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Quantitative and qualitative methods advance the science of clinical workflow research

2023·3 Zitationen·Journal of the American Medical Informatics AssociationOpen Access
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3

Zitationen

1

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2023

Jahr

Abstract

Throughout the decades of JAMIA's existence, the relationship between automation and clinical workflow has remained a hot topic. [1][2]2][3][4] A 2021 JAMIA issue focused on the relationship between health information technology and clinician burnout. 5In this editorial, I highlight four research and application papers and a brief communication that address aspects of clinician workflow.One paper asks the provocative question of "Are we there yet?" 6 and the five highlighted papers suggest that despite positive effects of health information technology on quality in some instances and the advances in the science of workflow research, 7,8 much remains to be done to match health information technology and clinician workflow.Three of the five studies emphasize the role of qualitative research in understanding this relationship 6,9,10 and another addresses the discrepancy between subjective perceptions and objective measures of clinician efficiency. 11oy et al 9 conducted semi-structured interviews with a national sample (n 24) of US prescribing providers and registered nurses who practice in the adult emergency department setting and use the Epic electronic health record (EHR) to understand perceptions of the role of EHRs and workflow fragmentation on clinician documentation burden in emergency departments.They analyzed interview transcripts using inductive thematic analysis and finalized six themes through a consensus process.EHR factors perceived to contribute to documentation burden included (1) lack of advanced EHR capabilities; (2) EHR documentation not optimized for clinicians;(3) EHR work volume hinders communication between clinicians internal and external to the EHR; (4) poor user interface design impacts clinician documentation habits; (5) high volume of manual EHR work; and (6) blockages in EHR impede documentation efficiency.Their findings highlight the importance of designing EHRs

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Machine Learning in HealthcareElectronic Health Records SystemsArtificial Intelligence in Healthcare and Education
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