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Health Status Adjustment to Initial Barrier-Free Demand Estimate. 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

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Presentation Transcript
starting point for health status adjustment
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

Conceptual Outline for Designation Component Integration

Quantify Need/Demand

(Visits for Benchmark,

Age Gender Adjusted,

Average Health Status)

Assess Health Outcome


(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


(Combined measure of

Supply vs Demand )

Scale(s) of Medical


(Assessed separately or

Integrated into an index)



Set Threshold(s) for

HPSA Designation

Set Threshold(s) for

MUA/P Designation



purpose of health status adjustment of demand
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
sensitivity analysis of utilization by fair poor health
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
assessing health status
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
assessing health status1
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, Mortality predication with a single general self-rated health question. A Meta-Analysis. Journal of General Internal Medicine. 2006. 21:267-75
relationship of smr to estimate health status
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)
table of demand multipliers w smr
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
example of application to demand
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
potential alternatives to smr as proxy
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