elliott fisher | monitoring variation in health care
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Monitoring variation in healthcare quality -an evidence base to improve healthcare
HARC is a as a partnership between the Sax Institute, Clinical Excellence Commission and the Greater Metropolitan Clinical Taskforce
Welcome to the 5th HARC Forum
Professor Elliott FisherProfessor of Community and Family Medicine at Dartmouth Medical School and Director of the Center for Health Policy Research at the Dartmouth Institute for Health Policy and Clinical Practice
US Dartmouth Atlas of Health Care Project -monitoring and explaining variation in healthcare to improve the health system
Keynote Speaker
Monitoring Variation in Health Care: An approach to improving the
evidence base for practice and policy
Elliott S. Fisher, MD, MPH
Professor of Medicine and Communityand Family Medicine
Dartmouth Medical School
Director for Population Health and PolicyThe Dartmouth Institute for Health Policy
and Clinical Practice
The usual suspects:Rising costsUneven qualityDeclining access to care
Houston, we’ve got a problem…
Some looming challengesLoss of professional authority of physiciansIntegrity and relevance of academic medicine
Traditional diagnoses:A shortage of moneyA shortage of doctorsA shortage of economists
Houston, we’ve got a problem…
Prescriptions:Spend moreTrain moreFocus on prices
Every system is perfectly designed to get theresults that it achieves
Paul Batalden
Insanity: doing the same thing day after day andexpecting different results
Einstein
Rethinking health careOrigins of the Dartmouth Institute – and Dartmouth Atlas Project
Science, December 14, 1973; Volume 182, pp 1102-08
Rethinking health careA simple analytic framework; a shared vision
Application of epidemiologic methods to health care servicesDefine population at riskDefine eventsExamine variations across relevant systems -- providersAsk good questions
Organizational DevelopmentIndependent institute within Medical SchoolInterdisciplinary research group; all with departmental appointmentsGovernance through a shared vision:
Exploring the causes and consequences of unwarranted variationsCommitment to making a difference (locally, regionally, nationally)
Major long-term funding helps maintain focus
Rethinking health careThe Dartmouth Atlas of Health Care
Methods:Population at risk – over 65Compare Hospital Referral RegionsEvents of interest -- many
Rethinking health careThe Dartmouth Atlas of Health Care
Categories of careSafe and effective carePreference sensitive careSupply-sensitive care
3.0
5.0
7.0
9.0
11.0
13.0
15.0
TUR
P fo
r BPH
Rethinking health carePreference-sensitive care Transurethral Prostatectomy for
Benign Prostatic Hypertrophy per 1000
2.0
4.0
6.0
8.0
10.0
12.0
30-D
ay M
orta
lity
Follo
win
g C
AB
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Rethinking health careSafe and Effective Care
30 Day Mortality Following CABG
5,000
7,000
9,000
11,000
13,000
15,000
Med
icar
e sp
endi
ng p
er e
nrol
lee
Rethinking health careSpending – and supply sensitive care
Medicare Spending per capita
20,000
40,000
60,000
80,000
100,000
120,000
Inpa
tient
+ P
art B
spe
ndin
g pe
r dec
eden
t
UCLA Medical Center 72,793New York-Presbyterian 69,962Johns Hopkins 60,653UCSF Medical Center 56,859Univ. of Washington 50,716Mass. General 47,880Barnes-Jewish 44,463Duke University Hosp. 37,765Mayo Clinic (St. Mary's) 37,271Cleveland Clinic 35,455
Rethinking health careSpending – and supply sensitive care Hospital and Physician Spending
last 2 years of life at USN&WR top 10 hospitals
How can the best medical care in the world cost twice as much as the best medical care in the world?
Uwe Reinhardt
1. What we know – 3 case studies2. What I think we’ve learned3. Translating evidence to policy4. Is there reason for hope?
Rethinking health careThe Dartmouth Atlas of Health Care
Preference Sensitive CareBuilding the evidence: the Prostate Patient Outcome Research TeamExploring the causes of variations in TURP for BPHInterdisciplinary team; multiple methods
Focus groups of urologists to determine clinical theoriesPreventive hypothesis: must operate early in a progressive diseaseQuality of life hypothesis
Clinical research: decision-analysis, cohort studiesNo survival benefit from surgeryBenefit of surgery depends upon patients’ values (symptoms vs sexual
dysfunction)Patients’ values differed dramatically
Implications:Broadly applicable – orthopedics, cardiology, oncology, etcNeed for accurate information on risks and benefitsStructured approach to supporting informed patient choiceStudies have now demonstrated effectiveness of decision aids
Preference Sensitive CareBuilding the evidence: the Prostate PORT
Interdisciplinary team; multiple methodsFocus groups of urologists to determine clinical theories
Preventive hypothesis: must operate early in a progressive diseaseQuality of life hypothesis
Clinical research: decision-analysis, cohort studiesNo survival benefit from surgeryBenefit of surgery depends upon patients’ values (symptoms vs sexual
dysfunction)Patients’ values differed dramatically
Implications:Broadly applicable – orthopedics, cardiology, oncology, etcNeed for accurate information on risks and benefitsStructured approach to supporting informed patient choiceStudies have now demonstrated effectiveness of decision aids
Preference Sensitive CareTranslating evidence into policy
Underlying problemsInadequate information on risks and benefits of biologically targeted treatmentsProvider-dominated decision-making
RemediesOutcomes research (comparative effectiveness)Informed patient choice
Policy implications and progressMajor investment in comparative effectiveness researchNational standards now include informed choice as core quality measureMany integrated delivery systems are moving to adopt shared decision-makingStates moving to require informed patient choice as legal standard
Safe and Effective carePopulation: Patients undergoing Coronary Artery Bypass GraftProviders: Cardiovascular surgery centers in New England
Fletcher Allen Health Care
Eastern Maine Medical Center
Maine Medical Center
Dartmouth Hitchcock Medical Center
Concord Hospital
Northern New England Cardiovascular Disease
Study Group
Origins: threatened public report of unadjusted CABG mortality rates
New England rates varied two fold: 3.1% to 6.3%
Surgeons agreed to collect relevant clinical data
Safe and Effective carePopulation: Patients undergoing Coronary Artery Bypass GraftProviders: Cardiovascular surgery centers in New England
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1 2 3 4 5Center
In-H
ospi
tal M
orta
lity
Rat
e
O’Connor et al, JAMA, 1991;266:803-809
Adjusted mortality no less variable:
2.3% to 6.3%
Near death experience of study group
Now over 20 years ofexperience; 100+papers published; allsites still participatingin 3 meetings per year
Safe and Effective CareImprovement achieved as research advanced
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1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999Year
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talit
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Mode of death study- low output heart failure major cause of in-hospital mortality
Process mapping and identification of high leverage areas
Initial intervention-data feedback, site visits and CQI training
Safe and Effective CareTranslating evidence into policy
Underlying problemsInadequate data: on patient attributes, process of care and outcomesSmall numbers, lack of follow-up prevent learningFlawed professional model: individual responsibility and autonomy
RemedyTechnical: registries to support ongoing study of variation in outcomes
Define relevant local care system / teams (to allow comparison with others)Measure and compare processes and outcomes
Cultural: create teams and systems capable of learningEngage clinicians in practice-based research and improvementEnable reflective practice – timely, relevant feedback
Policy implications and progressPotential benefits – to patients, physicians, managers and policy-makers -- of
practice-based research networks is substantialLack of government support remains challenge. Most efforts are voluntary, self-
funded.
Variations in spendingBuilding the evidence base
“How can the best medicalcare in the world cost twiceas much as the best medicalcare in the world?
Health implications of variations in spendingStudy population: Medicare patients with AMI, colon cancer, hip fracture Comparison: across (1) regions; (2) academic medical centers – grouped
according to “intensity” – price and illness adjusted spending. Measures: content, quality and outcomes of care
(1) Fisher et al. Ann Intern Med: 2003; 138: 273-298 (2) Baicker et al. Health Affairs web exclusives, October 7, 2004(3) Fisher et al. Health Affairs, web exclusives, Nov 16, 2005(4) Skinner et al. Health Affairs web exclusives, Feb 7, 2006(5) Sirovich et al Ann Intern Med: 2006; 144: 641-649(6) Fowler et al. JAMA: 299: 2406-2412
Variations in spendingBuilding the evidence base
Robert Wood Johnson FoundationNational Institute of AgingCalifornia Healthcare FoundationAetna FoundationWellpoint FoundationUnited Healthcare Foundation
1.00 1.5 2.00.5 2.5
Reperfusion in 12 hours (Heart attack)Effective Care: benefit clear for all
Ratio of rate in high spending to low spending regions
Preference Sensitive: values matter
Supply sensitive: often avoidable care
Evaluation and Management (visits)ImagingDiagnostic Tests
Inpatient Days in ICU or CCUTotal Inpatient Days
Total Hip ReplacementTotal Knee ReplacementBack SurgeryCABG following heart attack
Aspirin at admission (Heart attack)Mammogram, Women 65-69Pap Smear, Women 65+Pneumococcal Immunization (ever)
If bar on this side higher spending regions get more
What do they get more of?
Outcomes and QualityHigh spending compared to low spending regions
(1) Fisher et al. Ann Intern Med: 2003; 138: 273-298 (2) Baicker et al. Health Affairs web exclusives, October 7, 2004(3) Fisher et al. Health Affairs, web exclusives, Nov 16, 2005(4) Skinner et al. Health Affairs web exclusives, Feb 7, 2006(5) Sirovich et al Ann Intern Med: 2006; 144: 641-649(6) Fowler et al. JAMA: 299: 2406-2412
Health Outcomes
No gain in survival
No better function
Physician’s Perceptions
Worse communication
Greater difficulty ensuring coordination
Greater perception of scarcity
Patient-Perceived Quality
Lower satisfaction with hospital care
Worse access to primary care
No sense that care is rationed
The paradox of plentyPop Quiz….
If we cut spending so that all U.S. regions were receiving the same per-capita amount as the lowest spending regions, which of the following would apply:
1. U.S. healthcare spending would fall by 20% to 30%
2. The Medicare Trust Fund might survive a few years past it’s predicted collapse in 2017 (the year I become eligible).
3. We could send a third of the U.S. healthcare workforce to Africa and improve the health of both continents.
4. All of the above.
Assumption that more is better
Inadequate information on risks and benefits
Growing tension between science and professionalism --and -- market approach (health care as a commodity)
Variations in spendingWhat’s going on? General attributes of U.S. health care
Patient Demand
Little difference
Malpractice
Less than 10% of difference
Variations in spendingWhat’s going on? Exploring causes of regional variations
Patient Demand
Little difference
Malpractice
Less than 10% of difference
Supply & payment
Powerful influence
Explains less than 50% of difference
Variations in spendingWhat’s going on? Exploring causes of regional variations
Patient Demand
Little difference
Malpractice
Less than 10% of difference
Supply & payment
Powerful influence
Explains less than 50% of difference
1.0
3.0
4.0
10
40
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30
202.0
Hospital Beds Medical SpecialistsLow High Low High
32% higher
65% higher
RegionalSpending
Variations in spendingWhat’s going on? Exploring causes of regional variations
Patient Demand
Little difference
Malpractice
Less than 10% of difference
Supply & payment
Powerful influence
Explains less than 50% of difference
Variations in spendingWhat’s going on? Exploring causes of regional variations
Patient Demand
Little difference
Malpractice
Less than 10% of difference
Supply & payment
Powerful influence
Explains less than 50% of difference
New York TimesAugust 18, 2006
Variations in spendingWhat’s going on? Exploring causes of regional variations
Patient Demand
Little difference
Malpractice
Less than 10% of difference
Supply & payment
Powerful influence
Explains less than 50% of difference
Variations in spendingWhat’s going on? Exploring causes of regional variations
Evidence-based decisions – drawn from guidelinesDoctors sometimes disagreed – but was unrelated to regional differences in spending
Gray area decisions (more judgment required): For a patient with well-controlled high blood pressure and no other medical problems, when would you schedule the next visit?
Variations in spendingExploring causes -- gray area decisions
Physician - PatientEncounter
Clinical EvidenceProfessionalism
Clinical evidence is an important -- but limited --influence on clinical decision-making.
Consequence: reasonable individual clinical and local decisions lead, in aggregate, to higher utilization rates,greater costs -- and inadvertently -- worse outcomes
Physicians practice within a local organizationalcontext that profoundly influences their decision-making.
Payment system ensures that existing capacity is fully utilized. Physicians adapt to available resources:more referrals, more admissions, more ICU stays
Policy Environment(e.g. payment system)
LocalOrganizational Context(e.g. capacity - culture)
The more complicated care becomes, the more likely mistakes are to occur.
Hospitals are dangerous places if you don’t need to be there.
Variations in spendingExploring causes -- gray area decisions
Culture? Capacity? Both?Differences in spending and practice across top academic centers
Medicare beneficiaries with chronic illness, 2001-2005
2006 Spending 92-06 GrowthMcAllen $14,946 8.3%La Crosse $5,812 3.9%
Variations in spendingExploring causes: case studies beginning to shed light
“Here … a medical community came to treat patients the way subprime mortgage lenders treated home buyers: as profit centers.”
Atul Gawande
2006 Spending 92-06 GrowthMcAllen $14,946 8.3%La Crosse $5,812 3.9%
Variations in spendingExploring causes: case studies beginning to shed light
“…a culture that focuses on the wellbeing of the community, not just the financial health of our system.”
Jeff Thompson, MDCEO Gunderson-Lutheran
La Crosse, WI
“Here … a medical community came to treat patients the way subprime mortgage lenders treated home buyers: as profit centers.”
Atul Gawande
2006 Spending 92-06 GrowthMcAllen $14,946 8.3%La Crosse $5,812 3.9%
Variations in spendingExploring causes: case studies beginning to shed light
Organizatione.g. capacity, policies
practices, norms
Environmente,g, payment, regulations
measures, culture
Micro-systemHow care is provided
to each patient
Aims
Institute of Medicine: Crossing the Quality Chasm
La Crosse McAllen
What I think we knowPutting the pieces together: the IOM system of effect
Flawed conceptual model. Healthis produced by individual actions of“good” clinicians, working hard.
New model: It’s the system. Establish teams and organizations accountable for aims and capable of improving practice
Wrong incentives reinforce model, reward fragmentation, induce morecare and entrepreneurial behavior.
Rethink our incentives: Realign incentives – both financial and professional – with aims.
Underlying problem Key principles
41
Confusion about aims – what we’re trying to produce
Clarify aims: Better health, better carelower costs
Bad data allow MDs to discount it, and public to assume that medicine is science and that more is better.
Better information that engages physicians, creates tension for change, supports improvement; informs consumers
What I think we knowUnderlying problems – and principles to guide reform
Emerging alignment on aims: National Priorities PartnersImproving population healthImproving safety & reliability and coordination of careEngaging patients in managing their care and making informed decisionsEliminating overuse
Performance measurement: the critical leverNational Quality Forum “Episode measurement framework”Key notions
Core question: how did the patient do over the relevant time-course? Value: best judged from the patient’s perspective; is multidimensionalRequires organizational accountability – over time
Translating evidence to policyAims and Performance Measurement
Getting Better Living w/ Illness/Disability (T1)Coping w/ End of Life (T2)Staying Healthy
Post Acute/Rehabilitation Phase
20 Prevention
Episode begins –onset of symptoms
Post AMI Trajectory 2 (T2)Adult with multiple co-morbidities
Focus on:• Quality of Life• Functional Status• 20 Prevention Strategies• Advanced Care Planning• Advanced Directives• Palliative Care/Symptom Control
Assessment ofPreferences
AcutePhase
PHASE 1
PHASE 2 PHASE 3 PHASE 4
Episode ends –1 year post AMI
20 Prevention(CAD with prior AMI)Advanced Care Planning
Population at Risk 10 Prevention(no known CAD)
20 Prevention(CAD no prior AMI)
Post AMI Trajectory 1 (T1)Relatively healthy adult
Focus on:• Quality of Life• Functional Status• 20 Prevention Strategies• Rehabilitation• Advanced care planning
© NQF
Traditional modelAutonomy
Individual Responsibility
Needed modelAccountability
Shared Responsibility
Translating evidence to policyPerformance Measurement – across episodes
Effective registries are thus critical for a learning health system
To learn -- we need to know:Patient attributes and risks (including biologic markers)Specific targeted biologic interventions performedAttributes of system -- delivery methods -- where care providedHealth outcomes, patient experience and costs
Infrastructure would support Comparative effectiveness research: compare biologic and delivery
system interventions, controlling for patient and local attributes.Comparative performance assessment: compare providers and local
systems, controlling for patient attributes
Both are critical
Translating evidence to policyImplications for Health Information Technology
Accountable Care Organizations
Principles: Establish provider organizations that can effectively manage the full
continuum of care as a real or virtually integrated local delivery systemPerformance measurement – to support improvement and accountabilityPayment reform: establish target spending levels; shared savings
Potential ACOs Integrated delivery systems (Kaiser-Permanente, Group Health)Physician Networks; Hospital that employ primary care physiciansInsight from research:
Most physicians already practice within coherent local networksPerformance measurement at group level feasible Feasible to develop spending targets for most U.S. networks
Translating evidence to policyOrganizational Accountability and Payment Reforms
Fisher et al. Creating Accountable Care Organizations, Health Affairs 26(1) 2007:w44-w57.
Early pilots promising; many organizations supportivePhysician Group Practice demonstration successfulCongressional Budget Office scored as cost-savingSupport from key stakeholders has solidified
ACOs accepted as component of current billsSupport for extensive pilots, rapid expansion in House billsSenate Finance – voluntary program (not pilot) by 2012
Initiatives at state and local levelBrookings-Dartmouth supporting pilot development in multiple sitesPilots to start January 2010 in two (or more) sites (VA, KY, TX)Learning collaborative underway with 40+ health systemsMassachusetts, Vermont, others moving forward
Translating evidence to policyOrganizational Accountability and Payment Reforms
1. What we know – 3 stories2. What I think I know3. From insight to action4. Is there reason for hope?
Rethinking health careThe Dartmouth Atlas of Health Care
Health care is a complex adaptive systemAutonomous actors continuously adapt their behaviorSystem held in place by “attractors”, self-reinforcing behaviors
Change in complex systems occurs through: Exploring variation and paradox to create a tension for change;Creating better alternatives (better policies, better models of care)Supporting interaction and learning – so others can see new ways to goNew attractors (performance measurement, payment, positive deviants)
Implications for research – and policyPublic reporting: creates a tension for change, raises good questionsPolicy relevant research: has undermined flawed assumptions;
suggested path toward reformRegistries, practice networks, have developed evidence, engaged
clinicians, engaged local systems and communities
48
Is there reason for hope?Theories of change – can they help frame our thinking
Everett, WASacramento, CALa Crosse, WICedar Rapids, IATemple, TX
Portland, MESayre, PARichmond, VAAsheville, NCTallahassee, FL
“How do they do that?”conference
Lighter colors = lower spending
Common themesShared aims, accountable to communityStrong foundation of primary carePhysician engagement as leadersOrganizational support importantUse of data to drive change
Is there reason for hope?Theories of change – have stimulated new conversations
Everett, WASacramento, CALa Crosse, WICedar Rapids, IATemple, TX
Portland, MESayre, PARichmond, VAAsheville, NCTallahassee, FL
“How do they do that?”conference
Lighter colors = lower spending
Common themesShared aims, accountable to communityPhysician engagement as leadersStrong foundation of primary careOrganizational support importantUse of data to drive changeHigh self-efficacy; high morale
Is there reason for hope?Theories of change – have stimulated new conversations
1973 2009
Trends in important things in U.S. healthcare
uninsured, spending
1983
Have we made a difference?
1973 2009
Trends in important things in U.S. healthcare
insights, evidence, tests of change
1983
Have we made a difference?
Flawed conceptual model. Healthis produced by individual actions of“good” clinicians, working hard.
New model: It’s the system. Establish teams and organizations accountable for aims and capable of improving practice
Wrong incentives reinforce model, reward fragmentation, induce morecare and entrepreneurial behavior.
Rethink our incentives: Realign incentives – both financial and professional – with aims. Question payfor performance.
Underlying problem Key principles
54
Confusion about aims – what we’re trying to produce
Clarify aims: Better health, better carelower costs
Bad data allow MDs to discount it, and public to assume that medicine is science and that more is better.
Better information that engages physicians, creates tension for change, supports improvement; informs consumers
Have we made a difference? Exploring variation has helped to advance knowledge and policy
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