Identifying Multisite Chronic Pain with Electronic Health Records Data

Pain Med. 2020 Dec 25;21(12):3387-3392. doi: 10.1093/pm/pnaa295.


Background: Multisite chronic pain (MSCP) is associated with increased chronic pain impact, but methods for identifying MSCP for epidemiological research have not been evaluated.

Objective: We assessed the validity of identifying MSCP using electronic health care data compared with survey questionnaires.

Methods: Stratified random samples of adults served by Kaiser Permanente Northwest and Washington (N = 2,059) were drawn for a survey, oversampling persons with frequent use of health care for pain. MSCP and single-site chronic pain were identified by two methods, with electronic health care data and with self-report of common chronic pain conditions by survey questionnaire. Analyses were weighted to adjust for stratified sampling.

Results: MSCP was somewhat less common when ascertained by electronic health records (14.7% weighted prevalence) than by survey questionnaire (25.9% weighted prevalence). Agreement of the two MSCP classifications was low (kappa agreement statistic of 0.21). Ascertainment of MSCP with electronic health records was 30.9% sensitive, 91.0% specific, and had a positive predictive value of 54.5% relative to MSCP identified by self-report as the standard. After adjusting for age and gender, patients with MSCP identified by either electronic health records or self-report showed higher levels of pain-related disability, pain severity, depressive symptoms, and long-term opioid use than persons with single-site chronic pain identified by the same method.

Conclusions: Identification of MSCP with electronic health care data was insufficiently accurate to be used as a surrogate or screener for MSCP identified by self-report, but both methods identified persons with heightened chronic pain impact.

Keywords: Assessment; Chronic Pain.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Chronic Pain* / diagnosis
  • Chronic Pain* / epidemiology
  • Electronic Health Records
  • Humans
  • Opioid-Related Disorders*
  • Surveys and Questionnaires
  • Washington / epidemiology