title: Cost of health care for a community of older adults in an urban academic healthcare system.
abstract: BACKGROUND
  Urban academic medical centers provide care for large populations of vulnerable older adults. These patients often suffer a disproportionate share of chronic illnesses, disabilities, and social stressors that may increase health care costs.
  
  
  OBJECTIVE
  To describe the distribution and content of total healthcare costs accrued over a 4-year period by a community of older adults cared for in an urban academic healthcare system and to describe high-cost patients and utilization patterns.
  
  
  METHODS
  A cohort study.
  
  
  METHODS
  A tax-supported public healthcare system consisting of a 450-bed hospital and seven community-based ambulatory care centers.
  
  
  METHODS
  12,581 patients aged 60 years and older who had at least two ambulatory visits and/or one hospitalization within the healthcare system from 1993 through 1995.
  
  
  METHODS
  Patient demographic and clinical characteristics, hospital and ambulatory utilization rates, and all healthcare costs accrued from 1993 through 1996 were determined. Costs were estimated from the perspective of the healthcare system using cost to charge ratios.
  
  
  RESULTS
  The mean patient age was 70 years, 60% were women, 44% were Black, and 83% were covered by Medicare and/or Medicaid. Nearly 25% of patients were obese, 15.8% had a history of smoking, and 15.5% had evidence of malnutrition. The mean number of ambulatory visits per year was 4.3 (+/-7.2), and 38.1% of patients had been hospitalized one or more times. Within the 4-year window, 24.1% of patients had missed five or more appointments with their primary care physicians, 32.7% of patients had five or more unscheduled clinic visits, and 12.5% had five or more emergency room visits. Total health care costs for 4 years for this cohort of older adults was $125.2 million dollars, with per capita annual mean costs of $3893. Expenditures associated with hospitalizations accounted for 63.6% of healthcare costs. Total inpatient and outpatient costs for the 38% of patients hospitalized at least once accounted for 85.3% of all health care expenditures. Patients who died in the hospital did not accrue significantly greater costs than patients who died out of the hospital. Simulations of a random 5% adverse selection of high-cost patients among two capitated systems resulted in cost shifts of $11.1 million. Recorded smoking history, obesity, and low serum albumin were significantly associated with excess costs.
  
  
  CONCLUSIONS
  Healthcare costs are concentrated in a significant minority of older adults. Costs accrued in conjunction with hospital stays dominate healthcare expenditures for this cohort of older adults. However, most older adults (83%) have one or fewer hospital episodes in a 4-year period. Although patients who died accrued greater healthcare costs, these costs were not higher when the death occurred in the hospital. Self-care behaviors are an important target for interventions to reduce costs.
authors.affiliation: Regenstrief Institute for Health Care, Indiana University School of Medicine, Indianapolis 46202-2859, USA.
authors.forename: C M
authors.initials: CM
authors.lastname: Callahan
authors.forename: T E
authors.initials: TE
authors.lastname: Stump
authors.forename: K T
authors.initials: KT
authors.lastname: Stroupe
authors.forename: W M
authors.initials: WM
authors.lastname: Tierney
mesh_terms: D000046:Academic Medical Centers / Q000191:economics* / Q000706:statistics & numerical data / Q000639:trends; D000368:Aged; D015331:Cohort Studies; D003151:Community Health Centers / Q000191:economics / Q000706:statistics & numerical data / Q000639:trends; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data* / Q000639:trends; D006299:Health Services for the Aged / Q000191:economics* / Q000706:statistics & numerical data / Q000639:trends; D017721:Hospital Costs / Q000706:statistics & numerical data / Q000639:trends; D006801:Humans; D007196:Indiana; D008297:Male; D008875:Middle Aged; D012044:Regression Analysis; D019037:Urban Health Services / Q000191:economics* / Q000706:statistics & numerical data / Q000639:trends