title: Developing a Bayesian belief network for the management of geriatric hospital care.
abstract: Resource management is an essential feature of hospital management. This is especially true for geriatric services, as older people often have complex medical and social needs. Hospital management should benefit from an explanatory model that provides predictions of duration of stay and destination on discharge. We describe how a Bayesian belief network models the behaviour of geriatric patients using predictive variables: personal details, admission reasons and dependency levels. This approach is illustrated using data on 4,722 patients admitted to geriatric medicine at St. George's Hospital, London; distributions of the patient outcome given typical values of the predictive variables are provided.
authors.affiliation: School of Information and Software Engineering, Faculty of Informatics, University of Ulster, Northern Ireland. AH.Marshall@ulst.ac.uk
authors.forename: A H
authors.initials: AH
authors.lastname: Marshall
authors.forename: S I
authors.initials: SI
authors.lastname: McClean
authors.forename: C M
authors.initials: CM
authors.lastname: Shapcott
authors.forename: I R
authors.initials: IR
authors.lastname: Hastie
authors.forename: P H
authors.initials: PH
authors.lastname: Millard
mesh_terms: D000368:Aged; D001499:Bayes Theorem; D015984:Causality; D015577:Geriatric Assessment / Q000706:statistics & numerical data*; D006779:Hospitals, Public / Q000458:organization & administration / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008131:London; D010043:Outcome and Process Assessment, Health Care; D010351:Patient Discharge; D012984:Software