Evidence map›Paper›PMID 27364030›Full record

ArticleSouthern medical journal2016

A Comprehensive View of Frequent Emergency Department Users Based on Data from a Regional HIE.

Steven Howard Saef, Christine Marie Carr, Jeffrey S Bush, Marc T Bartman, Adam B Sendor, Wenle Zhao, Zemin Su, Jingwen Zhang, Justin Marsden, J Christophe Arnaud and 5 more

Abstract read
In one paragraph

Article in Southern medical journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Relationships Between Race/Ethnicity and Health Care Utilization Among Older Post-Acute Home Health Care Patients.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2020
    Article
  6. Article
  7. Emergency Department Utilization among Underserved African American Older Adults in South Los Angeles.International journal of environmental research and public health · 2019
    Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Steven Howard SaefFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Christine Marie CarrFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Jeffrey S BushFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Marc T BartmanFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Adam B SendorFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Wenle ZhaoFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Zemin SuFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Jingwen ZhangFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Justin MarsdenFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
J Christophe ArnaudFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Cathy L MelvinFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Leslie LenertFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
William P MoranFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Patrick D MauldinFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
Jihad S ObeidFrom the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.

Funding

South Carolina Clinical & Translational Research Institute (SCTR)UL1TR001450 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T., FLUME, PATRICK A · 2015 to 2024
$41.1M
South Carolina Clinical & Translational Research Institute (SCTR)UL1TR000062 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T. · 2012 to 2014
$9.4M
NCATS NIH HHS UL1 TR000062NCATS NIH HHS UL1 TR001450
6 · The paper itself

Abstract

objectivesA small but significant number of patients make frequent emergency department (ED) visits to multiple EDs within a region. We have a unique health information exchange (HIE) that includes every ED encounter in all hospital systems in our region. Using our HIE we were able to characterize all frequent ED users in our region, regardless of hospital visited or payer class. The objective of our study was to use data from an HIE to characterize patients in a region who are frequent ED users (FEDUs).

methodsWe constructed a database from a cohort of adult patients (18 years old or older) with information in a regional HIE for a 1-year period beginning in April 2012. Patients were defined as FEDUs (those who made four or more visits during the study period) and non-FEDUs (those who made fewer than four ED visits during the study period). Predictor variables included age, race, sex, payer class, county of residence, and International Classification of Diseases, Ninth Revision codes. Bivariate (χ(2)) and multivariate (logistic regression) analyses were performed to determine associations between predictor variables and the outcome of being a FEDU.

resultsThe database contained 127,672 patients, 12,293 (9.6%) of whom were FEDUs. Logistic regression showed the following patient characteristics to be significantly associated with the outcome of being a FEDU: age 35 to 44 years; African American race; Medicaid, Medicare, and dual-pay payer class; and International Classification of Diseases, Ninth Revision codes 630 to 679 (complications of pregnancy, childbirth, and puerperium), 780 to 799 (ill-defined conditions), 280 to 289 (diseases of the blood), 290-319 (mental disorders), 680 to 709 (diseases of the skin and subcutaneous tissue), 710 to 739 (musculoskeletal and connective tissue disease), 460 to 519 (respiratory disease), and 520 to 579 (digestive disease). No significant differences were noted between men and women.

conclusionsData from an HIE can be used to describe all of the patients within a region who are FEDUs, regardless of the hospital system they visited. This information can be used to focus care coordination efforts and link appropriate patients to a medical home. Future studies can be designed to learn the reasons why patients become FEDUs, and interventions can be developed to address deficiencies in health care that result in frequent ED visits.

Indexed as

Health Information ExchangeAdultAge FactorsEmergency Service, HospitalEthnicityFemaleHumansInternational Classification of DiseasesMaleMedical OveruseMedical Record LinkageMental DisordersPatient Identification SystemsPregnancyPregnancy ComplicationsSouth Carolina

Identifiers

PMID27364030
PMCPMC4933324

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.