Validity of Algorithms for Identification of Individuals Suffering from Chronic Noncancer Pain in Administrative Databases: A Systematic Review.
Accuracy
Administrative Databases
Algorithms
Back Pain
Chronic Pain
Claims
Complex Regional Pain Syndrome
Diagnostic Codes
Fibromyalgia
Headache
Migraine
Neck Pain
Neuropathic Pain
Sensitivity
Specificity
Validity
Journal
Pain medicine (Malden, Mass.)
ISSN: 1526-4637
Titre abrégé: Pain Med
Pays: England
ID NLM: 100894201
Informations de publication
Date de publication:
01 09 2020
01 09 2020
Historique:
pubmed:
7
3
2020
medline:
15
5
2021
entrez:
7
3
2020
Statut:
ppublish
Résumé
Secondary analysis of health administrative databases is indispensable to enriching our understanding of health trajectories, health care utilization, and real-world risks and benefits of drugs among large populations. This systematic review aimed at assessing evidence about the validity of algorithms for the identification of individuals suffering from nonarthritic chronic noncancer pain (CNCP) in administrative databases. Studies reporting measures of diagnostic accuracy of such algorithms and published in English or French were searched in the Medline, Embase, CINAHL, AgeLine, PsycINFO, and Abstracts in Social Gerontology electronic databases without any dates of coverage restrictions up to March 1, 2018. Reference lists of included studies were also screened for additional publications. Only six studies focused on commonly studied CNCP conditions and were included in the review. Some algorithms showed a ≥60% combination of sensitivity and specificity values (back pain disorders in general, fibromyalgia, low back pain, migraine, neck/back problems studied together). Only algorithms designed to identify fibromyalgia cases reached a ≥80% combination (without replication of findings in other studies/databases). In summary, the present investigation informs us about the limited amount of literature available to guide and support the use of administrative databases as valid sources of data for research on CNCP. Considering the added value of such data sources, the important research gaps identified in this innovative review provide important directions for future research. The review protocol was registered with PROSPERO (CRD42018086402).
Sections du résumé
BACKGROUND
Secondary analysis of health administrative databases is indispensable to enriching our understanding of health trajectories, health care utilization, and real-world risks and benefits of drugs among large populations.
OBJECTIVES
This systematic review aimed at assessing evidence about the validity of algorithms for the identification of individuals suffering from nonarthritic chronic noncancer pain (CNCP) in administrative databases.
METHODS
Studies reporting measures of diagnostic accuracy of such algorithms and published in English or French were searched in the Medline, Embase, CINAHL, AgeLine, PsycINFO, and Abstracts in Social Gerontology electronic databases without any dates of coverage restrictions up to March 1, 2018. Reference lists of included studies were also screened for additional publications.
RESULTS
Only six studies focused on commonly studied CNCP conditions and were included in the review. Some algorithms showed a ≥60% combination of sensitivity and specificity values (back pain disorders in general, fibromyalgia, low back pain, migraine, neck/back problems studied together). Only algorithms designed to identify fibromyalgia cases reached a ≥80% combination (without replication of findings in other studies/databases).
CONCLUSIONS
In summary, the present investigation informs us about the limited amount of literature available to guide and support the use of administrative databases as valid sources of data for research on CNCP. Considering the added value of such data sources, the important research gaps identified in this innovative review provide important directions for future research. The review protocol was registered with PROSPERO (CRD42018086402).
Identifiants
pubmed: 32142130
pii: 5788467
doi: 10.1093/pm/pnaa004
pmc: PMC7553015
doi:
Substances chimiques
Analgesics, Opioid
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
1825-1839Subventions
Organisme : CIHR
Pays : Canada
Informations de copyright
© 2020 American Academy of Pain Medicine.
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