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Pain Management Algorithms for Implementing Best Practices in Nursing Homes: Results of a Randomized Controlled Trial
Mary Ersek1, Moni Blazej Neradilek2, Keela Herr3
1Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA; University of Pennsylvania School of Nursing, Philadelphia, PA.
Objective:
To enhance pain practices in nursing homes (NHs) using pain assessment and management algorithms and intense diffusion strategies.
Design:
A cluster, randomized controlled trial. The intervention consisted of intensive training and support for the use of recommended pain assessment and management practices using algorithms (ALGs). Control facilities received pain education (EDU) only.
Setting:
Twenty-seven NHs in the greater Puget Sound area participated. Facilities were diverse in terms of size, quality, and ownership.
Participants:
Data were collected from 485 NH residents; 259 for the intervention and 226 for the control group.
Measurements:
Resident outcomes were nursing assistant (proxy) report and self-reported resident pain intensity. Process outcomes were adherence to recommended pain practices. Outcomes were measured at baseline, completion of the intervention (ALG) or training (EDU), and again 6 months later.
Results:
Among 8 comparisons of outcome measures between ALG and EDU (changes in 4 primary pain measures compared at 2 postintervention time points) there was only 1 statistically significant but small treatment difference in proxy- or self-reported pain intensity. Resident-reported worst pain decreased by an average of 0.8 points from baseline to 6 months among the EDU group and increased by 0.2 points among the ALG (P = .005), a clinically nonsignificant difference. There were no statistically significant differences in adherence to clinical guideline practice recommendations between ALG and EDU following the intervention.
Conclusions:
Future research needs to identify and test effective implementation methods for changing complex clinical practices in NHs, including those to reduce pain.
