HPSA/MUA Negotiated Rule Making Committee August 16, 2011

1. HPSA/MUA Negotiated Rule Making Committee August 16, 2011 HPSA Designations Overview

2. Goals for August Meeting • Select one model for geographic HPSA • Select one model for geographic MUA • Identify need for further testing/refinement • Reach consensus on population designation • Review implementation issues

3. Geographic HPSA Option 1 (A1) Population-to-Provider Ratio Count at 1.0 = MDs/DOs in GP, FP, General IM, General Pediatrics, Geriatrics, Adolescent Medicine Count at 0.25 = OB/GYN Count at 0.75 = Primary Care PAs and NPs, CNM (1) Do not count CHC, RHC, Look-alike, NHSC, J-1 visa, or loan repayment providers High P2P; HPSA Designation Low P2P; No HPSA Designation Step 1: Calculate Health Status, Barriers and Ability to Pay Index¹ (weighting at 33% for each) Step 2: Combine Index (weighted at 50%) with P2P Ratio (weighted at 50%) for overall score

4. Geographic HPSA Option: Salon Model (Model 2 and A1 Simplified) Population-to-Provider Ratio Count at 1.0 = MDs/DOs in GP, FP, General IM, General Pediatrics, Geriatrics, Adolescent Medicine Count at 0.25 = OB/GYN Count at 0.75 = Primary Care PAs and NPs, CNM (1) Do not count CHC, RHC, Look-alike, NHSC, J-1 visa, or loan repayment providers High P2P; HPSA Designation Low P2P; No HPSA Designation Step 1: Combine Standard Mortality Rate and Poverty Step 2: Combine with P2P

5. HPSA Geographic Models: Results Being Presented Today • Model 1 = Model A1, tiered with full factors (health status, barriers and ability to pay) • Model 2 = Salon model (A1 simplified) (Poverty and SMR for designation between thresholds) • Both use straight line between thresholds • Model 1A = Model 1 with curve between thresholds • Model 2A/Salon = Model 2 with curve

6. Curved Slope Models

7. HPSA Geographic Models: Results Being Presented Today-Thresholds • Models 1 and 2 Thresholds • Greater than 3000:1 designation by P2P ratio only • Ratio between 2000:1 and 3000:1 designation by P2P and other factors • Models 1A and 2A (“curved slope”) • Greater than 3000:1 designation by P2P only • Ratio between1300:1 and 3000:1 designation by P2P and other factors

8. Elements in the Models • Full back-out of federal practitioners • NPs and PAs counted as .75 • Complex model (1 and 1A) Factors considered for areas in-between thresholds: • Ability to pay, barriers (highest one) and health status (one third each) • Population density

9. How to use these results • To inform our thinking about the models • Pick best model based on our judgment of the best way to determine underserved areas • Models have flexibility and can be tweaked • Use results to guide us to make the big decisions

10. Results Presentation: Background Geographic Areas: National (Universal) RSAs • State RSAs • PCSAs • Counties Current HPSA geography Different thresholds Straight line vs curve

11. The National HPSA Analysis • HRSA will assess eligibility across the nation • PCOs and others will submit applications for: • Additional geographic HPSAs • Population HPSAs • Facility HPSAs • Hence, these results present the minimum areas to be designated

12. Options: Additional Decisions • If chose Model 1 or 1A (Complex Model): • How combine factors/weights • Density vs. Travel time • NP/PA weighting • Handling of barriers • Provider back-outs • Thresholds • If chose Model 2 or 2A (simplified): • How combine/weight poverty and SMR • Provider back-outs • Thresholds • If chose 1A or 2A • Curves

13. Two Ways of Looking at the Results Summary Table 1 Summary Table 2 Impact on Current HPSAs Designated by New Models

14. Two Ways of Looking at the Results Areas Designated by New Models (National RSAs) Current HPSAs Summary Table 1 Summary Table 2

15. Some Initial Observations and Findings COMPARING MODEL RESULTS TO CURRENT DESIGNATIONS PROFILE • Models 1 and 2, within the ratio ranges chosen as described earlier, would designate more areas and people than currently designated; some current areas would be lost but more would be gained. • Models capture areas with a much higher P2P than the current method. • If the national results are compared to the current HPSAs in terms of the demographic and health status factors, the models capture fewer populations with those characteristics. • However, when the models are compared using the current HPSA geography, the population characteristics are very similar. This reflects that fact that current HPSA geography is often based on these kinds of characteristics; if local RSAs were used across the country the results of a national analysis would probably be more similar to the currently designated population.

16. Some Initial Observations and Findings, continued COMPARING MODELS TO EACH OTHER Models 1 and 2 are very similar in their results overall in terms of total numbers and characteristics of the populations. Both models show a decline in Frontier. Model 1 captures a slightly greater percentage of metro and frontier areas; Model 2 captures more non-metro areas. When the areas excluded by p2P only, it appears that these are areas with a much higher percentage of care provided by NP/Pas. Model 2 captures slightly more of the populations with characteristics of most barriers (race, poverty, etc.), access (ASCS), and health status (SMR, Disability, diabetes, etc.) than Model 1, which captures more USC and Hispanic/LEP).