Predictive model of length of stay in hospital among older patients View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-09-06

AUTHORS

Radcliffe Lisk, Mahir Uddin, Anita Parbhoo, Keefai Yeong, David Fluck, Pankaj Sharma, Michael E. J. Lean, Thang S. Han

ABSTRACT

BACKGROUND: Most National Health Service (NHS) hospital bed occupants are older patients because of their frequent admissions and prolonged length of stay (LOS). We evaluated demographic and clinical factors as predictors of LOS in a single NHS Trust and derived an equation to estimate LOS. METHODS: Stepwise logistic and linear regressions were used to predict prolonged LOS (upper-quintile LOS > 17 days) and LOS respectively, from demographic factors and acute and pre-existing conditions. RESULTS: Of 374 (men:women = 127:247) admitted patients (20% to orthogeriatric, 69% to general medical and 11% to surgical wards), median age of 85 years (IQR = 78-90), 77 had acute first hip fracture; 297 had previous hip fracture (median time since previous fracture = 2.4 years) and 21 (7.1%) had recurrent hip fracture, with median time since first fracture = 2.4 years. Median LOS was 6.5 days (IQR = 1.8-14.8), and 38 (10.2%) died after 4.8 days (IQR = 1.6-14.3). Prolonged LOS was associated with discharge to places other than usual residence: OR = 3.1 (95% CI 1.7-5.7), acute stroke: OR = 10.1 (3.7-26.7), acute first hip fractures: OR = 6.8 (3.1-14.8), recurrent hip fractures: OR = 9.5 (3.2-28.7), urinary tract infection/pneumonia: OR = 4.0 (2.1-8.0), other acute fractures: OR = 9.8 (3.0-32.3) and malignancy: OR = 15.0 (3.1-71.8). Predictive equation showed estimated LOS was 11.6 days for discharge to places other than usual residence, 15 days for pre-existing or acute stroke, 9-14 days for acute and recurrent hip fractures, infections, other acute fractures and malignancy; these factors together explained 32% of variability in LOS. CONCLUSIONS: A useful estimate of outcome and LOS can be made by constructing a predictive equation from information on hospital admission, to provide evidence-based guidance for resource requirements and discharge planning. More... »

PAGES

1-7

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40520-018-1033-7

DOI

http://dx.doi.org/10.1007/s40520-018-1033-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106829213

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30191455


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