Assessing risk of hospital readmissions for improving medical practice

Health Care Management Science

Volumn 19, Issue 3, 2016, Pages 291-299

  Kulkarni, Parimal ^a   Smith, L Douglas ^b   Woeltje, Keith F ^c  

^a UNIVERSITY OF MISSOURI ST LOUIS   (United States)

^b UNIVERSITY OF MISSOURI ST LOUIS   (United States)

^c WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Decision trees; Healthcare analytics; Neural networks; Readmissions; Regression

Indexed keywords

AGE; AGED; ARTIFICIAL NEURAL NETWORK; DECISION TREE; ENVIRONMENT; HEALTH INSURANCE; HOSPITAL BED CAPACITY; HOSPITAL DISCHARGE; HOSPITAL READMISSION; HUMAN; LENGTH OF STAY; MEDICINE; MIDDLE AGED; RISK ASSESSMENT; RISK FACTOR; SEVERITY OF ILLNESS INDEX; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

AGE FACTORS; AGED; DECISION TREES; ENVIRONMENT; HOSPITAL BED CAPACITY; HUMANS; INSURANCE, HEALTH; LENGTH OF STAY; LOGISTIC MODELS; MEDICINE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); PATIENT DISCHARGE; PATIENT READMISSION; RISK ASSESSMENT; RISK FACTORS; SEVERITY OF ILLNESS INDEX;

EID: 84927945803     PISSN: 13869620     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10729-015-9323-5     Document Type: Article

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