Explaining Variability in Electronic Health Record Effort in Primary Care Ambulatory Encounters

Overhage, J. Marc; Qeadan, Fares; Choi, Eun Ho Eunice; Vos, Duncan; Kroth, Philip J.

doi:10.1055/s-0044-1782228

Cited by 2 publications

References 35 publications

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Consistency is key: documentation distribution and efficiency in primary care

Apathy,

Biro,

Holmgren

2024

Journal of the American Medical Informatics Association

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Objectives We analyzed the degree to which daily documentation patterns in primary care varied and whether specific patterns, consistency over time, and deviations from clinicians’ usual patterns were associated with note-writing efficiency. Materials and Methods We used electronic health record (EHR) active use data from the Oracle Cerner Advance platform capturing hourly active documentation time for 498 physicians and advance practice clinicians (eg, nurse practitioners) for 65 152 clinic days. We used k-means clustering to identify distinct daily patterns of active documentation time and analyzed the relationship between these patterns and active documentation time per note. We determined each primary care clinician’s (PCC) modal documentation pattern and analyzed how consistency and deviations were related to documentation efficiency. Results We identified 8 distinct daily documentation patterns; the 3 most common patterns accounted for 80.6% of PCC-days and differed primarily in average volume of documentation time (78.1 minutes per day; 35.4 minutes per day; 144.6 minutes per day); associations with note efficiency were mixed. PCCs with >80% of days attributable to a single pattern demonstrated significantly more efficient documentation than PCCs with lower consistency; for high-consistency PCCs, days that deviated from their usual patterns were associated with less efficient documentation. Discussion We found substantial variation in efficiency across daily documentation patterns, suggesting that PCC-level factors like EHR facility and consistency may be more important than when documentation occurs. There were substantial efficiency returns to consistency, and deviations from consistent patterns were costly. Conclusion Organizational leaders aiming to reduce documentation burden should pay specific attention to the ability for PCCs to execute consistent documentation patterns day-to-day.

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Consistency is key: documentation distribution and efficiency in primary care

Apathy,

Biro,

Holmgren

2024

Journal of the American Medical Informatics Association

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A Framework to Assess Clinical Safety and Hallucination Rates of LLMs for Medical Text Summarisation

Asgari,

Montaña-Brown,

Dubois

et al. 2024

Preprint

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The integration of large language models (LLMs) into healthcare settings holds great promise for improving clinical workflow efficiency and enhancing patient care, with the potential to automate tasks such as text summarisation during consultations. The fidelity between LLM outputs and ground truth information is therefore paramount in healthcare, as errors in medical summary generation can lead to miscommunication between patients and clinicians, leading to incorrect diagnosis and treatment decisions and compromising patient safety. LLMs are well-known to produce a variety of errors. Currently, there is no established clinical framework for assessing the safety and accuracy of LLM-generated medical text. We have developed a new approach to: a) categorise LLM errors within the clinical documentation context, b) establish clinical safety metrics for the live usage phase, and c) suggest a framework named CREOLA for assessing the safety risk for errors. We present clinical error metrics over 18 different LLM experimental configurations for the clinical note generation task, consisting of 12,999 clinician-annotated sentences. We illustrate the utility of using our platform CREOLA for iteration over LLM architectures with two experiments. Overall, we find our best-performing experiments outperform previously reported model error rates in the note generation literature, and additionally outperform human annotators. Our suggested framework can be used to assess the accuracy and safety of LLM output in the clinical context.

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Explaining Variability in Electronic Health Record Effort in Primary Care Ambulatory Encounters

Cited by 2 publications

References 35 publications

Consistency is key: documentation distribution and efficiency in primary care

Consistency is key: documentation distribution and efficiency in primary care

A Framework to Assess Clinical Safety and Hallucination Rates of LLMs for Medical Text Summarisation

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