The quality of reporting methods and results of cost-effectiveness analyses in Spain: a methodological systematic review

Background Cost-effectiveness analysis has been recognized as an important tool to determine the efficiency of healthcare interventions and services. There is a need for evaluating the reporting of methods and results of cost-effectiveness analyses and establishing their validity. We describe and examine reporting characteristics of methods and results of cost-effectiveness analyses conducted in Spain during more than two decades. Methods A methodological systematic review was conducted with the information obtained through an updated literature review in PubMed and complementary databases (e.g. Scopus, ISI Web of Science, National Health Service Economic Evaluation Database (NHS EED) and Health Technology Assessment (HTA) databases from Centre for Reviews and Dissemination (CRD), Índice Médico Español (IME) Índice Bibliográfico Español en Ciencias de la Salud (IBECS)). We identified cost-effectiveness analyses conducted in Spain that used quality-adjusted life years (QALYs) as outcome measures (period 1989–December 2014). Two reviewers independently extracted the data from each paper. The data were analysed descriptively. Results In total, 223 studies were included. Very few studies (10; 4.5 %) reported working from a protocol. Most studies (200; 89.7 %) were simulation models and included a median of 1000 patients. Only 105 (47.1 %) studies presented an adequate description of the characteristics of the target population. Most study interventions were categorized as therapeutic (189; 84.8 %) and nearly half (111; 49.8 %) considered an active alternative as the comparator. Effectiveness of data was derived from a single study in 87 (39.0 %) reports, and only few (40; 17.9 %) used evidence synthesis-based estimates. Few studies (42; 18.8 %) reported a full description of methods for QALY calculation. The majority of the studies (147; 65.9 %) reported that the study intervention produced “more costs and more QALYs” than the comparator. Most studies (200; 89.7 %) reported favourable conclusions. Main funding source was the private for-profit sector (135; 60.5 %). Conflicts of interest were not disclosed in 88 (39.5 %) studies. Conclusions This methodological review reflects that reporting of several important aspects of methods and results are frequently missing in published cost-effectiveness analyses. Without full and transparent reporting of how studies were designed and conducted, it is difficult to assess the validity of study findings and conclusions. Electronic supplementary material The online version of this article (doi:10.1186/s13643-015-0181-5) contains supplementary material, which is available to authorized users.


Background
Cost-effectiveness analysis has been recognized as an important tool to assist clinicians, scientists and policymakers in determining the efficiency of healthcare interventions, guiding societal decision-making on the financing of healthcare services and establishing research priorities. Given that the information provided by cost-effectiveness analysis has the potential to impact population health and health services, there is a need for evaluating the reporting of methods and results of cost-effectiveness analyses and establishing their validity to inform policymaking [1][2][3][4].
Diverse approaches to synthesize evidence have been considered in biomedical research [5][6][7][8], including economic evaluations of healthcare interventions [9][10][11][12][13][14][15][16]. At the same time, decision-making in health care requires an understanding of the state of economic evaluation at a national level, where the completeness of the reporting is generally less well understood but where specific priorities are often set. As a way of understanding the maturity and growth of the field, several smaller studies have examined a limited set of reporting characteristics of cost-effectiveness analyses published in Spain [17][18][19][20]. Spain was a pioneer in proposing the standardization and reporting of methodology applicable to costeffectiveness analysis [21,22]. However, the institutional and regulatory framework has so far not helped the application of the methodology to the public health decisions. The central government of Spain is the main decision-maker in pricing and reimbursement related to new medicines and healthcare technologies, although with a high decentralization of health jurisdictions in several regional health services, but traditionally, there have been no national requirements related to the costeffectiveness for making coverage decisions.
We present herein a case study about reporting practices of economic evaluations of healthcare interventions in one Western European country: Spain. Specifically, this study expands upon previous research [23,24] to comprehensively describe and examine reporting characteristics of methods and results of cost-effectiveness analyses conducted in Spain during more than two decades.

Methods
This methodological systematic review has been reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [25] (see Additional file 1: Table S3). A brief protocol was developed prior to the initiation of this review. It can be acquired by request from the corresponding authors. We did not register the protocol with PROSPERO given that the register does not accept methodological reviews.

Literature search
The results from a previous review that examined collaborative patterns of scientific production in a cohort of cost-effectiveness analyses conducted in Spain within the period 1989-2011 [23] were updated with the studies published until December 2014 and subsequently analysed. A systematic search was performed in PubMed/ MEDLINE and other databases such as Scopus, ISI Web of Science, National Health Service Economic Evaluation Database (NHS EED) and Health Technology Assessment (HTA) databases of the Centre for Reviews and Dissemination (CRD) at the University of York, UK, as well as Índice Médico Español (IME) and Índice Bibliográfico Español en Ciencias de la Salud (IBECS). The search included a broad range of terms related to economic evaluations of healthcare interventions, costeffectiveness analyses and the geographical area "Spain". For the section of geographical area, the search was based on a previously validated filter by Valderas [26] to minimize bias regarding the indexing of geographical items. This filter is constructed around three complementary approaches: (a) the term "Spain" and its variants in various languages; (b) related mainly to region and province place names and (c) acronyms for regional health services. PubMed/MEDLINE and the above mentioned complementary databases were searched from January 1, 2011 to December 31, 2014; the PubMed/ MEDLINE search strategy is provided in an online supplement to this review (see Additional file 1: Table S1). Furthermore, manual searches were made for publicly available reports from the Health Technology Agencies and publications in specialized Spanish journals.

Inclusion criteria and study selection
Our selection of studies was based on cost-effectiveness analyses of healthcare interventions that used qualityadjusted life years (QALYs) as outcome measure (see Table 1 for terminology). In the health economic Table 1 Terminology Cost-effectiveness analysis is a specific form of economic evaluation comparing two or more alternative programmes by measuring costs and consequences. Consequences are measured in natural units (e.g. life years gained or cases averted). Cost-utility analysis is a variant of cost-effectiveness analysis, where consequences are measured in terms of summary measures of population health such as quality-adjusted life years. Cost-effectiveness acceptability curve is a graphical representation of the cost-effectiveness comparison between two interventions and plots the probability that one intervention is more cost-effective than other, as a function of the willingness-to-pay threshold for one additional unit of benefits. Incremental cost-effectiveness ratio (ICER) is the ratio of the change in costs of an intervention (compared to the alternative) to the change in effects of the intervention. Quality-adjusted life years (QALYs) are a measure that combines length of life and quality of life in a single outcome. literature, this type of studies is sometimes known as "cost-utility analyses". We selected this type of costeffectiveness analyses because many scientists and policymakers have recommended the QALY framework as the standard reference for cost-effectiveness [27]. Studies had to be undertaken in the Spanish population. Review studies, editorials, and abstracts of congresses were excluded. If an article was found repeated in several publications, that published earlier (e.g. when there are two or more articles of the same study) and/or published in a journal with higher impact factor (e.g. when there exists a study published in both health technology assessment report and journal manuscript) was included.
All citations of potential relevance identified from the literature search were screened by one reviewer. Two reviewers reviewed all potentially relevant articles in full text. Final inclusion was confirmed if both reviewers felt the study was directly relevant to the objectives of this methodological review. Planned involvement of a third party to deal with unresolved discrepancies was not required.

Data collection
Two reviewers (with expertise in health economics and evidence synthesis) extracted data from each retrieved paper independently. Data were collected using a selfdeveloped item data collection form designed to assess reporting details of the studies. The process of data extraction was piloted in 20 records. A final data extraction form was then agreed. To enable description of the characteristics and the quality of reporting of costeffectiveness analyses in each report, we gathered the following information from all studies: year and journal of publication, impact factor (according to 2014 Journal Citation Report), country of first author, mention of a protocol, study objective, study design (e.g. randomized trial, observational study, simulation model), intervention targeted (e.g. prevention, diagnosis/prognosis, treatment, rehabilitation), type of comparators (e.g. active alternative, do nothing or placebo, usual care), perspective of analysis (in terms of which costs are considered, e.g. society, national healthcare system, hospital, others), type of costs (e.g. direct or indirect) and sources of information, the main cause of disease to which the intervention or health programme was addressed, description of population characteristics, time horizon, sources of clinical effectiveness (e.g. based on a single study or based on systematic reviews and meta-analyses), full description of methods for QALY calculation, discussion of assumptions and validation of models (if applicable), discount rates for costs and outcomes, results for the primary outcome in the base case scenario (e.g. "more costs, more QALYs", "less costs, more QALYs", "less costs, comparable QALYs"), incremental analyses including incremental cost-effectiveness ratios (ICERs), uncertainty measures (e.g. confidence intervals, acceptability curves), sensitivity analyses, limitations of study, comparison of results with those of other studies, hypothetical willingness-to-pay threshold and study conclusions. Conclusions reported in the published article were defined as follows: favourable if the intervention was clearly claimed to be the preferred choice (e.g. cited as "cost-effective", "reduced costs", "produced cost savings", "an affordable option", "value for money"); unfavourable if the final comments were negative (e.g. the intervention is "unlikely to be cost-effective", "produced higher costs", "is economically unattractive" or "exceeded conventional thresholds of willingness to pay"); and neutral or uncertain when the intervention of interest did not surpass the comparator and/or when some uncertainty was expressed in the conclusions. Disclosures of funding source, conflicts of interest and authors' contributions were also evaluated.

Statistical analysis
A descriptive analysis was performed using frequency and percentage counts. All calculations were performed using Stata (Version 13, StataCorp LP, College Station, TX, USA).

Search
The flow diagram in Additional file 1: Figure S1 presents the process of study selection.
Eight out of 131 identified studies from the cohort of cost-effectiveness analysis conducted within the period 1989-2011 [23] were excluded for not meeting the defined criteria. Our updated search identified 2014 records. Initial screening excluded 1914 records. The remaining 100 full-text articles were assessed for additional scrutiny, of which 21 where ineligible. Complementary searches through other sources (e.g. publicly available reports from the Health Technology Agencies and publications in specialized Spanish journals) identified 21 additional studies and were added to the previously identified, obtaining a total sample of 223 studies (see Additional file 1: Table S2).

General characteristics
The 223 studies were published in 98 journals (206; 92.4 %) or assessment reports by the health technology assessment agencies (17; 7.6 %). The majority of the journals published only one cost-effectiveness analysis although 15 journals each published four or more studies (Table 2). Most studies were published in journals with impact factors ≤5.0 and only four studies were published in journals with impact factor >10. The number of studies increased exponentially over the study period (Additional file 1: Figure S2), with nearly half of the cost-effectiveness analyses published during 2011-2014 (110; 49.3 %). More than half (127; 57.0 %) of the reports were written in English. The studies included a median of six authors although 44 (19.7 %) were authored by eight or more authors and only 3 (1.3 %) reports were single authored. The majority of the interventions were classified as treatments (189; 84.8 %)-of which more than 75 % (143/189) were pharmaceuticals. Cardiovascular diseases (47; 21.1 %) and malignant neoplasms (36; 16.1 %) were the disease conditions most commonly studied. Table 3 provides a summary of the descriptive and reporting characteristics of the included studies. The majority of the study reports used the specific terms "cost-effectiveness" or "cost-utility analysis" in the title (181; 81.2 %) and presented clearly the study question (187; 83.9 %). However, only 10 studies (4.5 %) reported working from a protocol-of which 7 were randomized controlled trials, 2 were simulation models and 1 was an observational study.

Reporting characteristics of methods and results
Of the identified studies, 200 (89.7 %) were model-based being Markov models as the most frequently reported (135; 60.5 %). A minimal number of non-model-based studies were randomized controlled trials (10; 4.5 %).
Overall, most of the analyses were conducted in the adult population (170; 76.    Effectiveness of data was derived from a single study in 87 (39.0 %) analyses. Only 40 (17.9 %) used evidence synthesis-based estimates (e.g. systematic reviews and meta-analyses).
The methods that were reported for calculating QALYs are detailed in Table 4 (161) of studies discounted both costs and QALYs. Of the studies with a time horizon greater than 1 year (Table 5), the most commonly used was a 3 % discount rate.
In terms of results (  ) reported a willingness-to-pay curve ("costeffectiveness acceptability curve") to contrast the results of the analyses against an arbitrary efficiency threshold. Overall, 90.1 % (201) of studies reported sensitivity analyses. About half of the studies (110; 49.3 %) conducted a probabilistic sensitivity analysis. The majority of the studies (147; 65.9 %) reported that the study intervention produced "more costs and more QALYs" than the alternative comparator for the primary outcome of the base case scenario. Sixty-three (28.3 %) studies reported that the intervention was a dominant strategy, that means that the study intervention was "more effective and less costly" than the alternative.

Discussion
In this methodological systematic review, we identified 223 reports of cost-effectiveness analyses conducted in Spain over the period 1989-2014. Overall, the studies covered a wide range of disease conditions but predominantly addressed questions about the efficiency of therapeutic interventions. Our review, as well as other previously published reviews [11][12][13][14], showed that the quality of reporting of cost-effectiveness analyses varies widely and, in many cases, essential components of reporting methods and results were missing in published reports, such as the use of study protocols, the adequate description of patient characteristics, the measurement of clinical effectiveness using a systematic review process or the adequate description of QALY calculation.
Our study suggests the need for improvement in several aspects of published cost-effectiveness analyses. An important element in assessing research conduct and reporting is the study protocol. As showed in this review, only 4 % of studies reported working from a protocol. Study protocols play an essential role in planning, conduct, interpretation, and external review of primary studies, but also in evidence synthesis of primary research. For example, the preparation and publication of a well-written protocol may reduce arbitrariness in decision-making when extracting and using data from primary research for populating health economic models. When clearly reported protocols are made available, they enable readers to identify deviations from planned methods and whether they bias the interpretation of results and conclusions [28,29]. International registries (such as ClinicalTrials.gov for clinical trials and PROSPERO for systematic reviews and metaanalysis) are now a reality. Similarly, in recent years, reporting guidelines for protocols have been endorsed and implemented (e.g. Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) for protocols of clinical trials [28] and PRISMA for protocols (PRISMA-P) of systematic reviews [29]). However, in view of our results, this revolution has not occurred yet in the field of cost-effectiveness research and, thus, could warrant further pragmatic action. Many cost-effectiveness analyses (about 53 %) did not report detailed information on baseline clinical characteristics (e.g. eligibility and exclusion criteria of participants, the severity of disease, the stage in the natural history of the disease, comorbidities). Inadequate reporting of the characteristics of the target population is a far greater barrier to the assessment of the study's generalizability (applicability) and relevance to decision-making [30][31][32]. It is possible that this poor reporting reflects a major problem in secondary publications, such as many cost-effectiveness analyses using simulation models. Given that a clear understanding of these elements is required to judge to whom the results of a study apply (as the Consolidated Standards of Reporting Trials (CONSORT) [31,32] statement underlines for randomized controlled trials), this information should also be provided in the report of cost-effectiveness analyses (e.g. in main text or in online supplement when allowed).
The vast majority (about 90 %) of published costeffectiveness analyses used decision modelling as the main methodology. Decision modelling is considered a methodological approach of evidence synthesis that reaches beyond the scope of systematic reviews and meta-analyses. It is essential for cost-effectiveness research to use all relevant evidence on the effectiveness of interventions under evaluation. Rarely will all relevant evidence come from a single study, and typically, it will have to be drawn from several clinical studies [33]. A disappointing result of this review is that few published studies reported the use of a systematic review process for the measurement of clinical effectiveness. While systematic reviews and meta-analyses are considered to be the gold standard in knowledge synthesis, only 18 % of published cost-effectiveness analyses used evidence synthesis-based estimates of effect. Instead, 43 % of the studies make arbitrary decisions about what studies to use to inform effectiveness data, whereas 39 % of the studies reported that the effectiveness data derived from a single study (generally, without a clear description of why the single study was a sufficient source of all relevant clinical evidence). The use of QALYs is recognized as the main valuation technique to measure health outcomes in cost-effectiveness analyses. However, in our review, it was also troubling that few studies (19 %) reported a full description of methods for QALY estimation, thus potentially impairing confidence in the results and conclusions. Future studies should be transparent in reporting these important aspects.
Strong evidence of publication bias and other potential sources of bias have been reported in biomedical research [34][35][36][37][38]. For example, randomized controlled trials with "positive" findings are published more often, and more quickly, than trials with "negative" findings [37]. Similarly, empirical studies have detected that most published cost-effectiveness analyses report favourable findings [38]. In our review, very few published studies (about 10 %) reported unfavourable or neutral conclusions. Although it is somewhat premature to comment on this finding, this could be indicative of potential biases, such as publication bias or even potential screening a priori that may have been performed by the producers of studies, which would make that costeffectiveness analyses would have been only conducted in cases where a "positive" result was expected. In our opinion, this issue requires further investigation.
Several reporting guidelines are available and endorsed for many types of biomedical research [25,28,29,31,39] but also for cost-effectiveness analyses [40][41][42][43][44][45][46]. Such tools promote the consistent reporting of a minimal set of information for scientists and researchers reporting studies and the editors and peer reviewers assessing them for publication. Endorsement of reporting guidelines by journals for randomized controlled trials [47] and systematic reviews [48] has been shown to improve the quality of reporting. The incorporation of reporting guidelines within the peer-review process could potentially contribute to improvements in the quality of reports of cost-effectiveness analyses. On this regard, the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement [40] has been proposed as an attempt to consolidate and update previous efforts [41][42][43][44][45][46] into a single useful reporting guideline for costeffectiveness research. Authors, peer reviewers and editors can promote reporting guideline endorsement and implementation as an important way to improve transparency and completeness of what they published, reducing waste in reporting research and increasing value [49,50] of cost-effectiveness research.
Our study has several limitations. First, although the review has been drawn from an exhaustive review of original reports of cost-effectiveness analyses, it is possible that the search missed some articles with relevant elements or that some studies conducted may not have been published. In addition, for some reports repeated in several publications, our approach was the inclusion of those published in a journal with higher impact factor and/or published earlier [23,24]. Thus, the decision to use report level instead treating the study as the unit of analysis may have limited the collection of all the reporting characteristics from multiple reports of the same study (where there exist). Second, we restricted our analysis to cost-effectiveness analyses that used QALYs as health outcome measure (namely, cost-utility analyses). In a previous descriptive analysis of economic evaluations conducted in Spain [24], only about 15 % are costutility analyses. It would be interesting to explore whether other forms of economic evaluations using alternative outcome measures results in similar reporting patterns. Third, we relied upon the expertise and experience of our authorship team and on existing documents [16,22] to identify core items related to the conduct and reporting that we would like to see (in the position of potential readers) in any published cost-effectiveness analysis. Given the dynamic nature of research, some opportunities for future research and development could be the impact assessment of a specific reporting guideline (such as the CHEERS statement [40]) and/or local recommendations on the reporting quality of published studies [51]. Fourth, the extent of the reporting of costeffectiveness analyses was limited to the information publicly available in the corresponding report (and online data supplements when available). There were no further inquiries or attempts to verify the data sources and tools used in the studies and only information about reporting characteristics was taken into account in the review, without considering other possible sources (e.g. contacting authors and/or their sponsors).

Conclusions
We presented a national case study for more generalizable discussions about quality and transparency issues of reporting cost-effectiveness analyses, likely to be of interest to authors, peer reviewers and editors-but also research funders and regulators-both within and beyond Spain. Based on the existing evidence, several deficiencies in the reporting of important aspects of methods and results are apparent in published costeffectiveness analyses.
Our study raises challenges for increasing value and reducing waste in cost-effectiveness research. Without full and transparent reporting of how studies were designed and conducted, it is difficult to assess validity of study findings and conclusions of published studies. This review also reinforces the need to improve mechanisms of peer review and publication process of costeffectiveness research.

Additional file
Additional file 1: Reporting methods and results of CEA Spain_annex. Table S1. PubMed/MEDLINE search strategy. Table S2. Included studies. Table S3. PRISMA Checklist. Figure S1. Flow diagram for study selection.