march 2017 - nalashaa health...population health as defined by c.-e.a. winslow, founder of yale...

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The science and art

behind Population Health

March 2017

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I n t r o d u c t i o n

T he advent of value based reimbursement model has the payers

asking providers to shift from volume-based care to a value-based

reimbursement structure.

Population Health as defined by C.-E.A. Winslow, founder of Yale Department of

Public Health, as “the science and art of preventing disease, prolonging life, and

promoting health through the organized efforts and informed choices of society,

organizations, public and private communities, and individuals.”, can be im-

proved by leveraging automation and robust analytic capabilities that define

measurements for health outcomes and patterns from historical data. This not

only helps in improving delivery of care to a group of individuals with similar

needs, but also helps in meeting the paradigm shift from acute care to popula-

tion centric care.

Various community based health systems have practices using different EHR/

EMR and their clinical workflow varies significantly such that time and efforts

required to gather and interpret member information is overwhelming due to

diverse sources of data. Thus, there is a need to transform the traditional

“isolated" care model into a “network” care model, both for increased care coor-

dination and the ability to scale effective interventions with the Population

Health approach. Whether it’s about managing chronic conditions by effectively

identifying high risk patients or identification of care gaps against pre-defined

quality measures like HEDIS, there are growing needs to enhance clinical ana-

lytics for better care coordination and improved outcomes.

Care management, care coordination and lower aggregate costs can be

achieved at patient level by integrating and collating data from claim based,

PHR and EHR based data sources. This can help health insurers, community

based health systems and their affiliates play an active and increasingly person-

The science and art behind Population Health

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alized role to help patients’ engagement in their care and wellbeing.

Care Management is just not necessary to improve & track patient health but it’

s also a strategic and important tool for health plans as they find ways to con-

tain costs in modern data-centric era. Predictive analytics and modeling tech-

niques can be used to identify members with high risk of hospitalization, plan

necessary care interventions and ensure medication adherence to mitigate that

risk. This data-centric action-planning can provide meaningful insights into

quality, safety and cost of care available at contracting providers.

Given that population health management (PHM) and Care management are so

closely related in spirit, we have chosen to use those terms interchangeably in

this paper. The capabilities that one offers can be leveraged by the other to

offer meaningful capabilities to healthcare providers.

W h o b e n e f i t s ?

E very innovation aimed at reducing cost or improving quality implicitly has

the patient as the primary beneficiary. However, as the economics im-

pacts the rest of the ecosystem positively, it’s the players such as the following

who need to take the initiative to put systems in place that can accomplish the

goals of quality and cost.

Below are key benefits that they stand to derive from such a solution:

Health Insurer (s), ACO, HMO

The core competence for healthcare payers is risk identification and mitigation.

They need to know and predict the patient cohorts that are likely to impact

their financials adversely. Additionally, they need to ensure that they minimize

the likelihood of those patients going back to care facilities. The best place for

them to start this is data, not just medical data of the patients but their well-

ness data too. While that is a start, it’s not the end of the tunnel for them.

They need to ‘read’ and monitor the continuum of care and the providers that

will prove to be their most profitable allies. A well-designed care management

Healthcare payers

need to minimize

the likelihood of

patients going to

healthcare facilities

by identifying risks

and mitigating

them.


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solution can help the payers:

Stratify and clinically define the population that poses risk for them.

This would help them contain their financial risk

Systematically improve the quality of care being delivered to that pop-

ulation and ensure appropriate care to minimize conditions associated

with skyrocketing expenses

Eliminate waste within the care delivery process, thus reducing the cost

per member per month

Track HEDIS measures performance on monthly basis and align busi-

ness decisions with outcomes

Make data-driven decisions resulting in increased patient safety, im-

proved quality of care and reduction in healthcare costs

Community Based Health Systems & Practices, Providers, Care Team (s)

With the government and the industry gearing up to say goodbye to the FFS

model, the care providers have to adapt. Under value based care, providers will

be accountable for the overall wellbeing of the healthcare consumers. In order

to ensure that they do not bleed through unwarranted expenses, providers need

to be empowered with tools to follow the patients through the care continuum.

These powerful solutions will enable the providers to:

Identify care gaps in existing quality programs like HEDIS, PQRS, eCQM

Improve performance in risk contracts/value based care incentives

Meet performance measures as specified in Quality Payment Program and

get a better composite score resulting in better payments from CMS

Identify high risk patients based on clinical indicator( s) available and

provision preventive care mechanisms in place to eliminate costs related to

corrective care provisioning

Better utilization of organizational resources by focusing on the right ar-

eas, identified by analyzing the data relating to patient health, care delivery

and investments in care provisioning

Prevent unwanted

expenses by analyz-

ing data relating to

patient health and

identify gaps in

care quality and

performance.


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EHR vendor (s)

Most of the EHRs were built to streamline the workflows within the healthcare

facilities, but none of them were designed for a customer-centric healthcare

ecosystem. This leads to most EHRs failing miserably when it comes to custom-

er relationship management which is essentially the mantra behind the

‘consumerism’ wave. In essence, the solutions that were expected to take care

of the care provisioning AFTER the patient was in the care facility are now ex-

pected to take care of the patient OUTSIDE of the facility itself. Evidently, the

expectation seems unrealistic.

Technology vendors are either coming up with these capabilities within the EHR

or aim to fulfil this through add-on solutions. While there are repercussions of

both, for their providers to be successful, they need to:

Support transition to value based care without hurting provider pay-

ments.

Not only generate quality data for clinical quality measures but also pro-

vide a way to increase performance on these measures by improving

care provisioning processes.

Provide integrated analytics covering not only clinical workflows but

also financial implications of the actions taken or processes followed up-

stream.

Leverage information available in partner systems by embracing in-

teroperability support offered by CCDA, FHIR etc.

What must your care management solution have?

C are Management solutions address the continuum of care through data

integration, population stratification, identification, consumer engage-

ment and program evaluation. While traditional EHRs are equipped to cater to

the workflows WITHIN the care facilities, care management and population

health solutions ensure patient wellbeing outside of those.

Following are some key highlights of such solutions:

Transition to a EHR

which can provide

passive care to pa-

tients even when

they are outside the

care facility


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1. Collate data from diverse data sources which includes eligibility, claims,

encounters, lab results and prescriptions. More the data, better the care

planning and provisioning.

2. Subject patient data obtained from these sources to pre-specified rules

based on CQM/HEDIS measures. While these measures serve as a good

starting point, providers should be able to configure rules that better

suit their context.

3. Provide a list of patients to be pursued based on open care gaps with an

opportunity score. This helps identify the priorities for the care provid-

ers.

4. Identify care gaps in members’ health and notify the providers or payers

based on actions defined in #2. Patients with chronic conditions may need

more frequent help and follow-ups from providers to keep them healthy.

Their health data can be used to identify the need for timely interven-

tions.

5. Quick view of patient health information, episodes and health plan infor-

mation to ensure that interventions are performed by qualified providers

using complete and most current data.

6. Enable sharing member clinical information with other providers, patients,

next-of-kin etc. The channels could range from CCDA packets to APIs

depending on the destination system.

7. Ability to reach out to members with care gaps for scheduling appoint-

ments/care plan discussion, interventions, general engagement and so

on. Automation can ensure that a plan for each of those patients is in

place and nothing gets missed.

8. Suppression of identified care gaps if patient has already mitigated

the same. This ensures that the patient or the providers aren’t over-

whelmed with the bells and whistles in the care provisioning process.

Integrate, stratify

and identify your

consumer to engage

effectively for a bet-

ter care manage-

ment solution.


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9. Allow providers to attest to specific services rendered which can automati-

cally close care-gaps.

10. Personalization of health alerts sent to patients through patient portals,

emails and SMS. It is important to ensure that they feel connected with

the care team and don’t see these communications as an intrusive.

11. Provide key utilization indicators including 30/45 day readmits, cost per

member per month, % of generic medications prescribed and Acute/ER

admits per 1000. This is the dashboard that helps drive the whole machin-

ery in the right direction. While the numbers may not present the solution

itself, they can help in the identification of the problem areas.

As the numbers on the dashboards improve, the following would definitely

be impacted positively:

Patient health and safety as the focus is on overall wellbeing as op-

posed to quality care in the care facility.

Provider scoring on the quality measures as automation inculcated

discipline and streamlines processes.

Better AR conversion for providers as they eliminate denial reasons

by fixing care provisioning.

Reduced expenses (attributed to preventive care and waste reduc-

tion) for the payers.

Anatomy of a PHM System

P opulation health management is a rather tricky endeavor requiring unre-

lenting discipline. Owing to the nature of the objective, it demands coordi-

nation across several individuals right from identifying key clinical processes, care

delivery workflows, decision making rules and identifying registry integrations.

Many crucial decisions for a patient can be made accurately with a comprehensive

view of the treatment process the patient has gone through by using analytics

built on a data warehouse comprising of aggregated data from multiple sources.

Automation of

tasks will improve

quality of care and

personalization will

drive patient en-

gagement, and

both in turn will

drive reduction in

expenses.


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Integrating with different disease registries of AHRQ also provides insights and

classifies patients into different disease stratifications, helping both clinicians &

care teams identify and improve care, resulting in

Reduced frequency of health crises and costly ED visits and length of stay

during hospitalizations

Lower per service costs, through an integrated delivery of care team ap-

proach which includes clinicians, social workers, physical therapists and be-

havioral health care professionals.

Improvement of patient experience, by providing better access to care.

Promoting patient engagement and empowering patients to better self-

manage their health and participate in the decision making process.

Identifying readmissions or death in a specific timeframe after discharge.

Improving the health outcomes of patients by identifying the disease con-

ditions and defining the right care paths and reducing the overall cost.

Following are some of the use cases:

EHRs comprising of patient details and clinical data may not completely help in de-

riving any decisions. But in-order to understand a patient in the context of popula-

tion health, bring together:

Clinical and claims information

Lab & imaging, along with other sources of medical data

Data from social apps which helps in understand the cost of care deliv-

ery, who is most efficient at delivering care, compliance of patients.

How all this is brought together is depicted in the following diagram:

Understand your

patient in the con-

text of population

health. Coordinate

with various sys-

tems and offices to

help deliver a com-

plete healthcare .


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Fig 1: Anatomy of a PHM system

A study by HIMSS Analytics highlights that diabetes is one of the most common condition that chronic

patients suffer from. (As shown below)


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So, let’s take this as an example to demonstrate how population health system can help improve the

health and wellbeing of a patient John Doe.

ETL

ETL is not just a dump & load activity; It lays the foundation for a 360 degree view of patients to ensure

their wellbeing outside of healthcare facilities. There is currently no one system I the healthcare ecosys-

tem that can provide that. Hence, data from disparate sources needs to be pooled together to get a

complete picture of the patient.

As a result, an ETL (Extract, Transform and Load) system becomes the first essential component of such

a solution. The data from different systems needs to be sanitized and massaged before it can be used

meaningfully. While mundane, this is the basic ingredient of the system to ensure downstream activities.

Data Mart

As there are myriad objectives and perspectives of population health and care management, the tech-

nical design must be adaptive and extensible enough to qualify the litmus test of real life use cases. The

John is a diabetic type 2 patient who also has been diagnosed with a kidney condition. He is being treat-

ed at home with regular dialysis by Ms. Patty and also visits Dr. Jones’ clinic on a regular basis. Now,

both these care givers, in order to ensure the best course of action for John, need to have the complete

picture of his health. While the patient is the same and is being treated by two care givers for two differ-

ent conditions, a trigger from one could severely impact the other. For instance, John needs to go for

many tests including A1c, fasting lipids, blood pressure, micro-albumin etc. The results from these tests

are vital for decisions that either of the care givers take such as medications to be prescribed, regimen to

be followed etc. Also, in case John acquires another condition such as cardiovascular, both care givers

need to know, to ensure no adverse reactions are triggered because of a prescription from them. If lab

test results, prescription refills from pharmacy etc. are made available to Jones and Patty, they can stay

updated on John’s condition to give him the best care.

As Jones and Patty may or may not know each other well enough to discuss John’s health, it’s important

that their systems share this information with each other. There are technical means to pull the clinical in-

formation from their respective EHRs (using CCDA or FHIR), Real time sync of Lab/Diagnostic results (using

HL7), remits from John’s payers (using EDI), John’s vitals from a wearable device that he uses.


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data marts will allow stratification and analysis of data from these diverse sources. Only then can one

derive actionable insights and make use of them.

Analytics Engine

With the ground set for making use of the data, a powerful analytics engine must be leveraged to con-

vert it into actionable information. While most traditional systems have the reporting capability, they

provide a historical log and the user may be able to get some of the answers they seek. However, with

the complex and multi-faceted healthcare context, a bigger challenge is problem identification. The ana-

lytics engine should be configured and customized to enable pattern and problem identification. Empow-

ered users will be able to proactively find and fix problems they may not have been aware of earlier.

A few guidelines can be found through quality reporting requirements under PQRS, HEDIS and QPP. The

way measures are chosen under these requirements align with the triple goal of improving care quality,

enhancing access and reducing cost.

While these are a good start, there is more ground to be covered especially in case of niches. Their con-

text should dictate the way the analytics engine is configured and leveraged to derive actionable.

DataMart act as a repository for all the pieces of information pertaining to John’s health received from multi-

ple sources. Marts’ design is very crucial as it impacts analytic / transaction response time. Some possible

ways of designing marts can be based on hospital’s specialisation streams / patient problems / services ren-

dered / financials / Facilities (locations) etc.

Analytic engine can help Jones and Patty to observe patterns in John’s regular A1c test results and predict

any high risk complications based on those. A slight point rise in A1c blood test results can increase the risk

of eye, kidney, and nerve disease complications by over 40%.

If Jones and Patty participate in PQRS and/or QPP, they would be expected to report for CMS122. The an-

alytics engine will help them prescribe tests for John and track them in a timely manner. For instance, the

system could trigger alerts for them to raise a lab order (Hemoglobin A1c/ Hemoglobin.total in Blood by

HPLC, Hemoglobin A1c/ Hemoglobin.total in Blood, Hemoglobin A1c/ Hemoglobin.total in Blood by Electro-

phoresis)), prompting them to check with the labs for John’s results or send a reminder to John about a

lab test. All of the above would ensure that the proper course of care action is followed so that they

achieve a higher score for the performance period.


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Business Process management (BPM) Engine

Taking care of the entire population is as difficult as the number of people involved in the process and

clinical precision is difficult to achieve when it comes to orchestration of the show. Along with the

change in the care paradigm, the process only becomes all the more tricky to achieve as the care teams

are still learning the tricks of the trade.

A solution to this situation is workflow automation. Powerful tools are available that have the potential

to configure real life complex workflows and help users perform required tasks with discipline. For in-

stance, a business process can be setup to monitor and track workflows, having criteria configured for

certain events, which will alert the care team based on selected events, guide their care actions and re-

peat that periodically. This would ensure that the care provisioning resources (including the provider’s

time) are wisely used, driving interventions only when they are warranted.

End User Tools

A robust back end system can pave the way for end users to perform care management activities easily

without feeling burnt out. Streamlined workflows when automated and presented meaningfully to end

users improve adoption of the solution while improving their efficiency.

They can effectively:

Derive learning and choose the problems they would like to address. For instance they can strati-

fy the population, identify the cohorts with high risk associated with them and trace the rea-

sons or the root cause leading to care gaps.

Design programs for the high-risk populations, define the segments to be enrolled into those

programs, run them successfully and observe the effect of those programs on the outcomes.

Plan care teams and assign them populations. Through automation, managing the time of the

care team without missing out on necessary interventions becomes possible.

Reach out to identified populations with personalized content and engage them better to drive

care actions or lifestyle choices resulting in improved health.


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A bo ut Na l a s haa

Nalashaa believes in simple solutions to derive meaningful insights and in exceeding your expectations. Our

clarity of thought has earned us many laurels in this fast paced world where healthcare technology advance-

ments are roll ing out continuously.

A b o u t t h e A u t h o r

Ami t Manra l

Amit is a healthcare enthusiast who is passionate about the application of creative ideas to

improve the healthcare ecosystem. He has been involved with US healthcare for over a

decade and loves to understand challenges of various stakeholders, impact of regulations

on them and figure out ways to leverage technology that wil l impact business positively.


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march 2017 - nalashaa health...population health as defined by c.-e.a. winslow, founder of yale...

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