Roles of disease severity and post-discharge outpatient visits as predictors of hospital readmissions

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dc.creatorWang, Hao
dc.creatorJohnson, Carol
dc.creatorRobinson, Richard D.
dc.creatorNejtek, Vicki A.
dc.creatorSchrader, Chet D.
dc.creatorLeuck, JoAnna
dc.creatorUmejiego, Johnbosco
dc.creatorTrop, Allison
dc.creatorDelaney, Kathleen A.
dc.creatorZenarosa, Nestor R.
dc.creator.orcid0000-0001-6935-1739 (Nejtek, Vicki A.)
dc.date.accessioned2022-10-14T14:32:33Z
dc.date.available2022-10-14T14:32:33Z
dc.date.issued2016-10-10
dc.description.abstractBACKGROUND: Risks prediction models of 30-day all-cause hospital readmissions are multi-factorial. Severity of illness (SOI) and risk of mortality (ROM) categorized by All Patient Refined Diagnosis Related Groups (APR-DRG) seem to predict hospital readmission but lack large sample validation. Effects of risk reduction interventions including providing post-discharge outpatient visits remain uncertain. We aim to determine the accuracy of using SOI and ROM to predict readmission and further investigate the role of outpatient visits in association with hospital readmission. METHODS: Hospital readmission data were reviewed retrospectively from September 2012 through June 2015. Patient demographics and clinical variables including insurance type, homeless status, substance abuse, psychiatric problems, length of stay, SOI, ROM, ICD-10 diagnoses and medications prescribed at discharge, and prescription ratio at discharge (number of medications prescribed divided by number of ICD-10 diagnoses) were analyzed using logistic regression. Relationships among SOI, type of hospital visits, time between hospital visits, and readmissions were also investigated. RESULTS: A total of 6011 readmissions occurred from 55,532 index admissions. The adjusted odds ratios of SOI and ROM predicting readmissions were 1.31 (SOI: 95 % CI 1.25-1.38) and 1.09 (ROM: 95 % CI 1.05-1.14) separately. Ninety percent (5381/6011) of patients were readmitted from the Emergency Department (ED) or Urgent Care Center (UCC). Average time interval from index discharge date to ED/UCC visit was 9 days in both the no readmission and readmission groups (p > 0.05). Similar hospital readmission rates were noted during the first 10 days from index discharge regardless of whether post-index discharge patient clinic visits occurred when time-to-event analysis was performed. CONCLUSIONS: SOI and ROM significantly predict hospital readmission risk in general. Most readmissions occurred among patients presenting for ED/UCC visits after index discharge. Simply providing early post-discharge follow-up clinic visits does not seem to prevent hospital readmissions.
dc.identifier.citationWang, H., Johnson, C., Robinson, R. D., Nejtek, V. A., Schrader, C. D., Leuck, J., Umejiego, J., Trop, A., Delaney, K. A., & Zenarosa, N. R. (2016). Roles of disease severity and post-discharge outpatient visits as predictors of hospital readmissions. BMC health services research, 16(1), 564. https://doi.org/10.1186/s12913-016-1814-7
dc.identifier.issn1472-6963
dc.identifier.issue1
dc.identifier.urihttps://hdl.handle.net/20.500.12503/31862
dc.identifier.volume16
dc.publisherBioMed Central Ltd.
dc.relation.urihttps://doi.org/10.1186/s12913-016-1814-7
dc.rights.holder© 2016 The Author(s).
dc.rights.licenseAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceBMC Health Services Research
dc.subjectapr-drg
dc.subjectHospital readmission
dc.subjectPost-discharge visit
dc.subjectPrediction
dc.subject.meshAdult
dc.subject.meshAftercare
dc.subject.meshAmbulatory Care / statistics & numerical data
dc.subject.meshDiagnosis-Related Groups
dc.subject.meshFemale
dc.subject.meshHomeless Persons
dc.subject.meshHumans
dc.subject.meshLogistic Models
dc.subject.meshMale
dc.subject.meshMiddle Aged
dc.subject.meshPatient Readmission / statistics & numerical data
dc.subject.meshRetrospective Studies
dc.subject.meshSeverity of Illness Index
dc.subject.meshSurvival Analysis
dc.titleRoles of disease severity and post-discharge outpatient visits as predictors of hospital readmissions
dc.typeArticle
dc.type.materialtext

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