Impact of computerized provider order entry (CPOE) on length of stay and mortality.

Objective: To examine changes in patient outcome variables, length of stay (LOS), and mortality after implementation of computerized provider order entry (CPOE). Materials and Methods: A 5-year retrospective pre-post study evaluated 66 186 patients and 104 153 admissions (49 683 pre-CPOE, 54 470 post-CPOE) at an academic medical center. Generalized linear mixed statistical tests controlled for 17 potential confounders with 2 models per outcome. Results: After controlling for covariates, CPOE remained a significant statistical predictor of decreased LOS and mortality. LOS decreased by 0.90 days, P < .0001. Mortality decrease varied by model: 1 death per 1000 admissions (pre = 0.006, post = 0.0005, P < .001) or 3 deaths (pre = 0.008, post = 0.005, P < .01). Mortality and LOS decreased in medical and surgical units but increased in intensive care units. Discussion: This study examined CPOE at multiple levels. Given the inability to randomize CPOE assignment, these results may only be applicable to the local setting. Temporal trends found in this study suggest that hospital-wide implementations may have impacted nursing staff and new residents. Differences in the results were noted at the patient care unit and room levels. These differences may partly explain the mixed results from previous studies. Conclusion: Controlling for confounders, CPOE implementation remained a statistically significant predictor of LOS and mortality at this site. Mortality appears to be a sensitive outcome indicator with regard to hospital-wide implementations and should be further studied.

Identifying potentially ineffective care in a community hospital.

OBJECTIVES: To develop a formula to predict mortality for intensive care unit patients between day 5 in an intensive care unit and 100 days after hospital discharge from a community hospital. DESIGN: Retrospective 1-yr derivation study with validation on a subsequent year's intensive care unit population. SETTING: An 850-bed, not-for-profit community hospital with three adult intensive care units, including medical-surgical, cardiac-medical, and cardiac-surgical units. PATIENTS: The development patient set included 4045 consecutive adult admissions to the intensive care unit between July 1995 and June 1996. The validation sample consisted of 4084 admissions between July 1996 and June 1997. RESULTS: During the first year, 100-day posthospital discharge mortality was predicted by the combination Acute Physiology and Chronic Health Evaluation (APACHE) III predicted mortality on day 5 of >0.92 or the product of day 1 and day 5 APACHE predicted mortality of >0.40, with an increase in the APACHE predicted mortality from day 1 to day 5 of >0.10. Specificity in the development cohort was 0.99, sensitivity was 0.30, and positive predictive value was 0.95. The second-year validation study demonstrated a specificity, sensitivity, and positive predictive value of 0.98, 0.29, and 0.91, respectively, when applying the model to the validation sample. CONCLUSIONS: By using readily available APACHE III data, we were able to identify patients at high risk of dying between intensive care unit day 5 and 100 days after discharge. Although the low sensitivity limits the number of patients for whom death at 100 days is predicted, the high specificity and positive predictive value suggests this information may provide useful information for families and physicians. If these formulas can be validated in diverse institutional settings, decisions regarding short- and long-term outcomes may be improved by using objective survival predictions from two time points.