWE) business, including the development of RWE strategy,offerings, collaborations and foundational technologies to meet the RWE needs of healthcare stakeholders.

• A former Legislative Research Assistant in Washington DC and member of the Professional Health andSocial Security staff for the US Senate Committee on Finance, Jon has 10 years consulting experience atIMS. He was most recently responsible for leading the European management consulting team and globalHEOR business teams of 300 colleagues, advising clients on a wide range of strategic, pricing and marketaccess issues.

• Jon holds an MBA from the Kellogg School of Management, Northwestern University, with a major inManagement & Strategy, Finance, Health Industry Management and Biotechnology.

Michael Nelson, PHARM D • Dr. Michael Nelson is Senior Principal HEOR at IMS Health, with particular expertise in retrospective databaseresearch, prospective observational research, health program evaluation, and cost-effectiveness analysis.

• During a career that includes leadership roles in HEOR at PharmaNet, i3 Innovus, SmithKline Beecham, andDPS/UnitedHealth Group, Mike has gained extensive experience in health information-based productdevelopment, formulary design, drug use evaluation, and disease management program design andimplementation.

• A thought leader in health economics for more than 20 years, Mike holds a doctorate in Pharmacy and aBachelor of Science degree, both from the University of Minnesota College of Pharmacy. He also served as anadjunct clinical faculty member at the University of Minnesota whilst in clinical pharmacy practice.

Amy O’Sullivan, PHD• Dr. Amy O’Sullivan is Principal HEOR at IMS Health, with a particular focus on global economic modeling to supportproduct reimbursement in jurisdictions around the world.

• Highly experienced in the economic evaluation of medical technologies, Amy’s background includes roles at PolicyAnalysis Inc. (PAI) and most recently in a senior capacity at OptumInsight (formerly i3 Innovus). She has lednumerous pharmacoeconomic and outcomes research studies including cost-effectiveness analyses, budgetaryimpact analyses, burden-of-illness studies and piggyback economic evaluations. Her research spans a wide range oftherapeutic areas, including autoimmune conditions, CV disease, CNS and behavioral health disorders, metabolicdisorders, musculoskeletal conditions, oncology, respiratory disease and women’s health.

• Amy holds a PhD in Health Economics from the Johns Hopkins University Bloomberg School of Public Health,Baltimore, and a BA in Economics and English from Boston College.

Carme Piñol, MD, MSC• Dr. Carme Piñol is Principal HEOR at IMS Health, with more than 20 years experience in the pharmaceutical industryspanning clinical research, health economics and market access.

• Previously Head of Market Access for Spain at Bayer, a role that included pricing, HEOR, advocacy and institutionalrelations with the Regions, Carme is a Board member of the Spanish Association of Health Economics as well as theISPOR Spain Regional Chapter and coordinator of the Pharmacoeconomics Interest Group of the Spanish Associationof Medicine of the Pharmaceutical Industry (AMIFE). She has authored more than 60 communications ininternational and national congresses and more than 20 papers in peer-reviewed journals.

• Carme holds an MD from the Autonomous University of Barcelona, an MSc in Pharmacoeconomics and HealthEconomics from Pompeu Fabra University, an MSc in Health Research from Castilla-La Mancha University (UCLM),and an Executive Program Degree from ESADE Business School, Barcelona, Spain. She is currently completing a PhDin Health Research at UCLM.

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EXPERTISE | IMS


Arnaud Troubat, PHARM D, MBA, MHEM• Dr. Arnaud Troubat is Principal HEOR at IMS Health. He has extensive consulting experience and specialexpertise in the development of registration dossiers and market access strategies across a large numberof therapeutic areas.

• A pharmacist by training, Arnaud began his career at the French pharmaceutical industry association(LEEM), supporting members in understanding and interpreting the changing economical environment inFrance. He then spent a number of years in pharmaceutical affairs at ICI, leading regulatory work onregistration submissions and reimbursement strategies, before subsequently moving into consulting. Mostrecently, he was Director at Carré-Castan Consultants, managing a team working for a wide range ofpharmaceutical companies.

• Arnaud holds a Doctor of Pharmacy degree and an MBA from IAE Paris and a Master’s in Health Economicsand Management from Paris-Dauphine University.

Núria Lara Surinach, MD, MSC• Dr. Núria Lara is Principal HEOR at IMS Health, with a particular focus on the design and coordination of local andinternational observational and patient-reported outcomes studies.

• A former practicing GP and clinical researcher, Núria’s experience spans roles in outcomes research at theInstitute of Public Health in Barcelona and in Catalan Health Authorities, and consulting positions within thepharmaceutical and medical device industries focusing on medical regulatory and pricing affairs,pharmacoeconomics and market access strategies.

• Núria holds an MD (specializing in Family and Community Medicine in Barcelona), and a Master’s in PublicHealth from the London School of Hygiene and Tropical Medicine and London School of Economics.

Christian Thielscher, MD, MBA, PHD• Dr. Christian Thielscher is Principal HEOR at IMS Health and Professor for Health Economics at the FOMUniversity in Germany, with expertise in clinical medicine, health economics, strategic consulting,business administration and innovative service development.

• Christian began his career in medical practice before moving into healthcare consulting at McKinsey,where he established one of the first disease management programs in Germany. He later founded GHXEurope where his work included developing the “health card” and the first German internet-based hospitalguide.

• Founding president of the DGFM eV and editor of ‘Medizinökonomie’, Christian’s current research interestsinclude quality in medicine and healthcare business management and marketing. He holds an MD fromBonn University, an MBA, and a PhD in Economics from the University of Frankfurt am Main, Germany.

Massoud Toussi, MD, MSC, PHD • Dr. Massoud Toussi is Medical Director HEOR at IMS Health with particular expertise in methodological andoperational aspects of clinical research to assure the quality of interventional, observational and databasestudies.

• Previously Head of Global Clinical Research Operations at Cegedim, Massoud has also worked at the French HighAuthority for Health and various CROs as Project Lead, Scientific Manager and Operations Director. Hisexperience includes defining and elaborating a new service process in drug safety signal detection andtransmission.

• Massoud holds an MD from Mashad University in Iran, an MSc in Medical Informatics and CommunicationTechnology from Paris IV, a PhD in Medical Informatics from Paris XIII University and a diploma in TransculturalPsychiatry from Paris Nord University.

Jovan Willford, MBA• Jovan Willford is Principal Real-World Evidence Solutions at IMS Health, supporting growth strategy, offeringdevelopment and commercialization of RWE solutions.

• Jovan’s background includes more than 10 years of strategic advisory experience across payers, providers, lifescience organizations and technology companies, including several cross-industry collaborations to advance qualityand value of care delivery.

• Jovan holds an MBA from the Kellogg School of Management, Northwestern University, with majors in Management& Strategy, Managerial Economics and International Business, and an undergraduate degree from the University ofNotre Dame with majors in Marketing and Philosophy.

ABOUT IMS

IMS Health is the leading provider of information services for the healthcare industry around the world. The companydraws on its global technology infrastructure and unique combination of in-depth, sophisticated analytics, on-shore andoff-shore commercial services, and consulting platforms to help clients better understand the performance and value ofmedicines. With a presence in 100+ countries and more than 55 years of industry experience, IMS Health serves leadingdecision makers in healthcare, including pharmaceutical manufacturers and distributors, providers, payers, governmentagencies, policymakers, researchers and the financial community. Additional information is available atwww.imshealth.com

HEORAP1112©2012 IMS Health Incorporated and its affiliates. All rights reserved. Trademarks are registered in the United States and in various other countries.

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