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Using Quality Measurement and Reporting to Confront Disparities Yiscah Bracha, M.S. Research Director Center for Urban Health at HCMC Minneapolis Medical Research Foundation
Today’s presentation will discuss: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Today’s presentation will discuss: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Goal of Quality Measurement & Reporting ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
When does care most matter to health? ,[object Object],[object Object],[object Object],[object Object]
Who is most sick and at risk in Minnesota? ,[object Object],[object Object]
Premature mortality in MN by race:
Child health indicators in MN by race *Source:  Minnesota Department of Health, Spring 2006
Indicators of SES by Minnesota race 46  14  23  12  6  16  11  8  39  4  n/a  6 Numbers inside bars represent Minnesota’s rank among states. Employer-sponsored insurance and Medicaid for non-elderly.
Ways to improve MN’s overall health: ,[object Object],[object Object],[object Object]
Today’s presentation will discuss: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Growth in MN non-white population: Source:  Minnesota State Demographic Center, August 2006
Change in MN youth population: Source:  Minnesota State Demographic Center, August 2006
Projected changes in MN population: Source:  Minnesota State Demographic Center, August 2006
Conclusions: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Today’s presentation will discuss: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How QM&R could address disparities: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Helping ptts use reports (?) ,[object Object],[object Object],[object Object],[object Object],[object Object]
How QM&R could address disparities: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Goal of Quality Measurement & Reporting ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How QM&R could address disparities: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
1.  Measures relevant to disparities ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Other measures relevant to disparities: ,[object Object],[object Object],[object Object],[object Object]
How QM&R could address disparities: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
2a.  Stratify reports ,[object Object],[object Object],[object Object],[object Object],[object Object]
How QM&R could address disparities: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
2b. Structure of reports  ,[object Object],[object Object],[object Object],[object Object]
Who is favored by what structure decision? Low resource providers Low resource patients High resource providers Low resource patients Observed to Expected Low resource providers Any kind of patient High resource providers Any kind of patient Adjusted or stratified: Low resource providers High resource patients High resource providers High resource patients Unadjusted Improvement Absolute target Reward Based on Achieving Outcome measure is:
Decisions now favor: Low resource providers Low resource patients High resource providers Low resource patients Observed to Expected Low resource providers Any kind of patient High resource providers Any kind of patient Adjusted or stratified: Low resource providers High resource patients High resource providers High resource patients Unadjusted Improvement Absolute target Reward Based on Achieving Outcome measure is:
Decisions  could  favor: Low resource providers Low resource patients High resource providers Low resource patients Observed to Expected Low resource providers Any kind of patient High resource providers Any kind of patient Adjusted or stratified: Low resource providers High resource patients High resource providers High resource patients Unadjusted Improvement Absolute target Reward Based on Achieving Outcome measure is:
Today’s presentation will discuss: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Questions, answers & implications: Develop & use new measures relevant to disparities.  No Do existing measures assess equity or equality in quality? Reimbursement higher when contributions from non-medical agents are low Family, patient, community, public policies Which non-medical agents affect MNCM outcome measures?  ,[object Object],[object Object],Very likely. Known that low SES    worse outcomes Does patient race & SES affect MNCM outcomes measures? Policy implications Answer Question
The Bad News: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The good news: ,[object Object],[object Object],[object Object],[object Object],[object Object]
This problem is solvable! Let’s start.
Extra slides
Chronic Care Model from  E.H. Wagner 1998.  What will it take to improve care for chronic illness?  Effective Clinical Practice . 1(1):2-4
Visioning a new reimbursement structure: ,[object Object],[object Object],[object Object],[object Object],[object Object]
How healthy is Minnesota? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],* Source: United Health Foundation’s  America’s Health Rankings.
MN Health Strengths by Race* *Source:  Minnesota Department of Health, Spring 2006 .
MN population growth rates by race:
Changes in MN demography by county
Some answers to empirical Qs: ,[object Object],[object Object],[object Object],[object Object],[object Object]

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03. Quality Measurement and Report: Implications for Disparities

  • 1. Using Quality Measurement and Reporting to Confront Disparities Yiscah Bracha, M.S. Research Director Center for Urban Health at HCMC Minneapolis Medical Research Foundation
  • 2.
  • 3.
  • 4.
  • 5.
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  • 8. Child health indicators in MN by race *Source: Minnesota Department of Health, Spring 2006
  • 9. Indicators of SES by Minnesota race 46 14 23 12 6 16 11 8 39 4 n/a 6 Numbers inside bars represent Minnesota’s rank among states. Employer-sponsored insurance and Medicaid for non-elderly.
  • 10.
  • 11.
  • 12. Growth in MN non-white population: Source: Minnesota State Demographic Center, August 2006
  • 13. Change in MN youth population: Source: Minnesota State Demographic Center, August 2006
  • 14. Projected changes in MN population: Source: Minnesota State Demographic Center, August 2006
  • 15.
  • 16.
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  • 28. Who is favored by what structure decision? Low resource providers Low resource patients High resource providers Low resource patients Observed to Expected Low resource providers Any kind of patient High resource providers Any kind of patient Adjusted or stratified: Low resource providers High resource patients High resource providers High resource patients Unadjusted Improvement Absolute target Reward Based on Achieving Outcome measure is:
  • 29. Decisions now favor: Low resource providers Low resource patients High resource providers Low resource patients Observed to Expected Low resource providers Any kind of patient High resource providers Any kind of patient Adjusted or stratified: Low resource providers High resource patients High resource providers High resource patients Unadjusted Improvement Absolute target Reward Based on Achieving Outcome measure is:
  • 30. Decisions could favor: Low resource providers Low resource patients High resource providers Low resource patients Observed to Expected Low resource providers Any kind of patient High resource providers Any kind of patient Adjusted or stratified: Low resource providers High resource patients High resource providers High resource patients Unadjusted Improvement Absolute target Reward Based on Achieving Outcome measure is:
  • 31.
  • 32.
  • 33.
  • 34.
  • 35. This problem is solvable! Let’s start.
  • 37. Chronic Care Model from E.H. Wagner 1998. What will it take to improve care for chronic illness? Effective Clinical Practice . 1(1):2-4
  • 38.
  • 39.
  • 40. MN Health Strengths by Race* *Source: Minnesota Department of Health, Spring 2006 .
  • 41. MN population growth rates by race:
  • 42. Changes in MN demography by county
  • 43.

Notes de l'éditeur

  1. February 7, 2007. Quality Measurement & Reporting. Conference hosted by MN Community Measurement, in collaboration with Halleland Health Consulting, National Institute of Health Policy, University of St. Thomas. St. Paul, MN.