A Tool to Predict Readmission to the Intensive Care Unit in Surgical Critical Care Patients-The RISC Score.

BACKGROUND: Readmission to the Intensive Care Unit (ICU) is associated with a high risk of in-hospital mortality and higher health care costs. Previously published tools to predict ICU readmission in surgical ICU patients have important limitations that restrict their clinical implementation. We sought to develop a clinically intuitive score that can be implemented to predict readmission to the ICU after surgery or trauma. We designed the score to emphasize modifiable predictors. METHODS: In this retrospective cohort study, we included surgical patients requiring critical care between June 2015 and January 2019 at Beth Israel Deaconess Medical Center, Harvard Medical School, MA, USA. We used logistic regression to fit a prognostic model for ICU readmission from a priori defined, widely available candidate predictors. The score performance was compared with existing prediction instruments. RESULTS: Of 7,126 patients, 168 (2.4%) were readmitted to the ICU during the same hospitalization. The final score included 8 variables addressing demographical factors, surgical factors, physiological parameters, ICU treatment and the acuity of illness. The maximum score achievable was 13 points. Potentially modifiable predictors included the inability to ambulate at ICU discharge, substantial positive fluid balance (>5 liters), severe anemia (hemoglobin <7 mg/dl), hyperglycemia (>180 mg/dl), and long ICU length of stay (>5 days). The score yielded an area under the receiver operating characteristic curve of 0.78 (95% CI 0.74-0.82) and significantly outperformed previously published scores. The performance of the underlying model was confirmed by leave-one-out cross-validation. CONCLUSION: The RISC-score is a clinically intuitive prediction instrument that helps identify surgical ICU patients at high risk for ICU readmission. The simplicity of the score facilitates its clinical implementation across surgical divisions.

A multidimensional framework for assessing patient room configurations.

PURPOSE: A framework for multidimensional assessment of patient room configurations is presented. Twenty-three issues are considered and categorized under six domains of assessment: (1) patient safety, (2) staff efficiency, (3) circulation, (4) infection control, (5) patient considerations, and (6) family amenities. Use of the framework to rank issues by importance and assess six alternative patient room configurations by a diverse group of experts in a symposium is described. BACKGROUND: One of the key questions posed during inpatient room design is the location of the bathroom. What issues are affected by the variations in room configuration that arise from bathroom location? A complete articulation of the issues that potentially are affected by room configuration is not available in the literature. FRAMEWORK: The list of issues was developed by the authors in preparation for a symposium. The symposium was organized in May 2007 and attended by 14 experts from four institutions. Six alternative room configurations were used. Variations in the configurations included: (1) three same-handed and three mirror-image rooms; (2) three outboard, two inboard, and one nested bathroom; and (3) three rooms with footwall bathrooms and three with headwall bathrooms. In a four-step process, the attendees ranked the issues, discussed them in detail, rated each room configuration against each issue on a seven-point suitability scale, and conducted an overall assessment of the six configurations. CONCLUSIONS: Based on the ratings and rankings provided by the symposium participants, outboard bathroom locations were found to be most suitable, followed by nested and inboard configurations. Furthermore, configurations with patient bathrooms located on the footwall were rated as more suitable than headwall locations. The authors recommend, however, that the framework be used to determine a suitable room configuration in a specific context, rather than to identify configurations that will perform well universally.