The unforeseen tradeoff: could AI scribes alter the cognitive and relational work of clinical documentation?

AI scribes can reduce the documentation burden and allow clinicians to spend more face time with patients. However, we propose a hypothesis-generating concern that by reducing the active cognitive work of composing clinical notes, AI scribes may alter the encoding of patient encounter details into memory, particularly the narrative and relational details, as distinct from the informational content already captured in the chart. Our viewpoint advances a theoretically grounded hypothesis based on clinical observations and existing literature directly or indirectly relevant to clinical documentation, warranting future empirical investigation. The proposed tradeoff is most relevant to longitudinal care and may vary with documentation workflow and clinician experience. Because relational continuity and clinician recall may be important to the doctor-patient relationship, the shift toward AI-generated notes therefore raises questions about how to preserve meaningful cognitive engagement while benefiting from reliable clinical records.

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Publication Details

Journal
Postgraduate Medicine
Published
2026-10-29
DOI
https://doi.org/10.1080/00325481.2026.2754554
Primary Topic
Electronic Health Records Systems
Type
article
Field-Weighted Citation Impact
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article

The unforeseen tradeoff: could AI scribes alter the cognitive and relational work of clinical documentation?

Jacob Hascalovici, Tianrun Pan, Elizabeth A.C. Kera
5 links
Postgraduate Medicine
Electronic Health Records Systems
article

The unforeseen tradeoff: could AI scribes alter the cognitive and relational work of clinical documentation?

Jacob Hascalovici, Tianrun Pan, Elizabeth A.C. Kera
article en

Abstract

AI scribes can reduce the documentation burden and allow clinicians to spend more face time with patients. However, we propose a hypothesis-generating concern that by reducing the active cognitive work of composing clinical notes, AI scribes may alter the encoding of patient encounter details into memory, particularly the narrative and relational details, as distinct from the informational content already captured in the chart. Our viewpoint advances a theoretically grounded hypothesis based on clinical observations and existing literature directly or indirectly relevant to clinical documentation, warranting future empirical investigation. The proposed tradeoff is most relevant to longitudinal care and may vary with documentation workflow and clinician experience. Because relational continuity and clinician recall may be important to the doctor-patient relationship, the shift toward AI-generated notes therefore raises questions about how to preserve meaningful cognitive engagement while benefiting from reliable clinical records.

Postgraduate Medicine
Hackensack University Medical Center (US)
Openalex Percentile: Top 8%
Electronic Health Records Systems
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