ArticlePerspectives in health information managemen2016
Developing Methods of Repurposing Electronic Health Record Data for Identification of Older Adults at Risk of Unintentional Falls.
Article in Perspectives in health information managemen, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The use of Electronic Health Records to Support Population Health: A Systematic Review of the Literature.Journal of medical systems · 2018Pooled it
- Development and Internal Validation of a Risk Prediction Model for Falls Among Older People Using Primary Care Electronic Health Records.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022Article
- Potentially inappropriate medications and their effect on falls during hospital admission.Age and ageing · 2022Observational
- Using Health Information Technology to Create Pathways for Hepatitis C Treatment and Cure in West Virginia.Perspectives in health information managemen · 2022Article
- Screening for elder mistreatment in emergency departments: current progress and recommendations for next steps.Journal of elder abuse & neglect · 2020Article
- An Electronic Health Record Data-driven Model for Identifying Older Adults at Risk of Unintentional Falls.Perspectives in health information managemen · 2017Article
- "Salt in the Wound": Safety Net Clinician Perspectives on Performance Feedback Derived From EHR Data.The Journal of ambulatory care managementArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Nationally, nearly 40 percent of community-dwelling adults age 65 and older fall at least once a year, making unintentional falls the leading cause of both fatal and nonfatal injuries among this age group. Addressing this public health problem in primary care offers promise. However, challenges in incorporating fall risk screening into primary care result in a problem of missed opportunities for screening, counseling, intervention, and ultimately prevention. Given these barriers, this study examines the potential for the innovative use of routinely collected electronic health record data to provide enhanced clinical decision support in busy, often resource-thin primary care environments. Using de-identified data from a sample of West Virginia primary care centers, we find that it is both feasible and worthwhile to repurpose routinely collected data for the purpose of identification of older adults at risk of falls. Searching of both free-text and semistructured data was particularly valuable.
Indexed as
Identifiers
27134607PMC4832126What 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.