Diagnostic accuracy of algorithms to identify hepatitis C status, AIDS status, alcohol consumption and illicit drug use among patients living with HIV in an administrative healthcare database.

This study aims to develop and evaluate diagnostic algorithms for AIDS, hepatitis C status, alcohol abuse and illicit drug use in the administrative healthcare database of the Province of Quebec, Canada (Régie de l'assurance-maladie du Québec (RAMQ)). We selected HIV-positive patients contributing to both the RAMQ database and a local clinical database, which was used as gold standard. We developed algorithms to identify the diagnoses of interest in RAMQ using data from hospital discharge summaries and medical and pharmaceutical claims databases. We estimated and compared sensitivity, specificity, positive predictive and negative predictive values and area under receiver operating curve for each algorithm. Four hundred twenty patients contributed to both databases. Prevalence of conditions of interest in the clinical database was as follows: AIDS 233 (55%), hepatitis C infection 105 (25%), alcohol abuse 106 (25%), illicit drug use 144 (34%) and intravenous drug use 107 (25%). Sensitivity to detect AIDS, hepatitis C, alcohol abuse, illicit drug use and intravenous drug use was 46% [95%CI: 39-53], 26% [18-35], 50% [37-57], 64% [55-72] and 70% [61-79], respectively. Specificity to detect these conditions was 91% [86-95], 97% [94-98], 92% [88-95], 95% [92-97] and 90% [87-93], respectively. Positive predictive values were 87% [80-92], 71% [54-85], 68% [56-78], 87% [79-93] and 72% [62-80], respectively. Area under receiver operating curve varied from 0.62 [0.57-0.65] for hepatitis C to 0.80 [0.76-0.85] for intravenous drug use. Sensitivity was low to detect AIDS, alcohol abuse, illicit drug use and especially hepatitis C in RAMQ. Researchers must be aware of the potential for residual confounding and must consider additional methods to control for confounding.

Durand M ，Wang Y ，Venne F ，Lelorier J ，Tremblay CL ，Abrahamowicz M ... -  《-》

Is the Quebec provincial administrative database a valid source for research on chronic non-cancer pain?

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. 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. 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). 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.

Lacasse A ，Ware MA ，Dorais M ，Lanctôt H ，Choinière M ... -  《-》

Accuracy of Self-reported Prescribed Analgesic Medication Use: Linkage Between the Quebec Pain Registry and the Quebec Administrative Prescription Claims Databases.

Lacasse A ，Ware MA ，Bourgault P ，Lanctôt H ，Dorais M ，Boulanger A ，Cloutier C ，Shir Y ，Choinière M ... -  《-》

The validity of diagnosing chronic obstructive pulmonary disease from a large administrative database.

Lacasse Y ，Montori VM ，Lanthier C ，Maltis F ... -  《Canadian Respiratory Journal》

A systematic review of validated methods for identifying patients with rheumatoid arthritis using administrative or claims data.

To review the evidence supporting the validity of billing, procedural, or diagnosis code, or pharmacy claim-based algorithms used to identify patients with rheumatoid arthritis (RA) in administrative and claim databases. We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to RA and reference lists of included studies were searched. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria and extracted the data. Data collected included participant and algorithm characteristics. Nine studies reported validation of computer algorithms based on International Classification of Diseases (ICD) codes with or without free-text, medication use, laboratory data and the need for a diagnosis by a rheumatologist. These studies yielded positive predictive values (PPV) ranging from 34 to 97% to identify patients with RA. Higher PPVs were obtained with the use of at least two ICD and/or procedure codes (ICD-9 code 714 and others), the requirement of a prescription of a medication used to treat RA, or requirement of participation of a rheumatologist in patient care. For example, the PPV increased from 66 to 97% when the use of disease-modifying antirheumatic drugs and the presence of a positive rheumatoid factor were required. There have been substantial efforts to propose and validate algorithms to identify patients with RA in automated databases. Algorithms that include more than one code and incorporate medications or laboratory data and/or required a diagnosis by a rheumatologist may increase the PPV.

Chung CP ，Rohan P ，Krishnaswami S ，McPheeters ML ... -  《-》