ArticleJournal of the American Medical Informatics Association : JAMIA2013
Using the computer in the clinical consultation; setting the stage, reviewing, recording, and taking actions: multi-channel video study.
Article in Journal of the American Medical Informatics Association : JAMIA, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed, 4 syntheses or guidelines pooled it, 83 citations in OpenAlex.
- Understanding "Alert Fatigue" in Primary Care: Qualitative Systematic Review of General Practitioners Attitudes and Experiences of Clinical Alerts, Prompts, and Reminders.Journal of medical Internet research · 2025Pooled it
- Pooled it
- Developing an evidence base of best practices for integrating computerized systems into the exam room: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2017Pooled it
- Impact of Electronic Medical Record Use on the Patient-Doctor Relationship and Communication: A Systematic Review.Journal of general internal medicine · 2016Pooled it
- Observer: creation of a novel multimodal dataset for outpatient care research.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- A nursing perspective on human-AI collaboration in personalized breast cancer care pathways.Frontiers in oncology · 2026Article
- Observer: Creation of a Novel Multimodal Dataset for Outpatient Care Research.medRxiv : the preprint server for health sciences · 2025Article
- Article
- An integrative review exploring the impact of Electronic Health Records (EHR) on the quality of nurse-patient interactions and communication.Journal of advanced nursing · 2023Review
- Barriers and Facilitators to the Initiation of Injectable Therapies for Type 2 Diabetes Mellitus: A Mixed Methods Study.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2022Article
- Oncologist responses to advanced cancer patients' lived illness experiences and effects: an applied conversation analysis study.BMC palliative care · 2022Article
- Article
- Efficient Clinical Counseling for Sickle Cell Disease.Journal of the National Medical Association · 2021Review
- Improving the Management of Atrial Fibrillation in General Practice: Protocol for a Mixed Methods Study.JMIR research protocols · 2020Article
- Impacts of Operational Failures on Primary Care Physicians' Work: A Critical Interpretive Synthesis of the Literature.Annals of family medicine · 2020Review
- Provider Preference in Exam Room Layout Design and Computing.Applied clinical informatics · 2019Article
- Intensification to injectable therapy in type 2 diabetes: mixed methods study (protocol).BMC health services research · 2019Article
- Article
- Estimating the burden on general practitioner services in England from increases in respiratory disease associated with seasonal respiratory pathogen activity.Epidemiology and infection · 2018Article
- Finding Meaning in Medication Reconciliation Using Electronic Health Records: Qualitative Analysis in Safety Net Primary and Specialty Care.JMIR medical informatics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveElectronic patient record (EPR) systems are widely used. This study explores the context and use of systems to provide insights into improving their use in clinical practice.
methodsWe used video to observe 163 consultations by 16 clinicians using four EPR brands. We made a visual study of the consultation room and coded interactions between clinician, patient, and computer. Few patients (6.9%, n=12) declined to participate.
resultsPatients looked at the computer twice as much (47.6 s vs 20.6 s, p<0.001) when it was within their gaze. A quarter of consultations were interrupted (27.6%, n=45); and in half the clinician left the room (12.3%, n=20). The core consultation takes about 87% of the total session time; 5% of time is spent pre-consultation, reading the record and calling the patient in; and 8% of time is spent post-consultation, largely entering notes. Consultations with more than one person and where prescribing took place were longer (R(2) adj=22.5%, p<0.001). The core consultation can be divided into 61% of direct clinician-patient interaction, of which 15% is examination, 25% computer use with no patient involvement, and 14% simultaneous clinician-computer-patient interplay. The proportions of computer use are similar between consultations (mean=40.6%, SD=13.7%). There was more data coding in problem-orientated EPR systems, though clinicians often used vague codes.
conclusionsThe EPR system is used for a consistent proportion of the consultation and should be designed to facilitate multi-tasking. Clinicians who want to promote screen sharing should change their consulting room layout.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.