Evidence map›Paper›PMID 31907245›Full record

ArticleJournal of the American Board of Family Medicine : JABFM

Factors That Influence Changes to Existing Chronic Pain Management Plans.

Julie Diiulio, Laura G Militello, Barbara T Andraka-Christou, Robert L Cook, Robert W Hurley, Sarah M Downs, Shilo Anders, Burke W Mamlin, Elizabeth C Danielson, Christopher A Harle

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Article in Journal of the American Board of Family Medicine : JABFM. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

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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

10 authors.

Julie DiiulioFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH). j.diiulio@applieddecisionscience.com.
Laura G MilitelloFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH).
Barbara T Andraka-ChristouFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH).
Robert L CookFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH).
Robert W HurleyFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH).
Sarah M DownsFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH).
Shilo AndersFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH).
Burke W MamlinFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH).
Elizabeth C DanielsonFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH).
Christopher A HarleFrom Applied Decision Science, LLC, Dayton, OH (JD, LGM); Department of Health Management & Informatics, University of Central Florida, Orlando, FL (BTAC); University of Florida Gainesville, FL (RLC); Department of Anesthesiology and Public Health Science, Wake Forest University School of Medicine, Winston Salem, NC (RWH); Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN (SMD, ECD, CAH); Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN (SA); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN (BWM); Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN (BWM, CAH).

Funding

Designing User-Centered Decision Support Tools for Chronic Pain in Primary CareR01HS023306 · AHRQ · INDIANA UNIVERSITY INDIANAPOLIS · PI HARLE, CHRISTOPHER ALBERT · 2015 to 2018
$2.0M
AHRQ HHS R01 HS023306
6 · The paper itself

Abstract

backgroundThe objective of this qualitative study is to better understand primary care clinician decision making for managing chronic pain. Specifically, we focus on the factors that influence changes to existing chronic pain management plans. Limitations in guidelines and training leave clinicians to use their own judgment and experience in managing the complexities associated with treating patients with chronic pain. This study provides insight into those judgments based on clinicians' first-person accounts. Insights gleaned from this study could inspire innovations aimed at supporting primary care clinicians (PCCs) in managing chronic pain.

methodsWe conducted 89 interviews with PCCs to obtain their first-person perspective of the factors that influenced changes in treatment plans for their patients. Interview transcripts were analyzed thematically by a multidisciplinary team of clinicians, cognitive scientists, and public health researchers.

resultsSeven themes emerged through our analysis of factors that influenced a change in chronic pain management: 1) change in patient condition; 2) outcomes related to treatment; 3) nonadherent patient behavior; 4) insurance constraints; 5) change in guidelines, laws, or policies; 6) approaches to new patients; and 7) specialist recommendations.

conclusionsOur analysis sheds light on the factors that lead PCCs to change treatment plans for patients with chronic pain. An understanding of these factors can inform the types of innovations needed to support PCCs in providing chronic pain care. We highlight key insights from our analysis and offer ideas for potential practice innovations.

Indexed as

Practice Patterns, Physicians'Analgesics, OpioidChronic PainClinical Decision-MakingFemaleHumansMaleMedication AdherencePain ManagementPractice Guidelines as TopicPrimary Health CareQualitative ResearchAnalgesics, OpioidChronic PainClinical Decision MakingOpioidsPain ManagementPrimary Health CareQualitative Research

Identifiers

PMID31907245
PMCPMC7301400

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.