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. 1991 Sep;39(9):895-904.
doi: 10.1111/j.1532-5415.1991.tb04457.x.

Trends in elderly hospitalization and readmission rates for a geographically defined population: pre- and post-prospective payment

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Trends in elderly hospitalization and readmission rates for a geographically defined population: pre- and post-prospective payment

C L Leibson et al. J Am Geriatr Soc. 1991 Sep.

Abstract

To address the paucity of patient-level data regarding the effectiveness of Medicare's prospective payment system (PPS), we conducted a population-based study of inpatient hospitalizations among individually identified elderly residents of Olmsted County, Minnesota, 1970-1987. A 4.3% increase in total days of care/1000 population from 2,652/1,000 in 1970 to 2,766/1,000 in 1980 was followed by a 9.8% decline from 1980 to 1987 (2,495/1,000). The decline was due primarily to a 13.4% decrease in mean length stay (9.7 days in 1980 to 8.4 days in 1987). The number of hospitalizations/1,000 Olmsted County elderly in 1980 was already below 1987 U.S. figures and did not exhibit the decline evidenced nationally between 1980 and 1987. A 4.6% decline in the proportion of county residents age 65-74 years who were hospitalized (174/1,000 in 1980 to 166/1,000 in 1987) was offset by an 8.3% increase for persons age greater than or equal to 75 (252/1,000 to 273/1,000) and by a 5.7% increase in the number of hospitalizations per individual hospitalized for persons age 65-74 years (1.34 to 1.42). Using a time-dependent Cox model, which adjusted for differences in patients characteristics between years, there was a significantly higher risk of readmission within 14 days in 1987 vs 1980 (hazard ratio (HR) = 1.33, 95% confidence interval (CI) = 1.05-1.70). The difference between years was no longer evident at 30 or 60 days (HR = 0.84, 95% CI = 0.63-1.11 between 15 and 30 days; HR = 1.12, 95% CI = 0.84-1.49 between 31 and 60 days). This study suggests that initial effects of PPS on utilization may be temporary and that more research is needed to appreciate the impact of cost-containment on patient outcome.

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