ArticleJournal of the American Medical Informatics Association : JAMIA2014
The impact of electronic health records on people with diabetes in three different emergency departments.
Article in Journal of the American Medical Informatics Association : JAMIA, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 20 citations in OpenAlex.
- Trial
- Count data models for outpatient health services utilisation.BMC medical research methodology · 2022Article
- [Information on medical history in the emergency department : Influence on therapy and diagnostic decisions].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2021Observational
- Physician Use of Electronic Health Records: Survey Study Assessing Factors Associated With Provider Reported Satisfaction and Perceived Patient Impact.JMIR medical informatics · 2019Article
- Electronic health record phenotyping improves detection and screening of type 2 diabetes in the general United States population: A cross-sectional, unselected, retrospective study.Journal of biomedical informatics · 2016Article
- How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use.Journal of the American Medical Informatics Association : JAMIAArticle
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
Abstract
objectiveTo evaluate if electronic health records (EHR) with prior clinical information have observable effects for patients with diabetes presenting to emergency departments (ED), we examined measures of quality and resource utilization. MATERIALS AND
methodsRetrospective observational studies of patients in three ED (A=5510; B=4393; C=3324) were conducted comparing patients with prior information in the EHR to those without such information. Differences with respect to hospitalization, mortality, length of stay (LOS), and numbers of ED orders for tests, procedures and medications were examined after adjusting for age, gender, race, marital status, comorbidities and for acuity level within each ED.
resultsThere were 7% fewer laboratory test orders at one ED and 3% fewer at another; fewer diagnostic procedures were performed at two of the sites. At one site 36% fewer medications were ordered. The odds of being hospitalized were lower for EHR patients at one site and hospital LOS was shorter at two of the sites. EHR patient ED LOS was 18% longer at one site. There was no demonstrable impact of an EHR on mortality. Results varied in magnitude and direction by site. DISCUSSION: The pattern of significant results varied by ED but tended to reveal reduced utilization and better outcomes for patients although EHR patients' ED LOS was longer at one site.
conclusionsThe presence of prior information in an EHR may be a valuable adjunct in the care of diabetes patients in ED settings but the pattern of impact may vary from ED to ED.
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.