Validation of knee osteoarthritis case identification algorithms in a large electronic health record database.

ABSTRACT:

Purpose

To facilitate studies of knee osteoarthritis (OA) in large databases, case finding algorithms with high levels of diagnostic performance are needed.

Methods

From a UK general practitioner (GP) practice derived database, we selected adults ages 40-90 years meeting algorithms that included various combinations of codes for knee OA or knee pain and imaging. The GP for each patient was mailed a questionnaire to assess the cause of knee pain and provide knee x-ray and/or MRI findings. We considered knee pain with x-ray and/or MRI findings consistent with OA the gold standard. We calculated positive predictive values (PPV) and sensitivity for case identification algorithms.

Results

Of 100 questionnaires sent, 93 were returned; we excluded 8 subjects who had other rh

SUBMITTER: Yau MS 

PROVIDER: S-EPMC9122022 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature