Evidence map›Paper›PMID 41917295›Full record

ArticleJournal of general internal medicine2026

Exploring the Patient's Lifeworld: A Qualitative Study of Personalizing Language in Electronic Health Records.

Akanksha Suresh, Priyanka Fernandes, Ayah Zirikly, Elaine C Thompson, Anne R Links, Keith Harrigian, Brant Chee, Mark Dredze, Mary Catherine Beach, Somnath Saha

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Article in Journal of general internal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Akanksha SureshSchool of Medicine, Johns Hopkins University, Baltimore, MD, USA.
Priyanka FernandesSchool of Medicine, Johns Hopkins University, Baltimore, MD, USA.
Ayah ZiriklyDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA.
Elaine C ThompsonDepartment of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA.ORCID 0000-0003-1293-6247
Anne R LinksDepartment of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Keith HarrigianDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA.
Brant CheeApplied Physics Lab, Johns Hopkins University, Baltimore, MD, USA.
Mark DredzeDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA.
Mary Catherine BeachDepartment of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA. mcbeach@jhmi.edu.ORCID 0000-0002-1112-6309
Somnath SahaDepartment of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

Funding

Improving Patient Care through Respectful Medical Record LanguageR01MD017048 · NIMHD · JOHNS HOPKINS UNIVERSITY · PI MARY CATHERINE BEACH · 2022 to 2026
$3.9M
NIH HHS R25 DC021243-01NIMHD NIH HHS R01 MD017048
6 · The paper itself

Abstract

backgroundPhysicians' understanding of patients as persons can bolster relationships and help patients feel seen. Including personal details in electronic health records (EHR) may enhance care, but the types of details physicians document about patients' lifeworlds remain largely uncharacterized.

objectiveTo assess the prevalence and types of personalizing language written by physicians in clinical encounter notes.

designCross-sectional qualitative content analysis of physician-written history and physical (H&P) notes. PATIENTS: Adult patients admitted to the internal medicine inpatient service at an urban academic tertiary care hospital. APPROACH: We performed an inductive content analysis of H&P notes. Two authors independently coded instances of personalizing language: details about patients' unique identities, social context, life experiences, and perspectives. The study team met periodically to discuss examples and categories and compare assessments until thematic saturation was reached. We summarized the prevalence of personalizing language and described its content. KEY

resultsWe reviewed 570 H&P notes written about 437 unique patients (median age 57; 53% Black, 38% White; 54% male) by 186 physicians. More than half of notes (60%) contained at least one instance of personalizing language (median 2, range 1-7 per note). We identified 840 instances of personalizing language across seven domains: family (41%), work/education (32%), residence (21%), personal interests (2.9%), pets (1.8%), travel (0.6%), and goals/priorities (0.6%). Nearly half (47%) referred to general social context; 51% provided more detailed information. Only 1.9% described patients' thoughts, feelings, or goals. Personalizing language was more commonly used in notes for men vs women (70% vs 60%, p = 0.02).

conclusionsMost H&P notes included personalizing language, though many provided limited detail and very few described patients' interests, goals, and priorities. Future studies should evaluate patient perceptions of personalizing language in the medical record and its impact on physician attitudes towards and relationships with patients.

Indexed as

Electronic Health RecordsLanguagePhysician-Patient RelationsAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedQualitative Researchbiaselectronic health recordlanguagepersonalizingstigma

Identifiers

PMID41917295
PMCPMC13305229

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