Health care priority setting in Norway a multicriteria decision analysis

In all health care systems, choices in the allocation of resources are necessary. Public resources, in both low- and high-income settings, are insufficient to provide all possible services to the entire population at all times. Priority setting in the allocation of health interventions across ranges of health services or target groups becomes inevitably and at best should be explicit[1, 2].

Scarcity of resources and rational priority setting lead to identification of national packages of health services and to explicit reimbursement decisions [3]. In health, policy makers often may have to confront many groups with different and conflicting interests [4]. Rational approaches to guide policy makers become desirable and allow for navigation of complex social processes and to handle multifaceted information. The rise of evidence-based health policy has lead to a wealth of information on the nature and distribution of the disease burden and related societal costs as well on the effectiveness and efficiency of health interventions, and on their budget impact [5]. Existing approaches may concentrate on one or two criteria like safety and effectiveness, or also efficiency [6, 7] with real world decision makers having to handle multidimensional information [2, 8]. So far, priority setting tends to focus primarily on effectiveness and efficiency and less on equity-related social values [9].

Norway has adopted a well-developed comprehensive system in which complex problems and scientific support mechanisms such as health technology assessment and value-based priority-setting criteria were brought together to generate transparent solution [10]. As one of the richest countries it ranks second following the United States in health care spending and it enjoys one of the highest population health levels in the world. (OECD 2011[11]) The key elements of its health policy include provisions of health services for all based on needs regardless of personal income, local and regional accountability, public commitment and political interest in improving the health system [12]. Its health system is described as a decentralized national health service with universal coverage of primary care under the responsibility of the municipalities and with specialized care under national governance.

Our study objective is to assess if policy-makers' actual value preferences agree with those formulated in the legal domain through the Patient Rights Act (PRA). The Act identifies three prioritizing rules: severity of the condition (those most in need must be helped first), expected health outcome, and, lastly, proportionality between need and treatment (with cost-effectiveness analysis providing this information). We used discrete choice experiments (DCE), a methodology that allows simultaneous assessment of multiple policy preferences in multi-criteria decision analysis (MCDA) for policy as we reported earlier in other case studies[9, 13‐15].

MCDA consists of four steps: (I) identification of policy criteria and metrics, (II) identifying series of alternative package vignettes based on various combinations of policy criteria, (III) measuring performance of alternatives by criteria (this is often done through a DCE questionnaire but can also be completed in various other ways), and (IV) determining the preferred selection through scoring intervention options against those criteria. The last step provides a broad classification and ranking of interventions within a chosen context or specific disease area (a composite league table). Although the league table is not an integral part of the MCDA methods but rather an illustrative application, it is often seen as the most important contribution of a MCDA.

All 34 respondents completed and returned the whole survey questionnaire. Table 4 shows the results of the random effects regression model. A positive sign for a particular level implies a positive impact on the probability of choosing interventions with that level. As mentioned, the absolute values of the regression coefficients indicate their relative importance in priority setting, in that respect, cost-effectiveness, individual benefits and severity of diseases are the most important criteria. Except for middle age group and the willingness-to-subsidize criterion, all coefficients showed to be significant, and their signs had the expected direction.

Table 3 shows the composite league table results. The interventions with the highest priority are those addressing cardio-vascular diseases, and next the respiratory diseases. Those receiving the lowest attractively are related to mental health.

The results from composite league table can be considered indicative. It provides an insight in intervention priorities they are giving or neglecting to address chronic diseases. Only if cardiovascular diseases and respiratory diseases are properly addressed, mental health conditions - such as depression, alcohol disorders and Alzheimer's disease - may become attractive. This may be in conflict with already existing central government initiatives that aim to promote control of neuropsychiatric conditions, in particular dementia [20].

A limitation in our study is that we did not use well defined and easily quantifiable criteria based on locally formulated standards. Recognizing this, we do not avoid a realistic debate on policy setting in Norway as the criteria selected ex ante are close to the country specific and country-relevant, as well as the levels of attributes. Our present full set of criteria chosen describes the most important generic aspects of a health intervention as also is found in the two large reviews [6, 7]. Also, our findings are comparable to the preferences of Dutch policy makers [9]. These two countries seem to favor efficiency to equity. Additionally, the trends in weights among Dutch health care groups are similar. Moreover, interventions will certainly have different perceived or measured characteristics in other countries. Some of criteria may not be relevant in other countries, yet this is accounted for by the country-specific weights that policy-makers in other settings may give to those criteria.

The second constraint i.e. the assumed independence of the criteria as they are defined in the DCE is important. Our approach is not only based on assumed independence but also assumed comprehensiveness and exclusiveness of the selected criteria, especially in the ranking of interventions. This is reflected and has been tested in the multi-variate regression approach, yet we cannot not exclude other relevant additional criteria in real-life settings. In addition, we also need to acknowledge that this type of MCDA provides a way to account for quantifiable elements of the decision-making process, yet other elements like feasibility, transaction costs, historical or local context, among others, may be difficult to incorporate into the approach [21]. The latter are much more related to implementation as to an informed and explicit priority setting. The present findings are important as they confirm current policies and do not lead to new insights in the approach of the policy makers. So, the study and the matching of criteria provides policymakers with an explicit structure to assess the extent to which current and future investments in health interventions in Norway may serve the country's societal objectives.

Health decision-makers make difficult decisions on the use of public funds either in a context-specific priority setting for reimbursement of interventions, prioritization between a few options within a constrained budget or, in a general policy setting where no specific choice has to be made in a specific resource allocation. At the moment, Norway is given only an average score in the OECD's new health system report [22]. A more formalized and explicit approach that includes methodological guidance, the use of health information and a transparent debate on policy formulation may improve the policy process [23]. Here, to balance policy makers taking ad-hoc or biased decisions, an approach like MCDA, while using a composite ranking method may be a valuable tool[2]. Ghana is a positive example and has successfully used explicit criteria to set its interventions priorities through the Strategic Plan for health 2007-2012 while other very divers countries with (almost) universal access systems continue to develop policy processes that includes both equity and efficiency factors such as in the UK, The Netherlands, Thailand, China, and others [15].

Although this study used general priority criteria, three criteria showed to be relevant to Norwegian policymakers. The existing implementation of appropriate, transparent, and fair national guidelines is in line with the legal, and hence societal values and reflects the Patients Rights of Act. Priority rankings based on the same criteria show how MCDA can be used and may invite a discussion on priority policies across major disease areas. The findings allow for a prioritization based on existing features of the modern health care complexities that policy makers are facing.