title: Pain Management Algorithms for Implementing Best Practices in Nursing Homes: Results of a Randomized Controlled Trial.
abstract: OBJECTIVE
  To enhance pain practices in nursing homes (NHs) using pain assessment and management algorithms and intense diffusion strategies.
  
  
  METHODS
  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.
  
  
  METHODS
  Twenty-seven NHs in the greater Puget Sound area participated. Facilities were diverse in terms of size, quality, and ownership.
  
  
  METHODS
  Data were collected from 485 NH residents; 259 for the intervention and 226 for the control group.
  
  
  METHODS
  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.
authors.affiliation: Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA; University of Pennsylvania School of Nursing, Philadelphia, PA. Electronic address: ersekm@nursing.upenn.edu.
authors.forename: Mary
authors.initials: M
authors.lastname: Ersek
authors.affiliation: The Mountain-Whisper-Light Statistics, Seattle, WA.
authors.forename: Moni Blazej
authors.initials: MB
authors.lastname: Neradilek
authors.affiliation: Adult and Gerontology Nursing, College of Nursing, University of Iowa, Iowa City, IA.
authors.forename: Keela
authors.initials: K
authors.lastname: Herr
authors.affiliation: College of Nursing, Seattle University, Seattle, WA.
authors.forename: Anita
authors.initials: A
authors.lastname: Jablonski
authors.affiliation: The Mountain-Whisper-Light Statistics, Seattle, WA.
authors.forename: Nayak
authors.initials: N
authors.lastname: Polissar
authors.affiliation: Bainbridge Island, WA.
authors.forename: Anna
authors.initials: A
authors.lastname: Du Pen
mesh_terms: D000368:Aged; D000465:Algorithms; D004059:Diffusion of Innovation; D019317:Evidence-Based Medicine; D005260:Female; D019983:Guideline Adherence; D006801:Humans; D008297:Male; D009735:Nursing Homes; D059408:Pain Management / Q000592:standards*; D010147:Pain Measurement / Q000379:methods*; D010166:Palliative Care; D017064:Process Assessment, Health Care; D013548:Sweden
keywords: Pain; algorithm; clinical trial; diffusion of innovations; evidence-based practice; nursing homes; older adults; palliative care