title: Multi-criteria assessment of county public health capability disparities.
abstract: OBJECTIVE
  This paper proposes an analytical approach to the assessment of geographic population health disparities that are measured as the consolidation of public health related indicators into geographic-specific scores, and are representative of the level of public health capability within counties in the state of Mississippi.
  
  
  METHODS
  A multi-criteria decision model was employed to develop an additive scoring system that assigns a numerical score of public health capability disparities for a geographical area (county).
  
  
  METHODS
  Routinely collected indicators were used to measure each county's current public health related concerns. These indicators include access, risks, health care quality, and outcomes data. Public health experts rated and ranked indicators to generate indicator weight.
  
  
  RESULTS
  A county score was developed to rank Mississippi counties based on relative public health capability. This scoring system depicts population health disparities among Mississippi counties.
  
  
  CONCLUSIONS
  The model is useful and ideal for establishing expectations and benchmarks for reduction or equalization of disparities. This information can be used to manage geographic population health disparities by guiding policy formulation and implementation.
authors.affiliation: South Texas Center, Texas A&M University System Health Science Center, USA.
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Zuniga
authors.forename: Genny
authors.initials: G
authors.lastname: Carrillo-Zuniga
authors.forename: Yoon Ho
authors.initials: YH
authors.lastname: Seol
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Fos
mesh_terms: D018672:Community Health Planning / Q000379:methods*; D003661:Decision Support Techniques; D006297:Health Services Accessibility; D054624:Health Status Disparities; D006305:Health Status Indicators; D006801:Humans; D008922:Mississippi; D011634:Public Health / Q000706:statistics & numerical data*; D011787:Quality of Health Care; D018570:Risk Assessment