Observational studyComputers, informatics, nursing : CIN2017
Modeling Flowsheet Data to Support Secondary Use.
Observational study in Computers, informatics, nursing : CIN, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis 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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Impact of Patient Interactive Systems on the Management of Pain in an Inpatient Hospital Setting: A Systematic Review.Applied clinical informatics · 2019Pooled it
- Choosing between Patient Care Needs and Accurate Data Capture: Exploring Nurses' Experiences of Excessive Documentation Burden.Applied clinical informatics · 2025Article
- Semi-automated pipeline to accelerate multi-site flowsheet alignment and concept mapping in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Facilitators and Barriers to ICU Providers' Usability of Electronic Health Records Screens.Studies in health technology and informatics · 2025Article
- EHR Documentation Frequency Changes Across the COVID-19 Pandemic.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Information Model on pain management for elder adults aged 75 years or older.Revista latino-americana de enfermagem · 2024Observational
- Identifying Reuse and Redundancies in Respiratory Flowsheet Documentation: Implications for Clinician Documentation Burden.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Machine learning for predicting readmission risk among the frail: Explainable AI for healthcare.Patterns (New York, N.Y.) · 2022Article
- Development of a standards-based phenotype model for gross motor function to support learning health systems in pediatric rehabilitation.Learning health systems · 2022Article
- A refined methodology for validation of information models derived from flowsheet data and applied to a genitourinary case.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Machine Learned Mapping of Local EHR Flowsheet Data to Standard Information Models using Topic Model Filtering.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2019Article
- Validation and Refinement of a Pain Information Model from EHR Flowsheet Data.Applied clinical informatics · 2018Observational
- Improving Documentation of Postdischarge Issue Mitigation during Postdischarge Phone Calls.Pediatric quality & safetyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
The purpose of this study was to create information models from flowsheet data using a data-driven consensus-based method. Electronic health records contain a large volume of data about patient assessments and interventions captured in flowsheets that measure the same "thing," but the names of these observations often differ, according to who performs documentation or the location of the service (eg, pulse rate in an intensive care, the emergency department, or a surgical unit documented by a nurse or therapist or captured by automated monitoring). Flowsheet data are challenging for secondary use because of the existence of multiple semantically equivalent measures representing the same concepts. Ten information models were created in this study: five related to quality measures (falls, pressure ulcers, venous thromboembolism, genitourinary system including catheter-associated urinary tract infection, and pain management) and five high-volume physiological systems: cardiac, gastrointestinal, musculoskeletal, respiratory, and expanded vital signs/anthropometrics. The value of the information models is that flowsheet data can be extracted and mapped for semantically comparable flowsheet measures from a clinical data repository regardless of the time frame, discipline, or setting in which documentation occurred. The 10 information models simplify the representation of the content in flowsheet data, reducing 1552 source measures to 557 concepts. The amount of representational reduction ranges from 3% for falls to 78% for the respiratory system. The information models provide a foundation for including nursing and interprofessional assessments and interventions in common data models, to support research within and across health systems.
Indexed as
Identifiers
What 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.