From efficacy to equity: Literature review of decision criteria for resource allocation and healthcare decisionmaking
© Guindo et al.; licensee BioMed Central Ltd. 2012
Received: 20 January 2012
Accepted: 28 June 2012
Published: 18 July 2012
Resource allocation is a challenging issue faced by health policy decisionmakers requiring careful consideration of many factors. Objectives of this study were to identify decision criteria and their frequency reported in the literature on healthcare decisionmaking.
An extensive literature search was performed in Medline and EMBASE to identify articles reporting healthcare decision criteria. Studies conducted with decisionmakers (e.g., focus groups, surveys, interviews), conceptual and review articles and articles describing multicriteria tools were included. Criteria were extracted, organized using a classification system derived from the EVIDEM framework and applying multicriteria decision analysis (MCDA) principles, and the frequency of their occurrence was measured.
Out of 3146 records identified, 2790 were excluded. Out of 356 articles assessed for eligibility, 40 studies included. Criteria were identified from studies performed in several regions of the world involving decisionmakers at micro, meso and macro levels of decision and from studies reporting on multicriteria tools. Large variations in terminology used to define criteria were observed and 360 different terms were identified. These were assigned to 58 criteria which were classified in 9 different categories including: health outcomes; types of benefit; disease impact; therapeutic context; economic impact; quality of evidence; implementation complexity; priority, fairness and ethics; and overall context. The most frequently mentioned criteria were: equity/fairness (32 times), efficacy/effectiveness (29), stakeholder interests and pressures (28), cost-effectiveness (23), strength of evidence (20), safety (19), mission and mandate of health system (19), organizational requirements and capacity (17), patient-reported outcomes (17) and need (16).
This study highlights the importance of considering both normative and feasibility criteria for fair allocation of resources and optimized decisionmaking for coverage and use of healthcare interventions. This analysis provides a foundation to develop a questionnaire for an international survey of decisionmakers on criteria and their relative importance. The ultimate objective is to develop sound multicriteria approaches to enlighten healthcare decisionmaking and priority-setting.
KeywordsDecisionmaking Resource allocation Priority-setting Criteria Healthcare
Resource allocation and priority setting are challenging issues faced by health policy decisionmakers requiring careful consideration of many factors, including objective (e.g., reason) and subjective (e.g., empathy) elements . Criteria used to evaluate healthcare interventions and allocate resources are likely to have profound implications, especially regarding ethical aspects. Ethical principles of resource allocation set forth by the World Health Organization (WHO) include efficiency (maximizing population health), fairness (minimizing health differences) and utility (greatest good for the greatest number) . Consideration of these often conflicting principles requires pragmatic frameworks and the engagement of a broad range of stakeholders to provide accountability for reasonableness (A4R) [3–7]. Limited resources and inequities in healthcare in both wealthy and developing countries underline the need to allocate optimally .
As argued by various authors [9–12], choices may not be based on rational and transparent processes highlighting the need for processes that take this into account. Indeed, if the mechanism employed to guide the distribution of resources is inequitable, the outcome is also likely to be. Thus, how resources are allocated by health policy decisionmakers around the world remains a challenging issue . Priority-setting is defined as the process by which healthcare resources are allocated among competing programs or people . In the context of increasing healthcare costs in many countries around the world, effective approaches to explicit appraisal and priority setting are becoming critical to allocate resources to healthcare interventions that provide the most benefit to patient health as well as contributing to healthcare systems’ sustainability, equity and efficiency. Indeed, elucidating decision criteria and how they are considered are key to establishing accountability and reasonableness of decisions and fulfils the A4R framework set forth by Daniels and Sabin .
Over the past decades, a number of empirical studies have explored systematic approaches to optimize evaluation of healthcare interventions and priority-setting. A number of tools with defined criteria to evaluate and rank interventions have been developed, recognizing the need for such approaches [10, 15–28]. As part of a larger collaborative endeavour exploring decision criteria, the aim of this study was to analyse the peer-reviewed literature to identify criteria reported in empirical studies that involved healthcare decisionmakers and in studies describing multicriteria tools. The specific objectives were to identify, categorize and estimate the frequency of decision criteria reported in the literature. This work will support the design of an international survey of decisionmakers on criteria and their relative importance as well as providing a resource for developers of multicriteria-based frameworks.
Search strategy and article selection
An extensive literature search was carried out in June 2010 on Medline and EMBASE databases to identify articles reporting healthcare decision criteria. Because studies reporting criteria (or factors or principles or components) are usually not indexed with such generic terms and because these terms are used in many fields (e.g., diagnostic criteria), a number of algorithms were explored to optimize the search strategy. The optimized search strategy included the following keywords: “decision-making”, “priority-setting”, and “resource allocation”, combined with “funding”, “budget”, “cost-benefit analysis”, “cost-effectiveness analysis”, and “equity”. The research was limited to articles published in English, French, or German over the last 10 years and excluded the following types of studies: clinical trials (phase I to IV), editorials, letters, randomized controlled trials, case reports, and comparative studies. Bibliographies of relevant articles were also searched.
Abstracts of articles thus retrieved were screened to identify appropriate inclusion and exclusion criteria. Studies were included if they reported a set (i.e., > 1) of decision criteria and were:
empirical studies conducted with healthcare decisionmakers (including field-testing of decisionmaking tools, focus groups, questionnaires, interviews)
reviews of such empirical studies, and
conceptual studies describing or proposing a set of decision criteria or a decisionmaking tool.
Studies were excluded if they focused on a single criterion (e.g., cost-effectiveness only) or described a priority-setting exercise without explicitly identifying decision criteria. Studies discussing the goals and advantages of priority-setting per se without reporting specific criteria were also excluded. To avoid double-counting of decision criteria, only one publication was included if several publications from the same group described the same set of decision criteria. For the same reason, studies reported in review articles that we included in our analysis and which reported the criteria of the original studies were also excluded.
Full texts of selected articles were reviewed and data extracted into a table identifying: 1) first author; 2) year of publication 3) method of criteria elicitation or identification, 4) decisionmaking setting, 5) exact term for each criterion as reported in the publication.
The number of times each criterion was cited in the studies retrieved was used as a proxy to identify the criteria perceived to be most important. Descriptive statistics were performed and each occurrence of a term belonging to that criterion was counted. If a study reported two different terms that we grouped under the same criterion, both terms were counted. For example, if a study reported “side effects” and “harm” as separate terms, we counted both of them under the criterion “Safety”. The numbers of citations for each criterion and for each category of criteria were analyzed.
Identification of decision criteria from the literature review
Studies identified in the literature and included in the analysis
Studies reporting on decision criteria
Studies describing a decisionmaking tool
Type of study and level of decisionmaking*
1. Andreae et al. , 2009
1. Bowen et al. , 2005
2. Asante et al. , 2009
Interviews, meso & macro
2. Browman et al. , 2008
3. Baltussen et al. , 2007
Focus group, macro
3. Ghaffar et al. , 2010
4. Baltussen et al. , 2006
Focus group, meso & macro
5. Baltussen et al. , 2006
5. Golan et al. , 2010
6. Dionne et al. , 2009
6. Hailey et al. , 2009
7. Dolan et al. , 2010
7. Honore et al. , 2010
8. Duthie et al. , 1997
Interviews, micro, meso & macro
8. Johnson et al. , 2009
9. Gibson et al. , 2006
Focus group & interviews, meso & macro
9. Kirby et al. , 2008
10. Hofmann et al. , 2005
10. Meagher et al. , 2010
11. Irving et al. , 2010
11. Menon et al. , 2010
12. Jehu-Appiah et al. , 2008
Focus group, macro
12. Tannahill et al. , 2008
13. Kapiriri et al. , 2009
Interviews, micro, meso & macro
13. The University of York , 2002
14. Koopmanschap et al. , 2010
Focus group, macro
14. Wilson et al. , 2006
15. Lasry et al. , 2010
16. Lehoux et al. , 2007
17. Lopert et al. , 2009
Focus group, macro
18. Martin et al. , 2001
Focus group, macro
19. Mitton et al. , 2006
Focus group, macro
20. Mullen et al. , 2004
21. Noorani et al. , 2007
Literature review and interviews, macro
22. Saarni et al. , 2008
Consensus procedure, macro
23. Vuorenkoski et al. , 2008
24. Wilson et al. , 2007
Focus group, macro
25. Wirtz et al. , 2005
26. Youngkong et al. , 2009
Decision criteria classification and descriptive statistics
Classification of terms reported in the literature
Categories of classification system
Criteria of classification system
Terms used in articles
A-Health outcomes and benefits of intervention
Number of criteria: 6
Number of terms: 44
A1: Health benefits: 7 terms, cited 10 times
A2: Efficacy/effectiveness: 11 terms, cited 29 times
· A2 – efficacy [13, 47], efficacy/effectiveness [10, 19, 20, 25, 27, 28, 44, 48], effectiveness [14, 22, 26, 32–34, 48], clinical benefit [19, 22, 24, 42, 47], clinical impact , clinical merit , relative clinical benefit in relation with current standards , determine relative value for degree of benefit against benchmarks , magnitude of treatment effect , response rate , onset and duration of treatment/program effect 
A3: Life saving: 4 terms, cited 5 times
A4: Safety: 11 terms, 19 times
· A4 – side effects [33, 41, 47], unintended consequences , safety [9, 22, 26, 31], safety and tolerability [10, 19, 20], risks [20, 22], risk management , harm , adverse effects , inconvenience , risk of event , reduction in symptomatic toxicity compared with standard therapy 
A5: PRO: 10 terms, 17 times
· A5 – patients reported outcomes , quality of life [19, 42, 44, 52], impact on quality of life [22, 43], number of QALYs gained per patient [36, 39], disability adjusted life years , likely impact on patient , patient preference , patient autonomy [26, 35, 40], relative value to patient , best for patient 
A6: Quality of care: 1 term, 1 time
· A6 – overall gain in quality of care 
B-Type of health benefit
Number of criteria: 2
Number of terms: 12
B1: Population effect (prevention): 6 terms, 11 times
B2: Individual effect (medical service): 6 terms, 7 times
· B2 – type of medical service , relief/prevention of symptoms/complications of disease , health gain or maintenance , individual effects , individual impact and benefit [13, 33], the composition of the health gain 
C-Impact of the disease targeted by intervention
Number of criteria: 4
Number of terms: 21
C1: Disease severity: 2 terms, 9 times
C2: Disease determinants: 2 terms, 2 times
C3: Disease burden: 7 terms, 13 times
· C3 – burden of disease [9, 13, 22, 33], disease burden [17, 25, 45, 48], burden of illness , burden of therapy , cost to treat disease , cost to prevent disease , national cost of the disease/condition to the healthcare system 
C4: Epidemiology: 10 terms, 16 times
· C4 – prevalence [9, 13], number of potential beneficiaries [35, 37, 40], indirect beneficiaries , size of population [10, 19], prevalence and incidence of disease [23, 25, 43], number of residents benefiting , number of clients served , number of patients , social/demographics , incidence 
D-Therapeutic context of intervention
Number of criteria: 4
Number of terms: 18
D1: Treatment alternatives: 5 terms, 13 times
· D1 – treatment alternatives [13, 22], availability of alternatives [16, 19, 25, 42, 44, 47], availability of effective intervention and preventable , alternatives [35, 40, 45], benchmark comparators 
D2: Need: 8 terms, 16 times
· D2 – comparative interventions limitations (unmet needs) , need [19, 22, 28, 38, 42, 44, 49], clinical impact (need and trends) , emergencies and need , apparent need , clinical need [36, 41, 50], desirability of effects , meets patient’s basic need 
D3: Clinical guidelines & practices: 4 terms, 7 times
D4: Pre-existing use: 1 term, 1 time
· D4 – pre-existing prescribing of the drug 
E-Economic impact of intervention
Number of criteria: 9
Number of terms: 36
E1: Cost: 3 terms, 11 times
E2: Budget impact: 6 terms, 11 times
· E2 – budget impact on health plan [10, 19, 25, 47], total budget impact , budget impact [32, 45, 47], usage and cost implications of competing new drugs if approved , affordability , operating and start-up costs 
E3: Broad financial impact: 7 terms, 7 times
· E3 – impact on other spending , financial impact on government , economic impact , economics , national medical costs per-year , cost-saving , national saving in costs of absence per year 
E4: Poverty reduction: 1 terms, 3 times
E5: Cost-effectiveness: 5 terms, 23 times
· E5 – cost-effectiveness [9, 10, 13, 14, 17, 20, 22, 25–27, 30, 34, 37, 39, 41, 44], economic evaluations , cost and consequences [9, 13, 14, 41], pharmacoeconomic analysis , cost utility expressed as cost per QALY 
E6: Value: 2 terms, 3 times
E7: Efficiency and opportunity costs: 6 terms, 10 times
· E7 – efficiency of intervention , efficiency [10, 19, 22, 23, 44], opportunity costs , opportunity costs to the population/society , best within available resources , interdependencies 
E8: Resources: 5 terms, 6 times
E9: Insurance premiums: 1 term, 1 time
· E9 – impact on health insurance premiums 
F-Quality and uncertainty of evidence
Number of criteria: 6
Number of terms: 34
F1: Evidence available: 7 terms, 9 times
· F1 – evidence [22, 42, 45], proof , scientific evidence , current level of knowledge , time of assessment in technology development , timelines of review , therapy mechanism of action 
F2: Strength of evidence: 14 terms, 20 times
· F2 – strength of evidence [16, 44], quality of evidence , quality of data and past decisions , quality of data , quality , validity of evidence [10, 19], related degree of knowledge certainty , certainty , consistency [19, 22, 44], consistent , completeness and consistency of reporting evidence , openness [26, 44], selection of studies [35, 40], precision of treatment effect 
F3: Relevance of evidence: 5 terms, 8 times
· F3 – relevance of evidence [10, 19], representativeness of users (studies vs. real world) [35, 40], level of generalization [35, 40], effectiveness in real practice , evidence of effectiveness 
F4: Evidence characteristics: 5 terms, 7 times
· F4 – normative characteristics of study [35, 40], choice of endpoints [35, 40], clinical trial data , multiple randomized trials or meta-analysis/single randomized trial of reasonable size/small randomized trial , phase II 
F5: Research ethics: 2 terms, 4 times
F6: Evidence requirements: 1 term, 1 time
· F6 – adherence to requirement of decision making body 
G-Implementation complexity of intervention
Number of criteria: 9
Number of terms: 57
G1: Legislation: 6 terms, 6 times
G2: Organizational requirements and capacity to implement: 15 terms, 17 times
· G2 – system requirements , physical environment , environment [22, 26], system capacity , local capacity , ability to implement , implementation , organization’s structure , organizational burden , logistics , process , well-organized , organizational feasibility [22, 25], feasibility of delivery , deliverability 
G3: Skills: 6 terms, 6 times
· G3 – knowledge and skills , nature of staff , clinical education and training , human resources availability , recruitment and retention of staff , attracting/retaining scarce clinical staff 
G4: Flexibility of implementation: 7 terms, 8 times
G5: Characteristics of intervention: 6 terms, 8 times
G6: Appropriate use: 3 terms, 3 times
G7: Barriers and acceptability: 3 terms, 4 times
G8: Integration and system efficiencies: 9 terms, 9 times
· G8 – system integration (best use of elements of healthcare system) , integration into local community , ease of integration , impact on other services , links to other services , compatibility , reduction of the monitoring , reduction of waiting list size , impact 
G9: Sustainability: 2 terms, 4 times
H-Priorities, fairness and ethics
Number of criteria: 7
Number of terms: 55
H1 Population priorities: 5 terms, 5 times
H2 : Access: 10 terms, 17 times
· H2 – population access , access [19, 27, 47, 49], equity of access improvement , access to care easier [31, 33, 34], distribution and access to healthcare [35, 40], accessibility [22, 44], equity of access , access to health system , geographical equity , timeliness of access 
H3 : Vulnerable and needy population: 9 terms, 11 times
· H3 – vulnerable population [37, 38], potential victims , particular social groups with high risk and/or increased vulnerability , compassion for the vulnerable , particularly needy/vulnerable groups , age of targeted group [13, 30], maternal mortality , quality of maternity care services , population equity 
H4: Equity, fairness and justice: 12 terms, 32 times
· H4 – equity [8, 13, 14, 19, 22, 25, 27, 40, 44, 46, 48], fairness [10, 14, 40, 44, 47], health equity [23, 26], equality [19, 26, 38], distributive justice [23, 25], formal justice , social justice , justice [26, 46], social injustice , addressing health status inequalities at a population level , human integrity and dignity [35, 40], basic human rights 
H5 : Utility: 2 terms, 3 times
H6: Solidarity: 6 terms, 8 times
H7: Ethics and moral aspects: 11 terms, 14 times
· H7 – ethics [14, 22], ethical values , values , values and beliefs , consistency with societal values , ethical implications , moral obligation to implement a technology [35, 40], rule of rescue , priority to basic and necessary care , moral consequence of HTA [35, 40], moral challenges related to certain components of HTA 
Number of criteria: 11
Number of terms: 83
I1: Mission and mandate of health system: 13 terms, 19 times
· I1 – goals of healthcare [52, 53], goals , beneficence , non-maleficience and justice , beneficence/non-maleficience [17, 26, 53], strategic fit [9, 23], medical and social worth , relevance , present social consensus, [17, 49] consensus regarding public funding of a therapy [17, 53], government mandate , national standards , healthcare context positioning 
I2: Overall priorities: 6 terms, 6 times
I3: Financial constraints: 8 terms, 13 times
· I3 – budget constraints [13, 33, 45], cost-containment [42, 49], budget level [13, 19, 45], social economical context , limited provincial health resources , budget implementation challenges , economic feasibility , reliance of other services/sectors(on investment) 
I4: Incentives: 4 terms, 5 times
I5: Political aspects: 5 terms, 7 times
I6: Historical aspects: 3 terms, 3 times
I7: Cultural aspects: 7 terms, 10 times
· I7 – culture and religious convictions [19, 28, 47], stigma , compatibility with values , challenge of social and values arrangements [28, 47], conception of certain persons or disease , psychosocial implications , public preference 
I8: Innovation: 3 terms, 3 times
I9: Partnership and leadership: 8 terms, 9 times
· I9 – partnership and networking , partnerships , maintaining relationship , leadership , community development , academic commitments: research and education [9, 23], partnership and collaboration across organizations , contribution to position as a learning organization 
I10: Citizen involvement: 3 terms, 3 times
I11: Stakeholders interests and pressures: 23 terms, 28 times
· I11-stakeholders pressure , advocacy [16, 45], pressure from physician and patients groups and past decisions , clinical expert opinions , patient representative group opinions , power relations among stakeholders , user of the technology interests , challenge the relationship between patient and physician , professional prestige [28, 47], clinicians excitement and decisions in other hospitals , public reaction and public accountability , HTA’s producer interest [28, 47], company activities , researchers ethics interests [28, 47], third party agents involved , recommendations made by other countries , status in other jurisdictions , current status of public funding in other jurisdictions , drugs used in other hospitals , expressed demand [14, 37], patient demand , expected level of interest (patient and medical) , entitlement 
This literature review revealed a burgeoning number of studies examining healthcare decision criteria and criteria-based decisionmaking tools, especially over the last five years. Criteria were identified from studies performed in several regions of the world involving decisionmakers at micro, meso and macro levels of decision and from studies reporting on multicriteria tools. Increasingly, the healthcare community is aware that beyond cost-effectiveness, other criteria must be taken explicitly into account for transparent and consistent healthcare decisionmaking and priority-setting [54–56]. Indeed, elucidating decision criteria and how they are considered are key to establishing accountability and reasonableness of decisions. This is necessary to fulfill the relevance condition of the accountability for reasonableness (A4R) framework of Daniels and Sabin , which states that “Decisions should be made on the basis of reasons (i.e. evidence, principles, values, arguments) that ‘fair-minded’ stakeholders can agree are relevant under the circumstances”.
This analysis revealed a predominance of normative criteria, that is, answering the question “what should be done?” This highlights the importance of considering the actual worth or value of healthcare interventions rather than just feasibility criteria, (“What can be done?”). Of the ten most frequently cited criteria, eight were normative (equity and fairness, efficacy, cost-effectiveness, strength of evidence, safety, mission and mandate of healthcare system, need, patient-reported outcomes) and two were feasibility criteria (stakeholder pressures and interests, organizational requirements and capacity). This is aligned with a review of studies on decision criteria in developing countries , and points to the need to include both normative and feasibility criteria in decision and prioritization tools to fully reflect and support the decisionmaking process.
The criterion “equity and fairness” was the most frequently reported. This may reflect that equity is a guiding principle in defining the values on which decisions are based. Equity is difficult to operationalize in decisionmaking and priority-setting processes in a pragmatic manner. It is a complex ethical concept that eludes precise definition and is synonymous with social justice and fairness . It is referred to as “a fair chance for all,”  “equality of access to healthcare resources on the basis of need,”  “absence of systematic disparities in health (or in the major social determinants of health) between groups with different levels of underlying social advantage/disadvantage” . The WHO advocates concepts of “horizontal equity, providing healthcare to all those who have the same health need, and vertical equity, providing preferentially to those with the greatest need” . The difficulty of considering equity in a pragmatic manner points to the need to include it systematically as operationalizable criteria in the decision process. If not systematic, it is less likely that decisions will be equitable. Decisions are generally fairest when standards are predetermined, explicit and consistently applied . Equity is embedded in consideration of disease severity in prioritization of healthcare interventions. Decisionmakers generally attach more value to interventions for severe disease than for mild disease. This is also translated in the worst-off principle, which relates to an independent concern for severity; “the worse off an individual would be without an intervention, the more highly society tends to value that intervention” . Systematic consideration of criteria defined on the basis of population priorities identified by decisionmakers (e.g., more value for interventions targeted to vulnerable populations such as children, the elderly, those in remote areas) is another pragmatic way to incorporate equity into decisionmaking. Integration of ethical considerations in operationalizable criteria was developed for the comprehensive multicriteria framework EVIDEM . Ethical issues are an integral part of the EUnetHTA core model to ensure their explicit considerations , and several frameworks focusing on equity  and ethical issues  have recently emerged.
Efficacy/effectiveness was the second most frequently reported criterion; as Hawkes discussed recently, “governments are wrestling with the issues of efficacy and fairness in healthcare delivery” . While efficacy measures the effect of an intervention treatment under controlled conditions (such as during clinical trials), effectiveness provides critical information on outcomes actually achieved by an intervention in real life settings. Efficacy and effectiveness are fundamental criteria considered at the regulatory (e.g., FDA, EMA) and reimbursement levels for medicines in many jurisdictions [65–67]. Because decisions concerning interventions at policy, clinical and patient level are made with reference to a given context of care (usually standard of care), improvement over existing care rather than absolute efficacy or effectiveness provides the most informative evidence . Indeed, decisions about usefulness of interventions are usually based on relative advantage compared to existing approaches . Comparative effectiveness, “the comparative assessment of interventions in routine practice settings”  is meant to help answer the question “does it work in my context?” and is demand-driven research aimed directly at decisionmaker needs . For new interventions, however, effectiveness data is usually not available and decisions are often made on the basis of efficacy data, with the uncertainty inherent in innovation . Evidence-based decisionmaking relies on actual benefits derived from an intervention so mechanisms (such as defining subcriteria) outlining specifically the most relevant outcomes of efficacy/effectiveness in real life are critical to ensure that the dimensions of efficacy/effectiveness are fully captured and communicated.
The third most commonly reported criterion refers to stakeholder interests and pressures. Macro-level decisions are influenced by public pressure and advocacy [13, 15, 38] and the demand for a new program is a powerful argument for decisionmakers at the political level . In a study exploring the basis for immunization recommendations, while vaccine safety was reported as important or very important in making immunization recommendations by all countries regardless of economic status, low and lower middle income countries were significantly more likely than developed countries to report that public pressure was an important factor . Because pressures from groups of stakeholders are often part of the context , being aware of pressures and interests at stake and how they may affect decisionmaking and implementation is important and should be explicitly tackled using a framework that encourage systematic consideration of their potential implications when making healthcare decisions.
Cost-effectiveness was the fourth most commonly reported criterion. Cost-effectiveness is frequently used in healthcare decisionmaking [65, 71] but its usefulness is the subject of debate [54, 56]. A review of 36 empirical studies reported that the influence of cost-effectiveness was moderate at micro, meso and macro levels of decision . Designed to incorporate several criteria of decision (e.g., cost, efficacy/effectiveness, safety, quality of life) into an aggregated ratio allowing comparisons of interventions, it fails to include important criteria such as equity and the severity of the targeted condition . In addition, cost-effectiveness thresholds are commonly mistaken for affordability thresholds . Beyond cost-effectiveness ratios, health economic studies generate data that are necessary to evaluate healthcare interventions (e.g., resource utilization and cost consequences of a new intervention compared to existing care).
This study also revealed that strength of evidence is an important aspect in decisionmaking, highlighting the influence of evidence-based medicine. Evidence is usually sought to demonstrate effectiveness (“it works”), show the need for policy action (“it solves a problem”), guide effective implementation (“it can be done”), and clarify cost-effectiveness (“it provides value for money”) . The quality of evidence that decisionmakers use can only be determined when several concepts are considered, such as scientific validity, completeness and relevance to the decisionmaking context . The strength of evidence builds with time as interventions are used in real life and initial decisions made in a context of uncertainty (e.g., randomized clinical trial data in limited populations) may be revisited as evidence accumulates. A common question is how much evidence is enough to make an evidence-based decision . Beyond scientific evidence, decisionmaking also relies on colloquial evidence . Consideration of strength and quality of the different types of evidence remain an important part of the appraisal of interventions.
Safety, a critical element of policy and clinical practice, was the sixth most cited criterion. Safety refers to the frequency and severity of adverse events or complications arising as a result of using the new technology compared to an alternative . Efficacy and safety are the main criteria in the initial evaluation of a new intervention . And the risk-to-benefit equation is a critical component of clinical and regulatory decisionmaking .
A number of other criteria were identified highlighting the complexity of healthcare decisionmaking and the need to support this process with tools to ensure consistency, transparency and accountability for reasonableness. An important milestone towards that goal would be to harmonize terminology. Indeed, a large variety of terminology was found in the literature during analysis and classification of criteria. Although a systematic approach was used to classify terms into criteria and overarching categories using the principles of MCDA, such analyses are limited by the subjective interpretation of terms reported by authors. For example, the terms reported in published studies such as “side effects,” “unintended consequences,” “risks,” “harm,” or “adverse effects” were all grouped under the criterion “Safety.” These variations of terminology underline the difficulty of harmonizing the decisionmaking processes, as several authors have noted [10, 11]. It calls for well-defined criteria to avoid confusion and ensure sound application of multicriteria approaches to decisionmaking [11, 73].
Although this analysis was limited to published studies, an extensive analysis of decisionmaking processes from jurisdictions around the world for coverage of healthcare interventions was performed to define the criteria of the EVIDEM framework, which are included in this analysis [10, 18]. In addition, the large number of terms retrieved covers criteria currently used in more than 25 decisionmaking processes for coverage of medicines .
This study highlights the importance of considering both normative and feasibility criteria for decisionmaking and priority setting of healthcare interventions. By providing a comprehensive classification of decisionmaking criteria, this analysis can promote reflection on the value of harmonizing terminology in this field. It can also serve as a resource when considering which criteria to include in sound multicriteria approaches (i.e., fulfilling principles of completeness, lack of redundancy, mutual independence, operationalizability and clustering). This analysis is also used as a foundation for the development of an international survey on criteria expected to further expand our knowledge of real-life decisionmaking and advance multicriteria approaches.
Such approaches have the potential to integrate and facilitate pragmatic operationalization of a large range of considerations, including ethical considerations, in a transparent and consistent process. They could provide a common metric for curative and preventive interventions to clearly define best health improvements within resource available, as recently advocated by Volp and colleagues . They may also provide a road map to develop more participative decisionmaking processes by “better combining of many elements” proposed by Culyer .
This study was partially funded by a grant from the Canadian Institutes of Health Research (CIHR # 228208).
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.