ArticleBMC medical informatics and decision making2021
EMS utilization predictors in a Mobile Integrated Health (MIH) program.
Article in BMC medical informatics and decision making, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed, 5 citations in OpenAlex.
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe provision of unnecessary Emergency Medical Services care remains a challenge throughout the US and contributes to Emergency Department overcrowding, delayed services and lower quality of care. New EMS models of care have shown promise in improving access to health services for patients who do not need urgent care. The goals of this study were (1) to identify factors associated with EMS utilization (911) and (2) their effects on total EMS calls and transports in an MIH program.
methodsThe study sample included 110 MIH patients referred to the program or considered high-users of EMS services between November 2016 and September 2018. The study employed descriptive statistics and Poisson regressions to estimate the effects of covariates on total EMS calls and transports.
resultsThe typical enrollee is a 60-year-old single Black male living with two other individuals. He has a PCP, takes 12 medications and is compliant with his treatment. The likelihood of calling and/or being transported by EMS was higher for males, patients at high risk for falls, patients with asthma/COPD, psychiatric or behavioral illnesses, and longer travel times to a PCP. Each prescribed medication increased the risk for EMS calls or transports by 4%. The program achieved clear reductions in 911 calls and transports and savings of more than 140,000 USD in the first month.
conclusionsThis study shows that age, marital status, high fall risk scores, the number of medications, psychiatric/behavioral illness, asthma/COPD, CHF, CVA/stroke and medication compliance may be good predictors of EMS use in an MIH setting. MIH programs can help control utilization of EMS care and reduce both EMS calls and transports.
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