Medical Marijuana (MMJ) is available in Pennsylvania (PA) and participation in the state-regulated program requires a patient to register and receive certification by an approved physician. There is currently no integration of MMJ certification data in PA into health records that would allow for clinicians to rapidly identify patients that are using MMJ, as there are with other scheduled drugs. This absence of a formal data sharing structure necessitates tools that aid in consistent documentation practices to enable comprehensive patient care. Customized smart data elements (SDEs) were made available to clinicians at an integrated health system, Geisinger, following MMJ legalization in PA. The purpose of this project was to examine and contextualize the use of MMJ SDEs in the Geisinger population. We accomplished this goal by developing a systematic chart review protocol, with the goal of creating a tool that resulted in consistent human data extraction. We developed a chart review protocol for extracting MMJ-related information. The protocol was developed between August to December of 2022 and focused on a patient group that received one of several MMJ SDEs between 1/25/2019 and 5/26/2022. Characteristics were first identified on a small pilot sample of patients (n=5), which were then iteratively reviewed to optimize for consistency. Following the pilot, two reviewers were assigned 200 patient charts, selected randomly from the larger cohort, with a third reviewer examining a subsample (n=30) to determine reliability. We then summarized the clinician-level and patient-level features from 156 charts with a table-format SDE that best captured MMJ information. We found the chart review protocol was feasible for those with minimal medical background to complete, with high inter-rater reliability (Kappa = .966 (P<.001), 95% CI (.954 - .978)). MMJ certification was largely documented by nurses and medical assistants (88.5%) and typically within primary care settings (68.6%). The SDE has six pre-set field prompts with heterogeneous documentation completion rates, including certifying conditions (93.6%), product (92.9%), authorized dispensary (87.8%), active ingredient (83.3%), certifying provider (61.5%), and dosage (30.8%). We found pre-set fields were overall well-recorded (76.6% across all fields). Primary diagnostic codes recorded at documentation encounters varied, with the most frequent being routine exams and testing (21.8%), musculoskeletal/nervous conditions (13.5%), and signs and symptoms not classified elsewhere (13.5%). This method of chart review yields high quality data extraction that can serve as a model for other health record inquiries. Our evaluation showed relatively high completeness of SDE fields, primarily by clinical staff responsible for rooming patients. Additional data captured presents an overview of the conditions under which MMJ is currently being documented. Improving adoption and fidelity of SDE data collection may present a valuable data source for future research on patient MMJ use, treatment efficacy, and outcomes.
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