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Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
Shap aug2011 blewett_final
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Shap aug2011 blewett_final

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  • Review two page analysis – help them draw conclusions???
  • Primary Care is a uniquely important category given that it is often the access point to the broader health care system.Roughly 45,000 physicians needed in the next 15 years, not accounting for insurance expansion (Hofer, 2011)Hofer and colleagues suggest that the 32 million anticipated newly insured from ACA will generate 15-25 million new primary care visits in 2019.
  • Previous literature has found 1,500:1 denotes an adequate level. Furthermore, this ratio roughly equates to early estimates of a barrier free approach from HRSA’s rule making committee. Based on work by Tom Ricketts (2007), this barrier free demand method compares the idealized level of demand in a community (if no access barriers existed) to the available visit supply.
  • We also obtained variables from ARF that indicated metro status, census region, and county-level uninsurance estimates from the census bureau.
  • The ACS is an annual general population survey conducted by the U.S. Census Bureau. The annual files contain roughly 4 million records and the 5-year file contains 20 million person records. 2014 Medicaid expansion population will include Non-Elderly (19-64) Low-Income (>139 FPL) Adults.-To link the ACS summary file and the ARF, Alaskan counties were aggregated into county groups.
  • Note: May change cut points on map.-We observed 956 counties below 1,500 to 1; -2,183 above 1,500 to 1; and 680 above 3,500 to 1.62% of the population lived in area with adequate supply (below 1500:1), 38% in counties with more than 1,500 to 1, and 3.5% above 3,500 to 1. This compares to 11.8% of the population living in an official HPSA. Discrepancies could be due to differences in measures, geographic areas, and/or the timeliness of our data.-52% of adequately supplied counties were non-metro compared to 70% above 1,500 to 1 and 71% above 3,500 to 1.-As is evident from the map, roughly half of the least supplied counties were in the south and a third were in the Midwest, while only a faction of such counties were in the north-east.
  • -Among all counties, the average county was 50% female, 24% below 17, 60% 18-64 and 15.3% elderly.-In counties with more than 3,500 to 1 people per provider the average county was 10% African American, compared to 8% in adequately supplied counties (less than 1,500 to 1).
  • -The average share that were college graduates was 13% in counties above 3,500 to 1; 14% in counties above 1,500 to 1 and 22% in adequately supplied counties.-Poverty rate: 17% (3,500:1); 16% (<1,500:1); 14% (>1,500:1)-Uninsurance rate (non-elderly): 21% (3,500:1), 19% (<1,500:1), 17% (>1,500:1). Pattern consistent for children and non-elderly adults.- Employment rates similar, counties with the largest pop to provider ratios had twice the share that worked outside the county, compared to counties with the lowest pop to provider ratio.
  • -MAY REFORMAT COLOR-Only 5 states did not have enough physicians to over-come the gap. And many states had physicians well in excess of the 1,500 to 1 mark.
  • The y axis describes the percent of counties. The X-axis divides counties into three groups. Those with the lowest, average, and highest share that is non-elderly (19-64) and low-income (<139% FPL). The least supplied counties have a disproportionate share of 2014 Medicaid Eligible.
  • Review two page analysis
  • Transcript

    1. Health Reform and Provider Capacity<br />Lynn A. Blewett, PhD<br />Director<br />State Health Access Data Assistance Center<br />University of Minnesota, School of Public Health<br />HRSA SHAP Grantee Meeting<br />Washington, D.C.<br />August 23, 2011<br />
    2. Presentation Outline<br />Importance of provider capacity analysis<br />Key analytic steps<br />Alternative ways to monitor and assess provider capacity issues<br />Sample analysis using existing federal data<br />2<br />
    3. 3<br />Importance of Provider Capacity Analysis<br />
    4. Health Reform and Provider Capacity <br />Long-term concerns about adequacy of supply of primary care physicians in U.S.<br />Fewer physicians choosing primary care<br />Aging physician workforce<br />Growing health needs of aging population<br />Likely exacerbated by coverage expansion under national health reform in 2014<br />Large, newly-covered population will seek care <br />Introduction of ACOs, medical home & payment reform may help in long-run but unlikely to help much by 2014<br />4<br />
    5. Analytic Questions (1)<br />Newly eligible adults – how many and..<br />What is their current health insurance coverage? <br />What are their current health care needs and patterns of health care access and use? <br />Who are the providers that they currently rely on for care?<br /> Remaining uninsured – how many and…<br />What are their current health care needs and patterns of health care access and use? <br />Who are the providers that they are relying on for care now?<br />5<br />
    6. Analytic Questions (2)<br /> Access and use of services:<br />Variation across the states? <br />Variation across key population subgroups? <br />Variation by key characteristics, such as by age, income, or type of health insurance coverage? <br />Variation by community characteristics, such as population characteristics (poverty, linguistic isolation, race/ethnicity segregation)? <br />6<br />
    7. Analytic Questions (3)<br />  Provider and Facility Supply:<br />Variation across states? <br />Variation within states?<br />What level of supply (people per providers) needed?<br />Type and mix of providers (docs, nurses, etc.)? <br />Role of the safety net?<br />7<br />
    8. Analytic and Data Collection Initiatives <br />Assessment of existing data – think outside the box!<br />Review state licensure and other regulatory data<br />Do provider organization/associations collect data they would share?<br />Are there data on all providers and entities of interest?<br />Do you have adequate practice information from providers?<br />New data collection <br />Add questions or “surveys” to licensure process<br />Work with provider organization/associations to field a survey<br />Use mapping to visualize different capacity data together to get a picture of overall capacity (e.g. provider location and uninsured)<br />8<br />
    9. 9<br />Analysis Using Existing Federal Data: <br />Potential Gaps in the Availabilityof Primary Care Physiciansunder Health Reform<br />
    10. Measures of adequacy of primary care physician capacity in local area<br />Ratio of local population size to number of primary care physicians in area<br />HRSA’s current Health Professional Shortage Area (HPSA) definition<br />Adequate supply<br />1 physician per 1500 people <br />Potentially inadequate supply<br />Definition 1: Moderate ≥1,500: 1 <br />Definition 2: Low ≥ 3,500: 1<br />10<br />
    11. Analysis<br />Identify number of primary care physicians by county<br />Who is potentially impacted?<br />Examine county characteristics (demographic, economic, health market) and different measures of adequate supply <br />Are there enough excess physicians in adequately supplied counties to cover the gap in inadequately supplied counties?<br />Compare counties with potentially inadequate supply and adequately supply<br />Do potential shortage areas = potential areas of demand?<br />Identify distribution projected Medicaid eligible population<br />Identify areas of high potential eligibility with areas of low adequacy <br />11<br />
    12. Data: Primary care physician supply<br />2009/10 HRSA Area Resource File (ARF)<br />2008 Primary care physicians (PCP)<br />Includes general, family, or general internal medicine; general pediatrics, OB/GYN (M.D.’s and D.O’s)<br />Limited to active, non-federal, office-based, full-time physicians<br />Local area defined as county<br />12<br />
    13. Data: County Population Estimates<br />American Community Survey (ACS)<br />Population size and characteristics<br />2005-2009 pooled summary file<br />Estimate of 2014 Medicaid-eligible population <br />19-64 year olds at or below 138% FPL<br />Pooled 2008-09 ACS PUMS<br />13<br />
    14. Overview Descriptive<br />3,139 counties (or county equivalent areas)in U.S. with average population of 96,000<br />235,771 primary care physicians in US, for average of 75 in each county<br />186 counties with no primary care physicians <br />14<br />
    15. 15<br />
    16. 16<br />
    17. Key Points<br />Adequate Supply <br /> 956 counties < 1,500:1<br />62% of the population<br />52% non-metro<br />Inadequate Supply<br />2,183 counties > 1,500:1 (38% of population and 70% non-metro)<br />680 counties > 3,500:1 (3.5% of population and 71% non-metro)<br />17<br />
    18. CountyDemographic Characteristics<br />18<br />
    19. County Economic Characteristics<br />19<br />
    20. Health Market Characteristics<br />20<br />
    21. Health Market Characteristics (2)<br />21<br />
    22. How do primary care physician “gaps” and “surpluses” play out within states?<br />There is evidence that work-force shortages are due to “geographic mal-distribution” rather than a lack of providers <br />Calculated the size of the physician gap in counties with potentially inadequate supply and the physician surplus in adequately supplied counties<br />At state level, determine if reallocating physicians from surplus counties to gap counties could eliminate the primary care physician shortage<br />22<br />
    23. 23<br />
    24. 24<br />
    25. Location of “2014” Medicaid Eligible Population<br />25<br />Newly Eligible % of County Population<br />
    26. 26<br />
    27. Limitations<br />Provider supply is measured with error, particularly when considering providers who will see Medicaid population<br />Little consensus on appropriate measure of adequate primary care physician supply<br />County is not necessarily relevant market area for primary care<br />27<br />
    28. Summary of Key Findings (1)<br />Counties with potentially inadequate PCP supply…<br />Exist everywhere, but have a greater concentration in the South and non-metropolitan areas<br />Similar demographics, although higher concentration of African-American residents<br />Worse off on socioeconomic characteristics of the population, including lower education, higher poverty and more uninsurance<br />28<br />
    29. Summary of Key Findings (2)<br />PCP supply gap largely a spatial mismatch<br />Encouraging movement of PCP from surplus counties to gap counties would eliminate problem in all but 5 states<br />Non-physician providers could address part of problem, but have similar spatial mismatch<br />Counties with potentially inadequate supply less likely to have non-physician providers<br />Important variation at local level in 2014 eligible population relative to provider supply<br />29<br />
    30. Policy Implications<br />Findings suggest policies aimed at encouraging movement primary care providers, not simply increasing supply<br />Population eligible for Medicaid under ACA more heavily concentrated in counties with potentially inadequate supply<br />Will face additional barriers from modest provider participation in Medicaid<br />30<br />
    31. Future Work with National Data<br />Better provider data: more refined geographic information; more refine practice characteristics<br />Better population data: Census 2010 SF-1<br />Adopt barrier free method currently being considered by the HRSA neg. rule making cmte.<br />31<br />
    32. 32<br />State-Specific Analysis<br />
    33. SHADAC TA<br />Provide state-level information on adequacy thresholds shown above<br />Map state data against data presented today (e.g. potentially newly eligible)<br />Help identify strategies for monitoring capacity issues, including use of existing data and need for new data<br />33<br />
    34. Acknowledgments<br />Funding support<br />RWJF grant to the State Health Access Data Assistance Center<br />Collaborators<br />Michel Boudreaux, SHADAC <br />Sharon Long, SHADAC<br />Joanna Turner, SHADAC<br />Karen Turner (GIS Support), SHADAC<br />34<br />
    35. 35<br />Contact Information<br />Lynn A. Blewett, PhD<br />Professor and Director<br />blewe001@umn.edu<br />State Health Access Data Assistance Center <br />University of Minnesota, Minneapolis, MN<br />www.shadac.org<br />©2002-2009 Regents of the University of Minnesota. All rights reserved.The University of Minnesota is an Equal Opportunity Employer<br />
    36. State Health Access Data Assistance Center <br />University of Minnesota, Minneapolis, MN<br />612-624-4802<br />Sign up to receive our newsletter and updates at www.shadac.org<br />www.facebook.com/shadac4states<br />@shadac<br />

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