Conceptual Outline for Designation Component Integration

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

8. 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

9. ‘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?

10. 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?

11. 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

12. 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

13. 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

14. 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)

15. 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

16. 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

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