1. Health Status Adjustment to Initial Barrier-Free Demand Estimate

2. 2 Starting Point for Health Status Adjustment The basic Barrier Free calculation produces an Age/Gender adjusted estimate of primary care demand for a population, assuming that population is of ‘average’ health status –Adjustment made using the US average for self assessed health status (% reporting “fair” or “poor” health) as a benchmark Question asked of respondents in MEPS survey Same question asked in BRFSS

3. 3 Quantify Need/Demand (Visits for Benchmark, Age Gender Adjusted, Average Health Status) Adjust for Population Health Status (Increase if below avg. health status, decrease if above ) Quantify Supply (Visit capacity for appropriate primary care providers ) Scale(s) of Provider Adequacy/Shortage (Combined measure of Supply vs Demand ) Set Threshold(s) for HPSA Designation Assess Health Outcome Deficits/Disparities (Areas/Populations with persistently and significantly negative health indicators ) Assess Other Indicators of Med.Underservice (Nature/Indicators TBD) Scale(s) of Medical Underservice (Assessed separately or Integrated into an index) Set Threshold(s) for MUA/P Designation or

4. 4 Purpose of Health Status Adjustment of Demand Goal: To incorporate an adjustment factor which modifies estimated Barrier Free demand to reflect the degree to which a population’s health status is above or below the national average. –Initial analysis of MEPS showed that health status is a driver of demand independent of age, gender, and barriers to care –Measure based on a broad-based assessment of health status that can be equated to the health status parameter used in MEPS

5. 5 Sensitivity Analysis of Utilization by % Fair-Poor Health National average for % Fair-Poor Health is approximately 14% overall –Barrier free population weighted to this value Proportion of population reporting Fair-Poor health weighted Up/Down from average with resulting primary care utilization examined Results converted into a scale of multipliers representing the ratio of utilization at Actual/Average % Fair-Poor Health –Multiplier can be used to vary estimated demand derived based on average health status

6. 6 Sensitivity Analysis Results

7. 7 Assessing Health Status Direct: Actual % Fair-Poor Health –Derived from Behavioral Risk Factor (BRFSS) Survey –2002-2008 age adjusted rates reported in RWJF County Health Rankings Available for 2,711 of 3,141 counties (86%) –Represents 98% of US population Some states oversample for more detailed local data –For Sub-Populations Overall % Fair-Poor Health multiplier can be calculated if attribute is available in MEPS or BRFSS

8. 8 Assessing Health Status Indirect: Health Status measure correlated with Fair- Poor health status –Select a broad-based measure that is more readily available at a local level / narrower time frame –Standardized Mortality Ratio (SMR) Actual Deaths / Expected deaths (national age*gender rates) 5-Year rate can be calculated for every county (WONDER 2002-6) May be available/calculable for smaller geographic units and some sub-populations at the state level –Requires age/gender distribution of pop. and total deaths for the group Correlate with Fair-Poor Health Status to apply to demand estimation Relationship between self-rated health and mortality validated in literature as a ‘method to identify vulnerable persons with the greatest health needs’ »DeSalvo KB, et.al. Mortality predication with a single general self- rated health question. A Meta-Analysis. Journal of General Internal Medicine. 2006. 21:267-75

9. 9 Relationship of SMR to Estimate Health Status Robust positive relationship to % Fair-Poor Health (age adj.) –Significant: p-value of <0.0001, Correlation Coefficient = 0.6 –Beta Coefficient: 0.0179 For every 5% increase in fair/poor health status, the SMR increases by approximately 0.09 (.0179 * 5)

10. 10 Table of Demand Multipliers w/ SMR Crosswalks SMR to % Fair-Poor Health based on ‘best fit’ relationship –Ties SMR to variation in Barrier Free use

11. 11 Example of Application to Demand Sample County, US –Direct Barrier Free Demand Visits = 45,000 % Fair/Poor Health = 25% Health Status Multiplier = 1.07 (+7%) Adjusted Barrier Free demand (45,000*1.07 = 48,150) OR (if % Fair/Poor not known) SMR = 1.20 –Equates to Fair-Poor Health = 25% Sample Low Income Population –Low Income Pop Fair-Poor Health = 24% (from MEPS, age adj.) Health Status Multiplier = approx. 6% All low income designations would get same % boost unless better local data or SMR available to support different adjustment

12. 12 Potential Alternatives to SMR as Proxy Age Adjusted Mortality Rate –Need all deaths reported by age Life Expectancy –Requires valid age-specific death rates for local population –Years of Potential Life Lost (YPLL) Other BRFSS based measures –Unhealthy Days –Combination Measures Health Adjusted Life Expectancy (HALE) Years of Healthy Life Disability Adjusted Life Years (DALY) Multivariate analysis of social factors as drivers of SMR or Health Status