The Problem of Pain in Rheumatology: Variations in Case Definitions Derived From Chronic Pain Phenotyping Algorithms Using Electronic Health Records.

OBJECTIVE: The aim of this study was to investigate and compare different case definitions for chronic pain to provide estimates of possible misclassification when researchers are limited by available electronic health record and administrative claims data, allowing for greater precision in case definitions. METHODS: We compared the prevalence of different case definitions for chronic pain (N = 3042) in patients with autoimmune rheumatic diseases. We estimated the prevalence of chronic pain based on 15 unique combinations of pain scores, diagnostic codes, analgesic medications, and pain interventions. RESULTS: Chronic pain prevalence was lowest in unimodal pain phenotyping algorithms: 15% using analgesic medications, 18% using pain scores, 21% using pain diagnostic codes, and 22% using pain interventions. In comparison, the prevalence using a well-validated phenotyping algorithm was 37%. The prevalence of chronic pain also increased with the increasing number (bimodal to quadrimodal) of phenotyping algorithms that comprised the multimodal phenotyping algorithms. The highest estimated chronic pain prevalence (47%) was the multimodal phenotyping algorithm that combined pain scores, diagnostic codes, analgesic medications, and pain interventions. However, this quadrimodal phenotyping algorithm yielded a 10% overestimation of chronic pain compared to the well-validated algorithm. CONCLUSION: This is the first empirical study to our knowledge that shows that established common modes of phenotyping chronic pain can lead to substantially varying estimates of the number of patients with chronic pain. These findings can be a reference for biases in case definitions for chronic pain and could be used to estimate the extent of possible misclassifications or corrections in using datasets that cannot include specific data elements.

The Problem of Pain in Rheumatology: Clinical Profiles Associated With Concomitant Diagnoses With Chronic Overlapping Pain Conditions.

OBJECTIVE: The chronification of pain is heterogeneous in rheumatology. Chronic overlapping pain conditions (COPCs) such as fibromyalgia, endometriosis, migraine, and back pain may co-occur with one another and in rheumatic diseases. We describe the sociodemographic and clinical profiles associated with concomitant COPCs among patients with rheumatic diseases. METHODS: We retrospectively identified patients visiting rheumatology clinics at a single institution from 2010 to 2020 for five common rheumatic conditions: psoriatic arthritis (PsA), rheumatoid arthritis (RA), Sjögren syndrome (SjS), systemic lupus erythematosus (SLE), and systemic sclerosis (SSc). We compared sociodemographic, clinical, and lifestyle factors by rheumatic condition and by COPC status. We also report sex-stratified diagnosis of COPCs. The primary outcome was diagnostic validation of one or more COPCs. RESULTS: We identified 5992 rheumatology patients: 846 with PsA, 2605 with RA, 956 with SjS, 975 with SLE, and 610 with SSc. Approximately 36-62% of patients had a concomitant COPC diagnosis. Patients with SjS had the highest prevalence (62%). Diagnosis of one or more COPCs was highest among Black patients and lowest among Asian patients. Patients using public insurance had a higher prevalence of one or more COPCs compared with those with private insurance. Patients with one or more COPCs had more depression and anxiety and more frequent emergency department visits, surgeries, and hospitalizations. CONCLUSION: Our findings suggest that COPCs are strikingly common among patients with rheumatic disease and are associated with lower quality of life and greater health care needs. Future research may elucidate drivers of chronic pain and how to best address the unique analgesic needs of this multimorbid population.