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Pain Management in Primary Care: A Randomized Controlled Trial of a Computerized Decision Support Tool - 20/12/21

Doi : 10.1016/j.amjmed.2021.07.014 
Lara Dhingra, PhD a, b, , Robert Schiller, MD c, d, Raymond Teets, MD c, d, Sarah Nosal, MD c, d, e, Nathan F. Dieckmann, PhD f, g, Regina Ginzburg, PharmD c, h, Ebtesam Ahmed, PharmD a, h, Jack Chen, MBS a, i, Sandra Rodriguez, MPH a, j, Nandini Schroff, MPH c, Saskia Shuman, MHS c, Stephanie DiFiglia, PhD a, Russell Portenoy, MD a, b, k
a MJHS Institute for Innovation in Palliative Care, New York, NY 
b Department of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, NY 
c The Institute for Family Health, New York, NY 
d Department of Family Medicine and Community Health, Icahn School of Medicine at Mount Sinai, New York, NY 
e The Institute for Family Health, Bronx, NY 
f School of Nursing, School of Medicine, Oregon Health & Science University, Portland, OR 
g Decision Research, Eugene, OR 
h St. John's University, Queens, NY 
i Cohen Children's Medical Center, General Pediatrics, New Hyde Park, NY 
j Columbia University School of Social Work, New York, NY 
k Department of Neurology, Albert Einstein College of Medicine, Bronx, NY 

Requests for reprints should be addressed to Lara Dhingra, MJHS Institute for Innovation in Palliative Care, 39 Broadway, 3rd Floor, New York, New York 10006.MJHS Institute for Innovation in Palliative Care39 Broadway, 3rd FloorNew YorkNew York10006

Abstract

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.

El texto completo de este artículo está disponible en PDF.

Keywords : Chronic pain, Decision support, Federally Qualified Health Centers, Health information technology, Pain management


Esquema


 Funding: This work was supported by a grant from Pfizer's Office of Independent Grants for Learning and Change (8408357; RP).
 Conflicts of Interest: There are no competing interests declared.
 Authorship: All authors had access to the data and a role in writing this manuscript.


© 2021  Elsevier Inc. Reservados todos los derechos.
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Vol 134 - N° 12

P. 1546-1554 - décembre 2021 Regresar al número
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