Study Rationale: In the absence of new or emerging therapies, there is strong interest in repurposing medications for treatment of Parkinson’s Disease (PD) progression if promising signals can be identified in existing electronic health record (EHR) data from clinical practice. To effectively achieve this goal, it is essential to first establish a uniform set of measures of PD progression that are consistently documented in real-world clinical practice. Once these measures are established and validated, medication exposures that may be associated with PD progression will be evaluated in subsequent work.
Hypothesis: To establish and describe a longitudinal cohort of patients with incident diagnosis of PD; identify a set of structured and unstructured measures of disease progression from clinical practice that are routinely documented in the EHR; and describe the concurrent medication profiles of PD patients over time.
Study Design: A mixed-method design will be used. First, structured data elements will be identified and extracted from the demographic, encounter, procedure, diagnosis, and pharmacy tables in the EHR to describe the patient cohort and potential measures that reflect longitudinal progression of PD. Second, neurologists with experience in treating PD will be interviewed to identify key content and terminology commonly used to document PD progression in clinical practice. Third, a random sample of electronic health records will undergo a thorough case review of unstructured data fields within the EHR to determine availability of data from neurologist interviews. Finally, structured and unstructured data will be summarized and reported in a longitudinal manner to identify patterns that reflect PD progression.
Impact on Diagnosis/Treatment of Parkinson’s disease: The proposed study enables identification of an incident sample and data availability to inform longitudinal study of clinically relevant structured and unstructured measures of PD progression that may be embedded in the EHR. The incident-based approach establishes temporal sequencing essential for studying medications that may positively impact PD progression.
Next Steps for Development: Importantly, this study establishes a common data framework to facilitate a larger investigation that will seek to identify medications that could potentially be considered for repurposing to treat PD progression if promising signals are identified.