A qualitative evidence synthesis to explore healthcare professionals’ experience of prescribing opioids to adults with chronic non-malignant pain View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

Fran Toye, Kate Seers, Stephanie Tierney, Karen Louise Barker

ABSTRACT

BACKGROUND: Despite recent guidelines suggesting that patients with chronic non-malignant pain might not benefit, there has been a significant rise in opioid prescription for chronic non-malignant pain. This topic is important because an increasing number of HCPs are prescribing opioids despite very limited evidence for long-term opioid therapy for chronic non-malignant pain outside of end-of-life care. To better understand the challenges of providing effective treatment, we conducted the first qualitative evidence synthesis to explore healthcare professionals' experience of treating people with chronic non-malignant pain. We report findings that explore healthcare professionals' experience of prescribing opioids to this group of patients. METHODS: We searched five electronic bibliographic databases (Medline, Embase, CINAHL, PsychINFO, AMED) from inception to November 2015 and screened titles, abstracts and full texts of potential studies. We included studies in English that explored healthcare professionals' experience of treating adults with chronic non-malignant pain. Two reviewers quality appraised each paper. We used the methods of meta-ethnography developed and refined for large reviews, and the GRADE-CERQual framework to rate confidence in review findings. RESULTS: We screened 954 abstracts and 184 full texts, and included 77 studies in the full review. 17 of these 77 studies included concepts that explored the experience of prescribing opioids. We abstracted these concepts into 6 overarching themes: (1) Should I, shouldn't I? (2) Pain is Pain; (3) Walking a fine line; (4) Social guardianship; (5) Moral boundary work; (6) Regulations and guidelines. We used the GRADE-CERQual framework to evaluate confidence in findings. A new overarching concept of 'ambiguity' explains the balancing required around the factors taken into account when prescribing opioids. Managing this ambiguity is challenging and these findings can inform healthcare professionals dealing with these decisions. CONCLUSIONS: This conceptual model demonstrates the complexity of making a decision to prescribe opioids to someone with chronic non-malignant pain. Although opioid prescription is underpinned by the therapeutic aim of alleviating pain, this aim may be misplaced. This has implications for education in light of the new regulations for opioid prescription. Findings also demonstrate that the decision is influenced by intra- and interpersonal factors and broader external concerns. More... »

PAGES

94

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12875-017-0663-8

DOI

http://dx.doi.org/10.1186/s12875-017-0663-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092983249

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29178843


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    "description": "BACKGROUND: Despite recent guidelines suggesting that patients with chronic non-malignant pain might not benefit, there has been a significant rise in opioid prescription for chronic non-malignant pain. This topic is important because an increasing number of HCPs are prescribing opioids despite very limited evidence for long-term opioid therapy for chronic non-malignant pain outside of end-of-life care. To better understand the challenges of providing effective treatment, we conducted the first qualitative evidence synthesis to explore healthcare professionals' experience of treating people with chronic non-malignant pain. We report findings that explore healthcare professionals' experience of prescribing opioids to this group of patients.\nMETHODS: We searched five electronic bibliographic databases (Medline, Embase, CINAHL, PsychINFO, AMED) from inception to November 2015 and screened titles, abstracts and full texts of potential studies. We included studies in English that explored healthcare professionals' experience of treating adults with chronic non-malignant pain. Two reviewers quality appraised each paper. We used the methods of meta-ethnography developed and refined for large reviews, and the GRADE-CERQual framework to rate confidence in review findings.\nRESULTS: We screened 954 abstracts and 184 full texts, and included 77 studies in the full review. 17 of these 77 studies included concepts that explored the experience of prescribing opioids. We abstracted these concepts into 6 overarching themes: (1) Should I, shouldn't I? (2) Pain is Pain; (3) Walking a fine line; (4) Social guardianship; (5) Moral boundary work; (6) Regulations and guidelines. We used the GRADE-CERQual framework to evaluate confidence in findings. A new overarching concept of 'ambiguity' explains the balancing required around the factors taken into account when prescribing opioids. Managing this ambiguity is challenging and these findings can inform healthcare professionals dealing with these decisions.\nCONCLUSIONS: This conceptual model demonstrates the complexity of making a decision to prescribe opioids to someone with chronic non-malignant pain. Although opioid prescription is underpinned by the therapeutic aim of alleviating pain, this aim may be misplaced. This has implications for education in light of the new regulations for opioid prescription. Findings also demonstrate that the decision is influenced by intra- and interpersonal factors and broader external concerns.", 
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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12875-017-0663-8'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12875-017-0663-8'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12875-017-0663-8'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12875-017-0663-8'


 

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