A Cost-Effectiveness Model for Frail Older Persons: Development and Application to a Physiotherapy-Based Intervention
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The clinical importance of frailty is increasing. Existing economic evaluations of interventions to manage frailty have limited time horizons, but even in older populations there may be important longer-term differences in costs and outcomes. This paper reports on the development of a cost-effectiveness model to predict publicly funded health and aged care costs and quality-adjusted life years (QALYs) over the remaining lifetime of frail Australians and a model-based cost-utility analysis of a physiotherapy-based intervention for frail individuals.
A cohort-based state transition (Markov) model was developed to predict costs and QALYs over the remaining lifetime of a frail population. Frailty is defined using the phenotypic definition of frailty, and the model comprises health states that describe frailty status, residential status, the experience of bone fractures and depression, and death. Model input parameters were estimated and calibrated using the Dynamic Analyses to Optimise Ageing dataset, supplemented with data from the published literature.
The cost-effectiveness model was subject to a range of validation approaches, which did not negate the validity of the model. The evaluated physiotherapy-based frailty intervention has an expected incremental cost per QALY gained of Australian $8129 compared to usual care, but there is a probability of 0.3 that usual care is more effective and less costly than the intervention.
Frailty reduces quality of life, is costly to manage and it’s prevalence is increasing, but new approaches to managing frailty need to demonstrate value for money. The value of the reported cost-effectiveness model is illustrated through the estimation of all important costs and effects of a physiotherapy-based frailty intervention, which facilitates comparisons with funding decisions for other new technologies in Australia.
KeywordsResidential Care QALY Gain Frailty Status Residential Aged Care Frailty Phenotype
Funding provided by the NHMRC for the Centre for Research Excellence in Frailty and Healthy Ageing (ID 1102208) is acknowledged. Investigators of the NHMRC funded Frailty Intervention Trial (ID402791), in particular Nicola Fairhall, are acknowledged for completing the supporting clinical trial and economic evaluation alongside the clinical trial of the evaluated intervention. The data on which this research is based were drawn from several Australian longitudinal studies including the following: the Australian Diabetes, Obesity and Lifestyle (AusDiab) study, the Australian Longitudinal Study of Ageing (ALSA), the Australian Longitudinal Study of Women’s Health (ALSWH), the Blue Mountains Eye Study (BMES), the Canberra Longitudinal Study of Ageing (CLS), the Household, Income and Labour Dynamics in Australia study (HILDA), the Melbourne Longitudinal Studies on Healthy Ageing (MELSHA), the Personality And Total Health Through Life Study (PATH), and the Sydney Older Persons Study (SOPS). These studies were pooled and harmonised for the Dynamic Analyses to Optimise Ageing (DYNOPTA) Project. DYNOPTA was funded by an NHMRC Grant (ID 410215). All study researchers would like to thank the participants for volunteering their time to be involved in the respective studies. Details of all studies contributing data to DYNOPTA, including individual study leaders and funding sources, are available on the DYNOPTA website (http://dynopta.anu.edu.au). The findings and views reported in this paper are those of the authors and not those of the original studies or their respective funding agencies.
Jonathan Karnon conceptualised the study, led the model development, implementation and analysis, and finalised the manuscript. Hossein Haji Ali Afzali co-supervised the development and implementation of the model and the literature reviews and reviewed and edited the manuscript. Gregorius Virgianto Arpuji Anggoro Putro, Phyu Win Thant, Ameline Dompok, Ingrid Cox, Owen Henry Chikhwaza, Xian Wang, Mercy Mukui Mwangangi and Matahari Farransahat contributed to the development and implementation of the model, undertook literature reviews to estimate model input parameters and drafted the first version of the manuscript. Ian Cameron advised on the interpretation of the clinical trial results and reviewed and edited the manuscript.
Compliance with Ethical Standards
Conflict of interest
Ian Cameron was the lead investigator on the clinical trial of the evaluated frailty intervention. All other authors have no competing interests to declare.
Hossein Haji Ali Afzali is part-funded by the NHMRC Centre for Research Excellence in Frailty and Healthy Ageing (ID 1102208). No other funding was received for this study.
Availability of data and materials
The Frailty Cost-Effectiveness model, implemented in an Excel workbook, is available for use by external parties. Interested users are required to sign a License Application Form. No charge is made to academic organisations, but commercial organisations must pay an appropriate fee. In either case, it is a requirement to acknowledge the use of the Frailty Cost-Effectiveness model in any publications that make use of it, and to provide the corresponding author (JK) with the reference for each publication. It is not possible to provide access to the DYNOPTA dataset, as separate applications for data access are required.
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