Ensemble Risk Model of Emergency Admissions (ERMER)
- Submitting institution
-
The University of Westminster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- q0v0w
- Type
- D - Journal article
- DOI
-
10.1016/j.ijmedinf.2017.04.010
- Title of journal
- International Journal of Medical Informatics
- Article number
- -
- First page
- 65
- Volume
- 103
- Issue
- -
- ISSN
- 1386-5056
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Developing decision support tools for identification of patients’ emergency readmission risk is an important area of research. The use of a Bayesian approach with ensemble modelling has not been researched. Comparison of prediction performances, using England inpatient data, strongly indicates that the proposed Ensemble Risk Modelling of Hospital Readmission (ERMER) framework produces significant improvements in terms of precision and accuracy. Also, a generic, open-source and easy-to-use software toolkit has been developed to model the emergency readmission using ERMER, to expose it to the academic community and healthcare researchers and encourage a wider adaptation.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
