Abstract
Introduction
Examples of precision medicine are complex interventions featuring both testing and treatment components. Due to this complexity, there are often barriers to the introduction of such interventions. Few economic evaluations attempt to determine the impact of these barriers on the cost-effectiveness of the intervention. This study presents a case study economic evaluation which illustrates how value of implementation methods may be used to quantify the impact of capacity constraints in a decision-analytic model.
Methods
A baseline decision-analytic model-based economic evaluation of ALK mutation testing was reproduced from a published technology appraisal. Three constraints (commissioning awareness, localisation of testing, and pathology laboratory capacity) were identified using qualitative interviews, parameterised, and incorporated into the model. Value of implementation methods were used alongside incremental cost-effectiveness ratios (ICERs) to quantify the impact on the cost-effectiveness and net monetary benefit (NMB) of each capacity constraint and from the three constraints combined.
Results
Each of the three capacity constraints resulted in a loss of NMB ranging from £7,773 (0.1% of the total) per year for localised testing to £4,907,893 (77%) for a lack of awareness about commissioning ALK testing. When combined, the constraints resulted in a loss of NMB of £5,289,414 (83%). The localisation and limited pathology capacity constraints slightly increased the ICER but the lack of commissioning awareness constraint did not change the ICER.
Conclusions
Capacity constraints may have a significant impact on the NMB produced by examples of precision medicine. Value of implementation methods can be used to quantify the impact of such constraints by combining the impact of the constraints on the cost-effectiveness of the intervention with the impact on the number of patients receiving the intervention.
Examples of precision medicine are complex interventions featuring both testing and treatment components. Due to this complexity, there are often barriers to the introduction of such interventions. Few economic evaluations attempt to determine the impact of these barriers on the cost-effectiveness of the intervention. This study presents a case study economic evaluation which illustrates how value of implementation methods may be used to quantify the impact of capacity constraints in a decision-analytic model.
Methods
A baseline decision-analytic model-based economic evaluation of ALK mutation testing was reproduced from a published technology appraisal. Three constraints (commissioning awareness, localisation of testing, and pathology laboratory capacity) were identified using qualitative interviews, parameterised, and incorporated into the model. Value of implementation methods were used alongside incremental cost-effectiveness ratios (ICERs) to quantify the impact on the cost-effectiveness and net monetary benefit (NMB) of each capacity constraint and from the three constraints combined.
Results
Each of the three capacity constraints resulted in a loss of NMB ranging from £7,773 (0.1% of the total) per year for localised testing to £4,907,893 (77%) for a lack of awareness about commissioning ALK testing. When combined, the constraints resulted in a loss of NMB of £5,289,414 (83%). The localisation and limited pathology capacity constraints slightly increased the ICER but the lack of commissioning awareness constraint did not change the ICER.
Conclusions
Capacity constraints may have a significant impact on the NMB produced by examples of precision medicine. Value of implementation methods can be used to quantify the impact of such constraints by combining the impact of the constraints on the cost-effectiveness of the intervention with the impact on the number of patients receiving the intervention.
| Original language | English |
|---|---|
| Journal | Medical Decision Making |
| DOIs | |
| Publication status | Published - 25 Oct 2021 |