ArticleCanadian journal of pain = Revue canadienne de la douleur2020
Identifying cases of chronic pain using health administrative data: A validation study.
Article in Canadian journal of pain = Revue canadienne de la douleur, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Genome-Wide Association Study of Chronic Dizziness in the Elderly Identifies Loci Implicating MLLT10, BPTF, LINC01224, and ROS1.Journal of the Association for Research in Otolaryngology : JARO · 2023Pooled it
- Access to primary care for people with chronic pain: a lived/living experience-informed mixed-methods study protocol.BMJ open · 2026Article
- Opioid analgesics for chronic noncancer pain in patients prescribed opioid agonist therapy or with opioid use disorder: A systematic review.Canadian journal of pain = Revue canadienne de la douleur · 2025Review
- Chronic pain management in primary care: Using population-based data to examine family physician practice patterns.Canadian family physician Medecin de famille canadien · 2024Article
- Chronic noncancer pain management: Integration of a nurse-led program in primary care.Canadian family physician Medecin de famille canadien · 2023Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMost prevalence estimates of chronic pain are derived from surveys and vary widely, both globally (2%-54%) and in Canada (6.5%-44%). Health administrative data are increasingly used for chronic disease surveillance, but their validity as a source to ascertain chronic pain cases is understudied.
aimThe aim of this study was to derive and validate an algorithm to identify cases of chronic pain as a single chronic disease using provincial health administrative data.
methodsA reference standard was developed and applied to the electronic medical records data of a Newfoundland and Labrador general population sample participating in the Canadian Primary Care Sentinel Surveillance Network. Chronic pain algorithms were created from the administrative data of patient populations with chronic pain, and their classification performance was compared to that of the reference standard via statistical tests of selection accuracy.
resultsThe most performant algorithm for chronic pain case ascertainment from the Medical Care Plan Fee-for-Service Physicians Claims File was one anesthesiology encounter ever recording a chronic pain clinic procedure code OR five physician encounter dates recording any pain-related diagnostic code in 5 years with more than 183 days separating at least two encounters. The algorithm demonstrated 0.703 (95% confidence interval [CI], 0.685-0.722) sensitivity, 0.668 (95% CI, 0.657-0.678) specificity, and 0.408 (95% CI, 0.393-0.423) positive predictive value. The chronic pain algorithm selected 37.6% of a Newfoundland and Labrador provincial cohort.
conclusionsA health administrative data algorithm was derived and validated to identify chronic pain cases and estimate disease burden in residents attending fee-for-service physician encounters in Newfoundland and Labrador.
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