Measuring Physician Adherence With Gout Quality Indicators: A Role for Natural Language Processing

Authors


Abstract

Objective

To evaluate physician adherence with gout quality indicators (QIs) for medication use and monitoring, and behavioral modification (BM).

Methods

Gout patients were assessed for the QIs as follows: QI 1: initial allopurinol dosage <300 mg/day for patients with chronic kidney disease (CKD); QI 2: uric acid within 6 months of allopurinol start; and QI 3: complete blood count and creatinine phosphokinase within 6 months of colchicine initiation. Natural language processing (NLP) was used to analyze clinical narrative data from electronic medical records (EMRs) of overweight (body mass index ≥28 kg/m2) gout patients for BM counseling on gout-specific dietary restrictions, weight loss, and alcohol consumption (QI 4). Additional data included sociodemographics, comorbidities, and number of rheumatology and primary care visits. QI compliance versus noncompliance was compared using chi-square analyses and independent-groups t-test.

Results

In 2,280 gout patients, compliance with QI was as follows: QI 1: 92.1%, QI 2: 44.8%, and QI 3: 7.7%. Patients compliant with QI 2 had more rheumatology visits at 3.5 versus 2.6 visits (P < 0.001), while those compliant with QI 3 had more CKD (P < 0.01). Of 1,576 eligible patients, BM counseling for weight loss occurred in 1,008 patients (64.0%), low purine diet in 390 (24.8%), alcohol abstention in 137 (8.7%), and all 3 elements in 51 patients (3.2%). Regular rheumatology clinic visits correlated with frequent advice on weight loss and gout-specific diet (P < 0.0001).

Conclusion

Rheumatology clinic attendance was associated with greater QI compliance. NLP proved a valuable tool for measuring BM as documented in the clinical narrative of EMRs.

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