A predictive model to identify Parkinson disease from administrative claims data.

ABSTRACT:

Objective

To use administrative medical claims data to identify patients with incident Parkinson disease (PD) prior to diagnosis.

Methods

Using a population-based case-control study of incident PD in 2009 among Medicare beneficiaries aged 66-90 years (89,790 cases, 118,095 controls) and the elastic net algorithm, we developed a cross-validated model for predicting PD using only demographic data and 2004-2009 Medicare claims data. We then compared this model to more basic models containing only demographic data and diagnosis codes for constipation, taste/smell disturbance, and REM sleep behavior disorder, using each model's receiver operator characteristic area under the curve (AUC).

Results

We observed all established associations between PD and age, sex, race/ethnici

SUBMITTER: Searles Nielsen S 

PROVIDER: S-EPMC5631173 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature