The relative contribution of provider and ED-level factors to variation among the top 15 reasons for ED admission

Abstract Study objective We examine adult emergency department (ED) admission rates for the top 15 most frequently admitted conditions, and assess the relative contribution in admission rate variation attributable to the provider and hospital. Methods This was a retrospective, cross-sectional study...

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Veröffentlicht in:The American journal of emergency medicine 2017-09, Vol.35 (9), p.1291-1297
Hauptverfasser: Khojah, Imad, MD, Li, Suhui, PhD, Luo, Qian, Davis, Griffin, MD, MPH, MBA, Galarraga, Jessica E., MD, MPH, Granovsky, Michael, MD, Litvak, Ori, MBA, Davis, Samuel, Shesser, Robert, MD, MPH, Pines, Jesse M., MD, MBA, MSCE
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container_end_page 1297
container_issue 9
container_start_page 1291
container_title The American journal of emergency medicine
container_volume 35
creator Khojah, Imad, MD
Li, Suhui, PhD
Luo, Qian
Davis, Griffin, MD, MPH, MBA
Galarraga, Jessica E., MD, MPH
Granovsky, Michael, MD
Litvak, Ori, MBA
Davis, Samuel
Shesser, Robert, MD, MPH
Pines, Jesse M., MD, MBA, MSCE
description Abstract Study objective We examine adult emergency department (ED) admission rates for the top 15 most frequently admitted conditions, and assess the relative contribution in admission rate variation attributable to the provider and hospital. Methods This was a retrospective, cross-sectional study of ED encounters (≥ 18 years) from 19 EDs and 603 providers (January 2012–December 2013), linked to the Area Health Resources File for county-level information on healthcare resources. “Hospital admission” was the outcome, a composite of inpatient, observation, or intra-hospital transfer. We studied the 15 most commonly admitted conditions, and calculated condition-specific risk-standardized hospital admission rates (RSARs) using multi-level hierarchical generalized linear models. We then decomposed the relative contribution of provider-level and hospital-level variation for each condition. Results The top 15 conditions made up 34% of encounters and 49% of admissions. After adjustment, the eight conditions with the highest hospital-level variation were: 1) injuries, 2) extremity fracture (except hip fracture), 3) skin infection, 4) lower respiratory disease, 5) asthma/chronic obstructive pulmonary disease (A&C), 6) abdominal pain, 7) fluid/electrolyte disorders, and 8) chest pain. Hospital-level intra-class correlation coefficients (ICC) ranged from 0.042 for A&C to 0.167 for extremity fractures. Provider-level ICCs ranged from 0.026 for abdominal pain to 0.104 for chest pain. Several patient, hospital, and community factors were associated with admission rates, but these varied across conditions. Conclusion For different conditions, there were different contributions to variation at the hospital- and provider-level. These findings deserve consideration when designing interventions to optimize admission decisions and in value-based payment programs.
doi_str_mv 10.1016/j.ajem.2017.03.074
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Methods This was a retrospective, cross-sectional study of ED encounters (≥ 18 years) from 19 EDs and 603 providers (January 2012–December 2013), linked to the Area Health Resources File for county-level information on healthcare resources. “Hospital admission” was the outcome, a composite of inpatient, observation, or intra-hospital transfer. We studied the 15 most commonly admitted conditions, and calculated condition-specific risk-standardized hospital admission rates (RSARs) using multi-level hierarchical generalized linear models. We then decomposed the relative contribution of provider-level and hospital-level variation for each condition. Results The top 15 conditions made up 34% of encounters and 49% of admissions. After adjustment, the eight conditions with the highest hospital-level variation were: 1) injuries, 2) extremity fracture (except hip fracture), 3) skin infection, 4) lower respiratory disease, 5) asthma/chronic obstructive pulmonary disease (A&amp;C), 6) abdominal pain, 7) fluid/electrolyte disorders, and 8) chest pain. Hospital-level intra-class correlation coefficients (ICC) ranged from 0.042 for A&amp;C to 0.167 for extremity fractures. Provider-level ICCs ranged from 0.026 for abdominal pain to 0.104 for chest pain. Several patient, hospital, and community factors were associated with admission rates, but these varied across conditions. Conclusion For different conditions, there were different contributions to variation at the hospital- and provider-level. These findings deserve consideration when designing interventions to optimize admission decisions and in value-based payment programs.</description><identifier>ISSN: 0735-6757</identifier><identifier>EISSN: 1532-8171</identifier><identifier>DOI: 10.1016/j.ajem.2017.03.074</identifier><identifier>PMID: 28410917</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adolescent ; Adult ; Age ; Asthma ; Chest ; Chronic infection ; Chronic obstructive pulmonary disease ; Codes ; Comorbidity ; Correlation coefficient ; Correlation coefficients ; Cost control ; Cross-Sectional Studies ; Economic indicators ; Emergencies - epidemiology ; Emergency ; Emergency medical care ; Emergency medical services ; Emergency Service, Hospital - statistics &amp; numerical data ; Expenditures ; Female ; Fractures ; Fractures, Bone - epidemiology ; Generalized linear models ; Health care policy ; Health Resources ; Hip ; Hospitals ; Humans ; Infections ; Lung diseases ; Male ; Medicaid ; Medicare ; Middle Aged ; Obstructive lung disease ; Pain ; Patient Admission - statistics &amp; numerical data ; Patient admissions ; Pediatrics ; Pneumonia ; Respiratory diseases ; Retrospective Studies ; Skin Diseases, Infectious - epidemiology ; Trauma ; United States ; Wounds and Injuries - epidemiology ; Young Adult</subject><ispartof>The American journal of emergency medicine, 2017-09, Vol.35 (9), p.1291-1297</ispartof><rights>2017 Elsevier Inc.</rights><rights>Copyright © 2017 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c439t-6306be6acf6d2fea461730eba4ac15897c2419f28cc0912622bcf75d6d8509533</citedby><cites>FETCH-LOGICAL-c439t-6306be6acf6d2fea461730eba4ac15897c2419f28cc0912622bcf75d6d8509533</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1945871183?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,777,781,3537,27905,27906,45976,64364,64366,64368,72218</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28410917$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Khojah, Imad, MD</creatorcontrib><creatorcontrib>Li, Suhui, PhD</creatorcontrib><creatorcontrib>Luo, Qian</creatorcontrib><creatorcontrib>Davis, Griffin, MD, MPH, MBA</creatorcontrib><creatorcontrib>Galarraga, Jessica E., MD, MPH</creatorcontrib><creatorcontrib>Granovsky, Michael, MD</creatorcontrib><creatorcontrib>Litvak, Ori, MBA</creatorcontrib><creatorcontrib>Davis, Samuel</creatorcontrib><creatorcontrib>Shesser, Robert, MD, MPH</creatorcontrib><creatorcontrib>Pines, Jesse M., MD, MBA, MSCE</creatorcontrib><title>The relative contribution of provider and ED-level factors to variation among the top 15 reasons for ED admission</title><title>The American journal of emergency medicine</title><addtitle>Am J Emerg Med</addtitle><description>Abstract Study objective We examine adult emergency department (ED) admission rates for the top 15 most frequently admitted conditions, and assess the relative contribution in admission rate variation attributable to the provider and hospital. Methods This was a retrospective, cross-sectional study of ED encounters (≥ 18 years) from 19 EDs and 603 providers (January 2012–December 2013), linked to the Area Health Resources File for county-level information on healthcare resources. “Hospital admission” was the outcome, a composite of inpatient, observation, or intra-hospital transfer. We studied the 15 most commonly admitted conditions, and calculated condition-specific risk-standardized hospital admission rates (RSARs) using multi-level hierarchical generalized linear models. We then decomposed the relative contribution of provider-level and hospital-level variation for each condition. Results The top 15 conditions made up 34% of encounters and 49% of admissions. After adjustment, the eight conditions with the highest hospital-level variation were: 1) injuries, 2) extremity fracture (except hip fracture), 3) skin infection, 4) lower respiratory disease, 5) asthma/chronic obstructive pulmonary disease (A&amp;C), 6) abdominal pain, 7) fluid/electrolyte disorders, and 8) chest pain. Hospital-level intra-class correlation coefficients (ICC) ranged from 0.042 for A&amp;C to 0.167 for extremity fractures. Provider-level ICCs ranged from 0.026 for abdominal pain to 0.104 for chest pain. Several patient, hospital, and community factors were associated with admission rates, but these varied across conditions. Conclusion For different conditions, there were different contributions to variation at the hospital- and provider-level. These findings deserve consideration when designing interventions to optimize admission decisions and in value-based payment programs.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Age</subject><subject>Asthma</subject><subject>Chest</subject><subject>Chronic infection</subject><subject>Chronic obstructive pulmonary disease</subject><subject>Codes</subject><subject>Comorbidity</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Cost control</subject><subject>Cross-Sectional Studies</subject><subject>Economic indicators</subject><subject>Emergencies - epidemiology</subject><subject>Emergency</subject><subject>Emergency medical care</subject><subject>Emergency medical services</subject><subject>Emergency Service, Hospital - statistics &amp; numerical data</subject><subject>Expenditures</subject><subject>Female</subject><subject>Fractures</subject><subject>Fractures, Bone - epidemiology</subject><subject>Generalized linear models</subject><subject>Health care policy</subject><subject>Health Resources</subject><subject>Hip</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Infections</subject><subject>Lung diseases</subject><subject>Male</subject><subject>Medicaid</subject><subject>Medicare</subject><subject>Middle Aged</subject><subject>Obstructive lung disease</subject><subject>Pain</subject><subject>Patient Admission - statistics &amp; 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Li, Suhui, PhD ; Luo, Qian ; Davis, Griffin, MD, MPH, MBA ; Galarraga, Jessica E., MD, MPH ; Granovsky, Michael, MD ; Litvak, Ori, MBA ; Davis, Samuel ; Shesser, Robert, MD, MPH ; Pines, Jesse M., MD, MBA, MSCE</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c439t-6306be6acf6d2fea461730eba4ac15897c2419f28cc0912622bcf75d6d8509533</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Age</topic><topic>Asthma</topic><topic>Chest</topic><topic>Chronic infection</topic><topic>Chronic obstructive pulmonary disease</topic><topic>Codes</topic><topic>Comorbidity</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Cost control</topic><topic>Cross-Sectional Studies</topic><topic>Economic indicators</topic><topic>Emergencies - epidemiology</topic><topic>Emergency</topic><topic>Emergency medical care</topic><topic>Emergency medical services</topic><topic>Emergency Service, Hospital - statistics &amp; 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Methods This was a retrospective, cross-sectional study of ED encounters (≥ 18 years) from 19 EDs and 603 providers (January 2012–December 2013), linked to the Area Health Resources File for county-level information on healthcare resources. “Hospital admission” was the outcome, a composite of inpatient, observation, or intra-hospital transfer. We studied the 15 most commonly admitted conditions, and calculated condition-specific risk-standardized hospital admission rates (RSARs) using multi-level hierarchical generalized linear models. We then decomposed the relative contribution of provider-level and hospital-level variation for each condition. Results The top 15 conditions made up 34% of encounters and 49% of admissions. After adjustment, the eight conditions with the highest hospital-level variation were: 1) injuries, 2) extremity fracture (except hip fracture), 3) skin infection, 4) lower respiratory disease, 5) asthma/chronic obstructive pulmonary disease (A&amp;C), 6) abdominal pain, 7) fluid/electrolyte disorders, and 8) chest pain. Hospital-level intra-class correlation coefficients (ICC) ranged from 0.042 for A&amp;C to 0.167 for extremity fractures. Provider-level ICCs ranged from 0.026 for abdominal pain to 0.104 for chest pain. Several patient, hospital, and community factors were associated with admission rates, but these varied across conditions. Conclusion For different conditions, there were different contributions to variation at the hospital- and provider-level. These findings deserve consideration when designing interventions to optimize admission decisions and in value-based payment programs.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>28410917</pmid><doi>10.1016/j.ajem.2017.03.074</doi><tpages>7</tpages></addata></record>
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subjects Adolescent
Adult
Age
Asthma
Chest
Chronic infection
Chronic obstructive pulmonary disease
Codes
Comorbidity
Correlation coefficient
Correlation coefficients
Cost control
Cross-Sectional Studies
Economic indicators
Emergencies - epidemiology
Emergency
Emergency medical care
Emergency medical services
Emergency Service, Hospital - statistics & numerical data
Expenditures
Female
Fractures
Fractures, Bone - epidemiology
Generalized linear models
Health care policy
Health Resources
Hip
Hospitals
Humans
Infections
Lung diseases
Male
Medicaid
Medicare
Middle Aged
Obstructive lung disease
Pain
Patient Admission - statistics & numerical data
Patient admissions
Pediatrics
Pneumonia
Respiratory diseases
Retrospective Studies
Skin Diseases, Infectious - epidemiology
Trauma
United States
Wounds and Injuries - epidemiology
Young Adult
title The relative contribution of provider and ED-level factors to variation among the top 15 reasons for ED admission
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