Pharmacoeconomic Guidelines: India
Country/Region: India
Published PE Recommendations
Development of the Indian Reference Case for undertaking economic evaluation for health technology assessment (2023)
Published PE Recommendations Source:
Sharma D, Prinja S, Aggarwal AK, Rajsekar K, Bahuguna P. Development of the Indian Reference Case for undertaking economic evaluation for health technology assessment. The Lancet Regional Health - Southeast Asia. 2023;16:100241. doi:10.1016/j.lansea.2023.100241
Information current as of Tuesday, May 21, 2024
Key Features
| Key Features | |
|---|---|
| Type of Guidelines | Published PE Recommendations |
| Title and year of the document | Development of the Indian Reference Case for undertaking economic evaluation for health technology assessment (2023) |
| Affiliation of authors | The Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India, and the Department of Health Research, Ministry of Health and Family Welfare, New Delhi, India. |
| Purpose of the document | To introduce the development of the Indian Reference Case (IRC) for undertaking economic evaluations for health technology assessment (HTA). The IRC is a set of standards that will be used to improve the quality and consistency of economic evaluations conducted in India. |
| Standard reporting format included | Yes. |
| Disclosure | The research received no specific grant from any funding agency, commercial, or not-for-profit sectors. It was undertaken as part of a doctoral thesis, with scholarship support from the Indian Council of Medical Research (ICMR), New Delhi, India. |
| Target audience of funding/ author's interests | The IRC will be useful for researchers, policymakers, and anyone involved in HTA. |
| Perspective | Economic evaluations should be conducted from the societal perspective. This means that all costs and consequences borne by society should be considered, regardless of who pays for them. For instance, if a new medical intervention is more expensive but also more effective than the current standard of care, the societal perspective would take into account the cost of the intervention to the healthcare system as well as the benefits to patients, such as increased productivity and quality of life. |
| Indication | Not specified. |
| Target population | The target population should be identified in economic evaluations for health technology assessment. It is important to consider subgroups within the target population, as the intervention may have different effects on these groups. |
| Subgroup analysis | Subgroup analysis should be conducted to assess population heterogeneity. This analysis should ideally be planned at the beginning of the study so that stratified data can be collected for the subgroups. Researchers should justify their rationale for identifying subgroups based on different characteristics. Subgroup analysis is important because it can help decision-makers understand how the intervention will affect different populations. For example, an intervention may be cost-effective for one subgroup but not for another. This information can then be used to target interventions to the populations that will benefit the most. |
| Choice of comparator | Choosing an appropriate comparator to ensure reliable economic evaluations is important. The recommended comparator is the current practice in use, which could be the standard treatment guidelines or the most widely used therapy. However, there may be situations where more than one alternative treatment is used. Other factors influencing comparator choice include the organization providing care and their specific health benefit package. Consider all relevant comparators, including current and future therapies. Justification for the chosen comparator(s) should be provided. |
| Time horizon | Not specified. |
| Assumptions required | Varying assumptions in analysis is recommended. |
| Preferred analytical technique | A systematic review and meta-analysis is the preferred analytical technique. It is the most robust method for obtaining generalizable results on clinical effectiveness. However, if time and resources are limited, then researchers can use evidence from existing systematic reviews. |
| Costs to be included | All costs borne by society should be considered. This might include direct medical costs (hospital stays, medications), direct non-medical costs (travel, lost productivity), and indirect costs (morbidity, mortality). Opportunity Costs: Consider opportunity costs when measuring costs. An opportunity cost is the value of the next best alternative forgone due to using a particular resource. For instance, if a hospital bed is occupied by a patient receiving a new treatment, the cost could include the value of that bed being used for another patient who needs it. |
| Source of costs | Use national government cost data or standard cost menus for valuing resource use. This ensures consistency and comparability across different studies. |
| Modeling | Probabilistic sensitivity analysis (PSA) to account for and determine the impact of the uncertainty present in results of economic evaluation is suggested. Additionally, undertaking deterministic sensitivity analysis to test the impact of key structural and model assumptions, and parameters which may strongly influence the results, is recommended. Scenario analysis (including best-case and worst-case scenario) is also recommended. |
| Systematic review of evidences | Yes. |
| Preference for effectiveness over efficacy | Yes, if possible. Since economic evaluations consider societal costs and benefits, it's more relevant to assess the intervention's effectiveness in a real-world setting. This takes into account factors like adherence to treatment, side effects, and broader healthcare system factors that might not be captured in a clinical trial. |
| Preferred outcome measure | QALYs (Quality-Adjusted Life Years) as the primary measure of health outcome. DALYs (Disability-Adjusted Life Years) may also be used. The reason given for preferring QALYs is that they are more appropriate for capturing the burden of non-communicable diseases (NCDs), which are becoming increasingly common in India. |
| Preferred method to derive utility | Not stated. |
| Equity issues stated | Equity should be evaluated using either a quantitative or qualitative approach, or as an additional evaluative criterion. All lives and QALYs (quality-adjusted life years) should be valued equally irrespective of age, gender or other socioeconomic characteristics. Use distributional cost-effectiveness analysis (DCEA) to analyse the equity considerations in an economic evaluation. |
| Discounting costs | Costs and outcomes that occur beyond one year should be discounted to their present value at a rate of 3% annually. This is because future costs are considered less significant than present costs. Conduct sensitivity analyses to test the robustness of the results by varying the discount rate from 0% to 5%. |
| Discounting outcomes | Costs and outcomes that occur beyond one year should be discounted to their present value at a rate of 3% annually. This is because future costs are considered less significant than present costs. Conduct sensitivity analyses to test the robustness of the results by varying the discount rate from 0% to 5%. |
| Sensitivity analysis-parameters and range | Analyze the impact of uncertainty in various parameters that can influence the cost-effectiveness results. These parameters might include: Cost parameters: Unit costs of medications, hospital stays, physician consultations, etc. Effectiveness parameters: Transition probabilities in a Markov model, mortality rates, utility values (QALYs). Discount rate: The rate at which future costs and outcomes are discounted to their present value. Time horizon: The duration over which costs and outcomes are measured. Vary each parameter within a plausible range to assess its impact on the results. This range should be based on relevant literature, expert opinion, or real-world data. Here are some examples: Cost parameters: The range could be based on the standard deviation or upper and lower bounds of published unit cost data. Effectiveness parameters: The range could be based on confidence intervals from clinical trials or observational studies. Discount rate: Using a range of 0% to 5% for the discount rate. Time horizon: The range could be based on the expected duration of the intervention's effect or the decision-maker's timeframe. |
| Sensitivity analysis-methods | One-way sensitivity analysis: This method involves varying one parameter at a time within its specified range and observing the impact on the cost-effectiveness results (e.g., ICER - Incremental Cost-Effectiveness Ratio). This helps to isolate the effect of individual parameters on the conclusions. Multi-way sensitivity analysis: This method involves varying multiple parameters simultaneously to assess how their combined uncertainty affects the results. The following techniques are recommended: Tornado sensitivity analysis: This method graphically depicts the effect of varying each parameter on the cost-effectiveness measure. It helps to visually identify which parameters have the greatest influence on the results. Monte Carlo simulation: This method involves randomly sampling values for multiple parameters from their probability distributions and running the economic model numerous times. This generates a distribution of possible cost-effectiveness results, providing a more comprehensive picture of the uncertainty surrounding the base-case estimate. The choice of method for sensitivity analysis depends on the specific economic evaluation and the number of parameters being considered. One-way sensitivity analysis is simpler to implement but may not capture the full impact of interacting uncertainties. Multi-way sensitivity analysis can be more complex but provides a richer understanding of how parameter uncertainty affects the results. Report the methods used for sensitivity analysis and the results obtained. This transparency allows decision-makers to understand the limitations of the economic evaluation and the robustness of the conclusions. |
| Presenting results | Not specified. |
| Incremental analysis | Not specified. |
| Total costs vs effectiveness (cost/effectiveness ratio) | Not specified. |
| Portability of results (Generalizability) | Systematic review and meta-analysis be the primary source of effectiveness data, as this approach is considered to generate the most generalizable results. |
| Financial impact analysis | A separate document is planned for budget impact analysis (BIA) specific to India. |
| Mandatory or recommended or voluntary | Recommended |
Acknowledgement:
| Adibabu Kadithi, MPhil, PMP, CDAIO |