title: [Towards a more equitable distribution of resources and assessment of quality of care: validation of a comorbidity based case-mix system].
abstract: BACKGROUND
  Equitable distribution of healthcare resources and fair assessments of providers' performance necessitates adjusting for case-mix. The feasibility and validity of applying case-mix measures, based on inpatient and outpatient diagnoses, has yet to be tested in Israel.
  
  
  OBJECTIVE
  Assessment of the feasibility and validity of applying the Johns-Hopkins University Adjusted Clinical Groups (JHU-ACG) case-mix system, using diagnoses from hospitalizations or physician visits, at Clalit Health Services (CHS).
  
  
  METHODS
  A representative sample of 117,355 enrollees during 2006. The distribution of ACG morbidity groups and relative resource weights in CHS and the degree to which it corresponds to ACGs' distribution in other countries was examined. The degree to which ACGs can explain utilization of primary and specialty care in CHS was determined.
  
  
  RESULTS
  ACGs explained a large percent of the variance in primary care and specialist visits (R2 = 38-54%), better than age and gender alone (R2 =12-13%). A high degree of correlation was found between the distribution of the population into ACG groups in CHS and samples from Canada or the United States (r = 0.91), and between the relative resource use for each ACG at CHS compared to the Canadian and US samples (r = 0.78-0.98).
  
  
  CONCLUSIONS
  The JHU-ACG case-mix system can be applied in the Largest healthcare organization in Israel based on diagnoses generated at hospitalizations and physician visits. The system can now be applied for a variety of purposes, including resource allocation according to medical need, and for conducting fair assessments of providers' performance, which are currently being tested by CHS.
authors.affiliation: Planning & Health Policy Division, Clalit Health Services Head Offices, Israel. rbalicer@clalit.org.il
authors.forename: Ran D
authors.initials: RD
authors.lastname: Balicer
authors.forename: Efrat
authors.initials: E
authors.lastname: Shadmi
authors.forename: Keren
authors.initials: K
authors.lastname: Geffen
authors.forename: Arnon D
authors.initials: AD
authors.lastname: Cohen
authors.forename: Chad
authors.initials: C
authors.lastname: Abrams
authors.forename: Karen Kinder
authors.initials: KK
authors.lastname: Siemens
authors.forename: Sigal
authors.initials: S
authors.lastname: Regev-Rosenberg
mesh_terms: D000367:Age Factors; D005240:Feasibility Studies; D015276:Health Care Rationing / Q000379:methods*; D006295:Health Resources / Q000706:statistics & numerical data / Q000600:supply & distribution*; D006801:Humans; D007557:Israel; D011320:Primary Health Care / Q000592:standards / Q000706:statistics & numerical data; D011787:Quality of Health Care; D012737:Sex Factors; D013038:Specialization