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The Geography of Health Care Utilization and Outcomes

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Title: The Geography of Health Care Utilization and Outcomes


1
The Geography of Health Care Utilization and
Outcomes
  • Jonathan Skinner
  • Department of Economics, Dartmouth College
  • The Dartmouth Institute for Health Policy and
    Clinical Practice, Dartmouth Medical School
  • jon.skinner_at_dartmouth.edu
  • November 9, 2010
  • Institute of Medicine, Washington DC

2
The Focus of This Talk Costs and Quality in the
Medicare Population
Congressional Budget Office, June 2010 (revised
Aug 2010), Extended baseline .
3
Two Policy Questions
  • What are the causes of geographic variation in
    health care?
  • What are the consequences of geographic variation
    in health care?
  • Todays objective Understanding how patient
    cohorts can help us to answer each question

4
Unexplained regional variation in Medicare
expenditures
Source Zuckerman, Berenson, Hadley, 2010
5
Where do we go from here?
Source Zuckerman, Berenson, Hadley, 2010
6
Choices, choices
  • Complete risk adjustment using Medicare claims
    data
  • Further risk adjustment using ecological (state
    or county) data
  • Better risk adjustment approaches (biomarkers,
    etc.)
  • Considering cohorts of patients with similar
    diseases

7
Diagnosis creep in high-intensity regions
  • Low-diagnosis
  • High-diagnosis
  • 19 lower risk-adjusted costs
  • 15 better risk-adjusted outcomes

8
Choices, choices
  • Complete risk adjustment using Medicare claims
    data
  • Further risk adjustment using ecological (state
    or county) data

9
Potential Pitfalls of Using Ecological
Risk-Adjusters
Cutler and Sheiner, AER May 1999
10
But Market-Level Explanations for Utilization
are Valid First, Chicago.
  • Chicago-area hospitals sacrifice revenue as they
    prepare for health care reform
  • By Mike Colias, Crains Chicago Business, July
    12, 2010
  • "It's not about building new facilities or
    mergers and acquisitionsThe hospitals that will
    fare best are the ones that are dealing most
    seriously with getting ready for these
    reimbursement changes and partnering with the
    right doctors.

Michael Nugent, Navigant Consulting
11
Then New York Fighting for Market Share
  • Soaring cancer-care costs strain budgets -
    Hospitals pour millions into new devices, talent
    as margins thin
  • By Judith Messina, Crains New York Business,
    August 22, 2010
  • All told, the city's major hospitals have spent
    more than 2 billion on cancer research and
    treatment over the past five years, in a race to
    carve out a bigger piece of a fast-growing pie.
  •  

12
Choices, choices
  • Complete risk adjustment using Medicare claims
    data
  • Further risk adjustment using ecological (state
    or county) data
  • Better risk adjustment approaches (biomarkers,
    etc.)
  • Considering cohorts of patients with similar
    diseases

13
Possible Low Variation Cohorts
  • Hip fracture
  • AMI
  • Stroke
  • Colon/Lung Cancer
  • Risk-adjusted end-of-life cohorts (by condition
    and presence of multiple conditions)

14
Example AMI Cohorts
  • One-year after AMI
  • Risk adjustment for type of AMI (location of the
    infarct), comorbidities (e.g., diabetes, COPD,
    cancer, dementia), zip code income, poverty in
    income, price adjustment, age-sex-race.
  • Currently Part A through 2005 could be Parts
    A,B, and D through 2008 or 2009.

15
Risk Price-Adjusted AMI and End-of-Life
Expenditures 2000-05 by Hospital
One-Year AMI Spending
N 1985, At least 400 AMIs
16
Two Policy Questions
  1. What are the causes of geographic variation in
    health care?
  2. What are the consequences of geographic variation
    in health care?

17
Provider-Specific Measures of Quality Spending
Typically Look Like This
Survival/Quality
Spending
18
This is waste
Survival/Quality
Spending
Low Cost
19
But this waste is even more important!
Survival/Quality
Best practice
Spending
20
A Simple Graph Spending vs. Survival/Quality of
Life
Survival/Quality
You are here
A
Spending
21
A Tale of Two Hospitals Every New Adoption is
Medically Effective
Survival/Quality
Hospital X
Hospital Y
A
Spending
But hospital X gets better outcomes at lower
costs!
22
Causes a Negative Correlation Between Spending
and Outcomes
Survival/Quality
Hospital X
Hospital Y
A
Spending
23
Differences in Efficiency A Concrete Example
Some Firms Get Double the Output at the Same
Cost!
Deviation from Mean in Total Factor Productivity
Syverson, C., Market Structure and Productivity
A Concrete Example, JPE 2004.
24
New Approaches Percent Men Age 80 Receiving PSA
Screening by HRR
Source Bynum, J., JAGS 58(4) April 2010
25
One measure of a bad outcome, 2006-07
Feeding Tube Use ()
Brigham-Womens (MA) 4.7
Lawnwood Regional (FL) 37.5
UCLA 0.0
Cedars Sinai 14.6
US 6.3
Cohort Nursing home patients with advanced
dementia admitted to hospital
26
Yet more ways to measure outcomes
  • Changes over time in measures of care
  • Deaths in hospitals or hospice, 2003-07 (D.
    Goodman et al.)
  • Low or high quality prescription (Part D)
  • Y. Zhang et al. (2010), N. Morden et al. (2010)
  • Burdensome transitions for nursing home patients
    (J. Teno, et al, 2010)
  • Multiple hospitalizations for UTI, pneumonia in
    last 120 days
  • Transitions in the last 72 hours of life
  • Lack of continuity among nursing homes

27
Conclusions
  • Challenges in measuring utilization and outcomes
    but necessary to reward efficiency
  • Serious limits to current risk-adjustment
    measures
  • Defining meaningful cohorts of patients
    reasonable step forward
  • Looking ahead new approaches to measuring
    outcomes
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