Risk-adjusted Hospital Mortality Research Articles

Developing risk-adjusted 30-day hospital mortality rates.

This article describes one risk-adjustment method useful for minimizing threats to internal validity that stem from the impact on the outcomes under investigation from patients' own characteristics and their associated risks. Mortality is the outcome used to illustrate the risk-adjustment approach. A two-step approach to outcomes research is suggested. The first step includes risk-adjusting outcomes for patient characteristics by developing standard mortality rates. In the second step these risk-adjusted standard rates can be used as dependent variables in outcomes analytic models. This article focuses on the first step. In the current study risk adjustment resulted in changes in both absolute values and rank ordering of hospital mortality rates compared to crude rates. This procedure is useful for developing risk-adjusted outcomes with administrative data similar to those used in this study.

Predictors of readmission for complications of coronary artery bypass graft surgery.

Risk factors for perioperative mortality after coronary artery bypass graft (CABG) surgery have been extensively studied. However, which factors are associated with early readmissions following CABG surgery are less clear. To identify significant predictors of readmission within 30 days following CABG surgery. Causes for readmission within 30 days were investigated for all patients discharged after CABG surgery in the state of New York from January 1, 1999, through December 31, 1999. A variety of patient demographics, preoperative risk factors, complications, operative and postoperative factors, and provider characteristics were considered as potential predictors of readmissions. Hospital readmissions within 30 days of discharge following CABG surgery. Of 16 325 total patients, 2111 (12.9%) were readmitted within 30 days for reasons related to CABG surgery. The most common causes of readmission were postsurgical infection (n = 598 [28%]) and heart failure (n = 331 [16%]). Eleven risk factors were found to be independently associated with higher readmission rates: older age, female sex, African American race, greater body surface area, previous myocardial infarction within 1 week, and 6 comorbidities. After controlling for these preoperative patient-level risk factors, 2 provider characteristics (annual surgeon CABG volume <100, hospital risk-adjusted mortality rate in the highest decile) and 2 postoperative factors (discharge to nursing home or rehabilitation/acute care facility, length of stay during index CABG admission of > or =5 days) were also related to higher readmission rates. Readmission within 30 days following discharge is an important adverse outcome of CABG surgery. Continued attempts should be made to explore the potential of readmission as a supplement to mortality in assessing provider quality.

Preoperative intraaortic balloon pumps in high-risk patients undergoing open heart surgery

Background. The use of the preoperative intraaortic balloon pump (IABP) in patients with severe left ventricular dysfunction or unstable angina with critical coronary anatomy is becoming more frequent as surgical casemix changes. The aim of this study was to determine the impact of preoperative IABP use on survival in high-risk patients having open heart surgery. Methods. Prospectively collected data for 645 consecutive patients were reviewed. Patients receiving an IABP were identified and grouped as follows: group A (preoperative IABP for high-risk nonemergent cases), group B (preoperative IABP for emergent cases), and group C (intra/postoperative IABP). Risk-adjusted hospital mortality rates in these three groups was compared using the modified Parsonnet score for preoperative risk stratification. Results. IABPs were used in 101 cases (16%). The predicted versus actual hospital mortality rate was 20% versus 5.7% in group A, 32.1% versus 47.6% in group B, and 12.6% versus 22.2% in group C (group A vs group B, p = 0.0014; group A vs group C, p = 0.012). IABP-related morbidity occurred in 3% of cases (all in group C). Conclusions. Risk-adjusted mortality was significantly lower in high-risk cases with preoperative IABPs compared with emergent cases and intraoperative/postoperative IABPs. We encourage the use of preoperative IABPs in selected high-risk patients.

Does Competition Kill? Hospital Quality and Competition

We seek to estimate the effects of competition for both Medicare and HMO patients on the quality decisions of hospitals in Southern California. We find that increases in the degree of competition for HMO patients decrease risk-adjusted hospital mortality rates. Conversely, increases in competition for Medicare enrollees are associated with increases in risk-adjusted mortality rates for hospitals. In conjunction with previous research, our estimates indicate that increasing competition for HMO patients appears to reduce price and save lives and hence appears to be welfare improving. However, increases in competition for Medicare appears to reduce quality, and perhaps reduces welfare. The net effect of a given merger on hospital quality will depend on the geographic distribution of different payer groups.

Risk adjusted and population based studies of the outcome for high risk infants in Scotland and Australia

OBJECTIVESTo compare outcomes of care in selected neonatal intensive care units (NICUs) for very low birthweight (VLBW) or preterm infants in Scotland and Australia (study 1) and perinatal care for...

Assessing the Outcomes of Coronary Artery Bypass Graft Surgery: How Many Risk Factors Are Enough?

Objectives. We sought to determine whether more comprehensive risk-adjustment models have a significant impact on hospital risk-adjusted mortality rates after coronary artery bypass graft surgery (CABG) in Ontario, Canada.Background. The Working Group Panel on the Collaborative CABG Database Project has categorized 44 clinical variables into 7 core, 13 level 1 and 24 level 2 variables, to reflect their relative importance in determining short-term mortality after CABG.Methods. Using clinical data for all 5,517 patients undergoing isolated CABG in Ontario in 1993, we developed 12 increasingly comprehensive risk-adjustment models using logistic regression analysis of 6 of the Panel’s core variables and 6 of the Panel’s level 1 variables. We studied how the risk-adjusted mortality rates of the nine cardiac surgery hospitals in Ontario changed as more variables were included in these models.Results. Incorporating six of the core variables in a risk-adjustment model led to a model with an area under the receiver operating characteristic (ROC) curve of 0.77. The ROC curve area slightly improved to 0.79 with the inclusion of six additional level 1 variables (p = 0.063). Hospital risk-adjusted mortality rates and relative rankings stabilized after adjusting for six core variables. Adding an additional six level 1 variables to a risk-adjustment model had minimal impact on overall results.Conclusions. A small number of core variables appear to be sufficient for fairly comparing risk-adjusted mortality rates after CABG across hospitals in Ontario. For efficient interprovider comparisons, risk-adjustment models for CABG could be simplified so that only essential variables are included in these models.

Assessing open heart surgery mortality in Catalonia (Spain) through a predictive risk model.

To develop a risk stratification model to assess open heart surgery mortality in Catalonia (Spain) in order to use risk-adjusted hospital mortality rates as an approach to analyze quality of care. Data were prospectively collected through a specific data-sheet during 6 1/2 months in consecutive adult patients subjected to open heart surgery. The dependent variable was surgical mortality, and independent variables included were presurgical (sociodemographic data, clinical antecedents, morphological and functional studies) and surgical. The model was built on a subsample (70% of study population) through univariate and logistic regression analysis and validated in the rest of the sample. The total sample was of 1309 procedures in seven hospitals; 47% of them were valve procedures. The overall crude mortality rate was 10.9% and varied among centers (range, 2.8-14.8%). Risk factors included in the model received a weight based on the logistic regression coefficient and a score was generated for each patient. The factors with the highest weight were patient older than 80 and second reoperation. Score was stratified in five categories of increasing risk. There was a good agreement between observed and predicted mortality rates in the validation group. Overall patient distribution was as follows: 52% low risk level, 16% fair, 13% high, 12% very high, and 6% extremely high risk level. Mortality rate increased from 4.2% in the low risk to 54.4% in the highest risk group. Case mix adjustment was performed through the risk score level. There were statistically significant differences in the risk profiles of patients admitted among centers. After adjustment by risk profiles, there were no differences in mortality by hospital. A risk stratification model through a multicentric, prospective and exhaustive collection of data in all types of open heart procedures was developed. In spite of wide differences on crude rates and in the risk profiles of patients admitted, we did not find statistically significant differences in adjusted mortality rates among centers. Timely and accurate information about surgical outcomes can lead to improvements in clinical practice and quality of care.

Racial Variation in Predicted and Observed In-Hospital Death

To compare observed, predicted, and risk-adjusted hospital mortality rates in white and African-American patients and to determine whether, as prior studies suggest, African-American patients would have higher predicted risks of death and similar or higher risk-adjusted mortality. Retrospective cohort study. Thirty hospitals in northeast Ohio. A total of 88205 eligible patients consecutively discharged in the years 1991 through 1993 with the following 6 diagnoses: acute myocardial infarction, congestive heart failure, obstructive airways disease, gastrointestinal hemorrhage, pneumonia, and stroke. We measured predicted risks of death at admission for each diagnosis using validated multivariable models based on standard clinical data abstracted from patients' medical records. We then adjusted in-hospital mortality rates in white and African-American patients for predicted risk of death and other covariates using logistic regression analysis. Predicted risk of death at admission and observed hospital mortality in white and African-American patients. Predicted risks of death were lower (P<.001) in African Americans for 4 of the 6 diagnoses. Adjusted odds of hospital death were lower (P<.01) in African Americans for 2 of the 6 diagnoses (congestive heart failure and obstructive airways disease) and similar for the other 4 diagnoses. For all diagnoses, in aggregate, the adjusted odds of hospital death were 13% lower in African-American compared with white patients (multivariable odds ratio, 0.87; 95% confidence interval, 0.80-0.94). Findings were similar if further adjustments were made for differences in length of stay, site of hospitalization, or discharge triage practices. Contrary to our a priori hypotheses, predicted risks of death and risk-adjusted mortality rates were generally lower in African-American patients. Our finding of lower predicted risk may reflect racial differences in hospital admission practices or in access to outpatient care. However, our findings suggest that, once hospitalized, African-American patients attained similar or better outcomes, as measured by an important measure--hospital mortality.

Judging hospitals by severity-adjusted mortality rates: the influence of the severity-adjustment method.

This research examined whether judgments about a hospital's risk-adjusted mortality performance are affected by the severity-adjustment method. Data came from 100 acute care hospitals nationwide and 11880 adults admitted in 1991 for acute myocardial infarction. Ten severity measures were used in separate multivariable logistic models predicting in-hospital death. Observed-to-expected death rates and z scores were calculated with each severity measure for each hospital. Unadjusted mortality rates for the 100 hospitals ranged from 4.8% to 26.4%. For 32 hospitals, observed mortality rates differed significantly from expected rates for 1 or more, but not for all 10, severity measures. Agreement between pairs of severity measures on whether hospitals were flagged as statistical mortality outliers ranged from fair to good. Severity measures based on medical records frequently disagreed with measures based on discharge abstracts. Although the 10 severity measures agreed about relative hospital performance more often than would be expected by chance, assessments of individual hospital mortality rates varied by different severity-adjustment methods.

Severity Measurement Methods and Judging Hospital Death Rates for Pneumonia

Payers and policymakers are increasingly examining hospital mortality rates as indicators of hospital quality. To be meaningful, these death rates must be adjusted for patient severity. This research examined whether judgments about an individual hospital's risk-adjusted mortality is affected by the severity adjustment method. Data came from 105 acute care hospitals nationwide that use the Medis-Groups severity measure. The study population was 18,016 adults hospitalized in 1991 for pneumonia. Multivariable logistic models to predict in-hospital death were computed separately for 14 severity methods, controlling for patient age, sex, and diagnosis-related group (DRG). For each hospital, observed-to-expected death rates and z scores were calculated for each severity method. The overall in-hospital death rate was 9.6%. Unadjusted mortality rates for the 105 hospitals ranged from 1.4% to 19.6%. After adjusting for age, sex, DRG, and severity, 73 facilities had observed mortality rates that did not differ significantly from expected rates according to all 14 severity methods; two had rates significantly higher than expected for all 14 severity methods. For 30 hospitals, observed mortality rates differed significantly from expected rates when judged by one or more but not all 14 severity methods. Kappa analysis showed fair to excellent agreement between severity methods. The 14 severity methods agreed about relative hospital performance more often than expected by chance, but perceptions of individual hospitals' mortality rates varied using different severity adjustment methods for almost one third of facilities. Judgments about individual hospital performance using different severity adjustment approaches may reach different conclusions.

Reoperation on prosthetic heart valves: Patient-specific estimates of in-hospital events

Reoperation on prosthetic heart valves is increasingly under consideration for both clinical and prophylactic indications. To determine the correlates of hospital events, including in-hospital mortality, new persisting neurologic deficit, and length of postoperative stay, a three-institution study of 2246 consecutive prosthetic valve reoperations performed on 1984 patients between 1963 and 1992 was undertaken. The combined experience ranged from high-risk patients coming moribund to the operating room to an important number of well individuals undergoing prophylactic reoperations on potentially failing valves. The risk-unadjusted hospital mortality was 10.8%, neurologic deficit at hospital discharge 1.1%, and length of stay 10 days (median). Multivariably determined correlates of outcome included age at reoperation, degree, severity, and acuity of impairment of cardiac function, extensiveness of valvular heart disease, coexisting morbid conditions, number of previous heart operations, and concomitant procedures. The risk-adjusted hospital mortality for the first elective reoperation in a good-risk patient was 1.3% (90% confidence limits 0.3% to 4.4%), neurologic deficit 0.3% (90% confidence limits 0.02% to 1.8%), and length of postoperative stay 7 days (90% confidence limits 4 to 13), emphasizing the wide variance in outcome events. Equations were developed to permit wide application of the results of the study for quantitatively estimating the risk of outcome events based on individual preoperative patient characteristics. These estimates should be useful for informed patient consent, considerations of prophylactic valve replacement, and cost and resource use. (J T horac C ardiovasc S urg 1995;109:30-48)

Chance, Continuity, and Change in Hospital Mortality Rates

To assess whether risk-adjusted mortality rates for hospitals reflect primarily chance variation. Observation over time. All 115 California hospitals with five or more coronary artery bypass graft (CABG) patients in any year 1983 to 1989. All CABG patients aged 18 years and older excluding those with other open heart procedures and percutaneous transluminal coronary angioplasty on the day of CABG surgery (n = 132,750). Inpatient mortality adjusted for age, gender, chronic comorbidities, timing of surgery, and presence of additional procedures. Data were derived from routinely collected hospital discharge abstracts. Observed and expected semiannual mortality rates were examined for each hospital to identify consistent patterns over time. Using the quartile of patients with the highest predicted risk (average mortality, 10%), high- and low-outlier hospitals were identified from 2 consecutive years of pooled data and outcomes 2 years later were examined. Each hospital-year observation was also examined individually to identify outliers and to assess differences for observed and expected death rates, patient volume, and other characteristics. Some hospitals showed consistently lower-than-expected inpatient mortality. Some hospitals had periods of significantly higher-than-expected mortality followed by a correction. High-outlier hospitals that were selected based on 2 years of data had mortality rates 2 years later that averaged 31% above expected, while low-outlier hospitals had rates 2 years later that averaged 28% below expected. On a contemporaneous basis, high outliers had proportionately more transfers to other acute care hospitals and longer postoperative stays among survivors. Risk-adjusted outcomes for CABG patients derived from administrative data exhibit substantial patterns of consistency. Such patterns cannot be detected for low-risk patients but are evident for the top quartile of patients stratified by risk. Even with reporting lags and changes in hospital outcomes over time, a policy of channeling high-risk patients away from high-outlier hospitals and toward low-outlier hospitals could lower their overall risk-adjusted mortality rate by 45% [corrected].

Risk Adjusted Hospital Mortality Norms

Healthcare Knowledge Systems, 1968 Green Road, Ann Arbor, MI 48106, 1988, 241 pages. 3-ring looseleaf binder, $85.00.