program and policy strategies to promote healthcare quality for children

Program and Policy Program and Policy Strategies to Promote Strategies to Promote Healthcare Quality for Healthcare Quality for

ChildrenChildren

Lisa A. Simpson, MB, BCh, MPH, FAAPNational Director, Child Health Policy, NICHQ

Endowed Chair, Child Health PolicyUniversity of South Florida

Today’s Popular Policy Today’s Popular Policy PlatformsPlatforms

Pay for Performance Health Information Technology Consumer driven health care

For each…– What do we know about use and/or

its effectiveness overall? – What do we know of its use and/or

effectiveness for children?

Pay for Performance (P4P)Pay for Performance (P4P) Incentive programs that provide monetary

bonuses to eligible participants linked to specific quality and/or efficiency standards established by the program

Initiated by government agencies, employers & health plans to stimulate quality improvement (one of the earliest from Aetna in 1987)

Financial rewards based on achievement related to – evidence-based clinical quality of care measures– patient satisfaction– efficiency/productivity– infrastructure of the practice (including use of

information technologies)

AMA, Physician Pay for Performance Initiatives, 2004.

P4P ProgramsP4P Programs Average incentive payment around 1-5% of a

physician’s total revenue from a given health plan (AMA, 2004)– in Anthem BC/BS (NH) in 2001, average bonus payment

$1,183 and the highest bonus payment $15,320– in IHA program, average group bonus about $200,000 and

will cover 24,000 primary care physicians (200 physician groups & 7 million beneficiaries)

2004 survey findings:– Majority of programs were targeted to PCPs, confined to

HMO, fully insured products with annual bonus incentives based on HEDIS performance measures

– Dramatic growth: November, 2004: 84 programs w/ 39 million beneficiaries March 2005: 104 programs

– By 2006, predicted to increase to 160 programsBaker & Carter, 2005

AMA, Physician Pay for Performance Initiatives, 2004

Key Trends in P4P ProgramsKey Trends in P4P Programs Product Spread:

– Expansion to PPOs & Consumer Directed Healthcare products– Expansion to specialists with use of specialty-specific measures

Changes in Measures:– Use of measures for positive savings (generic substitution &

efficiency)– Supplementing population-based HEDIS measures– Use of scorecards and actionable results reporting to change

behavior– Use of performance results for public reporting– Significant growth in health information technology adoption

measures Changes in types of payments

– Use of adjustable fee schedules instead of annual bonus payments– Return on investment analyses (i.e., what would have been the

financial and clinical outcome in the absence of a P4P program?) Center for Medicare and Medicaid Services as a P4P

market driver

Baker & Carter, Provider Pay-for-Performance Incentive Programs: 2004 National Study Results, 2005.

Landon et al, 2004

PP4P - Pediatric Pay for PP4P - Pediatric Pay for PerformancePerformance

Leapfrog compendium identifies 12 programs (out of 70)– 4 states (IA, RI, UT, WI) - target health plans– Rest target physicians– 3 BC/BS (IL, MA, MO)

States’ use of quality information– Varies by product: HMO and PPO

Rewarding Results

Leapfrog CompendiumLeapfrog Compendium

Focus on:– well visit (child and adolescent)– immunizations– appropriate antibiotic utilization– asthma (self management plans or

medication management)– IT. (not clear if applies to peds)– volume, timeliness, and quality of electronic

encounter data

New Leapfrog Hospital Rewards New Leapfrog Hospital Rewards ProgramProgram

All short term acute care hospitals Five clinical areas including newborn care

accounting for 33% commercial admissions & 20% commercial inpatient spending

Newborn care measures include: – Neonatal mortality– NICU – Process of Care -- 80%+ adherence: antenatal steroids for

certain high-risk deliveries– 3rd/4th degree lacerations – Computerized physician order entry (CPOE) system– Leapfrog Quality Index (NQF Safe Practices)

Factors in Determining Compensation Factors in Determining Compensation Florida Child Health Provider, 2005Florida Child Health Provider, 2005

Not a Factor (%)

Minor Factor (%)

Major Factor (%)

Use of clinical

IT 71.5 23.2 5.3

Email consultation

with patients

No

96.2

Yes, Health plan/HMO

2.1

Yes, Other

1.7

Note: sample size varies by question, overall N=1219

Effectiveness of Pediatric PFP Programs: Effectiveness of Pediatric PFP Programs: RCT’sRCT’s

Citation (abbr.) Focus

Physicians/Practices Assigned (N) Reward

Differences Between Groups

Davidson (1992)

Well-child Recommendations

Enhanced FFS (40)Control (40)

Higher reimbursement rates for all in FFS

No

Hillman (1999)

Well-child Recommendations & Immunizations

Bonus + Feedback (19)Feedback only (17)Control (17)

Bonus based on rank & degree of improvement

No (but all groups improved over time)

Fairbrother (2001)

Childhood Immunizations

Enhanced FFS (12)Bonus + Feedback (24)Feedback only (21)

Bonus based oncompliance rates

Overall improvement in FFS & bonus groups


Pay for Performance Health Information Technology Consumer driven health care

For each…– What do we know about use or its

effectiveness overall? – What do we know of its use or


Health Information Technology Health Information Technology (IT) Adoption by Physicians(IT) Adoption by Physicians

Physicians either routinely or occasionally use:– 79% electronic billing– 59% electronic access to patients' test results either

routinely or occasionally– 27% EMRs and electronic ordering of tests,

procedures, or drugs – 21% have automated patient reminders regarding

routine preventive care– 7% e-mail with other doctors– 6% electronic clinical decision support systems – 3% email with patients

Top 3 reported barriers – costs of system start-up and maintenance– lack of local, regional, and national standards – lack of time to consider acquiring, implementing, and

using a new systemAudet et al, Medscape 2004 and Health Affairs, 2005

““Unique” Issues for ChildrenUnique” Issues for Children

Not so unique at the technical level Differences emerge in

– Market availability– Policy focus– Adoption of HIT applications

Child Health Provider Adoption of HIT Child Health Provider Adoption of HIT Total & by Gender, Florida, 2005Total & by Gender, Florida, 2005

Methods– Mailed survey (two waves) between March

and May 2005– All licensed primary care physicians

(MD/DOs) and a 25% sample of ambulatory subspecialists

– N=1219 child health provider respondents Primary care pediatrics, family medicine and

pediatric subspecialists serving >0% children

Child Health Provider Adoption of HIT Child Health Provider Adoption of HIT Total & by Gender, Florida, 2005Total & by Gender, Florida, 2005

Routine office

computer use

Routine PDA use

Email use with

patients

Routine EHR use

Total 80.2% 40.1% 18.0% 24.3%

Male 81.2 44.5 18.6 26.5

Female 75.4 31.6 14.5 22.5

p value .046* <.001* .127 .186


Percent Adoption of HIT by Medical Training Percent Adoption of HIT by Medical Training Florida Child Health Providers, 2005Florida Child Health Providers, 2005

Primary CareRoutine office

computer use

Routine PDA use

Email use with

patients

Routine EHR use

Primary Care

Pediatrics79.9 38.4 14.3 17.0

Family Medicine

78.4 42.2 21.9 26.8

Other 86.7 38.4 16.4 36.4

p value .052 .419 .005* <.001*


Adoption of HIT by Provider Age Adoption of HIT by Provider Age Florida Child Health Providers, 2005Florida Child Health Providers, 2005

Age (years)Routine office

computer use

Routine PDA use

Email use with

patients

Routine EHR use

<40 79.8 40.2 11.5 27.9

40-59 81.8 42.5 20.8 26.9

60+ 67.9 29.3 12.4 17.1

p value .003* .029* .008* .081


Adoption of HIT by Provider RaceAdoption of HIT by Provider RaceFlorida Child Health Providers, 2005Florida Child Health Providers, 2005

RaceRoutine office

computer use

Routine PDA use

Email use with

patients

Routine EHR use

White 80.3 39.2 19.9 26.2

Black 77.8 47.7 13.3 21.4

Hispanic 81.5 41.2 15.2 20.0

Asian 79.4 37.9 9.4 23.1

Other/Unknown

79.3 50.0 20.7 14.3

p value .982 .597 .059 .269


Adoption of HIT by Practice SizeAdoption of HIT by Practice SizeFlorida Child Health Providers, 2005Florida Child Health Providers, 2005

No. of Physicians

Routine office

computer use

Routine PDA use

Email use with

patients

Routine EHR use

Solo 76.0 34.6 17.3 17.7

2-9 79.0 39.9 17.5 22.4

10-49 91.5 52.2 20.8 43.9

50+ 97.4 68.8 32.4 64.9

p value <.001* <.001* .110 <.001*


Adoption of HIT By Practice TypeAdoption of HIT By Practice TypeFlorida Child Health Providers, 2005Florida Child Health Providers, 2005

TypeRoutine office

computer use

Routine PDA use

Email use with

patients

Routine EHR use

Single-specialty

74.1 35.9 17.0 19.5

Multi-specialty

91.1 51.4 23.4 41.4

p value <.001* .002* .100 <.001*


Adoption of HIT By Medicaid VolumeAdoption of HIT By Medicaid VolumeFlorida Child Health Providers, 2005Florida Child Health Providers, 2005

Medicaid Providers

Routine office

computer use

Routine PDA use

Email use with

patients

Routine EHR use

Low-volume 77.1 30.7 20.0 24.5

High-volume (at least 20%

Medicaid)81.8 44.4 13.5 22.0

p value .145 <.001* .028* .460



Pay for Performance Health Information Technology Consumer Driven Health Care

For each…– What do we know about use or its

effectiveness overall? – What do we know of its use or


Consumer Use of Consumer Use of Quality InformationQuality Information

Consumer driven health care shifts more financial responsibility to consumers on the assumption that this will drive better decisions

Several initiatives to publicly report performance– Medicare driven– State driven

Having an abundance of information does not always translate into its use to inform choices

All health care decisions – plan, provider, treatment requires the use of information that: – Includes technical terms and complex ideas– Compares multiple options on several variables– Requires the consumer to differentially weight the various

factors according to individual values, preferences & and needs

Information presentation has a significant effect on impact and use

Hibbard & Peters, Annual Reviews of Public Health (2003)

Where Consumers FindWhere Consumers FindQuality InformationQuality Information

KFF/AHRQ/Harvard School of Public Health. Chart 7. National Survey on Consumers’ Experiences with Patient Safety & Quality Information, November 2004

(Conducted July7 – Sept 5, 2004)

Percent who say they would be "very likely" to do each to try to find health care quality information...

16%

18%

20%

36%

36%

37%

65%

65%

Refer to a section of the newspaper or magazine thatlists quality information

Contact a state agency

Order a printed booklet with quality information byphone, mail, or online

Contact someone at their health plan, or refer tomaterials provided by the plan

Contact the Medicare program (age 65+)

Go online to an Internet web site that posts qualityinformation

Ask their doctor, nurse or other health professional

Ask friends, family members or co-workers

Consumer Exposure Consumer Exposure to Quality Informationto Quality Information

Percent who say they saw information in the past year comparing quality among...

9%

15%

23%

11%

22%

28%

Doctors

Hospitals

Health insuranceplans

2004

2000

27%

35%

Percent who saythey saw

information onANY of the

above...



Consumer Use Consumer Use of Quality Informationof Quality Information



Percent who say they saw quality information in the past year and used this information to make health

care decisions...

12%

19%

2000

2004

Importance of Quality RatingsImportance of Quality Ratings

4846 45

49

61

33

50

38

4745

62

32

76

20

52

43

72

25

Surgeon who hastreated

friends/family

Surgeon that israted higher

Plan recommendedby friends

Plan highly ratedby experts

Hospital that isfamiliar

Hospital that israted higher

2004

2000

1996



Parental Use of Quality Parental Use of Quality InformationInformation

Little research specifically looking at this

CAHPS related research points to similarities

Existing evidence points to even greater difficulties for children due to– Poverty– Low educational attainment– LEP

ConclusionsConclusions

Current policy strategies have been less well thought out/tested in child health populations

CHSR community has opportunity to develop more evidence on these questions

program and policy strategies to promote healthcare quality for children

Documents