Decision-making for adding a new drug to the medicine reimbursement list of Iranian third-party payers (Insurers) is a complex process; so efficient and explicit processes to ensure transparency and consistency in considered factors are required. Also, the necessity to use clinical evidence and information regarding medicines coverage in decision making process of health insurance organizations is not really clear. There is a compelling need for a transparent and evidence-informed approach toward medicine reimbursement in Iran. Such an approach to show the relative advantages of medicine criteria selection, in order to inform reimbursement decision makers should be the goal.
Every year, more effective medicines are produced to deal with a large number of diseases. The availability of so many medicines raises this question: how can insurers provide their insured with access to essential medications, and meanwhile control the cost of drugs? As evidence-based medicine has become ubiquitous in clinical decision-making discussions, conflicts over definitions and proper application of evidences are a decade-old problem and remain controversial in medical necessities debates (
1,
2,
3).
Medicines with high benefits and low costs are the ideal drugs for insurers seeking to improve the health of the insured while managing drug costs; however, decision making in some situations is complicated. For instance, it should be investigated whether the cost of an effective and beneficial medicine is considered. Several beneficial methods are proposed and carried out by diverse countries such as Canada, China, Australia, Germany, and the United Kingdom. Methods including reference pricing (
4,
5), generic substitution (
6), income-based deductibles (
7), co-payments and coinsurance (
8,
9), incentive-based tiered formularies (
10), negative and positive subsidy lists (
11), prescribing budgets (
10,
12), and drug caps (
13), and each of them has led to varied results. In decision making for coverage, decision makers may face a dilemma between their interests in cost analyses and fear of public and even a professional backlash. General spending on health care are not immune to the pressures of political and social powers, which are a mixture of the existing injustice (
14).
In this paper, we explain an approach of decision making on medicine reimbursement for Iran’s health insurance organization by taking advantage of the “Borda” method, in a pilot study.
Decision-making organizations in Iran who are responsible for new medicines reimbursement (third-party payers) are various and multi-segmented. The details of these relationships and their impact on novel medicines reimbursement are shown in
Figure 1. Also, the reimbursement process for new medicines that takes place by health insurance organizations in Iran is depicted in
Figure 2. As shown in the Figure, the Compilation Council of Drug (CCD) of health insurances plays a significant role in the acceptance of an offer for new medicines that are usually generic medicines, and evaluates its characteristics using the information collected from Iranian drug-making companies or drug-importing firms. In this regard, information such as clinical benefits, clinical documentation, and guidelines and so on are not wholly clarified and stabled as they should be. Then, the council grants its recommendation to the High/superior Council of Health Insurance (HCHI). This superior council consists of members from ministry of health and medical education, ministry of labor, cooperation and social welfare, ministry of commerce, vice-president for strategic planning and supervision and medical council of the Islamic Republic of Iran (non-governmental). If the council agrees with the novel medicine’s reimbursement, they notify all Iranian health insurance organizations.
Relations of reimbursement decision maker bodies for new medicine selection in Iran health insurances
Process of reimbursement decision making for new medicine selection in Iranian public health based insurance organizations
How decisions and analyses are made? Guzman believed the main parts (
15) that must be considered in any decision evaluation are (
Figure 3):
Perspective (health trusts, governmental body, insurance companies, patients and society);
Time horizon;
Costs (direct medical costs, direct non-medical costs, indirect costs, intangible costs); and
Outcome (years of life saved, years of disease-free survival, cure rate).
How decisions analyses are made?
We will face the trouble of decision making when the costs and benefits of a new medication are both high and low (areas Ι and Ш in
Figure 3). Time and perspective affect the cost and benefits of medicines and in some cases, if there is valid quantitative evidence we can judge by it. When we do not have the adequate documentation, collection of experts and elites’ opinions, who have enough experience in the related area, is required.
As shown in
Figure 4 (cognitive dimensions of cognitive chain framework), analysis accuracy of the experts’ consensus judgment is moderate and it is more based on intuition than scientific analysis. The absence of much needed evidence, leads us to modes 5 and 6.
Measurement of magnitudes for modes of decision-making, Adopted from: Jack Dowie, Health Care Priority Setting, 2003, p: 10
In this article, decision-making is done at mode 5 (taking into account the previously mentioned points) (
16).
A drawback of simple methods is the risk of low discriminatory power. Many other methods those weight ideas differently (for example, analytical hierarchy process (AHP); multi attribute utility analysis; swing weighting and conjoint analysis) that have varying degrees of complexity (
17,
18).
Structure of research material collection is organized as 4 steps follow:
Step one: Extraction and classification of different criteria and first questionnaire construction.
26 effective criteria for medicine selection in the health insurance were extracted from the literature and articles from developed countries. Acquired criteria were categorized in 4 parts.
The first part, economic criterion, consisted of 7 criteria. The second part, clinical criterion, also consisted of 7 criteria. The third part, study quality criteria and finally the forth part, management criterion, both include 6 criteria. For data gathering a questionnaire was developed with 26 questions about criteria (
Table 1). Its reliability evaluation according to Cronbach's alpha was 96%.
| Part | Criteria | Reference |
|---|
| 1-economical | 1-economic evaluation guidelines by manufacturer2-ICER thresholds3-Budget impact4-Expected budget increase for third party payer5-Price in comparison to comparator drug6-Sales volume of drug7-Physicians demand | (19,20)(21-25)(21,26,27)(28,29)(30,31)(32)(33) |
| 2- clinical | 1-Considered RCT evidence2-DALY as an endpoint of drug3-Efficacy as a therapeutic value4-Availability of treatment alternative5-Condition is life threatening6-Target population7-Ability to reduce own health risk | (19,21,24,28,34,35)(24,34)(30,36,37)(21,24,26,38)(28,36,38)(24)(24) |
| 3-study quality | 1-Quality of evidence2-Quality of economic model3-Quality of economic evidence review of stakeholder perspectives4-Degree of uncertainty5-Consideration of HTA6-Year of study publication | (27,39)(24,28,35,40)(24,28,35,40)(24,28,35,40)(26,28,38)(19,41)(24) |
| 4-management field | 1-rule of rescue2-Ensure the availability of drugs3-Place in therapeutic strategy (e.g. 1st or 2nd line treatment)4-Objective of technology (e.g. prevention)5-Objective of technology (e.g. treatment)6-Expert Committee Decision | (42)(32)(36)(24,38)(24,38)(43,44) |
Step two: Determining the highest score (mean/SD) in each part using the feedbacks of drug and insurance experts. Responders included health insurance industry specialists and medical experts (purposed sampling). Measurement tool was a scale from 1 to 100 with 1 representing the least and 100 the most important criteria and each respondent was asked to mark the criterion importance on it. From 80 respondents, 45 questionnaires returned (
Table 2). Also we used the software “SPSS” 17 and Excel 2007.
In this step, 5 criteria reached the highest rank including:
A1-Expert Committee Decision
A2- Life- threatening condition
A3-Quality of evidence
A4- RCT evidence consideration
A5-Economic evaluation by manufacturer, (
Table 3)
| Variable | Range | n |
|---|
| Gender | MaleFemale | 2817 |
| Age | <40=>40, <=45>46, <=50>50 | 151884 |
| Education | MasterMDPhD | 32616 |
| Cross study | PhysicianPharmacyMedical sciences | 7317 |
| Work experiment(years) | O<3>=3,<=10>=11,<=15>=16,<=20>20 | 24791211 |
| Health insurance compilation council of Drug experiment (years) | O <3>=3,<=10>=11,<=15 | 27792 |
| High council of health insurance experiment(years) | O<3>=3,<=10>=11,<=15 | 28872 |
| Rank | Criteria | Score(mean/SD) |
|---|
| 1 | Expert Committee Decision | 5.763 |
| 2 | Condition is life- threatening | 5.405 |
| 3 | Quality of evidence | 4.831 |
| 4 | Considered RCT evidence | 4.484 |
| 5 | economic evaluation guidelines by manufacturer | 4.297 |
Step Three: Choosing 3 sub-criteria (x
1: Precision, x
2: Interpretability and x
3: Cost) (
45) that were rated by Delphi out of 8 sub-criteria, and advisers defined the weights in this order:
Then, we evaluated the 5 residual criteria under three sub-criteria in second questionnaire which planed on a 5 point LIKERT scale (1–very little 2–little 3–medium 4–much 5–very much).
Step Four: Determining the weight of 5 selected criteria in the second step using three sub-criteria selected in the third step by 6 elite members (
Table 4) of Iran’s Food and Drug organization (2 person), health insurance organization (2 person) and the University of Tehran’s Medical Ethics Department (2 person). These 6 experts were asked to weight the five main criteria from 1 to 5 while taking into account the 3 sub-criteria. 6 matrices were created and the results were obtained using the
Borda method and Mat-lab7 software.
| Variable | Range | n |
|---|
| Gender | MaleFemale | 51 |
| Age | =>40, <=45>46, <=50>50 | 123 |
| Education | MDPhD | 42 |
| Field of education | PhysicianPharmacy | 24 |
| Work experiment(years) | >=11,<=15>=16,<=20>20 | 114 |
| Experiment work in Healthinsurance compilationCouncil of Drug (years) | O >=3,<=10>=11,<=15 | 411 |
| Experiment work in High council of health insurance (years) | O>=3,<=10 | 42 |
MCDM models are used in different researches recently and the Borda rule, a well-known and appropriate group decision- making procedure was originally proposed for linear orders in Borda (
46) in what follows, we will call it classic Borda rule. It has been widespread analyzed and extended to more general orders from its initial design (
47,
48). In the last years it has also been considered in a fuzzy framework (
49-
52), and in a linguistic context (53).
“Borda” method prioritizes “m” options, against “n” indicators (quantitative and qualitative); by “k” decision-makers while using ordinal scale. Assuming a group of decision maker (DM) reach a consensus on common indicators, at first each DM ranks the indicators) DP) from the available options in the direction of the target of the issue, then analysis takes place according to the following steps:
1- Ratings results of all “k” decision makers, for jth indicator, forms the matrix Rj, So, "n" Matrix, for each" n" indicators, will be given.
2- Ranking of each matrix Rj for every indicator jth, converted to a Borda number for each decision maker pth (among the “k” decision makers). In the way that this option is ranked first by the decision maker pth has “m-1” relative value. The second option’s relative value is “m-2”, and option with the rank of “mth” will have relative value of “0”. In this way, Prof. “Borda” transformed a ratio scale to some kind of relative scale and made the additive practice possible.
3- Row sum up of the matrix Bj (“Borda” numbers), for "k" decision makers will be obtained and we will calculate the final ranking of each option for each indicator jth so that the row with maximum sum of Borda numbers will have the first rank and the row with minimum summation will get the mth rank (if a node was created, we’d open it properly).
of this matrix represents the rank of group consensus for the option ith for indicator jth.
1- As following, indicator weights (wj) are calculated appropriately, using SWING methods and then a weighted matrix of group consensus, with m rank of “m” option.
The parts of this matrix are , so that , if the option ith in rank tth return to indicator jth, and otherwise will be zero.
1- The following assignment-problem with variables of hit = {0, 1} must be solved to determine the final ranking of criteria.
In the final solution, hit = 1, if the rank of tth has been allocated to the option ith; otherwise, it is equal to zero.