Medical Marijuana Documentation Practices in Patient Electronic Health Records: A Retrospective Observational Study Using Smart Data Elements and Chart Review.

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES JMIR Formative Research Pub Date : 2024-10-10 DOI:10.2196/65957
Donielle Beiler, Aanya Chopra, Christina Gregor, Lorraine D Tusing, Apoorva M Pradhan, Katrina M Romagnoli, Chadd K Kraus, Brian J Piper, Eric A Wright, Vanessa Troiani
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Abstract

Background: 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.

Objective: 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.

Methods: 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.

Results: 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%).

Conclusions: 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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患者电子健康记录中的医用大麻文档实践:使用智能数据元素和病历审查的回顾性观察研究。
背景:宾夕法尼亚州(PA)提供医用大麻 (MMJ),参与该州监管的计划需要患者注册并获得认可医生的认证。目前,宾夕法尼亚州尚未将医用大麻认证数据整合到健康记录中,使临床医生能够像使用其他附表药物一样,快速识别使用医用大麻的患者。由于缺乏正式的数据共享结构,因此需要一些工具来帮助实现一致的文件记录实践,从而实现全面的患者护理。在宾夕法尼亚州 MMJ 合法化之后,一个综合医疗系统 Geisinger 的临床医生可以使用定制的智能数据元素(SDE):本项目的目的是研究和分析在 Geisinger 人口中使用 MMJ SDEs 的情况。为了实现这一目标,我们制定了一项系统的病历审查协议,目的是创建一种能够实现一致的人工数据提取的工具:我们制定了一份病历审查协议,用于提取 MMJ 相关信息。该协议于 2022 年 8 月至 12 月间制定,主要针对在 2019 年 1 月 25 日至 2022 年 5 月 26 日期间接受过多种 MMJ SDE 之一的患者群体。首先对一小部分试点样本患者(n=5)进行特征识别,然后对其进行反复审查,以优化一致性。试点结束后,两名审阅者被分配到 200 份患者病历中,这些病历是从更大的患者群中随机挑选的,第三名审阅者负责审阅一个子样本(n=30)以确定可靠性。然后,我们从 156 份病历中总结了临床医生层面和患者层面的特征,并采用了最能捕捉 MMJ 信息的表格格式 SDE:结果:我们发现,对于医学背景较浅的人来说,完成病历审查协议是可行的,而且评分者之间的可靠性很高(Kappa = .966):这种病历审查方法能提取高质量的数据,可作为其他健康记录查询的范例。我们的评估结果表明,SDE 字段的完整性相对较高,主要由负责患者分房的临床工作人员完成。获取的其他数据概述了目前记录 MMJ 的情况。提高 SDE 数据收集的采用率和忠实度可为未来研究患者 MMJ 使用情况、治疗效果和结果提供宝贵的数据来源。
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来源期刊
JMIR Formative Research
JMIR Formative Research Medicine-Medicine (miscellaneous)
CiteScore
2.70
自引率
9.10%
发文量
579
审稿时长
12 weeks
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