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dc.contributor.authorShwartz, Michael
dc.contributor.authorIezzoni, Lisa I.
dc.contributor.authorMoskowitz, Mark A.
dc.contributor.authorAsh, Arlene S.
dc.contributor.authorSawitz, Eric
dc.date2022-08-11T08:10:41.000
dc.date.accessioned2022-08-23T17:16:57Z
dc.date.available2022-08-23T17:16:57Z
dc.date.issued1996-08-01
dc.date.submitted2010-07-01
dc.identifier.citationMed Care. 1996 Aug;34(8):767-82. <a href="http://journals.lww.com/lww-medicalcare/Abstract/1996/08000/The_Importance_of_Comorbidities_in_Explaining.5.aspx">Link to article on publisher's site</a>
dc.identifier.issn0025-7079 (Linking)
dc.identifier.pmid8709659
dc.identifier.urihttp://hdl.handle.net/20.500.14038/47517
dc.description.abstractOBJECTIVES: The authors examine to what extent comorbidities contribute to differences in patient hospital costs. METHODS: The medical record data for this study were collected from 15 metropolitan Boston hospital for 4,439 patients admitted mostly in 1985 for one of eight common conditions. Massachusetts hospital discharge abstract data for 1985 and 1993 also were used. Comorbidities were identified from the medical record for the 15-hospital data set and from discharge abstracts for all cases. Stepwise regression models were used to develop comorbidity scores. RESULTS: Across all conditions, the medical record-based comorbidity score increased the R2 value from .42 in a model with diagnosis-related groups alone to .50. In condition-specific analyses, including the comorbidity score increased the R2 by more than 50% in six of eight conditions, and was more important than several other dimensions of severity in explaining condition-specific costs. When comorbidities were determined from discharge abstract data rather than medical records, only approximately half as much comorbidity was found. Also, there was much less explanatory power: the all-condition R2 only went from .42 to .44. However, a comorbidity score developed from statewide hospital discharge abstract data was more useful in explaining variations in charges in the eight condition-specific analyses conducted on patients 65 years and older. CONCLUSIONS: Comorbidities, particularly when determined from the medical record, are important determinants of patient costs.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=8709659&dopt=Abstract">Link to Article in PubMed</a>
dc.relation.urlhttp://journals.lww.com/lww-medicalcare/Abstract/1996/08000/The_Importance_of_Comorbidities_in_Explaining.5.aspx
dc.subjectAdolescent
dc.subjectAdult
dc.subjectAged
dc.subjectBias (Epidemiology)
dc.subjectBoston
dc.subject*Comorbidity
dc.subjectHealth Services Research
dc.subject*Hospital Costs
dc.subjectHospitals, Urban
dc.subjectHumans
dc.subjectMedical Records
dc.subjectMiddle Aged
dc.subjectPatient Discharge
dc.subjectPredictive Value of Tests
dc.subjectRegression Analysis
dc.subjectReproducibility of Results
dc.subjectSeverity of Illness Index
dc.subjectBiostatistics
dc.subjectEpidemiology
dc.subjectHealth Services Research
dc.titleThe importance of comorbidities in explaining differences in patient costs
dc.typeJournal Article
dc.source.journaltitleMedical care
dc.source.volume34
dc.source.issue8
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/qhs_pp/653
dc.identifier.contextkey1378799
html.description.abstract<p>OBJECTIVES: The authors examine to what extent comorbidities contribute to differences in patient hospital costs.</p> <p>METHODS: The medical record data for this study were collected from 15 metropolitan Boston hospital for 4,439 patients admitted mostly in 1985 for one of eight common conditions. Massachusetts hospital discharge abstract data for 1985 and 1993 also were used. Comorbidities were identified from the medical record for the 15-hospital data set and from discharge abstracts for all cases. Stepwise regression models were used to develop comorbidity scores.</p> <p>RESULTS: Across all conditions, the medical record-based comorbidity score increased the R2 value from .42 in a model with diagnosis-related groups alone to .50. In condition-specific analyses, including the comorbidity score increased the R2 by more than 50% in six of eight conditions, and was more important than several other dimensions of severity in explaining condition-specific costs. When comorbidities were determined from discharge abstract data rather than medical records, only approximately half as much comorbidity was found. Also, there was much less explanatory power: the all-condition R2 only went from .42 to .44. However, a comorbidity score developed from statewide hospital discharge abstract data was more useful in explaining variations in charges in the eight condition-specific analyses conducted on patients 65 years and older.</p> <p>CONCLUSIONS: Comorbidities, particularly when determined from the medical record, are important determinants of patient costs.</p>
dc.identifier.submissionpathqhs_pp/653
dc.contributor.departmentDepartment of Quantitative Health Sciences
dc.source.pages767-82


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