Units of Distinction: Creating a Blueprint for Recognition of High-Performing Medical-Surgical Nursing Units.

BACKGROUND: Hospital medical-surgical (M/S) nursing units are responsible for up to 28 million encounters annually, yet receive little attention from professional organizations and national initiatives targeted to improve quality and performance. OBJECTIVE: We sought to develop a framework recognizing high-performing units within our large hospital system. METHODS: This was a retrospective data analysis of M/S units throughout a 168-hospital system. Measures represented patient experience, employee engagement, staff scheduling, nursing-sensitive patient outcomes, professional practices, and clinical process measures. RESULTS: Four hundred ninety units from 129 hospitals contributed information to test the framework. A manual scoring system identified the top 5% and recognized them as a "Unit of Distinction." Secondary analyses with machine learning provided validation of the proposed framework. CONCLUSIONS: Similar to external recognition programs, this framework and process provide a holistic evaluation useful for meaningful recognition and lay the groundwork for benchmarking in improvement efforts.

Barriers for Hospital-Based Nurse Practitioners Utilizing Clinical Decision Support Systems: A Systematic Review.

There is a national focus on the adoption of healthcare technology to improve the delivery of safe, efficient, and high-quality patient care. Nurse practitioners fulfill an emerging strategic role in the hospital setting. A comprehensive literature review focused on the question: What are the barriers for nurse practitioners utilizing clinical decision support in the hospital setting? Nine studies conducted from 2011 to 2017 were the basis for this review, which identified 13 barriers for nurse practitioners utilizing clinical decision support in the hospital. Having the right information, including up-to-date evidence-based practice guidelines, accurate clinical pathways, and current clinical algorithms, was the most common barrier. Providing reliable clinical decision support is crucial as nurse practitioners become more dependent on hospital technology systems in the delivery of safe patient care. Eliminating barriers to the use of clinical decision support is important for informaticists and nurse practitioners because both groups concentrate on acceptance of decision support systems in the hospital to meet the goal of safe and high-quality patient care.

Evaluation of medication administration timing variance using information from a large health system's clinical data warehouse.

PURPOSE: An analysis to determine the frequency of medication administration timing variances for specific therapeutic classes of high-risk medications using data extracted from a health-system clinical data warehouse (CDW) is presented. METHODS: This multicenter retrospective, observational analysis of medication administration data from 14 hospitals over 1 year was conducted using a large enterprise health-system CDW. The primary objective was to assess medication administration timing variance for focused therapeutic classes using medication orders and electronic medication administration records data extracted from the electronic health record (EHR). Administration timing variance patterns between standard hospital staffing shifts, within therapeutic drug classes, and for as-needed (PRN) medications were also studied. To assess medication administration timing variance, calculated variables were created for time intervals of 30-59, 60-120, and greater than 120 minutes. Scheduled medications were assessed for delayed administration and PRN medications for early administration. RESULTS: A total of 5,690,770 medication administrations (3,418,275 scheduled and 2,272,495 PRN) were included in the normalized data set. Scheduled medications were frequently subject to delays of ≥60 minutes (15% of administrations, n = 275,257) when scheduled for administration between 9-10 AM and between 9-10 PM. By therapeutic drug class, scheduled administrations of insulins, heparin products, and platelet aggregation inhibitors were the most commonly delayed. For PRN medications, medications in the anticoagulant and antiplatelet agent class (most commonly heparin flushes and line-management preparations) were most likely to be administered early, defined as more than 60 minutes from the scheduled time of first administration. CONCLUSION: The findings of this study assist in understanding patterns of delayed medication administration. Medication class, time of day of scheduled administration, and frequency were factors that influenced medication administration timing variance.