Pain Management in Primary Care: A Randomized Controlled Trial of a Computerized Decision Support Tool

Lara Dhingra, Robert Schiller, Raymond Teets, Sarah Nosal, Nathan F. Dieckmann, Regina Ginzburg, Ebtesam Ahmed, Jack Chen, Sandra Rodriguez, Nandini Schroff, Saskia Shuman, Stephanie DiFiglia, Russell Portenoy

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Background: Primary care providers manage most patients with chronic pain. Pain is a complex problem, particularly in underserved populations. A technology-enabled, point-of-care decision support tool may improve pain management outcomes. Methods: We created an electronic health record (EHR)-based decision support tool, the Pain Management Support System–Primary Care (PMSS-PC), and studied the tool-plus-education in 6 Federally Qualified Health Center practices using a randomized, wait-list controlled design. The PMSS-PC generated “best practice alerts,” gave clinicians access to a pain assessment template, psychological distress and substance use measures, guidelines for drug and non-drug therapies, and facilitated referrals. Practices were randomly assigned to early vs delayed (after 6 months) implementation of the intervention, including technical support and 6 webinars. The primary outcome was change in worst pain intensity scores after 6 months, assessed on the Brief Pain Inventory-Short Form. Changes in outcomes were compared between the practices using linear multilevel modeling. The EHR provided clinician data on PMSS-PC utilization. Results: The 256 patients in the early implementation practices had significantly improved worst pain (standardized effect size [ES] = −.32) compared with the 272 patients in the delayed implementation practices (ES = −.11). There was very low clinician uptake of the intervention in both conditions. Conclusions: Early implementation of the PMSS-PC improved worst pain, but this effect cannot be attributed to clinician use of the tool. Further PMSS-PC development is not indicated, but practice-level interventions can improve pain, and studies are needed to identify the determinants of change.

Original languageEnglish
Pages (from-to)1546-1554
Number of pages9
JournalAmerican Journal of Medicine
Issue number12
StatePublished - Dec 2021


  • Chronic pain
  • Decision support
  • Federally Qualified Health Centers
  • Health information technology
  • Pain management


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