Biomedical subjects
Publications and source records attributed to Peter B Bach.
We estimated the impact of vancomycin-resistant Enterococcus (VRE) infection on the outcomes of patients with leukemia in a case-control study. Compared with their matched controls (n = 45), cases (n = 23) had 22% greater total charges and shorter survival (P = .04). These findings substantiate the need for aggressive interventions to prevent VRE transmission.
OBJECTIVE: To compare surgeon and hospital procedure volume as predictors of outcomes for patients with rectal cancer. SUMMARY BACKGROUND DATA: Although a "volume-outcome" relationship exists for several major cancer operations, the impact of procedure volume on outcomes following rectal cancer surgery remains uncertain, and it has not been determined whether hospital or surgeon volume is a more important predictor of outcomes. METHODS: A retrospective population-based cohort study utilizing the Surveillance, Epidemiology and End Results (SEER)-Medicare linked database identified 2,815 rectal cancer patients aged 65 and older who had surgery for a primary tumor diagnosed in 1992-1996 in a SEER area. Hospital- and surgeon-specific procedure volume was ascertained based on the number of claims submitted over the 5-year study period. Outcome measures were mortality at 30 days and 2 years, overall survival, and the rate of abdominoperineal resections. Age, sex, race, comorbid illness, cancer stage, and socioeconomic status were used to adjust for differences in case mix. RESULTS: Neither hospital- nor surgeon-specific procedure volume was significantly associated with 30-day postoperative mortality or rates of rectal sphincter-sparing operations. Although an association between hospital volume and mortality at 2 years was evident, this finding was no longer significant once surgeon-specific volume was controlled for. In contrast, surgeon-specific volume was associated with 2-year mortality and remained an important predictor even after adjustment for hospital volume. Surgeon volume was also better than hospital procedure volume at predicting long-term survival. CONCLUSIONS: Surgeon-specific experience as measured by procedure volume can have a significant impact on survival for patients with rectal cancer.
Users of the linked SEER-Medicare database commonly perform analyses that focus on the complex interactions among patient characteristics, cancer treatments, and outcomes. The authors review the source and scope of the patient-specific data elements, with a focus on three domains--demographic characteristics, socioeconomic characteristics, and survival status. They offer some concrete recommendations regarding the use of these data elements. In particular, they describe analyses that provide an estimate of the accuracy of the sex and age variables, and raise some cautionary notes about race and ethnicity variables. The authors describe the available measures of socioeconomic status, and recommend, with some caveats, the use of median income measures as a proxy for socioeconomic status. Finally, they describe the available data on date of death, and explain why confidence in these measures is justified.
The context in which health care is delivered may have an impact on the outcomes and processes of care. Researchers analyzing claims data that reflect care rendered at many institutions may wish to identify hospital characteristics such as bed size, teaching status, degree of specialization, and case volume to evaluate their influence on outcomes. The authors describe the resources available from administrative data for characterizing hospitals. The article focuses on analyses using the SEER-Medicare-linked data, but has direct relevance for investigators working with other sources of claims data. First, the authors focus on assessment of hospital case volume, which is the principal hospital attribute that can be obtained directly from the SEER-Medicare data files. Second, they assess the information regarding hospital characteristics that can be gleaned from the American Hospital Association (AHA) survey and the annual cost reports submitted to the Center for Medicare and Medicaid Services (CMS) by all certified hospitals. From a comparison of the responses of 4,434 hospitals to 1994 AHA and CMS surveys, the authors conclude that the two data sources contain very similar information, but that for most investigators, use of data from CMS cost reports will be preferable to use of AHA data because of higher survey-completion rates and public availability.
BACKGROUND: The Surveillance, Epidemiology and End Results (SEER)-Medicare-linked database combines clinical information from population-based cancer registries with claims information from the Medicare program. The use of this database to study cancer screening, treatment, outcomes, and costs has grown in recent years. RESEARCH DESIGN: This paper provides an overview of the SEER-Medicare files for investigators interested in using these data for epidemiologic and health services research. The overview includes a description of the linkage of SEER and Medicare data and the files included as part of SEER-Medicare. The paper also describes the types of research projects that have been undertaken using the SEER-Medicare data. The overview concludes with a comparison of selected characteristics of elderly persons residing in the SEER areas to the US total aged. RESULTS: The paper identifies a number of potential uses of the SEER-Medicare data. The comparison of the elderly population in SEER areas to the US total shows that in the SEER areas there are a lower percentage of white persons and individuals living in poverty, and a higher percentage of urban-dwellers than the US total. Elderly persons in the SEER regions also have higher rates of HMO enrollment and lower rates of cancer mortality. CONCLUSIONS: The SEER-Medicare data are a unique resource that can be used for a variety of health services research projects. Although there are some differences between the elderly residing in the SEER areas and the US total, the SEER-Medicare data offer a large population-based cohort that can be used to longitudinally track care for persons over the course of cancer diagnosis, treatment, and follow-up.