Anaïs Lacasse1,2, Mark A Ware3, Marc Dorais4, Hélène Lanctôt2, Manon Choinière2,5. 1. Département des sciences de la santé, Université du Québec en Abitibi-Témiscamingue, Rouyn-Noranda, Québec, Canada. 2. Centre de recherche du Centre hospitalier de l'Université de Montréal, Montréal, Québec, Canada. 3. Alan Edwards Pain Management Unit, McGill University Health Centre, Montréal, Québec, Canada. 4. StatSciences Inc., Notre-Dame-de-l'Île-Perrot, Québec, Canada. 5. Département d'anesthésiologie, Faculté de médecine, Université de Montréal, Montréal, Québec, Canada.
Abstract
PURPOSE: The objective of this study was to evaluate the validity of diagnostic codes recorded in the Régie de l'assurance maladie du Québec (RAMQ) administrative database for identifying patients suffering from various types of chronic non-cancer pain. METHODS: The validity of published International Classification of Diseases, Ninth Revision, coding algorithms for identifying patients with particular chronic pain syndromes in the RAMQ database was tested using pain specialist-established diagnostic data of 561 patients enrolled in the Quebec Pain Registry, which was used as the reference standard. Modified versions of these algorithms (i.e., adaptation of the number of healthcare encounters) were also tested. For each algorithm, sensitivity, specificity, positive/negative predictive values, and their respective 95% confidence intervals (95%CI) were calculated. RESULTS: In the RAMQ database, some previously published algorithms and modified versions of these algorithms were found to be valid for identifying patients suffering from chronic lumbar pain (sensitivity: 0.65, 95%CI: 0.59-0.71; specificity: 0.83, 95%CI: 0.79-0.87), chronic back pain (sensitivity: 0.70, 95%CI: 0.64-0.76; specificity: 0.73, 95%CI: 0.68-0.78), and chronic neck/back pain (sensitivity: 0.71, 95%CI: 0.65-0.76; specificity: 0.78, 95%CI: 0.72-0.82). Algorithms to identify patients with other types of chronic pain showed low sensitivity: complex regional pain syndrome (≤0.07), fibromyalgia (≤0.42), and neuropathic pain (≤0.39). CONCLUSIONS: Our study provides evidence supporting the value of the RAMQ administrative database for conducting research on certain types of chronic pain disorders including back and neck pain. Users should, however, be cautious about the limitations of this database for studying other types of chronic pain syndromes such as complex regional pain syndrome, fibromyalgia, and neuropathic pain.
PURPOSE: The objective of this study was to evaluate the validity of diagnostic codes recorded in the Régie de l'assurance maladie du Québec (RAMQ) administrative database for identifying patients suffering from various types of chronic non-cancer pain. METHODS: The validity of published International Classification of Diseases, Ninth Revision, coding algorithms for identifying patients with particular chronic pain syndromes in the RAMQ database was tested using pain specialist-established diagnostic data of 561 patients enrolled in the Quebec Pain Registry, which was used as the reference standard. Modified versions of these algorithms (i.e., adaptation of the number of healthcare encounters) were also tested. For each algorithm, sensitivity, specificity, positive/negative predictive values, and their respective 95% confidence intervals (95%CI) were calculated. RESULTS: In the RAMQ database, some previously published algorithms and modified versions of these algorithms were found to be valid for identifying patients suffering from chronic lumbar pain (sensitivity: 0.65, 95%CI: 0.59-0.71; specificity: 0.83, 95%CI: 0.79-0.87), chronic back pain (sensitivity: 0.70, 95%CI: 0.64-0.76; specificity: 0.73, 95%CI: 0.68-0.78), and chronic neck/back pain (sensitivity: 0.71, 95%CI: 0.65-0.76; specificity: 0.78, 95%CI: 0.72-0.82). Algorithms to identify patients with other types of chronic pain showed low sensitivity: complex regional pain syndrome (≤0.07), fibromyalgia (≤0.42), and neuropathic pain (≤0.39). CONCLUSIONS: Our study provides evidence supporting the value of the RAMQ administrative database for conducting research on certain types of chronic pain disorders including back and neck pain. Users should, however, be cautious about the limitations of this database for studying other types of chronic pain syndromes such as complex regional pain syndrome, fibromyalgia, and neuropathic pain.
Authors: M Choinière; M A Ware; M G Pagé; A Lacasse; H Lanctôt; N Beaudet; A Boulanger; P Bourgault; C Cloutier; L Coupal; Y De Koninck; D Dion; P Dolbec; L Germain; V Martin; P Sarret; Y Shir; M-C Taillefer; B Tousignant; A Trépanier; R Truchon Journal: Pain Res Manag Date: 2017-02-09 Impact factor: 3.037
Authors: Robyn Tamblyn; David Westfall Bates; David L Buckeridge; Will Dixon; Alan J Forster; Nadyne Girard; Jennifer Haas; Bettina Habib; Siyana Kurteva; Jack Li; Therese Sheppard Journal: BMJ Open Date: 2019-05-14 Impact factor: 2.692
Authors: Robyn Tamblyn; David W Bates; David L Buckeridge; William G Dixon; Nadyne Girard; Jennifer S Haas; Bettina Habib; Usman Iqbal; Jack Li; Therese Sheppard Journal: J Am Geriatr Soc Date: 2020-03-17 Impact factor: 5.562