EHR-Based Gout Register May Improve Disease Management

An automatic electronic health record (EHR)-based gout register was proven to be a feasible and valid option for assessing and improving gout management, according to a study published in Rheumatic & Musculoskeletal Diseases.¹ During the analysis, investigators also noted a substantial under-reporting and underdiagnosis of the disease since the beginning of the COVID-19 pandemic.

Although guidelines for the management of gout and how to treat acute flares or chronic gouty arthritis are readily available, previous research has shown the disease remains undertreated. For example, a recent study reported only 30% — 50% of patients with gout are prescribed urate lowering therapy and fewer than half of these patients adhere to their medication.²

“Despite the high prevalence of this disease, existing gout registers predominantly come from rheumatology settings which do not fully capture the disease’s spectrum,” wrote a team of investigators led by Nils Bürgisser, MD, associated with the Division of Rheumatology at Geneva University Hospitals (HUG) in Switzerland. “One of the barriers to create larger gout registers is their labor-intensive nature, requiring manual data collection by healthcare professionals. Furthermore, administrative datasets, a common source for research studies, often lack relevant clinical information such as laboratory data and specific patient-centered outcomes.”

The EHR collected information from all adult patients aged > 18 years from HUG, a French-speaking tertiary academic hospital, between January 2013 and December 2022. Gout diagnosis was based on 6 criteria: urate-lowering therapy prescription, monosodium urate crystals in joint aspiration, the International Classification of Diseases 10 (ICD 10) gout diagnosis, and gout-related terms in the problem lists, clinical reports, or imaging reports. The team evaluated the positive predictive value (PPV) and negative predictive value (NPV) of the query by the chart reviews.

Among a total of 2,110,902 patients, 10,289 exhibited ≥ 1 criteria for gout. A combination of joint aspiration or diagnostic in the problem list or ≥ 2 other criteria created a subcategory of 5138 patients. Of this register, 92.4% had a PPV (95% confidence interval [CI] 88.5% — 95.0%) and 94.3% had a NPV (95% CI 91.9% — 96.0%). The PPV and NPV were comparable among inpatients and outpatients.

The incidence was 2.9 per 1000 patient-years, which dropped by 30% at the beginning of the COVID-19 pandemic.

Patients with a gout diagnosis were predominantly male (76.5%), overweight (69.5%), had several comorbidities, and had an average age of 71.2 years. The most common comorbidities were hypertension (69.4%) and cardiovascular and ischemic disease (53.0%). Over half (57.4%) were prescribed a urate lowering therapy, 6.7% had either ≥ 2 flares within a year or were hospitalized due to gout, and 32.9% received a consultation from a rheumatologist.

Investigators noted selection bias as a main limitation of the study, which could also hinder generalizability. Additionally, the EHR could not evaluate any patients who consulted with clinicians in private clinics or practices and those who did not ultimately seek medical attention. However, HUG provides free care to the majority of the regional population, including inpatient and outpatient care to more vulnerable patients. Other important limitations were the use of a single hospital for the register, the possibility of misdiagnosis, and the chance that some patients with gout went undiagnosed due to missing information within the EHR.

“The automatic nature of the query makes this register inexpensive and sustainable, facilitating the assessment of the adequacy of gout management, the monitoring of indicators following quality improvement projects, and the detection of gout patients to be included in new studies or trials,” investigators summarized. “Also, the decline of gout diagnoses since 2020, especially evident in inpatient settings, prompts questions about how the pandemic may have affected healthcare access, patient behaviors and diagnostic approaches.”

References

1. ^{Bürgisser N, Mongin D, Mehouachi S, et al. Development and validation of a self-updating gout register from electronic health records data. RMD Open. 2024;10(2):e004120. Published 2024 Apr 24. doi:10.1136/rmdopen-2024-004120}
2. ^{Dehlin M, Jacobsson L, Roddy E. Global epidemiology of gout: prevalence, incidence, treatment patterns and risk factors. Nat Rev Rheumatol 2020;16:380–90. doi:10.1038/s41584-020-0441-1}