Biomedical subjects

J S Avrunin

Publications and source records attributed to J S Avrunin.

7 recordsLinked to original sources

PubMed1990

Explaining variability of cost using a severity-of-illness measure for ICU patients.

Factors related to hospital resource use by intensive care unit (ICU) patients, including severity of illness at admission and intensity of therapy during the first 24 ICU hours were explored in this study. Analysis was based on 2,749 patients admitted to the general medical-surgical ICU at Baystate Medical Center, Springfield, Massachusetts, between February 1, 1983 and January 10, 1985. Resource use was indexed by hospital length of stay (LOS) adjusted for differences between ICU and other hospital days. Severity of illness was measured by the Mortality Prediction Model (MPM0), a validated predictor of outcome but not previously used to analyze resource consumption. Intensity of therapy was measured using the Therapeutic Intervention Scoring System (TISS). The 10% of patients with longest ICU stays were significantly different from the other 90% with respect to previous ICU use, MPM probability, and TISS score. Variability in resource use was analyzed using four diagnosis-related groups (DRGs) accounting for large numbers of ICU patients. The relationship between severity of illness and resource was nonlinear: as severity increased from low levels, resource use increased at a decreasing rate, reached a plateau, and eventually declined. Within each DRG, MPM0 explained a statistically significant percentage of the variability in resource use.

Costs and Cost Analysis↗

PubMed1989

Intensive care unit patient follow-up. Mortality, functional status, and return to work at six months.

Six months after hospital discharge, we followed up 1545 patients who had received care in the general medical-surgical intensive care unit (ICU) of a tertiary care hospital. Vital status could not be ascertained for 200 of these patients. Of the 1345 former ICU patients for whom a determination of vital status could be made, 1261 (94%) were alive and 84 (6%) had died. Of those known to be living, 887 (70%) responded to a questionnaire regarding employment, functional, and social status. A large proportion of survivors less than 40 years of age had returned to work. Younger patients admitted to the hospital for elective surgery reported as much compromise of physical and psychological activity as did older patients admitted for emergency reasons. Older survivors reported an increase of interaction with family members and a decrease of social interaction with those other than family.

Adult↗

PubMed1988

Refining intensive care unit outcome prediction by using changing probabilities of mortality.

Estimating prognosis is potentially useful as a measure of ICU performance and as a guide for the clinical care of individual patients. In this study, mortality prediction models (MPMs) for patients in an adult general medical-surgical ICU were derived from data gathered at ICU admission and after 24 and 48 h of ICU care. A predictive model was developed which incorporated a sequence of probabilities collected over time in the ICU. The results of this study suggest that using serial observations may enhance substantially the usefulness of the MPM as a vehicle for helping families anticipate the patients' likely outcome.

Humans↗

PubMed1987

Validation of the mortality prediction model for ICU patients.

We tested recently developed admission and 24-h models of hospital mortality on 1,997 consecutive admissions to a general medical/surgical ICU. This study population was independent of the group used to develop the models. The admission prediction model estimated each patient's probability of hospital mortality based on seven routinely collected admission variables. The 24-h model utilized seven variables routinely available at 24 h in the ICU. The admission model accurately described the mortality experience of the new cohort, while the 24-h model did not. Advantages of the admission model are that it is evaluable at the time of ICU admission, is independent of ICU treatment, and can be used to stratify patients by severity of illness, thereby making ICU comparisons possible. Its excellent goodness-of-fit, correct classification rate, sensitivity, and specificity suggest that this model is now ready for multihospital testing.

Aged↗

PubMed1987

A comparison of methods to predict mortality of intensive care unit patients.

This paper presents results of the first study explicitly designed to compare three methods for predicting hospital mortality of ICU patients: the Acute Physiology Score (APS), the Simplified Acute Physiology Score (SAPS), and the Mortality Prediction Model (MPM). With respect to sensitivity, specificity, and total correct classification rates, these methods performed comparably on a cohort of 1,997 consecutive ICU admissions. In these patients from a single hospital, the APS overestimated and the SAPS underestimated the probability of hospital mortality. The MPM probabilities most closely matched the observed outcomes. Each method holds considerable promise for assessing the severity of illness of critically ill patients. The MPM should be particularly useful for comparing ICU performance, since it is independent of ICU treatment and can be calculated at the time a patient is admitted.

Diagnosis-Related Groups↗

PubMed1985

Applications of microcomputer spreadsheet packages as adjuncts to multiple logistic regression analysis.

This paper illustrates how a microcomputer spreadsheet package can be used by epidemiologists to facilitate the computation of multiple logistic regression (MLR) probabilities, as well as odds ratios and associated confidence intervals, given the coefficients of the MLR model. By formatting a spreadsheet, data entry is greatly simplified, and computations are accomplished without any arithmetic manipulations on the part of the user. This approach makes it feasible for clerical support staff to assist in the computation of seemingly complex expressions. The increasing availability of microcomputers in clinical and research settings suggests that numerous analytic applications are amenable to this approach, thereby decreasing reliance on mainframe computers and desk-top calculators.

Computers↗

PubMed1985

A method for predicting survival and mortality of ICU patients using objectively derived weights.

Data at ICU admission and after 24 h in the ICU were collected on 755 patients, to derive multiple logistic regression models for predicting hospital mortality. The derived models contained relatively few and easily obtained variables. The weight associated with each variable was determined objectively. There were seven admission variables, none of which were treatment dependent, and seven 24-h variables reflecting treatments and patients' conditions in the ICU. Predicted outcomes using these two models were closely correlated with actual outcome. Theoretically, a predictive model would be useful to physicians for triage decisions as well as determining aggressiveness of care through discussions with families, determining utilization of ICU facilities, and objectively comparing different ICUs. This research represents an initial attempt to develop models that are not based on subjectively determined weights.

Adolescent↗