Improving In-Hospital Patient Rescue: What Are Studies on Early Warning Scores Missing? A Scoping Review

Abstract

Objectives: Administrative and clinical efforts to improve hospital mortality and intensive care utilization commonly focus on patient rescue, where deteriorating patients are systematically identified and intervened upon. Patient rescue is known to depend on hospital context inclusive of technologic environment, structural features, and hospital organizational behavioral features. With widespread adoption of electronic medical records, early warning score (EWS) systems, which assign points to clinical data elements, are increasingly promoted as a tool for timely patient rescue by referencing their prediction of patient deterioration. We describe the extent to which EWS intervention studies describe the hospital environment of the intervention-details that would be critical for hospital leaders attempting to determine the real-world utility of EWSs in their own hospitals.

Data sources: We searched CINAHL, PubMed, and Scopus databases for English language EWS implementation research published between 2009 and 2021 in adult medical-surgical inpatients.

Study selection: Studies including pediatric, obstetric, psychiatric, prehospital, outpatient, step-down, or ICU patients were excluded.

Data extraction: Two investigators independently reviewed titles/abstracts for eligibility based on prespecified exclusion criteria.

Data synthesis: We identified 1,434 studies for title/abstract screening. In all, 352 studies underwent full-text review and 21 studies were summarized. The 21 studies (18 before-and-after, three randomized trials) detailed 1,107,883 patients across 54 hospitals. Twelve reported the staff composition of an EWS response team. Ten reported the proportion of surgical patients. One reported nursing ratios; none reported intensive care staffing with in-house critical-care physicians. None measured changes in bed utilization or availability. While 16 qualitatively described resources for education/technologic implementation, none estimated costs. None described workforce composition such as team stability or culture of safety in the hospitals.

Conclusions: Despite hundreds of EWS-related publications, most do not report details of hospital context that would inform decisions about real-world EWS adoption. To make informed decisions about whether EWS implementation improves hospital quality, decision-makers may require alternatives such as peer networks and implementation pilots nested within local health systems.

Keywords: clinical decision rules; clinical deterioration; early warning score; failure to rescue; implementation science.

Figure 1.

Framework for patient rescue. EWS = early warning score, MET = medical emergency team, RRT = rapid response team.

Figure 2.

Steps in health information technology research and evaluation.

Figure 3.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram. ED = emergency department, EWS = early warning score, OR = operating room, RRT = rapid response team.