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

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

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 Best Health Index Scoring Worst Health Low Provider Capacity Population to Provider (P2P) Ratio High Provider Capacity G EOGRAPHIC HPSA O PTION 1 (A1) High P2P; HPSA Designation Low P2P; No HPSA Designation Step 1: Calculate Health Status, Barriers and Ability to Pay Index ¹ (weighting at 33% for each) Step 2: Combine Index (weighted at 50%) with P2P Ratio (weighted at 50%) for overall score

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 Best Health Index Scoring Worst Health Low Provider Capacity Population to Provider (P2P) Ratio High Provider Capacity G EOGRAPHIC HPSA O PTION : S ALON M ODEL (M ODEL 2 AND A1 S IMPLIFIED ) High P2P; HPSA Designation Low P2P; No HPSA Designation Step 1: Combine Standard Mortality Rate and Poverty Step 2: Combine with P2P

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

Curved Slope Models

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

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

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

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

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

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

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

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

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.

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).