ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2010
Cognitive analysis of the summarization of longitudinal patient records.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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
17 citing papers in PubMed.
- Analysing EHR navigation patterns and digital workflows among physicians during ICU pre-rounds.Health information management : journal of the Health Information Management Association of Australia · 2021Observational
- What's in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization.Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting · 2021Article
- CERC: an interactive content extraction, recognition, and construction tool for clinical and biomedical text.BMC medical informatics and decision making · 2020Article
- Health IT Usability Focus Section: Data Use and Navigation Patterns among Medical ICU Clinicians during Electronic Chart Review.Applied clinical informatics · 2017Article
- A Multisite Survey Study of EMR Review Habits, Information Needs, and Display Preferences among Medical ICU Clinicians Evaluating New Patients.Applied clinical informatics · 2017Article
- Foraging for Information in the EHR: The Search for Adherence Related Information by Mental Health Clinicians.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Observational
- Automatic Generation of Conditional Diagnostic Guidelines.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- Can Patient Record Summarization Support Quality Metric Abstraction?AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- Automated methods for the summarization of electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2015Review
- HARVEST, a longitudinal patient record summarizer.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- The clinician in the Driver's Seat: part 1 - a drag/drop user-composable electronic health record platform.Journal of biomedical informatics · 2014Article
- What do physicians read (and ignore) in electronic progress notes?Applied clinical informatics · 2014Article
- Using language models to identify relevant new information in inpatient clinical notes.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- Longitudinal analysis of new information types in clinical notes.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2014Article
- Clinical Summarization Capabilities of Commercially-available and Internally-developed Electronic Health Records.Applied clinical informatics · 2012Article
- Degree centrality for semantic abstraction summarization of therapeutic studies.Journal of biomedical informatics · 2011Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Electronic health records contain an abundance of valuable information that can be used to guide patient care. However, the large volume of information embodied in these records also renders access to relevant information a time-consuming and inefficient process. Our ultimate objective is to develop an automated summarizer that succinctly captures all relevant information in the patient record. In this paper, we present a cognitive study of 8 clinicians who were asked to create summaries based on data contained in the patients' electronic health record. The study characterized the primary sources of information that were prioritized by clinicians, the temporal strategies used to develop a summary and the cognitive operations used to guide the summarization process. Although we would not expect the automated summarizer to emulate human performance, we anticipate that this study will inform its development in instrumental ways.
Indexed as
Identifiers
21347062PMC3041351What OpenQuestion holds
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.