Using PC-based decision-support technology to improve efficiency.

Healthcare organizations do not need advanced information technology systems to take advantage of the information they gather regarding clinical and operational efficiency. PC-based decision support technology is available to analyze an integrated delivery system's (IDS) existing data and integrate it with competitive healthcare industry data from public and proprietary sources. Many system executives have purchased such technology for their IDSs, but few use the data they generated properly or successfully.

Comparing low-severity hospital admissions in IPA HMOs and indemnity-type programs.

This study compares the proportion of low-severity hospital patients in independent practice association (IPA) HMOs and indemnity-type programs. The length of stay of such low-severity patients is also studied. Admissions of IPA patients under age 65 to ten hospitals are compared with admissions to the same hospital of patients covered by Blue Cross and Blue Shield plans or commercial insurance programs. Admissions to the adult medical service for the eight most frequently occurring DRGs with 5 percent or more patients in the low-severity category are included. A Logit model of the probability of low-severity admission controlling for age, sex, DRG, and hospital shows no significant IPA effect. However, a multiple regression model shows that the IPAs have significantly lower average length of stay for these low-severity patients.

Inter-hospital mortality and morbidity variation in Pennsylvania.

A 1986 Pennsylvania law requires the public disclosure of hospital mortality and morbidity rates. This study of hospital admissions in 1989 and 1990 examines the variation in these health-outcome indicators for the 10 most frequently occurring DRGs in the adult medical service in a sample of 20 Pennsylvania hospitals. These mortality and morbidity rates are adjusted for admission severity, DRG, age, and sex, using a logistic regression model. The null hypothesis of no significant variation among hospitals is rejected by the statistically significant (p < 0.01) results of a likelihood ratio test on the hospital variables in logit models for both mortality and morbidity. Test results also show that 4 (20 percent) of 20 hospitals have statistically significant (p < 0.05) adjusted mortality rates, and 4 (20 percent) of 20 hospitals have significant morbidity rates. Such information may impact hospital management practices in a variety of ways.

Interhospital variations in admission severity-adjusted hospital mortality and morbidity.

In this study hospital admissions are categorized into admission severity groups based on key clinical findings. Severity of illness is determined again later in the hospital stay after treatment has been initiated. High severity on this second review is labeled major morbidity or morbidity, depending on the severity level, and these rates serve as a health outcome indicator along with in-hospital mortality. This study's findings show, for ten hospitals randomly selected from MedisGroups users, considerable interhospital variation in standardized mortality and morbidity ratios for ten frequently occurring DRGs on the adult medical service. After adjusting for admission severity and case mix, three of the ten study hospitals have a statistically significant (p less than .01) difference between the hospital's standardized mortality ratio and 1.0. Such a significant difference exists for the standardized major morbidity ratio of four hospitals and for the standardized morbidity ratio of three hospitals. At the DRG-specific level, our results show that 8.9 percent, 4.4 percent, and 15.0 percent of the hospital-specific mortality, major morbidity, and morbidity ratios, respectively, are statistically significant. Most hospital outliers have fewer deaths or morbid cases than expected. We caution that the study hospitals may not be representative of a larger group of U.S. hospitals.

Comparing hospital length of stay in independent practice association HMOs and traditional insurance programs.

This study compares length of hospital stay in Independent Practice Association (IPA) HMOs and traditional insurance programs. Hospital admissions from 10 IPAs are compared with admissions to the same hospital of persons covered by Blue Cross and Blue Shield Plans or commercial insurance programs. Admissions of patients under age 65 to the adult medical service for the 10 most frequently occurring DRGs are included. Regression equations are estimated using length of stay as the dependent variable and IPA membership and hospital and patient characteristics as control variables. All 10 IPAs exhibit shorter lengths of stay as indicated by negative beta coefficients, and in 6 of the 10 IPAs this coefficient is statistically significant (p less than .05). This IPA effect occurs for 7 of the 10 study DRGs, and for MedisGroups Admission Severity Groups 0, 1, and 2.

Managing hospital quality through a clinical severity approach.

The authors briefly describe the Medical Illness Severity Groupings System (MedisGroups), a computerized hospital management information system focusing on health outcomes. The implications of health outcome information for hospital marketing activities are discussed. Important changes in the way hospitals currently approach these marketing functions are recommended.