Journal Article

An administrative data validation study of the accuracy of algorithms for identifying rheumatoid arthritis: the influence of the reference standard on algorithm performance

Ivers, Noah, Bombardier, Claire, Tu, Karen, Paterson, J Michael, Thorne, J Carter, Bernatsky, Sasha, Young, Jacqueline, Widdifield, Jessica, Jaakkimainen, R Liisa, Butt, Debra A, Green, Diane

2014

Overview

Background We have previously validated administrative data algorithms to identify patients with rheumatoid arthritis (RA) using rheumatology clinic records as the reference standard. Here we reassessed the accuracy of the algorithms using primary care records as the reference standard. Methods We performed a retrospective chart abstraction study using a random sample of 7500 adult patients under the care of 83 family physicians contributing to the Electronic Medical Record Administrative data Linked Database (EMRALD) in Ontario, Canada. Using physician-reported diagnoses as the reference standard, we computed and compared the sensitivity, specificity, and predictive values for over 100 administrative data algorithms for RA case ascertainment. Results We identified 69 patients with RA for a lifetime RA prevalence of 0.9%. All algorithms had excellent specificity (>97%). However, sensitivity varied (75-90%) among physician billing algorithms. Despite the low prevalence of RA, most algorithms had adequate positive predictive value (PPV; 51-83%). The algorithm of “[1 hospitalization RA diagnosis code] or [3 physician RA diagnosis codes with ≥1 by a specialist over 2 years]” had a sensitivity of 78% (95% CI 69–88), specificity of 100% (95% CI 100–100), PPV of 78% (95% CI 69–88) and NPV of 100% (95% CI 100–100). Conclusions Administrative data algorithms for detecting RA patients achieved a high degree of accuracy amongst the general population. However, results varied slightly from our previous report, which can be attributed to differences in the reference standards with respect to disease prevalence, spectrum of disease, and type of comparator group.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V
• Subject: Adrenal Cortex Hormones - therapeutic use / Adult / Aged / Aged, 80 and over / Algorithms / Anti-Inflammatory Agents, Non-Steroidal - therapeutic use / Antirheumatic Agents - therapeutic use / Arthritis, Rheumatoid - diagnosis / Arthritis, Rheumatoid - drug therapy / Arthritis, Rheumatoid - epidemiology / Databases, Factual / Diagnosis-Related Groups / Electronic Health Records / Electronic records / Epidemiology / Epidemiology of musculoskeletal disorders / Female / Health aspects / Health insurance / Hospitals / Humans / Internal Medicine / Male / Mass Screening / Medical care / Medical Record Linkage / Medical records / Medical research / Medicine / Medicine & Public Health / Middle Aged / Musculoskeletal diseases / Ontario - epidemiology / Orthopedics / Physicians / Predictive Value of Tests / Prevalence / Primary care / Primary Health Care - statistics & numerical data / Quality management / Reference Standards / Rehabilitation / Research Article / Retrospective Studies / Rheumatology / Sampling Studies / Sensitivity and Specificity / Single-Payer System - statistics & numerical data / Sports Medicine / Universal Coverage