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Conceptual Outline for Designation Component Integration

Review of Barrier Free Approach and Additional Analysis of MEPS Data Related to ‘Potential’ vs. ‘Experienced’ Barriers . Conceptual Outline for Designation Component Integration. Quantify Need/Demand (Visits for Benchmark, Age Gender Adjusted, Average Health Status).

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Conceptual Outline for Designation Component Integration

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  1. Review of Barrier Free ApproachandAdditional Analysis of MEPS Data Related to ‘Potential’ vs. ‘Experienced’ Barriers

  2. Conceptual Outline for Designation Component Integration Quantify Need/Demand (Visits for Benchmark, Age Gender Adjusted, Average Health Status) Assess Health Outcome Deficits/Disparities (Areas/Populations with persistently and significantly negative health indicators ) Quantify Supply (Visit capacity for appropriate primary care providers ) Adjust for Population Health Status (Increase if below avg. health status, decrease if above ) Assess Other Indicators of Med.Underservice (Nature/Indicators TBD) Scale(s) of Provider Adequacy/Shortage (Combined measure of Supply vs Demand ) Scale(s) of Medical Underservice (Assessed separately or Integrated into an index) or or Set Threshold(s) for HPSA Designation Set Threshold(s) for MUA/P Designation HPSA MUA/P

  3. Additional Discussion/Analysis • Relevance and Utility of Experienced Barriers • Adjustment of demand for variation in population health status • Discussion of any alternative approaches to estimating demand

  4. Review of ‘Barrier Free’ Concept for Estimating Demand • Approach presented thus far estimates demand based on utilization patterns of those without a series of known ‘Potential’ barriers to care: • Race/ethnicity: Non-Hispanic White • Poverty level: Income >200% of FPL • Education: HS+ education (or younger than 18 years) • Usual source of care: Has a usual provider • Insurance: Full year insured under Medicare or Private insurance • Language: Language spoken at home = English • Physician Availability: Does not live in a geographic HPSA • Resulting group weighted to correct for positive health status bias in the ‘Barrier Free’ group

  5. Application of Initial Barrier Free Demand • Produces a count of visits needed by a given population assuming they had no/minimal access barriers and were of average health status • Permits comparison of actual provider capacity/ accessibility to idealized demand • Not a measure of unmet need or provider shortage directly

  6. Benefits to Approach • Demand based on actual patterns of primary care access • Corrects for major known barriers to access collectively • Avoids need to quantify each barrier separately at the local level • Readily updated as utilization patterns change • Remains valid even as health care barriers are addressed • Directly adjusts for local variation in population demographics by age & gender • Establishes a fixed reference for population health status (average of US pop.) from which local variation can be measured and accounted for • Produces a single metric of primary care need • Total visits needed by a barrier-free population • Readily comparable to provider capacity by productivity

  7. ‘Experienced’ Barriers to Care • ‘Potential Barrier’ approach likely eliminates many individuals that do not actually face access barriers • Two questions related to to having ‘Experienced Barriers’ are included in MEPS: • In the last 12 months, was anyone in the family unable to obtain medical care, tests, or treatments they or a doctor believed necessary? • In the last 12 months, was anyone in the family delayed in getting medical care, tests, or treatments they or a doctor believed necessary? • Questions are not specific to primary care • Does not quantify delayed/avoided care in any way • Follow-on questions ask: • What was the main reason for delayed or avoided care? • How big a problem was delayed/avoided care?

  8. Purpose of ‘Experienced Barrier’ Analysis • How do the groups defined based on ‘Potential’ barriers compare to those that actually experienced barriers? • Can ‘Barrier Free’ be defined based on eliminating those that experienced barriers instead of those with potential barriers? • Should the absence of ‘experienced’ barriers be added to the other characteristics in the definition of the ‘barrier free’ population?

  9. Top-Level Findings • The group experiencing barriers is too small to explain observed differences in utilization • The Barrier Free group exhibits significantly different experience with barriers compared to the remainder of the population • Lower incidence of delayed/avoided care • Somewhat lower significance of impact • Very different reasons for delayed/avoided care • Experience of a barrier is heavily tied to high need and utilization of the system • Especially true amongst those otherwise Barrier Free

  10. Prevalence of Experienced Barriers • Low overall prevalence of experienced barriers perceived • Far too low to explain difference in utilization for Potential Barrier group • ‘Potential Barrier’ group is 3.5 times more likely to have experienced inability to get needed care • Difference less pronounced for delayed care

  11. Delayed/Avoided care was less of a problem overall for Barrier Free group • Delayed care was a more significant problem for ‘Barriered’ group • Majority of both groups rated inability to receive care a significant problem

  12. Care delayed for very different reasons • Barriered group far more likely to delay for reason of affordability • Barrier Free group more likely to delay for reasons related to convenience and insurance (‘Other’ most common)

  13. Differences in reasons for avoided care even more pronounced • Cost dominant amongst Barriered group • Insurance company denial and under-insurance account for half of avoided care for Barrier-Free group

  14. Considerations for Inclusion of “Experienced Barriers” in Definition • Exclusion of Population that Experienced a Barrier reduces Barrier Free sample by 3.4% • Eliminates 472 of 13,847 cases = 13,375 • Still represents approx. 22% of overall MEPS respondent sample • Excluding those that experienced barriers actually lowers overall utilization rate for the Barrier Free group • Having experienced delayed/avoided care appears to be largley a product of increased need for services and contacts with the system • Individuals otherwise barrier free that experienced barriers exhibit: • 53% higher average utilization (3.57 visits vs 2.34 visits) • Nearly triple the rate of fair/poor health status (24.7% vs 8.5% • More likely to fall above childhood but below Medicare • These effects far more pronounced amongst otherwise barrier-free individuals compared to the overall population experiencing barriers

  15. Net Effect on Estimated Utilization if ‘Experienced Barrier’ Group Excluded

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