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Article: Analyzing hospital length of stay mean or median regression?

TitleAnalyzing hospital length of stay mean or median regression?
Authors
Issue Date2003
PublisherLippincott Williams & Wilkins. The Journal's web site is located at http://www.lww-medicalcare.com
Citation
Medical Care, 2003, v. 41 n. 5, p. 681-686 How to Cite?
AbstractBACKGROUND. Length of stay (LOS) is an important measure of hospital activity and health care utilization, but its empirical distribution is often positively skewed. OBJECTIVE. This study reviews the mean and median regression approaches for analyzing LOS, which have implications for service planning, resource allocation, and bed utilization. METHODS. The two approaches are applied to analyze hospital discharge data on cesarean delivery. Both models adjust for patient and health-related characteristics, and for the dependency of LOS outcomes nested within hospitals. The estimation methods are also compared in a simulation study. RESULTS. For the empirical application, the mean regression results are somewhat sensilive to the magnitude of trimming chosen. The identified factors from median regression, namely number of diagnoses, number of procedures, and payment classification, are robust to high-LOS outliers. The simulation experiment shows that median regression can outperform mean regression even when the response variable is moderately positively skewed. CONCLUSION. Median regression appears to be a suitable alternative to analyze the clustered and positively skewed LOS, without transforming and trimming the data arbitrarily. © 2003 Lippincott Williams & Wilkins, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/172400
ISSN
2015 Impact Factor: 3.081
2015 SCImago Journal Rankings: 2.004
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLee, AHen_US
dc.contributor.authorFung, WKen_US
dc.contributor.authorFu, Ben_US
dc.date.accessioned2012-10-30T06:22:20Z-
dc.date.available2012-10-30T06:22:20Z-
dc.date.issued2003en_US
dc.identifier.citationMedical Care, 2003, v. 41 n. 5, p. 681-686en_US
dc.identifier.issn0025-7079en_US
dc.identifier.urihttp://hdl.handle.net/10722/172400-
dc.description.abstractBACKGROUND. Length of stay (LOS) is an important measure of hospital activity and health care utilization, but its empirical distribution is often positively skewed. OBJECTIVE. This study reviews the mean and median regression approaches for analyzing LOS, which have implications for service planning, resource allocation, and bed utilization. METHODS. The two approaches are applied to analyze hospital discharge data on cesarean delivery. Both models adjust for patient and health-related characteristics, and for the dependency of LOS outcomes nested within hospitals. The estimation methods are also compared in a simulation study. RESULTS. For the empirical application, the mean regression results are somewhat sensilive to the magnitude of trimming chosen. The identified factors from median regression, namely number of diagnoses, number of procedures, and payment classification, are robust to high-LOS outliers. The simulation experiment shows that median regression can outperform mean regression even when the response variable is moderately positively skewed. CONCLUSION. Median regression appears to be a suitable alternative to analyze the clustered and positively skewed LOS, without transforming and trimming the data arbitrarily. © 2003 Lippincott Williams & Wilkins, Inc.en_US
dc.languageengen_US
dc.publisherLippincott Williams & Wilkins. The Journal's web site is located at http://www.lww-medicalcare.comen_US
dc.relation.ispartofMedical Careen_US
dc.rightsMedical Care. Copyright © Lippincott Williams & Wilkins.-
dc.subject.meshCesarean Section - Statistics & Numerical Dataen_US
dc.subject.meshData Interpretation, Statisticalen_US
dc.subject.meshFemaleen_US
dc.subject.meshHealth Services Research - Methodsen_US
dc.subject.meshHumansen_US
dc.subject.meshLength Of Stay - Statistics & Numerical Dataen_US
dc.subject.meshOutliers, Drgen_US
dc.subject.meshPregnancyen_US
dc.subject.meshRegression Analysisen_US
dc.subject.meshUnited Statesen_US
dc.subject.meshUtilization Review - Methodsen_US
dc.titleAnalyzing hospital length of stay mean or median regression?en_US
dc.typeArticleen_US
dc.identifier.emailFung, WK: wingfung@hku.hken_US
dc.identifier.authorityFung, WK=rp00696en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1097/00005650-200305000-00015en_US
dc.identifier.pmid12719692-
dc.identifier.scopuseid_2-s2.0-0037980150en_US
dc.identifier.hkuros90701-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0037980150&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume41en_US
dc.identifier.issue5en_US
dc.identifier.spage681en_US
dc.identifier.epage686en_US
dc.identifier.isiWOS:000182695900016-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridLee, AH=26643271800en_US
dc.identifier.scopusauthoridFung, WK=13310399400en_US
dc.identifier.scopusauthoridFu, B=35957954300en_US

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