Abstract
Background:
Precision (stratified or personalised) medicine is underpinned by the premise that it is feasible to identify known heterogeneity using a specific test or algorithm in patient populations and use this information to guide patient care to improve health and wellbeing. This study aimed to understand if, and how, previous economic evaluations of precision medicine had taken account of the impact of capacity constraints
Methods
A meta-review was conducted of published systematic reviews of economic evaluations of precision medicine (test-treat interventions) and individual studies included in these reviews. Due to the volume of studies identified, a sample of papers published from 2007 to 2015 was collated. A narrative analysis identified whether potential capacity constraints were discussed qualitatively in the studies and, if relevant, which quantitative methods were used to account for capacity constraints.
Results
A total of 45 systematic reviews of economic evaluations of precision medicine were identified, from which 222 studies focussing on test-treat interventions, published between 2007 and 2015, were extracted. Of these studies, 33 (15%) qualitatively discussed the potential impact of capacity constraints including: budget constraints; quality of tests and the testing process; ease of use of tests in clinical practice; and decision uncertainty. Quantitative methods (9 studies) to account for capacity constraints included: static methods such as capturing inefficiencies in trials or models and sensitivity analysis around model parameters; and dynamic methods which allow the impact of capacity constraints on cost-effectiveness to change over time.
Conclusions
Understanding the cost-effectiveness of precision medicine is necessary evidence but not sufficient evidence for its successful implementation. There are currently few examples of evaluations that have quantified the impact of capacity constraints, which suggests an area of focus for future research.
Precision (stratified or personalised) medicine is underpinned by the premise that it is feasible to identify known heterogeneity using a specific test or algorithm in patient populations and use this information to guide patient care to improve health and wellbeing. This study aimed to understand if, and how, previous economic evaluations of precision medicine had taken account of the impact of capacity constraints
Methods
A meta-review was conducted of published systematic reviews of economic evaluations of precision medicine (test-treat interventions) and individual studies included in these reviews. Due to the volume of studies identified, a sample of papers published from 2007 to 2015 was collated. A narrative analysis identified whether potential capacity constraints were discussed qualitatively in the studies and, if relevant, which quantitative methods were used to account for capacity constraints.
Results
A total of 45 systematic reviews of economic evaluations of precision medicine were identified, from which 222 studies focussing on test-treat interventions, published between 2007 and 2015, were extracted. Of these studies, 33 (15%) qualitatively discussed the potential impact of capacity constraints including: budget constraints; quality of tests and the testing process; ease of use of tests in clinical practice; and decision uncertainty. Quantitative methods (9 studies) to account for capacity constraints included: static methods such as capturing inefficiencies in trials or models and sensitivity analysis around model parameters; and dynamic methods which allow the impact of capacity constraints on cost-effectiveness to change over time.
Conclusions
Understanding the cost-effectiveness of precision medicine is necessary evidence but not sufficient evidence for its successful implementation. There are currently few examples of evaluations that have quantified the impact of capacity constraints, which suggests an area of focus for future research.
| Original language | English |
|---|---|
| Journal | PharmacoEconomics |
| Early online date | 13 May 2019 |
| DOIs | |
| Publication status | Published - 1 Aug 2019 |
Research Beacons, Institutes and Platforms
- Lydia Becker Institute