IMPROVING PAIN ASSESSMENT IN CLINICAL PRACTICE

Monday, October 24, 2011
Grand Ballroom AB (Hyatt Regency Chicago)
Poster Board # 2
(DEC) Decision Psychology and Shared Decision Making

Liana Fraenkel, MD, MPH, VA CT Healthcare System; Yale School of Medicine, New Haven, CT, Paul R. Falzer, PhD, VA CT Healthcare System, West Haven, CT, Terri Fried, MD, Yale School of Medicine, West Haven, CO, Minna Kohler, Yale University, New Haven, CT, Robert Kerns, PhD, VA CT Healthcare System; Yale University School of Medicine, West Haven, CT, Ellen Peters, Ph.D., Decision Research, Eugene, OR and Howard Leventhal, PhD, Rutgers University, New Brunswick, NJ

Purpose: Routine assessments of pain using an intensity numeric rating scale (NRS) have improved documentation, but have not improved clinical outcomes. Ideally, a screening tool meant to trigger additional treatment would accurately reflect the impact of pain on patients’ current quality of life and correlate with patients’ willingness to accept additional therapy. The objective of this study was to examine whether patients’ illness perceptions more accurately reflect impact of pain and therefore better correlate with patient treatment preferences than the pain intensity NRS.

Methods: We interviewed outpatients with chronic, noncancer, musculoskeletal pain. Experience of pain was measured using 18 items drawn from Illness Perception Theory. The items were factor analyzed using the principal axis method. 38% of the variance was accounted for by a single factor that we labeled “impact of pain.” We used general linear models to examine how NRS scores compare with impact of pain in predicting preferences for highly effective/high risk treatment.

Results: 249 (43%) of 575 eligible subjects agreed to participate. 206 could not be contacted, 120 refused. 75% were male; 71% Caucasian; mean age was 53.5 (±19.5). 183 (73.5%) subjects preferred a highly effective/high risk treatment for pain versus a mildly effective/no risk treatment for pain. The principal axis factor analysis generated 5 factors and accounted for 67.1% of the variance. 37.9% of the variance was accounted for by a single factor that we labeled “impact of pain.” Pain intensity as measured by the NRS was not associated with subjects’ preference for a more effective and riskier treatment for pain [1.20 (0.97-1.26), df=1]. However, pain impact was significant in both the unadjusted [1.43 (1.06-1.92), df=1] and adjusted models [1.38 (1.01-1.87, df=1].

Conclusions: While there are numerous possible reasons for our failure to improve processes of care and outcomes for patients with chronic pain (including limitations in physician training, patient-physician communication, and lack of effective therapies), implementation of valid measures is critical if quality of care continues to be judged against the results of screening assessments. The results of this study suggest that patients’ illness perceptions related to the impact of pain are more informative than the NRS and therefore may be more likely to affect the care delivered to patients with chronic pain.