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Health Economics of Frailty

We aim to develop and test a frailty health economics model. This model will be made available to policy makers and funders, ensuring that future funding decisions will be based on economics modeling that better account for the impact of frailty.

  • Health Economics Project 1 -Developing a Frailty Economics Model

    Lead Investigator: Professor Jon Karnon

    As we learn more about frailty, funds will be required to provide effective services that are developed to delay or manage the effects of frailty. To make the case for the required funds where the overall budget situation is ‘tight’, it will be necessary to demonstrate that these services provide value for money compared to competing calls on limited healthcare budgets. Cost-effectiveness models are routinely used to demonstrate the value of patented technologies, but less so for the non-patented services of the type that may most effectively target frailty.

    This project aims to develop a ‘world first’ cost-effectiveness model. The model can be used to estimate the extended cost savings and health benefits of frailty interventions in an Australian setting. This use of the model to evaluate frailty interventions will support stronger cases to be made for the funding of new services and interventions to either prevent or better manage frailty.

    Progress to Date:  A cohort-based state transition model was developed. The model structure includes fracture, depression, admission to aged care facilities, and death. Model inputs were estimated and calibrated using the Dynamic Analyses to Optimise Ageing dataset, supplemented with data from the published literature. A paper describing the development and validation of the model was published in Applied Health Economics and Health Policy.

    Media Contact: Professor Jon Karnon

  • Health Economics Project 2 - Observed &Predicted Data Outcomes from FIT (Frailty Intervention Trial)

    Lead Investigators: Professors Jon Karnon and Ian Cameron

    The Frailty Intervention Trial (FIT) was an early and important Australian randomized controlled trial aiming to evaluate the effectiveness of a physiotherapy-based intervention for frail persons discharged from hospitals and specialized geriatrics or rehabilitation programs. The within-trail economic evaluation showed that the intervention reduced frailty in this population, but found no significant between-group difference in quality-adjusted life years (QALYs) over the 1-year duration of the trial.

    This project aims to use the cost-effectiveness model developed in Health Economics Project 1 to predict long-term cost savings and QALYs based on the differences observed within the trial.

    Progress to Date: The developed cost-effectiveness model was applied to the cost-effectiveness analysis of the trial. The model-based economic evaluation showed that the frailty intervention has an expected incremental cost per QALY gained of Australian $8,129 compared to usual care, highlighting the value of the intervention. However, there remains some uncertainty due to the size of the original clinical trial. The results were published in Applied Health Economics and Health Policy.

    Media Contact: Professor Jon Karnon

  • Health Economics Project 3- Evaluation of interventions implemented in aged care facilities.

    Lead Investigators: Professors Jon Karnon and and Dr Hossein Afzali

    There is evidence indicating that people living in aged care facilities are more likely to be admitted in hospitals. This project aims to evaluate the impact of the interventions implemented in aged care facilities on a range of health outcomes including hospital admissions, falls and mortality. A comprehensive review of the literature will be undertaken to identify relevant interventions and a cost-effectiveness model developed to estimate long-term costs and outcomes of the interventions.

    Progress to Date: The literature review was completed and, based on the results of quality appraisal, ‘medication review’ interventions were selected. We finalised the structure of the model (including fall, hospital admission, emergency department visits, and death). Data required to populate the model were identified (currently awaiting to access the data).

    Media Contact: Professor Jon Karnon

  • Health Economics Project 4: Developing a comprehensive decision analytic model

    Lead Investigators: Professors Jon Karnon and and Dr Hossein Afzali

    The structure of the model developed in Health Economics Project 1 represents some health states with evidence of strong associations with frailty. However, subsequent review of clinical literature showed that a more complicated cost-effectiveness model structure is needed to more accurately capture disease progression to ensure that the best possible model is used to assess the value of frailty services. Recent guidelines for good modelling practice highlight the need for a sufficiently detailed and model development process and recommend the design of a conceptual model as a basis to inform an appropriate model structure.  A conceptual model should ideally reflect the natural history of the condition under study, describing important clinical states/events and patient attributes that influence disease progression (e.g. age, gender, level of education). Important structural aspects are defined with respect to their potential impact on health care resources, final health outcomes (e.g. mortality and quality of life) or disease progression regardless of data availability.

    The aim of this project is to develop an improved version of the model developed in Project 1. We first develop an appropriate conceptual model which is subsequently used to guide the development of a more accurate cost-effectiveness model. We also aim to systematically identify and use relevant high quality datasets to populate the model.

    Progress to Date: We completed review of clinical literature and guidelines to study current knowledge of frailty. This resulted in the identification of important health states/events associated with frailty, patient attributes that influence the course of frailty and associations between them. As part of the conceptual model development process, we are currently undertaking online surveys to obtain expert opinion providing further insight into the natural history of frailty. Also, a number of quality datasets have been identified including The Survey of Health, Ageing and Retirement in Europe (SHARE), The English Longitudinal Study of Ageing (ELSA), and The Longitudinal Aging Study Amsterdam (LASA).

    Media Contact: Professor Jon Karnon

Centre of Research Excellence in
Frailty and Healthy Ageing



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