EMS utilization predictors in a Mobile Integrated Health (MIH) program: A retrospective analysis

dc.contributorFrankel, Brian
dc.contributor.authorPeralta, Luis Mauricio Pinet
dc.contributor.authorSanna, Evan
dc.contributor.authorFrankel, Brian
dc.contributor.authorLindqvist, Ernest
dc.contributor.authorGlos, Lukas
dc.date.accessioned2020-08-06T16:58:22Z
dc.date.available2020-08-06T16:58:22Z
dc.date.issued2020-07-08
dc.description.abstractAbstract Background. The provision of unnecessary Emergency Medical Services (EMS) care remains a challenge throughout the US and contributes to ER 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. Methods. The study sample included 110 MIH patients referred to the program or considered high-users of EMS services between November 2016-September 2018. The study employed descriptive statistics and Poisson regression to estimate the effects of covariates on total EMS calls and transports. Results. The typical enrollee is a 60-year old single African-American 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%. Conclusions. This 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.en_US
dc.description.urihttps://www.researchsquare.com/article/rs-38384/v1en_US
dc.format.extent18 pagesen_US
dc.genrejournal articles preprintsen_US
dc.identifierdoi:10.13016/m27qb7-vbxd
dc.identifier.citationPeralta, Luis Mauricio Pinet; Sanna, Evan; Frankel, Brian; Lindqvist, Ernest; Glos, Lukas; EMS utilization predictors in a Mobile Integrated Health (MIH) program: A retrospective analysis; BMC Medical Informatics and Decision Making (2020); https://www.researchsquare.com/article/rs-38384/v1en_US
dc.identifier.urihttps://doi.org/10.21203/rs.3.rs-38384/v1
dc.identifier.urihttp://hdl.handle.net/11603/19358
dc.language.isoen_USen_US
dc.publisherResearch Squareen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC School of Public Policy Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rightsAttribution 4.0 International (CC BY 4.0)*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.titleEMS utilization predictors in a Mobile Integrated Health (MIH) program: A retrospective analysisen_US
dc.typeTexten_US

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