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dc.contributor.authorIezzoni, Lisa I.
dc.contributor.authorShwartz, Michael
dc.contributor.authorAsh, Arlene S.
dc.contributor.authorMackiernan, Yevgenia D.
dc.date2022-08-11T08:10:41.000
dc.date.accessioned2022-08-23T17:16:55Z
dc.date.available2022-08-23T17:16:55Z
dc.date.issued1996-01-01
dc.date.submitted2010-07-01
dc.identifier.citationJ Gen Intern Med. 1996 Jan;11(1):23-31. <a href="http://dx.doi.org/10.1007/BF02603481">Link to article on publisher's site</a>
dc.identifier.issn0884-8734 (Linking)
dc.identifier.doi10.1007/BF02603481
dc.identifier.pmid8691283
dc.identifier.urihttp://hdl.handle.net/20.500.14038/47509
dc.description.abstractOBJECTIVE: To see whether predictions of patients, likelihood of dying in-hospital differed among severity methods. DESIGN: Retrospective cohort. PATIENTS: 18,016 persons 18 years of age and older managed medically for pneumonia; 1,732 (9.6%) in-hospital deaths. METHODS: Probability of death was calculated for each patient using logistic regression with age, age squared, sex, and each of five severity measures as the independent variables: 1) admission MedisGroups probability of death scores; 2) scores based on 17 admission physiologic variables; 3) Disease Staging's probability of mortality model; the Severity Score of Patient Management Categories (PMCs); 4) and the All Patient Refined Diagnosis-Related Groups (APR-DRGs). Patients were ranked by calculated probability of death; 5) rankings were compared across severity methods. Frequencies of 14 clinical findings considered poor prognostic indicators in pneumonia were examined for patients ranked differently by different methods. RESULTS: MedisGroups and the physiology score predicted a similar likelihood of death for 89.2% of patients. In contrast, the three code-based severity methods rated over 25% of patients differently by predicted likelihood of death when compared with the rankings of the two clinical data-based methods [MedisGroups and the physiology score]. MedisGroups and the physiology score demonstrated better clinical credibility than the three severity methods based on discharge abstract data. CONCLUSIONS: Some pairs of severity measures ranked over 25% of patients very differently by predicted probability of death. Results of outcomes studies may vary depending on which severity method is used for risk adjustment.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=8691283&dopt=Abstract">Link to Article in PubMed</a>
dc.relation.urlhttp://dx.doi.org/10.1007/BF02603481
dc.subjectAdolescent
dc.subjectAdult
dc.subjectAged
dc.subjectAged, 80 and over
dc.subjectCohort Studies
dc.subjectFemale
dc.subject*Hospital Mortality
dc.subjectHumans
dc.subjectLogistic Models
dc.subjectMale
dc.subjectMiddle Aged
dc.subjectOutcome Assessment (Health Care)
dc.subjectPneumonia
dc.subjectProbability
dc.subjectRetrospective Studies
dc.subject*Severity of Illness Index
dc.subjectSurvival Rate
dc.subjectUnited States
dc.subjectBiostatistics
dc.subjectEpidemiology
dc.subjectHealth Services Research
dc.titleUsing severity measures to predict the likelihood of death for pneumonia inpatients
dc.typeJournal Article
dc.source.journaltitleJournal of general internal medicine
dc.source.volume11
dc.source.issue1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/qhs_pp/644
dc.identifier.contextkey1378790
html.description.abstract<p>OBJECTIVE: To see whether predictions of patients, likelihood of dying in-hospital differed among severity methods.</p> <p>DESIGN: Retrospective cohort.</p> <p>PATIENTS: 18,016 persons 18 years of age and older managed medically for pneumonia; 1,732 (9.6%) in-hospital deaths.</p> <p>METHODS: Probability of death was calculated for each patient using logistic regression with age, age squared, sex, and each of five severity measures as the independent variables: 1) admission MedisGroups probability of death scores; 2) scores based on 17 admission physiologic variables; 3) Disease Staging's probability of mortality model; the Severity Score of Patient Management Categories (PMCs); 4) and the All Patient Refined Diagnosis-Related Groups (APR-DRGs). Patients were ranked by calculated probability of death; 5) rankings were compared across severity methods. Frequencies of 14 clinical findings considered poor prognostic indicators in pneumonia were examined for patients ranked differently by different methods.</p> <p>RESULTS: MedisGroups and the physiology score predicted a similar likelihood of death for 89.2% of patients. In contrast, the three code-based severity methods rated over 25% of patients differently by predicted likelihood of death when compared with the rankings of the two clinical data-based methods [MedisGroups and the physiology score]. MedisGroups and the physiology score demonstrated better clinical credibility than the three severity methods based on discharge abstract data.</p> <p>CONCLUSIONS: Some pairs of severity measures ranked over 25% of patients very differently by predicted probability of death. Results of outcomes studies may vary depending on which severity method is used for risk adjustment.</p>
dc.identifier.submissionpathqhs_pp/644
dc.contributor.departmentDepartment of Quantitative Health Sciences
dc.source.pages23-31


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