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Rationale, Aims and Objectives: Checklists have been adopted by various institutions to improve patient outcomes. In particular, readmission prevention checklists may be of potential value to improve patient care and reduce medical costs. As a result, a prior quality improvement study was conducted to create an intensive care unit readmission prevention checklist. The previous pilot demonstrated zero readmissions when the readmission prevention checklist was utilized but yielded low compliance (30%). Thus, a subsequent quality initiative was undertaken to refine the readmission prevention checklist with the primary aim of improved compliance while maintaining a reduced readmission rate that was observed with the original quality improvement study., Method: A single-centre, cross-sectional study for assessing baseline data and a prospective observational study to assess the effectiveness of a refined readmission prevention checklist tool in a 20-bed tertiary medical-surgical intensive care unit at an academic medical centre in Rochester, MN was conducted. Medical patients admitted through the emergency department, upon direct transfer from outside facility, and post-operative surgical patients at our institution were included. A refined readmission prevention checklist tool was administered during an 8-week pilot period for medical and post-operative surgical patients., Results: The refined readmission prevention checklist resulted in an even lower compliance (10.5%) from the initial phase likely resulting from utilization of a paper readmission prevention checklist in an electronic medical environment. Moreover, the refined readmission prevention checklist demonstrated a 22% unplanned readmission rate for patients in which the tool was utilized., Conclusions: In conclusion, the findings of the current quality improvement study may serve to rethink the process of health care delivery that applies paper tools in an electronic medical environment., (© 2014 John Wiley & Sons, Ltd.)

Objective: To investigate the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) III scoring system in patients admitted to the intensive care unit (ICU) after major vascular surgery. Design: Retrospective cohort study. Setting: A tertiary referral center. Participants: Three thousand one hundred forty-eight patients who underwent major vascular surgery between October 1994 and March 2006. Interventions: None. Measurements and Main Results: Data were abstracted from an institutional APACHE III database. Standardized mortality ratios (SMRs) (with 95% confidence intervals) were calculated. The area under the receiver operating characteristic curve (AUC) and Hosmer-Lemeshow C statistic were used to assess discrimination and calibration, respectively. The mean age of 3,148 patients studied was 70.5 years (±standard deviation 9.6). The mean Acute Physiology Score and the APACHE III score on the day of ICU admission were 31.0 (±17.5) and 45.1 (±18.8), respectively. The mean predicted ICU and hospital mortality rates were 3.2% (±7.8%) and 5.0% (±9.5%), respectively. The median (and interquartile range) ICU and hospital lengths of stay were 4.3 (3.6-5.1) and 14 days (11.9-16.8 days), respectively. The observed ICU mortality rate was 2.4% (75/3, 148 patients) and hospital mortality rate was 3.7% (116/3,148). The ICU and hospital SMRs were 0.74 (0.58-0.91) and 0.74 (0.61-0.88), respectively. The AUC of APACHE III–derived prediction of hospital mortality was 0.840 (95% confidence interval, 0.799-0.880), indicating excellent discrimination. The Hosmer-Lemeshow C statistic was 28.492, with a p value <0.01, indicating poor calibration. Conclusions: The APACHE III scoring system discriminates well between survivors and nonsurvivors after major vascular surgery, but calibration of the model is poor. [Copyright &y& Elsevier]