ArticleBMC medical informatics and decision making2022
Obtaining patients' medical history using a digital device prior to consultation in primary care: study protocol for a usability and validity study.
Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- Does an app make patients happy? Impact of a novel medical history app on patient satisfaction in urgent care consultations in Germany: cluster-randomized interventional trial 'DASI'.BMC health services research · 2026Trial
- A smartphone app for preschool wheezing and reliability of medical history collection.Italian journal of pediatrics · 2024Trial
- Evaluation of Prompt Design and Internal Reasoning in Chatbot-Based Medical History Taking: Simulation Study.JMIR medical informatics · 2026Article
- Safety-First Framework for AI-Enabled Anamnesis in Head and Neck Surgery: Evidence Synthesis from a Narrative Review.Journal of clinical medicine · 2026Review
- Taking a closer look: Can an app improve diagnostic accuracy in urgent care? Cluster-randomized interventional trial DASI.PLOS digital health · 2026Article
- Evaluation and practical application of prompt-driven ChatGPTs for EMR generation.NPJ digital medicine · 2025Review
- Concordance of data collected by an app for medical history taking and in-person interviews from patients in primary care.JAMIA open · 2024Article
- Usability of an App for Medical History Taking in General Practice From the Patients' Perspective: Cross-Sectional Study.JMIR human factors · 2024Article
- Neurological history both twinned and queried by generative artificial intelligence.Frontiers in medicine · 2024Article
- Evaluating an app for digital medical history taking in urgent care practices: study protocol of the cluster-randomized interventional trial 'DASI'.BMC primary care · 2023Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith the help of digital tools patients' medical histories can be collected quickly and transferred into their electronic medical records. This information can facilitate treatment planning, reduce documentation work, and improve care. However, it is still unclear whether the information collected from patients in this way is reliable. In this study, we assess the accuracy of the information collected by patients using an app for medical history taking by comparing it with the information collected in a face-to-face medical interview. We also study the app's usability from the patients' point of view and analysing usage data.
methodsWe developed a software application (app) for symptom-oriented medical history taking specialized for general practice. Medical history taking will take place involving patients with acute somatic or psychological complaints (1) using the app and (2) verbally with trained study staff. To assess the perceived usability, patients will complete a questionnaire for the System Usability Scale. We will collect sociodemographic data, information about media use and health literacy, and app usage data. DISCUSSION: Digital tools offer the opportunity to improve patient care. However, it is not self-evident that the medical history taken by digital tools corresponds to the medical history that would be taken in an interview. If simply due to a design flaw patients answer questions about signs and symptoms that indicate possible serious underlying conditions 'wrong', this could have severe consequences. By additionally assessing the app's usability as perceived by a diverse group of patients, potential weaknesses in content, design and navigation can be identified and subsequently improved. This is essential in order to ensure that the app meets the need of different groups of patients. Trial registration German Clinical Trials Register DRKS00026659 , registered Nov 03 2021. World Health Organization Trial Registration Data Set, https://trialsearch.who.int/Trial2.aspx? TrialID = DRKS00026659.
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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 Socratic graph.