Occupational impacts of early inflammatory arthritis: results from the National Early Inflammatory Arthritis Audit.

OBJECTIVES: Inflammatory arthritis (IA) causes significant work disability. Studies frequently fail to report important contextual information such as employment type. Our objective was to explore work participation, by gender and occupation type in early IA. METHODS: Data are from the National Early Inflammatory Arthritis Audit between 2018 and 2020. At diagnosis, clinicians collected information on demographics, IA disease activity and working status. Participants completed patient-reported outcomes at baseline, 3- and 12-months, including occupation and Work Productivity Activity Impairment (WPAI). Descriptive analyses of work participation and WPAI scores by occupational class at all timepoints were performed. Regression models examined associations between WPAI score and occupation. FINDINGS: 12 473 people received a diagnosis of IA and reported employment status, amongst whom 5,999 (47%) were in paid-work at least 20-h/week. At diagnosis, the working cohort had statistically significant lower measures of disease activity (p< 0.001). Occupation data were available for 3,694 individuals. At diagnosis, 2,793 completed a WPAI; 200 (7.2%) had stopped work and 344 (12.3%) changed jobs because of IA symptoms. There was a high burden of absenteeism (30%) and presenteeism (40%). Compared with managerial or professional workers, the burden of work disability was greater amongst those in routine (manual) occupations. During follow-up, 9.4% of WPAI completers had stopped work and 14.6% had changed roles. Work dropout occurred almost entirely amongst people doing routine jobs. CONCLUSION: IA associates with work disability within 12 months of diagnosis. It is easier to retain work in certain employment sectors. Participation in routine jobs is more affected, which may widen health inequalities.

Gout incidence and management during the COVID-19 pandemic in England, UK: a nationwide observational study using OpenSAFELY.

BACKGROUND: Gout is the most prevalent inflammatory arthritis, yet one of the worst managed. Our objective was to assess how the COVID-19 pandemic impacted incidence and quality of care for people with gout in England, UK. METHODS: With the approval of National Health Service England, we did a population-level cohort study using primary care and hospital electronic health record data for 17·9 million adults registered with general practices using TPP health record software, via the OpenSAFELY platform. The study period was from March 1, 2015, to Feb 28, 2023. Individuals aged 18-110 years were defined as having incident gout if they were assigned index diagnostic codes for gout, were registered with TPP practices in England for at least 12 months before diagnosis, did not receive prescriptions for urate-lowering therapy more than 30 days before diagnosis, and had not been admitted to hospital or attended an emergency department for gout flares more than 30 days before diagnosis. Outcomes assessed were incidence and prevalence of people with recorded gout diagnoses, incidence of gout hospitalisations, initiation of urate-lowering therapy, and attainment of serum urate targets (≤360 µmol/L). FINDINGS: From a reference population of 17 865 145 adults, 246 695 individuals were diagnosed with incident gout. The mean age of individuals with incident gout was 61·3 years (SD 16·2). 66 265 (26·9%) of 246 695 individuals were female, 180 430 (73·1%) were male, and 189 035 (90·9%) of 208 050 individuals with available ethnicity data were White. Incident gout diagnoses decreased by 30·9% in the year beginning March, 2020, compared with the preceding year (1·23 diagnoses vs 1·78 diagnoses per 1000 adults). Gout prevalence was 3·07% in 2015-16, and 3·21% in 2022-23. Gout hospitalisations decreased by 30·1% in the year commencing March, 2020, compared with the preceding year (9·6 admissions vs 13·7 admissions per 100 000 adults). Of 228 095 people with incident gout and available follow-up, 66 560 (29·2%) were prescribed urate-lowering therapy within 6 months. Of 65 305 individuals who initiated urate-lowering therapy with available follow-up, 16 790 (25·7%) attained a serum urate concentration of 360 µmol/L or less within 6 months of urate-lowering therapy initiation. In interrupted time-series analyses, urate-lowering therapy prescribing improved modestly during the pandemic, compared with pre-pandemic, whereas urate target attainment was similar. INTERPRETATION: Using gout as an exemplar disease, we showed the complexity of how health care was impacted during the COVID-19 pandemic. We observed a reduction in gout diagnoses but no effect on treatment metrics. We showed how country-wide, routinely collected data can be used to map disease epidemiology and monitor care quality. FUNDING: None.

Incidence and management of inflammatory arthritis in England before and during the COVID-19 pandemic: a population-level cohort study using OpenSAFELY.

Background: The impact of the COVID-19 pandemic on the incidence and management of inflammatory arthritis is not understood. Routinely captured data in secure platforms, such as OpenSAFELY, offer unique opportunities to understand how care for patients with inflammatory arthritis was impacted upon by the pandemic. Our objective was to use OpenSAFELY to assess the effects of the pandemic on diagnostic incidence and care delivery for inflammatory arthritis in England and to replicate key metrics from the National Early Inflammatory Arthritis Audit. Methods: In this population-level cohort study, we used primary care and hospital data for 17·7 million adults registered with general practices using TPP health record software, to explore the following outcomes between April 1, 2019, and March 31, 2022: (1) incidence of inflammatory arthritis diagnoses (rheumatoid arthritis, psoriatic arthritis, axial spondyloarthritis, and undifferentiated inflammatory arthritis) recorded in primary care; (2) time to first rheumatology assessment; (3) time to first prescription of a disease-modifying antirheumatic drug (DMARD) in primary care; and (4) choice of first DMARD. Findings: Among 17 683 500 adults, there were 31 280 incident inflammatory arthritis diagnoses recorded between April 1, 2019, and March 31, 2022. The mean age of diagnosed patients was 55·4 years (SD 16·6), 18 615 (59·5%) were female, 12 665 (40·5%) were male, and 22 925 (88·3%) of 25 960 with available ethnicity data were White. New inflammatory arthritis diagnoses decreased by 20·3% in the year commencing April, 2020, relative to the preceding year (5·1 vs 6·4 diagnoses per 10 000 adults). The median time to first rheumatology assessment was shorter during the pandemic (18 days; IQR 8-35) than before (21 days; 9-41). The proportion of patients prescribed DMARDs in primary care was similar before and during the pandemic; however, during the pandemic, fewer people were prescribed methotrexate or leflunomide, and more were prescribed sulfasalazine or hydroxychloroquine. Interpretation: Inflammatory arthritis diagnoses decreased markedly during the early phase of the pandemic. The impact on rheumatology assessment times and DMARD prescribing in primary care was less marked than might have been anticipated. This study demonstrates the feasibility of using routinely captured, near real-time data in the secure OpenSAFELY platform to benchmark care quality on a national scale, without the need for manual data collection. Funding: None.

A comprehensive high cost drugs dataset from the NHS in England - An OpenSAFELY-TPP Short Data Report.

Background: At the outset of the COVID-19 pandemic, there was no routine comprehensive hospital medicines data from the UK available to researchers. These records can be important for many analyses including the effect of certain medicines on the risk of severe COVID-19 outcomes. With the approval of NHS England, we set out to obtain data on one specific group of medicines, "high-cost drugs" (HCD) which are typically specialist medicines for the management of long-term conditions, prescribed by hospitals to patients. Additionally, we aimed to make these data available to all approved researchers in OpenSAFELY-TPP. This report is intended to support all studies carried out in OpenSAFELY-TPP, and those elsewhere, working with this dataset or similar data. Methods: Working with the North East Commissioning Support Unit and NHS Digital, we arranged for collation of a single national HCD dataset to help inform responses to the COVID-19 pandemic. The dataset was developed from payment submissions from hospitals to commissioners. Results: In the financial year (FY) 2018/19 there were 2.8 million submissions for 1.1 million unique patient IDs recorded in the HCD. The average number of submissions per patient over the year was 2.6. In FY 2019/20 there were 4.0 million submissions for 1.3 million unique patient IDs. The average number of submissions per patient over the year was 3.1. Of the 21 variables in the dataset, three are now available for analysis in OpenSafely-TPP: Financial year and month of drug being dispensed; drug name; and a description of the drug dispensed. Conclusions: We have described the process for sourcing a national HCD dataset, making these data available for COVID-19-related analysis through OpenSAFELY-TPP and provided information on the variables included in the dataset, data coverage and an initial descriptive analysis.

Centre effects and case-mix in early rheumatoid arthritis observational cohorts: a narrative review.

OBJECTIVES: Observational cohort studies in early RA are a key source of evidence, despite inconsistencies in methodological approaches. This narrative review assesses the spectrum of methodologies used in addressing centre-level effect and case-mix adjustment in early RA observational cohort studies. METHODS: An electronic search was undertaken to identify observational prospective cohorts of >100 patients recruited from two or more centres, within 2 years of an RA or early inflammatory arthritis diagnosis. References and author publication lists of all studies from eligible cohorts were assessed for additional cohorts. RESULTS: Thirty-four unique cohorts were identified from 204 studies. Seven percent of studies considered centre in their analyses, most commonly as a fixed effect in regression modelling. Reporting of case-mix variables in analyses varied widely. The number of variables considered in case-mix adjustment was higher following publication of the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) statement in 2007. CONCLUSION: Centre effect is unreported or inadequately accounted for in the majority of RA observational cohorts, potentially leading to spurious inferences and obstructing comparisons between studies. Inadequate case-mix adjustment precludes meaningful comparisons between centres. Appropriate methodology to account for centre and case-mix adjustment should be considered at the outset of analyses.