Profile of hospitalised elderly patients in Belgium—Analysis of factors affecting hospital costs

• Published in: The journal of the economics of ageing Vol. 15; p. 100209
• Main Authors: De Foor, Julie, Senterre, Christelle, Leclercq, Pol, Martins, Dimitri, Pirson, Magali
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-02-2020
• Subjects: Administrative database; Elderly; Epidemiological description; Hospital; Hospital costs; Hospital length of stay; Old inpatients; Hospital costs; Administrative database; Epidemiological description; Hospital length of stay; Hospital; Elderly; Old inpatients
• ISSN: 2212-828X
• DOI: 10.1016/j.jeoa.2019.100209

The objectives of this research are (i) to describe the medicoadministrative profiles of inpatients aged 65 and over and (ii) to determine the main hospitalisation-related diseases in order (iii) to assess and identify predictors influencing hospital costs and lengths of stay thanks to data collected in hospital administrative databases.
The study is based on 45,469 hospital stays of inpatients aged 65 and over, with data collected among ten Belgian general hospitals in 2014. We conduct a linear regression in order to isolate factors influencing hospital costs and length of stay.
The mean length of stay (SD) for older patients (65+) is 11 days (18.17) and the mean hospitalisation cost (SD) €6706 (9422). The main predictor of hospital costs is the length of stay. A linear regression (n = 41,348, R2 = 0.4520) reveals that predictors of a longer LOS for hospitalised older patients are: to be a male, to come from another hospital, to be sent to hospital by a general practitioner, to be admitted through the emergency department, to undergo a surgical procedure, to suffer from a major or extreme SOI or run a major or extreme mortality risk, to have a high score on the Charlson Comorbidity Index (CCI), to stay in an ICU, to belong to older age categories (85+), and to be institutionalised after discharge.
Advanced age is by itself only a weak predictor of hospital cost, but it is a good predictor of a longer hospital stay.