Beiler Donielle, Chopra Aanya, Gregor Christina M, Tusing Lorraine D, Pradhan Apoorva M, Romagnoli Katrina M, Kraus Chadd K, Piper Brian J, Wright Eric A, Troiani Vanessa
Autism and Developmental Medicine Institute, Geisinger, Lewisburg, PA, United States.
Center for Pharmacy Innovation and Outcomes, Geisinger, Danville, PA, United States.
JMIR Form Res. 2024 Dec 23;8:e65957. doi: 10.2196/65957.
Medical marijuana (MMJ) is available in Pennsylvania, and participation in the state-regulated program requires patient registration and receiving certification by an approved physician. Currently, no integration of MMJ certification data with health records exists in Pennsylvania that would allow clinicians to rapidly identify patients using MMJ, as exists with other scheduled drugs. This absence of a formal data sharing structure necessitates tools aiding 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 Pennsylvania.
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 protocol for review of medical records and creating a tool that resulted in consistent human data extraction.
We developed a protocol for reviewing medical records for extracting MMJ-related information. The protocol was developed between August and December of 2022 and focused on a patient group that received one of several MMJ SDEs between January 25, 2019, and May 26, 2022. Characteristics were first identified on a pilot sample (n=5), which were then iteratively reviewed to optimize for consistency. Following the pilot, 2 reviewers were assigned 200 randomly selected patients' medical records, with a third reviewer examining a subsample (n=30) to determine reliability. We then summarized the clinician- and patient-level features from 156 medical records with a table-format SDE that best captured MMJ information.
We found the review protocol for medical records was feasible for those with minimal medical background to complete, with high interrater reliability (κ=0.966; P<.001; odds ratio 0.97, 95% CI 0.954-0.978). MMJ certification was largely documented by nurses and medical assistants (n=138, 88.5%) and typically within primary care settings (n=107, 68.6%). The SDE has 6 preset field prompts with heterogeneous documentation completion rates, including certifying conditions (n=146, 93.6%), product (n=145, 92.9%), authorized dispensary (n=137, 87.8%), active ingredient (n=130, 83.3%), certifying provider (n=96, 61.5%), and dosage (n=48, 30.8%). We found preset fields were overall well-recorded (mean 76.6%, SD 23.7% across all fields). Primary diagnostic codes recorded at documentation encounters varied, with the most frequent being routine examinations and testing (n=34, 21.8%), musculoskeletal or nervous conditions, and signs and symptoms not classified elsewhere (n=21, 13.5%).
This method of reviewing medical records 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, with an overview of conditions under which MMJ is documented. Improving the adoption and fidelity of SDE data collection may present a valuable data source for future research on patient MMJ use, treatment efficacy, and outcomes.
宾夕法尼亚州可获取医用大麻(MMJ),参与该州监管项目要求患者进行注册并获得经批准医生的认证。目前,宾夕法尼亚州不存在将MMJ认证数据与健康记录整合的情况,这使得临床医生无法像对待其他处方药那样快速识别使用MMJ的患者。缺乏正式的数据共享结构使得需要工具来辅助进行一致的文档记录操作,以实现全面的患者护理。在宾夕法尼亚州将MMJ合法化后,综合医疗系统盖辛格向临床医生提供了定制的智能数据元素(SDE)。
本项目的目的是研究并分析盖辛格人群中MMJ SDE的使用情况。我们通过制定审查病历的系统方案并创建一个能实现一致的人工数据提取的工具来实现这一目标。
我们制定了一个审查病历以提取MMJ相关信息的方案。该方案于2022年8月至12月期间制定,重点关注在2019年1月25日至2022年5月26日期间接受了几种MMJ SDE之一的患者群体。首先在一个试点样本(n = 5)中确定特征,然后对其进行反复审查以优化一致性。试点之后,为两名审查员分配了200份随机选择的患者病历,第三名审查员检查一个子样本(n = 30)以确定可靠性。然后,我们使用能最佳捕获MMJ信息的表格形式的SDE总结了156份病历中的临床医生和患者层面的特征。
我们发现,对于医学背景有限的人来说,病历审查方案是可行的,评分者间信度很高(κ = 0.966;P <.001;优势比0.97,95%置信区间0.954 - 0.978)。MMJ认证大多由护士和医疗助理记录(n = 138,8