OBJECTIVES We sought to validate recently proposed risk adjustment models for in-hospital percutaneous transluminal coronary angioplasty (PTCA) mortality on an independent data set of high risk patients undergoing PTC...
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OBJECTIVES We sought to validate recently proposed risk adjustment models for in-hospital percutaneous transluminal coronary angioplasty (PTCA) mortality on an independent data set of high risk patients undergoing PTCA. BACKGROUND Risk adjustment models for PTCA mortality have recently been reported, but external validation on independent data sets and on high risk patient groups is lacking. METHODS Between July 1, 1994 and June 1, 1996, 1,476 consecutive procedures were performed on a high risk patient group characterized by a high incidence of cardiogenic shock (3.3%) and acute myocardial infarction (14.3%). Predictors of in-hospital mortality were identified using multivariate logistic regression analysis. Two external models of in-hospital mortality, one developed by the Northern New England Cardiovascular Disease Study Group (model NNE) and the other by the Cleveland Clinic (model CC), were compared using receiver operating characteristic (ROC) curve analysis. RESULTS In this patient group, an overall in-hospital mortality rate of 3.4% was observed. Multivariate regression analysis identified risk factors for death in the hospital that were similar to the risk factors identified by the two external models. When fitted to the data set, both external models had an area under the ROC curve >0.85, indicating overall excellent model discrimination, and both models were accurate in predicting mortality in different patient subgroups. There was a trend toward a greater ability to predict mortality for model NNE as compared with model CC, but the difference was not significant. CONCLUSIONS Predictive models for PTCA mortality yield comparable results when applied to patient groups other than the one on which the original model was developed. The accuracy of the two models tested in adjusting for the relatively high mortality rate observed in this patient group supports their application in quality assessment or duality improvement efforts. (J Am Coll Cardiol 1999;34:69
Background: Commonly performed elective gastrointestinal surgical procedures are carried out with low morbidity and mortality in hospitals throughout the United States. Complex operative procedures on the alimentary t...
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Background: Commonly performed elective gastrointestinal surgical procedures are carried out with low morbidity and mortality in hospitals throughout the United States. Complex operative procedures on the alimentary tract are performed with a relatively low frequency and are associated with higher mortality. Volume and experience of the surgical provider team have been correlated with better clinical and economic outcomes for one complex gastrointestinal surgical procedure, pancreaticoduodenectomy. This study evaluated whether provider volume and experience were important factors influencing clinical and economic outcomes for a variety of complex gastrointestinal surgical procedures in one state. Study Design: Complex high-risk gastrointestinal surgical procedures were defined as those with statewide in hospital mortality of greater than or equal to 5%, frequency of greater than 200 per year in the state, and requiring special surgical skill and expertise. Six procedures met these criteria. Using publicly available discharge data, all patients discharged from Maryland hospitals from July 1989 to June 1997 with a primary procedure code for one of the six study procedures were selected. Hospitals were classified into one of six groups based on the average number of study procedures per year: 10 or less;11 to 20;21 to 50;51 to 100;101 to 200;and 201 or more procedures per year. A hospital was included if at least one procedure was performed there during the study period. No providers fell within the 51 to 100, and 101 to 200 groups, so all analyses were performed for the remaining four volume groups that were classified, respectively, as minimal (10 or fewer procedures), low (11 to 20 procedures), medium (21 to 50 procedures)., and high-volume groups (201 or more procedures). Poisson regression was used to assess the relationship between in-hospital mortality and hospital volume after casemix adjustment. Multiple linear regression models were used to assess differences
The effectiveness of risk adjustment in improving mortality as a performance measure for hospitals remains uncertain. New techniques of risk adjustment should be empirically tested, and health care professionals, usin...
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The effectiveness of risk adjustment in improving mortality as a performance measure for hospitals remains uncertain. New techniques of risk adjustment should be empirically tested, and health care professionals, using the data derived from such measures, should be queried before final acceptance of these technologies of measurement is warranted. The Risk Adjusted Clinical Outcomes Methodology-Quality Measures (RACOM-QM), a relatively new risk-adjustment methodology developed by the QuadraMed Corporation, was used by Maryland hospitals for risk adjustment for the first time in 1997. A research study was undertaken by the Maryland Hospital Association to determine the impact of RACOM-QM on mortality rates, its empirical validity, and its acceptance in the field. The relationship between RACOM-QM mean risk scores and mortality rates was examined using inpatient hospital mortality data for Maryland in 1996. Using these same data, the empirical relationship between risk-adjusted and unadjusted mortality by diagnosis-related group (DRG) was also investigated. Case studies were undertaken to glean information about the use and acceptability of this new methodology in 2 hospital settings in Maryland. There was a strong relationship between mean mortality risk scores and mortality rates. The analysis of the empirical relationship between risk-adjusted and unadjusted mortality by DRG yielded support for the impact of RACOM-QM in adjusting inpatient mortality rates. The case studies supported the utility of this method of risk adjustment in increasing the interpretation of mortality data and in helping to identify areas in which to investigate quality in more depth in 2 hospital settings. This study provides overall support for the usefulness of risk adjustment and, specifically, the RACOM-QM, in increasing the interpretation of inpatient mortality rates in Maryland's acute care hospitals. This study also suggests that use of the RACOM-QM improved comparative analysis of inpa
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