Variations in Standardized Hospital Mortality Rates for Six Common Medical Diagnoses

Rosenthal, Gary E.; Shah, Amrik; Way, Lynne E.; Harper, Dwain L.

doi:10.1097/00005650-199807000-00003

Cited by 53 publications

(29 citation statements)

References 28 publications

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“…Most studies assessed the relationship for different medical diagnoses (e.g., pneumonia and acute myocardial infarction), and found weak correlations in mortality rates (8,9). There are two alternative explanations for the lack of correlations found in these studies.…”

Section: Discussionmentioning

confidence: 97%

“…Evidence from a prior simulation by Rosenthal et al supports this assertion. If the "true" correlations were perfect (r=1.0), it would require several thousand cases in each hospital to identify them (8). Second, the relationships between mortality with different medical conditions may truly be weak.…”

Section: Discussionmentioning

confidence: 99%

“…However, this approach will only be useful to the extent that hospital performance with different operations is correlatedi.e., that hospitals good at one operation are also good at others. While previous studies show relatively weak relationships between outcomes for different medical diagnoses, there is some reason to believe these relationships may be stronger in surgery (8,9). Many high-risk operations are dependent on the same hospital-level resources, staffing, and processes of care (10).…”

Section: Introductionmentioning

confidence: 98%

See 2 more Smart Citations

Are Mortality Rates for Different Operations Related?

Dimick¹,

Staiger²,

Birkmeyer³

2006

Medical Care

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Background-Except in cardiac surgery, measuring quality with procedure-specific mortality rates is unreliable due to small sample sizes at individual hospitals. Statistical power can be improved by combining mortality data from multiple operations. We sought to determine whether this approach would still be useful in understanding performance with individual procedures.Methods-We studied eleven high-risk operations performed in the national Medicare population (1996)(1997)(1998)(1999). For each operation, we calculated 1) the risk-adjusted mortality rate for the procedure and 2) the mortality rate with up to ten other operations combined ("other" mortality). To test for an association between these mortality rates, we calculated the correlation coefficient adjusting for random variation. We then collapsed hospitals into quintiles of other mortality and calculated procedure-specific mortality rates within each of these quintiles.Results-Mortality with specific operations was modestly correlated with other mortality: coefficients ranged from 0.14 for pneumonectomy to 0.35 for esophagectomy. Despite small to moderate correlations, other mortality was a good predictor of procedure-specific mortality for 10 of the 11 operations. Pancreatic resection had the strongest relationship, with procedure-specific mortality rates at hospitals in the worst quintile of other mortality 3-fold higher than those in the best quintile (15.2% vs. 6.3%, p<.001). Pneumonectomy had the weakest relationship, with no significant relationship between other mortality and procedure-specific mortality.Conclusions-Hospitals with low mortality rates for one operation tend to have lower mortality rates for other operations. These relationships suggest that different operations share important structures and processes of care related to performance. Future efforts aimed at predicting procedurespecific performance should consider incorporating data from other operations at that hospital. KeywordsMeasurement; surgery; quality; performance; hospitals IntroductionBecause of widespread recognition that surgical quality varies widely, there is growing demand from patients, providers, and payers for better measures of surgical outcomes (1,2). Riskadjusted mortality rates are a simple and reliable measure of surgical quality and have been used to good effect in cardiac surgery (3,4 frequently enough to reliably discriminate quality among individual hospitals using this approach (5,6).One way to improve outcomes measurement in non-cardiac surgery is to combine several operations together when assessing hospital mortality rates (7). However, this approach will only be useful to the extent that hospital performance with different operations is correlatedi.e., that hospitals good at one operation are also good at others. While previous studies show relatively weak relationships between outcomes for different medical diagnoses, there is some reason to believe these relationships may be stronger in surgery (8,9). Many high-risk operations are dependent ...

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

Are Mortality Rates for Different Operations Related?

Dimick¹,

Staiger²,

Birkmeyer³

2006

Medical Care

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“…[1][2][3] However, in recent years there has been renewed interest in overall hospital mortality, specifically the hospital standardized mortality ratio (HSMR) (Box 1). [4][5][6][7][8] Although efforts to measure performance represent welcome developments, the focus on the hospital standardized mortality ratio, especially when the ratio is derived solely from administrative data, goes against the results of decades of investigation.…”

mentioning

confidence: 99%

Hospital mortality: when failure is not a good measure of success

Shojania¹,

Forster²

2008

Canadian Medical Association Journal

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“…Whittle, et al (1998), Rosenthal, et al (1998, Iezzoni, et al (1996), Hartz et al (1989), Shortell and Hughes (1988) and Dubois, et al (1987)). Thus, our findings will provide some indication on the extent of the biases that may plague analyses that do not correct for selection.…”

mentioning

confidence: 99%

Estimating the quality of care in hospitals using instrumental variables

Gowrisankaran

Town

1999

Journal of Health Economics

161

145

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Mortality rates are a widely used measure of hospital quality. A central problem with this measure is selection bias: simply put, severely ill patients may choose high quality hospitals. We control for severity of illness with an instrumental variables (IV) framework using geographic location data. We use IV to examine the quality of pneumonia care in Southern California from 1989 to 1994. We find that the IV quality estimates are markedly different from traditional GLS estimates, and that IV reveals different determinants of quality. Econometric tests suggest that the IV model is appropriately specified, that the GLS model is inconsistent.

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Variations in Standardized Hospital Mortality Rates for Six Common Medical Diagnoses

Cited by 53 publications

References 28 publications

Are Mortality Rates for Different Operations Related?

Are Mortality Rates for Different Operations Related?

Hospital mortality: when failure is not a good measure of success

Estimating the quality of care in hospitals using instrumental variables

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