Incidence and prevalence of knee osteoarthritis using codified and narrative data from electronic health records: a population-based study

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Abstract

Objective: To determine the incidence and prevalence of knee osteoarthritis (OA) using codified and narrative data from general practices throughout The Netherlands. Methods: This retrospective cohort study was conducted using the Integrated Primary Care Information database. Patients with codified knee OA were selected, and an algorithm was developed to identify patients with narratively diagnosed knee OA only. Point prevalence proportions and incidence rates among people age ≥30 years were assessed from 2008 to 2019. The association of comorbidities with codified knee OA was analyzed using multivariable logistic regression. Results: The positive predicted value of narratively diagnosed knee OA only was 94.0% (95% confidence interval [95% CI] 87.4–100%) and for codified knee OA 96.0% (95% CI 90.6–100%). Including narrative data in addition to codified data resulted in a prevalence 1.83–2.01 times higher (over the study years); prevalence increased from 5.8% to 11.8% between 2008 and 2019. The incidence rate was 1.93–2.28 times higher and increased from 9.98 per 1,000 person-years to 13.8 per 1,000 person-years between 2008 and 2019. Among patients with codified knee OA, 39.4% were previously diagnosed narratively with knee OA, on average ~3 years earlier. Comorbidities influenced the likelihood of being recorded with codified knee OA. Conclusion: Our study of a Dutch primary care database showed that current incidence and prevalence estimates based on codified data alone from electronic health records are underestimated. Narrative data can be incorporated in addition to codified data to identify knee OA patients more accurately.

Original languageEnglish
Pages (from-to)937-944
Number of pages8
JournalArthritis Care and Research
Volume74
Issue number6
Early online date18 Jan 2022
DOIs
Publication statusPublished - Jun 2022

Bibliographical note

Funding Information:
This work was supported by the National Science Foundation for Young Scientists of China (no. 11901123), the Guangxi Natural Science Foundation (nos. 2018JJB110062, 2019AC20062) and the Xiangsihu Young Scholars Innovative Research Team of Guangxi University for Nationalities (no. 2019RSCXSHQN03)

Publisher Copyright:
© 2022 The Authors. Arthritis Care & Research published by Wiley Periodicals LLC on behalf of American College of Rheumatology.

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