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Policy Implications of Mapping Healthcare Outcomes

Policy Implications of Mapping Healthcare Outcomes. John D Rockefeller JD MPH Associate Dean and Lecturer Geisel School of Medicine Dartmouth College. 4TH LATIN AMERICAN MEETING ON THE RIGHT TO HEALTH AND HEALTH SYSTEMS, Bogotá, Colombia. April 2 to 4, 2014.

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Policy Implications of Mapping Healthcare Outcomes

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  1. Policy Implications of Mapping Healthcare Outcomes John D Rockefeller JD MPH Associate Dean and Lecturer Geisel School of Medicine Dartmouth College 4TH LATIN AMERICAN MEETING ON THE RIGHT TO HEALTH AND HEALTH SYSTEMS, Bogotá, Colombia. April 2 to 4, 2014

  2. 1973 – Measuring Health Care in Vermont Wennberg J, Gittelsohn A. Small area variations in health care delivery. Science 1973;182:1102-8.

  3. 1993: From the ashes of the Clinton Health Care Reform was born the Dartmouth Atlas of Health Care

  4. 2014: The Dartmouth Atlas of Health Care The Dartmouth Atlas of Health Care provides national public reporting of health system performance over time through the lens of variation in utilization, cost, quality, and patient experience. The Atlas highlights variation, its causes, and its consequences in order to provide target audiences with compelling data to effect positive changes in the health care system. 6 billion Medicare claims a year x many many years of data = lots of terabytes of data www.dartmouthatlas.org Current Funders Robert Wood Johnson Foundation California HealthCare Foundation Charles H. Hood Foundation

  5. Medicare is terrifically important, but so too are other populations:(U.S. Population by Insurance Type – 2010) Age < 19 19-25 26-34 35-44 45-54 55-64 ≥ 65 Medicaid Medicare fee-for-service Private/commercial Medicare “HMO” Uninsured Population: 79m 30m 37m 40m 44m 37m 39m Total Population = 305 million

  6. David Goodman, MD MS (Co-PI) Elliott Fisher, MD MPH (Co-PI) Jonathan Skinner, PhD John Wennberg, MD MPH (Founder) Kristen Bronner, MA (Managing Editor) Scott Chasan-Taber, PhD (Director of Atlas Analytics) Julie Bynum, MD MPH Nancy Morden, MD MPH Shannon Brownlee, MS Chiang-hua Chang, PhD Therese Stukel, PhD Jeff Munson, MD John Erik-Bell, MD MS Douglas Staiger, PhD James Weinstein, MD MS Phil Goodney, MD MS The Dartmouth Atlas of Health Care Faculty (a dynamic cohort) Leadership Group The Amazing Staff Nancy Marth, MS Sally Sharp, SM Jeremy Smith, MPH Yunjie Song, PhD Dean Stanley, RHCE Andrew Toler, MS Stephanie Tomlin, MPA Rebecca Zaha, MPH Weiping Zhou, MS Elisabeth Bryan, MS Thomas Bubolz, PhD Donald Carmichael, MDiv Julie Doherty Jennifer Dong, MS Daniel Gottlieb, MS JiaLan, MS Martha Lane, MA Stephanie Raymond, MA

  7. Price-adjusted Medicare spending per beneficiaryamong hospital referral regions (2010) $10,420 to 13,830 (61) 9,770 to < 10,420 (62) 8,920 to < 9,770 (60) 8,100 to < 8,920 (61) 6,910 to < 8,100 (62) Not populated

  8. What causes the variation in spending? What is the right rate? How can we make fair comparisons? Are there different causes of variation in utilization? How can we improve the value of health care?

  9. Percent of Medicare diabetics with eye examshospital service areas (2010) Effective care

  10. tdi.dartmouth.edu October 15, 2013

  11. Use of drugs to treat osteoporosis following fragility fracture among hospital referral regions (2006-10) 17 .4 to 28 .1% (48) 15 .2 to < 17 .4% (50) 13 .8 to < 15 .2% (46) 12 .3 to < 13 .8% (50) 6 .8 to < 12 .3% (48) Insufficient data (64) Not populated Effective care

  12. Use of beta-blockers 7-12 months following discharge for AMI (2008-10) 92 % or More (0) 84 % to < 92 % (42) 76 % to < 84 % (164) 68 % to < 76 % (86) Less than 68% (13) Insufficient data (1) Not populated Effective care

  13. Quality Dartboards for large Northern New England hospital service areasChildren < 18 yrs – all payer claims data, 2007-10 average

  14. Quality Dartboards for large Northern New England hospital service areasChildren < 18 yrs – all payer claims data, 2007-10 average

  15. Variation in Effective Care • The choice of service is dictated by strong evidence of effectiveness for almost all targeted patients. • The benefits almost always outweigh any adverse effects. • Risk adjustment is often not necessary. • The right rate is usually obvious.

  16. TURP for BPH discharges per 1,000 male Medicare enrollees (2007)age-sex-race adjusted 3.0 2.5 2.0 Ratio of TURP for BPH rate to U.S. average 1.5 1.0 0.5 0.0 Idaho Falls, ID 2.79 Panama City, FL 2.56 Gulfport, MS 2.46 Boston, MA 1.19 St. Louis, MO 1.07 Camden, NJ 1.07 Houston, TX 1.05 Los Angeles, CA 1.04 Manhattan, NY 1.03 Philadelphia, PA 1.01 Indianapolis, IN 1.00 East Long Island, NY 0.82 Orlando, FL 0.77 Atlanta, GA 0.71 Dallas, TX 0.62 Salinas, CA 0.24 Red dots indicate highest 3, lowest, and HRRs with at least 300,000 FFS Medicare beneficiaries

  17. Preference-Sensitive Care • Involves tradeoffs. • Scientific uncertainty often substantial. • The effect of supply (e.g. physicians) is variable. • Patient and provider values are often different. • Decisions that should be based on the patient’s own preferences. • Decision quality is improved through shared decision-making and decision aids.

  18. Percent of cancer patients dying in hospital among academic medical centers and NCI Cancer Centers (2010)adj. for age-sex-race, cancer type, non cancer conditions 55 50 45 40 35 Percent dying in hospital 30 25 20 15 10 Lenox Hill Hospital (New York, NY) 49.8 Maimonides Medical Center (Brooklyn, NY) 48.1 New York Methodist Hospital (Brooklyn, NY) 47.3 Mount Sinai Hospital (New York, NY) 46.9 Beth Israel Medical Center (New York, NY) 44.9 Allegheny General Hospital (Pittsburgh, PA) 16.6 Univ Hospitals of Cleveland (Cleveland, OH) 16.5 Univ of Kentucky Hospital (Lexington, KY) 16.5 Akron General Medical Center (Akron, OH) 12.2 St. Luke's Hospital (Bethlehem, PA) 11.5

  19. Capacity (i.e. supply) is often located without respect for need 12.0 10.0 8.0 Cardiologists per 100K 6.0 4.0 2.0 3.0 6.0 9.0 12.0 15.0 18.0 Acute Myocardial Infarction Rate per 1,000 Medicare Enrollees age-sex-race adjusted There is virtually no relationship between regional physician supply and health needs. Source: Wennberg, et al. Dartmouth Cardiovascular Atlas

  20. 2.5 2.0 1.5 Number of Visits per beneficiary 1.0 0.5 R2 = 0.49 0.0 0.0 2.5 5.0 7.5 10.0 12.5 15.0 Number of Cardiologists per 100,000 Physician Supply and Physician Visitsage-sex-race adj.Cardiologists

  21. Head CT Scans per 1,000 Children(2007-10, age-sex-payer adj.) 21 19 17 15 13 Head CT scans per 1,000 children 11 9 7 5 3 14 .7 to 19 .7 (13) 12 .3 to < 14 .7 (14) 10 .5 to < 12 .3 (14) 8 .9 to < 10 .5 (14) 4 .2 to < 8 .9 (13) Insufficient data (1) Not populated Bangor, ME 11.1 Portland, ME 9.7 Lebanon, NH 8.9 Burlington, VT 8.4

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