title: A retrospective analysis of health systems in Denmark and Kaiser Permanente.
abstract: BACKGROUND
  To inform Danish health care reform efforts, we compared health care system inputs and performance and assessed the usefulness of these comparisons for informing policy.
  
  
  METHODS
  Retrospective analysis of secondary data in the Danish Health Care System (DHS) with 5.3 million citizens and the Kaiser Permanente integrated delivery system (KP) with 6.1 million members in California. We used secondary data to compare population characteristics, professional staff, delivery structure, utilisation and quality measures, and direct costs. We adjusted the cost data to increase comparability.
  
  
  RESULTS
  A higher percentage of KP patients had chronic conditions than did patients in the DHS: 6.3% vs. 2.8% (diabetes) and 19% vs. 8.5% (hypertension), respectively. KP had fewer total physicians and staff compared to DHS, with 134 physicians/100,000 individuals versus 311 physicians/100,000 individuals. KP physicians are salaried employees; in contrast, DHS primary care physicians own and run their practices, remunerated by a mixture of capitation and fee-for-service payments, while most specialists are employed at largely public hospitals. Hospitalisation rates and lengths of stay (LOS) were lower in KP, with mean acute admission LOS of 3.9 days versus 6.0 days in the DHS, and, for stroke admissions, 4.2 days versus 23 days. Screening rates also differed: 93% of KP members with diabetes received retinal screening; only 46% of patients in the DHS with diabetes did. Per capita operating expenditures were PPP$1,951 (KP) and PPP $1,845 (DHS).
  
  
  CONCLUSIONS
  Compared to the DHS, KP had a population with more documented disease and higher operating costs, while employing fewer physicians and resources like hospital beds. Observed quality measures also appear higher in KP. However, simple comparisons between health care systems may have limited value without detailed information on mechanisms underlying differences or identifying translatable care improvement strategies. We suggest items for more in-depth analyses that could improve the interpretability of findings and help identify lessons that can be transferred.
authors.affiliation: Copenhagen Hospital Corporation, Bispebjerg Hospital, Copenhagen NV, Denmark. anne.frolich@dadlnet.dk
authors.forename: Anne
authors.initials: A
authors.lastname: Frølich
authors.forename: Michaela L
authors.initials: ML
authors.lastname: Schiøtz
authors.forename: Martin
authors.initials: M
authors.lastname: Strandberg-Larsen
authors.forename: John
authors.initials: J
authors.lastname: Hsu
authors.forename: Allan
authors.initials: A
authors.lastname: Krasnik
authors.forename: Finn
authors.initials: F
authors.lastname: Diderichsen
authors.forename: Jim
authors.initials: J
authors.lastname: Bellows
authors.forename: Jes
authors.initials: J
authors.lastname: Søgaard
authors.forename: Karen
authors.initials: K
authors.lastname: White
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002140:California / Q000453:epidemiology; D002648:Child; D002675:Child, Preschool; D002908:Chronic Disease / Q000453:epidemiology; D003695:Delivery of Health Care; D003718:Denmark / Q000453:epidemiology; D017048:Health Care Costs; D006279:Health Maintenance Organizations; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D015995:Prevalence; D012189:Retrospective Studies; D055815:Young Adult