Biomedical subjects

C L Leibson

Publications and source records attributed to C L Leibson.

23 records · Page 2Linked to original sources

PubMed1994

Accuracy of hospital discharge abstracts for identifying stroke.

BACKGROUND AND PURPOSE: Much of the available data on stroke occurrence, service use, and cost of care originated with hospital discharge abstracts. This article uses the unique resources of the Rochester Epidemiology Project to estimate the sensitivity and positive predictive value of hospital discharge abstracts for incident stroke. METHODS: The Rochester Stroke Registry was used to identify all confirmed first strokes (hospitalized and nonhospitalized) among Rochester residents for 1970, 1980, 1984, and 1989 (n = 364). The sensitivity of discharge abstracts was estimated by following these individuals for 12 months after stroke to determine the proportion assigned a discharge diagnosis of cerebrovascular disease (International Classification of Diseases [ICD] codes 430 through 438.9). The positive predictive value of discharge abstracts was assessed by identifying all hospitalizations of Rochester residents with an ICD code of 430-438.9 in 1970, 1980, and 1989 (n = 377). Events were categorized as incident stroke, recurrent stroke, stroke sequelae, or nonstroke after review of the complete community-based medical record by a neurologist. RESULTS: Only 86% (n = 313) of all first-stroke patients in 1970, 1980, 1984, and 1989 were hospitalized. Of hospitalized patients, only 76% were assigned a principal discharge diagnosis code of 430-438.9. Fatal strokes and those occurring during a hospitalization were less likely to be identified. Among all hospitalizations of Rochester residents in 1970, 1980, and 1989, there were 377 with a principal diagnosis code of 430-438.9. Less than half (n = 177) were determined by the neurologist to be incident stroke; only 60% (n = 225) were either incident or recurrent stroke. Comparison of alternative approaches showed the validity of discharge abstracts was enhanced by increasing the number of diagnoses and excluding codes with poor positive predictive value. CONCLUSIONS: This study provides previously unavailable estimates of the sensitivity of stroke-coded hospitalizations for a US community. A model for improving the sensitivity and positive predictive value of discharge abstracts is presented.

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PubMed1992

The Olmsted County Benchmark Project: primary study findings and potential implications for corporate America.

Since 1965, expenditures for medical care in the United States have increased 10-fold. As a result, corporate outlays for health benefits have skyrocketed. Employers have instituted various cost-containment measures based in part on reports of wide variations in rates of utilization and the assumption that unnecessary or inappropriate utilization of medical care contributes to increasing costs. Frequently, however, employers lack adequate means for identifying sources of variation or for evaluating its appropriateness. In this article, we report on a project in which hospital utilization among several US corporate populations was compared with that for a geographically defined benchmark population to assist employers in the assessment of their rates of utilization and expenditures and to identify specific areas that merit further investigation. Our findings illuminate the difficulties in constructing valid rates from medical-care claims data and emphasize potential biases due to problems of comparability between populations. We also address the potential value of such comparison for helping corporations identify areas in which cost-containment efforts may be most effective and yet not jeopardize the quality of medical care.

Adolescent↗

PubMed1992

Contribution of a measure of disease complexity (COMPLEX) to prediction of outcome and charges among hospitalized patients.

Attention has been focused on the need to adjust hospital reimbursement and outcomes of hospital care for level of illness. Extant measures of disease severity, however, fail to consider the contribution of disease complexity. We developed an easily retrievable measure of disease complexity (COMPLEX) by modifying an existing severity system, computerized Disease Staging. The contribution of COMPLEX (the number of body systems affected with a Disease Staging score of 2 or more) to the prediction of outcome was assessed in two studies: (1) a population-based analysis of readmission and mortality after hospitalization and (2) an analysis of hospital charges among patients who were in an intensive-care unit. The amount of variation in mortality explained by factors included in the Health Care Financing Administration model was significantly improved when COMPLEX was added to the model (adjusted odds ratio per body system, 1.83; 95% confidence interval, 1.61 to 2.08). A significant association was also observed between COMPLEX score and hospital readmission after adjustment for age, sex, case-mix, and disease severity (adjusted odds ratio, 1.31; 95% confidence interval, 1.20 to 1.44). When COMPLEX was added to case-mix and disease severity in a model for predicting hospital charges, the percentage of variation in hospital charges explained by the model increased from 25% to 38%. These findings demonstrate the important contribution of disease complexity to the analysis of outcome of medical care and utilization of resources. Outcome or reimbursement models that do not incorporate disease complexity may negatively affect institutions with a high proportion of patients who have complex conditions.

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PubMed1992

The compression of morbidity hypothesis: promise and pitfalls of using record-linked data bases to assess secular trends in morbidity and mortality.

Individuals who are 65 years of age and older have exhibited unprecedented declines in mortality over the past few decades in the United States. Whether this increased survival has been accompanied by delays in the onset of disease or greater age-specific morbidity remains unanswered because of a paucity of reliable information on secular trends in age-specific disease incidence and survival. The Rochester Epidemiology Project (REP) is one of a few existing medical record linkage systems that offer promise of providing some of the necessary information. Several examples are presented that illustrate the potential of medical record-linked data bases for examining secular trends in the association between age at onset of disease and age at death.

Age Factors↗

PubMed1991

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

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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