Dataset Information

Designing and Implementing an Electronic Health Record-Embedded Card Study in Primary Care: Methods and Considerations.

ABSTRACT: Card studies-short surveys about the circumstances within which patients receive care-are traditionally completed on physical cards. We report on the development of an electronic health record (EHR)-embedded card study intended to decrease logistical challenges inherent to paper-based approaches, including distributing, tracking, and transferring the physical cards, as well as data entry and respondent prompts, while simultaneously decreasing the complexity for participants and facilitating rich analyses by linking to clinical and demographic data found in the EHR. Developing the EHR-based programming and data extraction was time consuming, required specialized expertise, and necessitated iteration to rectify issues encountered during implementation. Nonetheless, future EHR-embedded card studies will be able to replicate many of the same processes as informed by these results. Once built, the EHR-embedded card study simplified survey implementation for both the research team and clinic staff, resulting in research-quality data, the ability to link survey responses to relevant EHR data, and a 79% response rate. This detailed accounting of the development and implementation process, including issues encountered and addressed, might guide others in conducting EHR-embedded card studies.

SUBMITTER: Bunce A

PROVIDER: S-EPMC9328703 | biostudies-literature | 2022 Jul-Aug

REPOSITORIES: biostudies-literature

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Designing and Implementing an Electronic Health Record-Embedded Card Study in Primary Care: Methods and Considerations.

Bunce Arwen A Middendorf Mary M Hoopes Megan M Donovan Jenna J Gold Rachel R

Annals of family medicine 20220701 4

Card studies-short surveys about the circumstances within which patients receive care-are traditionally completed on physical cards. We report on the development of an electronic health record (EHR)-embedded card study intended to decrease logistical challenges inherent to paper-based approaches, including distributing, tracking, and transferring the physical cards, as well as data entry and respondent prompts, while simultaneously decreasing the complexity for participants and facilitating rich ...[more]

PMID: 35879076

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Project description:ObjectiveAnalysis of routinely collected electronic health record (EHR) data from primary care is reliant on the creation of codelists to define clinical features of interest. To improve scientific rigour, transparency and replicability, we describe and demonstrate a standardised reproducible methodology for clinical codelist development.DesignWe describe a three-stage process for developing clinical codelists. First, the clear definition a priori of the clinical feature of interest using reliable clinical resources. Second, development of a list of potential codes using statistical software to comprehensively search all available codes. Third, a modified Delphi process to reach consensus between primary care practitioners on the most relevant codes, including the generation of an 'uncertainty' variable to allow sensitivity analysis.SettingThese methods are illustrated by developing a codelist for shortness of breath in a primary care EHR sample, including modifiable syntax for commonly used statistical software.ParticipantsThe codelist was used to estimate the frequency of shortness of breath in a cohort of 28 216 patients aged over 18 years who received an incident diagnosis of lung cancer between 1 January 2000 and 30 November 2016 in the Clinical Practice Research Datalink (CPRD).ResultsOf 78 candidate codes, 29 were excluded as inappropriate. Complete agreement was reached for 44 (90%) of the remaining codes, with partial disagreement over 5 (10%). 13 091 episodes of shortness of breath were identified in the cohort of 28 216 patients. Sensitivity analysis demonstrates that codes with the greatest uncertainty tend to be rarely used in clinical practice.ConclusionsAlthough initially time consuming, using a rigorous and reproducible method for codelist generation 'future-proofs' findings and an auditable, modifiable syntax for codelist generation enables sharing and replication of EHR studies. Published codelists should be badged by quality and report the methods of codelist generation including: definitions and justifications associated with each codelist; the syntax or search method; the number of candidate codes identified; and the categorisation of codes after Delphi review.

Project description:ImportancePhysicians across the US spend substantial time working in the electronic health record (EHR), with primary care physicians (PCPs) spending the most time. The association between EHR time and ambulatory care quality outcomes is unclear.ObjectiveTo characterize measures of EHR use and ambulatory care quality performance among PCPs.Design, setting, and participantsA cross-sectional study of PCPs with longitudinal patient panels using a single EHR vendor was conducted at Brigham and Women's Hospital and Massachusetts General Hospital during calendar year 2021.ExposuresIndependent variables included PCPs demographic and practice characteristics and EHR time measures (PCP-level mean of daily total EHR time, after-hours time, time from 5:30 pm to 7:00 am and time on weekends, and daily EHR time on notes, sending and receiving patient, staff, results, prescription, or system messages [in-basket], and clinical review).Main outcomes and measuresOutcome variables were ambulatory quality measures (year-end, PCP panel-level achievement of targets for hemoglobin A1c level control, lipid management, hypertension control, diabetes screening, and breast cancer screening).ResultsThe sample included 291 physicians (174 [59.8%] women). Median panel size was 829 (IQR, 476-1157) patients and mean (SD) clinical full-time equivalent was 0.54 (0.27). The PCPs spent a mean (SD) of 145.9 (64.6) daily minutes on the EHR. There were significant associations between EHR time and panel-level achievement of hemoglobin A1c control, hypertension control, and breast cancer screening targets. In adjusted analyses, each additional 15 minutes of total daily EHR time was associated with 0.58 (95% CI, 0.32-0.84) percentage point greater panel-level hemoglobin A1c control, 0.52 (95% CI, 0.33-0.71) percentage point greater hypertension control, and 0.28 (95% CI, 0.05-0.52) higher breast cancer screening rates. Each daily additional 15 minutes of in-basket time was associated with 2.26 (95% CI, 1.05-3.48) greater panel-wide hemoglobin A1c control, 1.65 (95% CI, 0.83-2.47) percentage point greater hypertension control, and 1.26 (95% CI, 0.51-2.02) percentage point higher breast cancer screening rates. Associations were largely concentrated among PCPs with 0.5 clinical full-time equivalent or less. There were no associations between EHR use metrics and diabetes screening or lipid management in patients with cardiovascular disease.Conclusions and relevanceThis cross-sectional study found an association between EHR time and some measures of ambulatory care quality. Although increased EHR time is associated with burnout, it may represent a level of thoroughness or communication that enhances certain outcomes. It may be useful for future studies to characterize payment models, workflows, and technologies that enable high-quality ambulatory care delivery while minimizing EHR burden.

Dataset Information

Designing and Implementing an Electronic Health Record-Embedded Card Study in Primary Care: Methods and Considerations.

Publications

Designing and Implementing an Electronic Health Record-Embedded Card Study in Primary Care: Methods and Considerations.

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