ABSTRACT: Data-Driven Interdisciplinary Interventions to Improve Inpatient Pain Management
Abstract
Pain during hospitalization and dissatisfaction with pain management are common. This project consisted of 4 phases: identifying a pain numeric rating scale (NRS) metric associated with patient satisfaction, identifying independent predictors of maximum NRS, implementing interventions, and evaluating trends in NRS and satisfaction. Maximum NRS was inversely associated with favorable pain satisfaction for both efficacy (n = 4062, χ2 = 66.2, P < .001) and staff efforts (n = 4067, χ2 = 30.3, P < .001). Independent predictors of moderate-to-severe maximum NRS were younger age, female sex, longer hospital stay, admitting department, psychoactive medications, and 10 diagnostic codes. After interventions, moderate-to-severe maximum NRS declined by 3.6% per quarter in 2010 compared with 2009. Satisfaction data demonstrated improvements in nursing units meeting goals (5.3% per quarter, r 2 = 0.67) and favorable satisfaction answers (0.36% per quarter, r 2 = 0.31). Moderate-to-severe maximum NRS was an independent predictor of lower likelihood of hospital discharge (likelihood ratio = 0.62; 95% confidence interval = 0.61-0.64). Targeted interventions were associated with improved inpatient pain management.
via Data-Driven Interdisciplinary Interventions to Improve Inpatient Pain Management.
Written by Brian S McGowan, PhD
Dr. McGowan has served in leadership positions in numerous medical educational organizations and commercial supporters and is a Fellow of the Alliance (FACEhp). He founded the Outcomes Standardization Project, launched and hosted the Alliance Podcast, and most recently launched and hosts the JCEHP Emerging Best Practices in CPD podcast. In 2012 he Co-Founded ArcheMedX, Inc, a healthcare informatics and e-learning company to apply his research in practice.
