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The Cost Effectiveness Analysis (CEA) Studies and the New Addition to GEAR Mindmap

Author: Sneha Rajbhandari
22 May 2020 757 0

The Cost-Effectiveness Analysis (CEA) studies compare the health outcomes and costs associated with competing health care programs. Such studies are used to identify the intervention with the best value for money for better resources allocation and to support priority setting. However, CEA studies pose many methodological issues, including their use and interpretation for policymakers. To help researchers address this issue, Guide to Economic Analysis and Research online resource (GEAR) has recently added a new central topic to the mindmap feature. (http://www.gear4health.com/gear/mind-map/11). On the right-hand side, the mindmap provides users with two immediate solutions as sub-branches i.e. comparing the CEA results with Incremental Cost Effectiveness Ratio (ICER) from evaluations of other treatments; and using a cost effectiveness threshold. And the left hand side of the mindmap presents the unanswered research questions regarding the interpretation of cost effectiveness analysis results. Now, lets explore the solutions and unanswered research questions as represented in the mindmap.

 1.  Immediate solutions:

        a.  Comparing the CEA results with Incremental Cost Effectiveness Ratio (ICER) from evaluations of other treatments:

CEA studies express costs in currencies and health benefits in units of health such as lives saved, cases averted and Quality Adjusted Life Years (QALY) gained. Now, when comparing interventions in CEA studies, the important question for resource allocation is how much additional benefit is achieved for the additional cost incurred[1]. It is therefore important to calculate incremental cost effectiveness of one intervention over another, often expressed as ICER, presented in a cost effectiveness plane. So in terms of interpreting CEA results for decision-making, it is best for policymakers to first compare their study results with ICERS from other treatments to allocate health care resources efficiently. Other than this, most Health Technology Assessment (HTA) organizations use cost effectiveness threshold to compare of interventions of competing interventions. However, there are many countries with HTA limited sectors, which do not yet have threshold values. Therefore, GEAR mindmap has enlisted three approaches in identifying the opportunity cost of an intervention to compare the CEA results of competing healthcare interventions i.e. using common outcome indicators that address level of the problem; comparing the results of the benchmark interventions; and using a league table approach that lists cost effectiveness ratios for different interventions and facilitates comparisons across interventions. In the mindmap. the researchers can learn more about these approaches in the detailed description box after clicking on each solution.

         b.  Using a cost effectiveness threshold:

Apart from the above solution, the other solution for policy makers to interpret whether the ICER of a healthcare technology will be acceptable or not is using  cost effectiveness threshold. It is the amount of money we are wiling to spend to gain a one-year of life. It presents the opportunity costs of investing in 1 QALY or Disability-Adjusted Life Year (DALY). However the choice of cost effectiveness threshold is a value judgement that depends on several factors like perspectives; how the policymakers values health outcomes and money; and resources available. There are ongoing controversies on what these values should be and varies between societies. For this, GEAR mindmap has proposed two approaches: using supply side derived threshold and demand side derived threshold, also known as willingness to pay threshold”. A common example of demand side derived threshold would be threshold based on per capita GDP. Supply side derived thresholds mainly take into account the budget constraint scenario i.e when there are limits in the overall healthcare budget available or when there are constraints on health systemsabilities to increase expenditure. Both these approaches has its pros and cons laid out in more detail in the description box below the mindmap.

 2. Unanswered research questions:

 a. Using the threshold based on per capita GDP might not be an appropriate assessment of willingness to pay and affordability in low and middle income countries:

              This unanswered research question is laid out in the left hand side of the mindmap. The sub-branches from this research questions reveals some more focused areas/questions where knowledge is scarce and future researches on cost effectiveness results interpretation could be explored. Specific research questions laid out in the mindmap are how should we identify/estimate threshold for HTA in low and middle income countries; estimating a supply side and demand side cost effectiveness threshold for a certain country; and how do supply side and demand side cost effectiveness threshold vary in low and middle income settings. These unanswered research questions in the mindmap are designed to shape methodological judgments in the long run for researchers interested in their area of interest.

 

The collective features in GEAR make it a very user-friendly and unique priority-setting global public good. It has high potential to make a difference to researchers, health economic practitioners, ministry of health employees or whoever trying to design, conduct, or analyze economic evaluation studies in a resource-limited setting, especially low and middle income countries. Register, explore, and try it out for yourself.

 

Visit the website at www.gear4health.com to learn more!

 

 

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[1] Interpretation of Cost-Effectiveness Analysis. J. Gen. Intern. Med. 1998;13.