Most decision-makers charged with prioritizing health technologies, including Israel’s Basket Committee, already consider the four variables included in the VfM Chart, but, because of the complexity involved, typically not in such a systematic and transparent fashion. It is important to appreciate that our proposed framework is not intended to replace decision-makers’ value judgments in any way. On the contrary, the VfM Chart is intended to serve as a decision-support tool that is very much based on decision-makers’ value judgments.
This dependence on decision-makers’ value judgments can be appreciated by recognizing that, first of all, to construct the VfM Chart decision-makers’ must reveal their preferences about the relative importance of the dimensions comprising the points system for the incremental-benefits variable (as explained earlier, by answering the pairwise-ranking questions). In addition, decision-makers need to rate each technology according to its performance on the points system’s dimensions. Naturally, such rating exercises can be difficult because of the uncertainties involved, and so decision makers are likely to need to deliberate. For example, with reference to Table 2 again, should the impact of growth hormone on the HRQoL of short-statured children be rated as a ‘medium’ or ‘large’ gain? Is prolonging a cancer patient’s life by 5 months a ‘medium’, ‘small’ or perhaps even ‘large’ benefit? Moreover, such uncertainties are magnified by the criticism that can be easily directed at these performance levels (‘small’, ‘medium’ and ‘large’): that they are overly simplistic and not descriptive enough. For real-world applications the points system’s dimensions and levels would need to be refined for the prioritization exercise in hand.
Obviously, the total scores calculated for the incremental-benefits variable of the affected technologies are sensitive to how they are rated by decision-makers.g Especially for new technologies, such uncertainties will almost always be compounded by deficiencies in the data available for forming judgments. Sensitivity analysis should be performed with respect to any controversial ratings to see what difference, if any, they make to the final decision about whether to add a technology to the basket or not. For each technology that looks like being rejected, and for which there is significant uncertainty surrounding any of its variables, decision-makers should ask themselves: “What would it take for this technology to be in contention (e.g. on or near the VfM Chart’s Pareto frontier), and how realistic is such a scenario?” The VfM Chart enables such ‘what-if’ experiments to be performed systematically.
The final respect in which the framework depends on decision-makers’ value judgments concerns the prioritization decisions themselves. As for all tools, how the VfM Chart is applied is at the discretion of decision-makers. They – rather than the tool – are ultimately responsible for deciding which technologies are selected. The VfM Chart simply displays the main variables for consideration and makes explicit the potential tradeoffs between the variables on the chart’s axes, where higher Total Cost can be compensated for by higher Benefits. It is up to decision-makers to determine the appropriate ‘rate of exchange’ between Total Cost and Benefits and also how to weigh the impact of Quality of Evidence and X-factors, all of which depend on value judgments.
The X-factors variable, in particular, serves as a potential ‘over-ride’ mechanism for enabling a particular technology to be prioritized ahead of others that are otherwise superior on the three other variables included in the VfM Chart. A well-known Israeli example is dental care for children (similar to t10 in Table 2 and Figures 2 and 3), which was introduced to the 2010 Basket Committee with a strict demand from the Deputy Health Minister, approved by the Cabinet, that it be added to the health basket, regardless any other considerations . If decision-makers (or their political masters) choose to invoke such X-factors, they are, in effect, forced to explicitly explain why such a technology – with high Total Cost and/or low Benefits and/or poor Quality of Evidence relative to other technologies – ought to be added to the health basket in preference to others. The VfM Chart ensures such decisions are transparent (and auditable).
As mentioned in the Methods section, points systems have been widely used for diagnostic and treatment-based decision-making and for prioritizing patients for specific elective services. Somewhat surprisingly, points systems have not been so widely used for prioritizing technologies, though there appears to be increasing interest in doing so (e.g. see the references in ), including, for example, a recent report that argued for their greater use in the NHS . One possible reason for this may be because, unlike diagnosing or prioritizing patients, prioritizing health technologies involves cost comparisons across technologies. Our proposed framework deals with this issue by including in the points system only dimensions related to the technologies’ incremental benefits, and then introducing their incremental costs to the prioritization exercise later when the VfM Chart is created.h
By focusing on each technology at the aggregate level – i.e. in terms of the effects of the overall intervention involving the technology on Israel’s population and health system respectively – the framework avoids the problems associated with using Incremental Cost-Effectiveness Ratios (ICERs) to prioritize technologies. Allocating a budget across possible interventions in reverse order of the technologies’ costs per QALY results in the maximization of QALYs only if two conditions are satisfied: (1) that interventions are sufficiently divisible for the technologies to be purchased in incremental units, and (2) that interventions are subject to constant returns to scale (so that changing how much of a technology is used affects the resulting health benefits by the same proportion) . These two conditions seldom hold  – in which case, ICERs convey nothing about how affordable interventions are. Affordability is important information when allocating a budget; for example, a technology with a very low cost per QALY might be used to treat such a large number of people that its total cost is unaffordable (e.g. potentially in excess of the budget). Stephen Birch and Amiram Gafni recommend an alternative conceptual approach to using ICERs based on “determin[ing] whether in choosing to use some of [the available budget] for one particular intervention, the health gains produced by this intervention exceed the health gains that are foregone by not using the same resources for all other possible interventions.” (p. 49) . “Because this involves the direct consideration of opportunity costs, measured in terms of health benefits foregone, it takes the form of a (non-monetary) cost-benefit analysis.” (p. 2099) . The VfM Chart is consistent with this conceptual approach.
As well as using the VfM Chart to represent potentially any number of technologies under consideration at a point of time (e.g. when the Basket Committee meets annually), technologies from the past (funded and/or not funded) could be super-imposed for comparison purposes. The VfM Chart could also be used in a ‘dynamic’ manner consistent with Program Budgeting and Marginal Analysis : as new technologies arise they could be introduced to the VfM Chart and considered for funding while, at the same time, old technologies are identified for decommissioning. Such a longitudinal focus would assist with achieving greater decision-making consistency over time.
Our proposed framework is compatible with the prioritization process currently followed by the Israeli Basket Committee, as summarized at the beginning of the article. In more detail here, this process begins with a discussion about each individual technology on its own – specifically, its contribution to patients’ health and society overall, independent of its cost. Technologies deemed deserving of further consideration proceed to the next stage where, after including cost data from the ‘Technical Sub-committee’, they are compared, subject to the budget constraint . This prioritization stage comprises two rounds: in the first round, technologies that are judged not to be worthwhile given the budget constraint are discarded; and in the second round, the Committee compares the remaining technologies in order to choose those that should be added to the health basket and that can be afforded.
The approach used to make the final prioritization decisions over the last few years is that each Committee member nominates his or her ‘top ten’ technologies. Technologies nominated by a majority of members are written on the board in the meeting room. Other technologies nominated by fewer members are also written on the board and flagged with a question mark (indicating less support). The costs of all the technologies on the board are summed. If the total exceeds the budget, then in theory all technologies on the board are included for discussion with respect to being dropped until the budget is met; but in practice usually only the question-marked technologies are considered. The order in which technologies are discussed by the Committee can be critical, as the inclusion of one technology, given the budget constraint, necessarily means that one or more later candidates will be excluded.
We believe that the VfM Chart would be a useful decision-support tool at both rounds of the prioritization stage outlined above, especially the second round.i All technologies that make it through to the prioritization stage could be represented in the VfM Chart, which could serve as the focal point to the Committee’s deliberations. In addition, the VfM Chart could be used as a powerful communication device to explain to stakeholders, including the general public, in an obvious visual fashion why particular technologies were prioritized over others. Such explanations might reduce feelings of injustice suffered by patients whose required technologies were not added to the health basket – to the extent, potentially, that even law suits might be averted.j