How data can improve health careWhat we don’t know can hurt us

Gov 2.0

September 10, 2009Elliott Fisher, MD, MPHDirector, Population Health and PolicyThe Dartmouth Institute for Health Policy and Clinical Practice

11

The current conundrum

Rising costs a serious threatMedicare Trust Fund – runs dry 2017

Cost of family coverage projected to double ($12,298 to $23,842 by 2020)

Two million Americans affected by medical bankruptcy each year

BarriersFear of rationing, of change, that lower cost = lower quality

Ignorance of where the money’s going in health careof how to do better

Data can help: four examplesRegional variations in spending and quality: where’s the waste?

Identifying high-performing systems -- from whom we can learn

Supporting change in clinical practice

Motivating change in health systems

Per-capita Medicare SpendingTrends: 1992 to 2006

Miami 5.0

Salem, OR 2.3

E. Long Island 4.0

Boston 3.0San Francisco 2.4

Annual GrowthRate

Source: Slowing the Growth of Health Care Spending: Lessons from Regional Variation. Fisher, Skinner, Bynum, New England Journal of Medicine, February 26, 2009

US Avg 3.5

33

What does higher spending buy?(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

Not better care orbetter outcomes

44

More “supply-sensitive services”

Lack of support for improvement, care management and coordination.

Local organizational support: Develop virtual or real integrated systems to support practice.

Payment system that rewards morecare, increased capacity, high margintreatments, entrepreneurial behavior.

Payment reform: foster accountability for capacity – and behavior: capitation or global shared savings.

Underlying problem Key principles

Moving forwardAddressing the underlying causes of rising costs, poor quality

55

Failure to recognize role of localsystem (e.g. capacity) as cost-driver.

Local accountability: Fosteraccountability for total costs – and capacity at local level.

Assumption that more is better.Equating less care with rationing.

Measurement: Comprehensive performance measures: outcomes, patient experience.

Data on regional performanceMarked variations highlight opportunities to improve

66

Everett, WASacramento, CALa Crosse, WICedar Rapids, IATemple, TX

Portland, MESayre, PARichmond, VAAsheville, NCTallahassee, FL

“How do they do that?”conference

Lighter colors = lower spending

Partici-pants

Qualifying Regions

All Others

Medicare Spending

$6,773 $7,098 $8,562

Hospital Days

1.52 1.56 1.90

Spending for Imaging(last 2 yrs)

$633 $662 $843

Hospital Quality Score

95% 95% 93%

Benchmarks of efficiencyPotential savings from achieving high performance

77

Everett, WASacramento, CALa Crosse, WICedar Rapids, IATemple, TX

Portland, MESayre, PARichmond, VAAsheville, NCTallahassee, FL

Category of Care

Potential Savings

Medicare spending

16%

Hospital days 17%

Specialist visits 36%

“How do they do that?”conference

Lighter colors = lower spending

How do they do that?Some preliminary insights

Common elements across regionsShared aims; “accountable” to the community;

Physician engagement as leaders; support for professional values

Strong primary care foundation

Use of data to support work; professional feedback; peer review

Data feedback – a critical componentOrganizational accountability – integrated systems to support feedback

Data itself – actual performance of providers

Data to improve qualitySupport for process management

Ch 7. BC James, JS Lazar. A health system’s use of clinical programs to build quality infrastructure. In: Practice-Based Learning and Improvement Second Edition. EC Nelson, PB Batalden, JS Lazar, Eds.

Intermountain Health Care

Focus on managing defined clinical populations

Care pathways defined by multi-disciplinary team

Protocols implemented through EHR with process, outcome tracking and feedback

Scientific review / updating on monthly basis.

Data to address variationsPartners Healthcare

Stafford RS Am J Heart 2003, 145:979-85.

Physician level (n = 117) Low: 0.0% High: 24.6%

Practice level (n = 10) Low: 1.0% High: 8.1%

Baseline variation in ordering

Impact of Individualized Feedback and Education.

Data to address variationsPartners Healthcare

May 29, 2008 Presentation at Federal Trade CommissionTom Lee, MD (Partners Healthcare System) (with permission)

And, perhaps, to stimulate changeMcAllen vs El Paso