Evidence map›Paper›PMID 26936453›Full record

Trial reportPain medicine (Malden, Mass.)2016

Development of the Chronic Pain Coding System (CPCS) for Characterizing Patient-Clinician Discussions About Chronic Pain and Opioids.

Stephen G Henry, Meng Chen, Marianne S Matthias, Robert A Bell, Richard L Kravitz

Abstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Pain medicine (Malden, Mass.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Observational
  3. Article
  4. Article
  5. Development of a tool for coding safety-netting behaviours in primary care: a mixed-methods study using existing UK consultation recordings.The British journal of general practice : the journal of the Royal College of General Practitioners · 2019
    Article
  6. Observational
  7. Review
  8. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Stephen G Henry*Department of Internal Medicine, University of California Davis, Sacramento, California; sghenry@ucdavis.edu.
Meng ChenDepartment of Communication, University of California Davis, Davis, California.
Marianne S MatthiasVA HSR&D Center for Health Information and Communication, Roudebush VA Medical Center, Indianapolis, Indiana.
Robert A BellDepartment of Communication, University of California Davis, Davis, California.
Richard L Kravitz*Department of Internal Medicine, University of California Davis, Sacramento, California.

Funding

UC Davis Clinical and Translational Science CenterUL1TR000002 · NCATS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI BERGLUND, LARS F · 2012 to 2015
$12.2M
Targeted and Tailored Messages to Enhance Depression CareR01MH079387 · NIMH · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KRAVITZ, RICHARD L · 2007 to 2011
$3.4M
UC Davis Clinical and Translational Science CenterKL2TR000134 · NCATS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI BERGLUND, LARS F · 2012 to 2015
$3.1M
N-of-1 Trials Using mHealth in Chronic PainR01NR013938 · NINR · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KRAVITZ, RICHARD L · 2012 to 2016
$2.9M
NCATS NIH HHS KL2 TR000134NCATS NIH HHS UL1 TR000002NIMH NIH HHS R01 MH079387NINR NIH HHS R01 NR013938
6 · The paper itself

Abstract

objectiveTo describe the development and initial application of the Chronic Pain Coding System.

designSecondary analysis of data from a randomized clinical trial.

settingSix primary care clinics in northern California. SUBJECTS: Forty-five primary care visits involving 33 clinicians and 45 patients on opioids for chronic noncancer pain.

methodsThe authors developed a structured coding system to accurately and objectively characterize discussions about pain and opioids. Two coders applied the final system to visit transcripts. Intercoder agreement for major coding categories was moderate to substantial (kappa = 0.5-0.7). Mixed effects regression was used to test six hypotheses to assess preliminary construct validity.

resultsGreater baseline pain interference was associated with longer pain discussions (P = 0.007) and more patient requests for clinician action (P = 0.02) but not more frequent negative patient evaluations of pain (P = 0.15). Greater clinician-reported visit difficulty was associated with more frequent disagreements with clinician recommendations (P = 0.003) and longer discussions of opioid risks (P = 0.049) but not more frequent requests for clinician action (P = 0.11). Rates of agreement versus disagreement with patient requests and clinician recommendations were similar for opioid-related and non-opioid-related utterances.

conclusionsThis coding system appears to be a reliable and valid tool for characterizing patient-clinician communication about opioids and chronic pain during clinic visits. Objective data on how patients and clinicians discuss chronic pain and opioids are necessary to identify communication patterns and strategies for improving the quality and productivity of discussions about chronic pain that may lead to more effective pain management and reduce inappropriate opioid prescribing.

Indexed as

Physician-Patient RelationsAdultAnalgesics, OpioidChronic PainClinical CodingFemaleHumansMaleMiddle AgedPain MeasurementPrimary Health CareAnalgesics, OpioidChronic PainCommunicationNegotiatingOpioid AnalgesicsPrimary CareResearch Methodology

Identifiers

PMID26936453
PMCPMC5003763

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.