Self-Reported Practices and Emotions in Prescribing Opioids for Chronic Noncancer Pain: A Cross-Sectional Study of German Physicians.

WHO III opioids chronic noncancer pain guideline adherence prescription

Journal

Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588

Informations de publication

Date de publication:
29 Apr 2022
Historique:
received: 03 04 2022
revised: 23 04 2022
accepted: 25 04 2022
entrez: 14 5 2022
pubmed: 15 5 2022
medline: 15 5 2022
Statut: epublish

Résumé

Background: The pressure on physicians when a patient seeks pain relief and their own desire to be self-effective may lead to the prescription of strong opioids for chronic noncancer pain (CNCP). This study, via physician self-reporting, aims to identify and measure (i) physician adherence to national opioid prescribing guidelines and (ii) physician emotions when a patient seeks a dosage increase of the opioid. Methods: Within a cross-sectional survey—conducted as part of a randomized controlled online intervention trial (ERONA)—600 German physicians were queried on their opioid prescribing behavior (choice and formulation of opioid, indications) for CNCP patients and their emotions to a case vignette describing a patient seeking an opioid dosage increase without signs of objective deterioration. Results: The prescription of strong opioids in this study was not always in accordance with current guidelines. When presented with a scenario in which a patient sought to have their opioid dose increased, some physicians reported negative feelings, such as either pressure (25%), helplessness (25%), anger (23%) or a combination. The risk of non-guideline-compliant prescribing behavior using the example of ultrafast-acting fentanyl for CNCP was increased when negative emotions were present (OR: 1.7; 95%-CI: 1.2−2.6; p = 0.007) or when sublingual buprenorphine was prescribed (OR: 15.4; 95%-CI: 10.1−23.3; p < 0.001). Conclusions: Physicians’ emotional self-awareness represents the first step to identify such direct reactions to patient requests and to ensure a responsible, guideline-based opioid prescription approach for the long-term well-being of the patient.

Identifiants

pubmed: 35566644
pii: jcm11092506
doi: 10.3390/jcm11092506
pmc: PMC9104176
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Federal Ministry of Health
ID : 2519ATS001

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Auteurs

Erika Schulte (E)

Department of Palliative Medicine, Universitätsmedizin Göttingen, 37075 Göttingen, Germany.

Frank Petzke (F)

Pain Clinic, Department of Anesthesiology, Universitätsmedizin Göttingen, 37075 Göttingen, Germany.

Claudia Spies (C)

Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, 13353 Berlin, Germany.

Claudia Denke (C)

Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, 13353 Berlin, Germany.

Michael Schäfer (M)

Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, 13353 Berlin, Germany.

Norbert Donner-Banzhoff (N)

Department of Primary Care, Phillips-Universität Marburg, 35043 Marburg, Germany.

Ralph Hertwig (R)

Center for Adaptive Rationality, Max-Planck-Institut für Bildungsforschung, 14195 Berlin, Germany.

Odette Wegwarth (O)

Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, 13353 Berlin, Germany.
Center for Adaptive Rationality, Max-Planck-Institut für Bildungsforschung, 14195 Berlin, Germany.

Classifications MeSH