Gilthorpe, MS orcid.org/0000-0001-8783-7695, Harrison, WJ, Downing, A orcid.org/0000-0002-0335-7801 et al. (2 more authors) (2011) Multilevel latent class casemix modelling: a novel approach to accommodate patient casemix. BMC Health Services Research, 11. 53. p. 53. ISSN 1472-6963
Abstract
BACKGROUND: Using routinely collected patient data we explore the utility of multilevel latent class (MLLC) models to adjust for patient casemix and rank Trust performance. We contrast this with ranks derived from Trust standardised mortality ratios (SMRs). METHODS: Patients with colorectal cancer diagnosed between 1998 and 2004 and resident in Northern and Yorkshire regions were identified from the cancer registry database (n = 24,640). Patient age, sex, stage-at-diagnosis (Dukes), and Trust of diagnosis/treatment were extracted. Socioeconomic background was derived using the Townsend Index. Outcome was survival at 3 years after diagnosis. MLLC-modelled and SMR-generated Trust ranks were compared. RESULTS: Patients were assigned to two classes of similar size: one with reasonable prognosis (63.0% died within 3 years), and one with better prognosis (39.3% died within 3 years). In patient class one, all patients diagnosed at stage B or C died within 3 years; in patient class two, all patients diagnosed at stage A, B or C survived. Trusts were assigned two classes with 51.3% and 53.2% of patients respectively dying within 3 years. Differences in the ranked Trust performance between the MLLC model and SMRs were all within estimated 95% CIs. CONCLUSIONS: A novel approach to casemix adjustment is illustrated, ranking Trust performance whilst facilitating the evaluation of factors associated with the patient journey (e.g. treatments) and factors associated with the processes of healthcare delivery (e.g. delays). Further research can demonstrate the value of modelling patient pathways and evaluating healthcare processes across provider institutions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Gilthorpe et al; licensee BioMed Central Ltd. 2011 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited |
Keywords: | Aged; Diagnosis-Related Groups; England; Female; Hospitals, Public; Humans; Male; Models, Statistical; Models, Theoretical; Neoplasms; Quality Assurance, Health Care; Registries; Reproducibility of Results; Risk Factors; Survival Analysis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Genetics, Health and Therapeutics (LIGHT) > Division of Epidemiology & Biostatistics (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Epidemiology and Biostatistics (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Health Sciences (Leeds) > Centre for Health Services Research (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 01 Nov 2017 16:07 |
Last Modified: | 08 Dec 2017 13:45 |
Status: | Published |
Publisher: | BioMed Central |
Identification Number: | 10.1186/1472-6963-11-53 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:88308 |