Evidence map›Paper›PMID 39715532›Full record

Observational studyJMIR formative research2024

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

Donielle Beiler, Aanya Chopra, Christina M Gregor, Lorraine D Tusing, Apoorva M Pradhan, Katrina M Romagnoli, Chadd K Kraus, Brian J Piper, Eric A Wright, Vanessa Troiani

Abstract readObservational Study
In one paragraph

Observational study in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Donielle BeilerAutism and Developmental Medicine Institute, Geisinger, Lewisburg, PA, United States.ORCID 0000-0002-4570-631X
Aanya ChopraCenter for Pharmacy Innovation and Outcomes, Geisinger, Danville, PA, United States.ORCID 0009-0005-6565-5571
Christina M GregorCenter for Pharmacy Innovation and Outcomes, Geisinger, Danville, PA, United States.ORCID 0009-0002-0141-7441
Lorraine D TusingCenter for Pharmacy Innovation and Outcomes, Geisinger, Danville, PA, United States.ORCID 0000-0002-9091-8178
Apoorva M PradhanCenter for Pharmacy Innovation and Outcomes, Geisinger, Danville, PA, United States.ORCID 0000-0002-1066-4973
Katrina M RomagnoliCenter for Pharmacy Innovation and Outcomes, Geisinger, Danville, PA, United States.ORCID 0000-0001-8473-2126
Chadd K KrausDepartment of Emergency and Hospital Medicine, Lehigh Valley Health Network, Hazelton, PA, United States.ORCID 0000-0003-3628-2073
Brian J PiperCenter for Pharmacy Innovation and Outcomes, Geisinger, Danville, PA, United States.ORCID 0000-0002-2295-445X
Eric A WrightCenter for Pharmacy Innovation and Outcomes, Geisinger, Danville, PA, United States.ORCID 0000-0003-1721-4104
Vanessa TroianiAutism and Developmental Medicine Institute, Geisinger, Lewisburg, PA, United States.ORCID 0000-0001-6689-8157

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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. 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 protocol for review of medical records and creating a tool that resulted in consistent human data extraction. Methods: 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. Results: 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%). Conclusions: 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.

Indexed as

DocumentationElectronic Health RecordsMedical MarijuanaAdultFemaleHumansMaleMedical RecordsMiddle AgedPennsylvaniaRetrospective StudiesMedical Marijuanacannabiscannabis usechart review protocoldata collectiondata sharingdosagedrug useelectronic health recordsEpichuman data extractionlearning health systemlegalizationmedical marijuanapatient carephysicianprescription drug monitoring program

Identifiers

PMID39715532
PMCPMC11684775

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.