Economic Evaluation Of Health Care Research Articles

Evaluation of Reporting Quality of Systematic Reviews on Health Economic Evaluation Studies Based on the CHEERS Statement: An Overview of Reviews.

Economic evaluations in healthcare are designed to inform decisions by the estimation of cost and effect trade-off of two or more interventions. We aimed to evaluate the standards of systematic reviews on health economic evaluation studies using the CHEERS (Consolidated Health Economic Evaluation Report Standards) tool. We searched the PubMed database with keywords CHEERS and its complete form in combination with keywords related to cost or economic evaluation without language and time limits until November 17, 2021. The CHEERS tool was then used to include systematic reviews. Overall, 32 systematic reviews, included 610 primary studies were included. Of the 32 included studies, only 1 study (3.1%) had poor quality, 5 studies (15.6%) had good quality, remaining studies had very good and excellent quality. Some studies still have problems in expressing the standards. The necessity of standards for reporting economic evaluation studies in the field of health is very serious, and Cheers is one of the most important tools.

Equity in national healthcare economic evaluation guidelines: Essential or extraneous?

BackgroundThe focus on health maximisation in a healthcare economic evaluation (HEE) – that is health gains are of equal value regardless of the recipient– has significant implications as health systems attempt to address persistent and growing health inequities. This study aimed to systematically compare and contrast the equity principles of different health technology assessment (HTA) agencies and how equity is addressed in HEE guidelines. MethodsHTA agencies were identified through the ISPOR, GEAR, iDSI, HTAi, INAHTA, HTAsiaLink, and RedETSA websites in June 2021 and updated in August 2023. Agencies websites were then searched to retrieve HEE guidelines. The guidelines were grouped into two categories: well-established and newly-developed agency guidelines, based on whether or not they published their first guidelines before 2009. Data extracted summarised the methodological details in the reference cases, including specifics on how equity featured and in what role. In those agencies where equity did not feature explicitly in the HEE guidelines, an additional search of the agency website was undertaken to understand if equity featured in those agencies’ decision-making frameworks. ResultsThe study included 46 guidelines from 51 countries. Only 30% of the guidelines were explicit about the equity assumptions. Health equity (using a broad definition) was mentioned in 29 guidelines and 14 included a specific definition while only seven recommended specific methods to incorporate inequalities. Addressing equity concerns was usually suggested as an additional analyses rather than a key part of the assessment. It was unclear how equity was incorporated into decision-making processes. In addition, equity was mentioned in other guidance – such as decision-making frameworks - provided by five agencies that did not mention it in the HEE guidelines, and 7 of 14 topic selection criteria that were identified. ConclusionEquity is given less attention than efficiency in HEE guidelines. This indicates that HTA agencies while subscribing to an extra-welfarist approach have a narrow evaluative space – focusing on maximising health and not considering the opportunity cost of the equity constraint. The omission of equity and the lack of systematic approaches in guidelines poses a threat to the international endeavours to reduce inequities. It is timely for HTA agencies to reconsider their positions on equity explicitly.

A multi-criteria decision analysis framework that prioritizes economic policy to enhance value based health care during the COVID-19 pandemic

ObjectiveTo investigate pandemic impacts on Value-Based Health Care (VBHC) globally, using multi-criteria decision analysis (MCDA) to address challenges through prioritizing economic policies.MethodsPreferred Reporting Items for Systematic reviews and Meta Analyses extension for Scoping-Reviews (PRISMA-ScR), PUBMED, Medline, and google-scholar were used to analyze pandemic impacts on VBHC domains. MCDA prioritized economic policies, utilizing the value-measurement model with additive-weighted scores. The criteria weighting-method used direct-rating, ranking and robust deliberation by four experts to priority rank economic policies for each VBHC domain.ResultsCOVID-19 impacted on all VBHC domains: Integrated Practice Units, outcome and cost measurement, Value-Based Reimbursement, Information Technology (IT), regional systems integration, geography of care and VBHC policy and institutions. There were changes in patient complexity, service delivery, activity, models of care, pricing, costs, IT, quality, and health status. COVID-19 pricing impacts included increased capacity costs, Personal Protective Equipment costs, cost per patient, service delivery changes, and telehealth costs. A median of 37% of patients globally avoided care, negatively impacting on diabetes, venous thromboembolism, Parkinson’s disease, kidney disease, myocardial infarction, stroke, and cancer patients. A consequence is inaccurate assessments of health status, underestimated projected health needs, and costs for risk-adjustment, impacting health services. Innovations include telehealth and changing service redesign. New care models include state-wide ICU-COVID Models of Care, Telehealth-Inpatient Physician Services, COVID-linked pathology testing, and increased Hospital in the Home. Artificial Intelligence innovations involved patient-screening, triage, risk-evaluation, care assessment, pathways, and laboratories. Risk-adjustment challenges impacted on Value-Based Reimbursement and patient risk-stratification. MCDA prioritized economic policies, including healthcare system performance, healthcare demand and supply, risk-adjustment, planning and market mechanisms, economic evaluation of healthcare, economic sustainability initiatives, and health determinants.ConclusionCOVID-19 demonstrated the limits of health systems globally, with increasing costs and limited budgets. The economic strategies identified can enhance VBHC globally.

Sensitivity to change in well-being and health-related quality of life in adults with eating disorder symptoms: ICECAP-A versus EQ-5D-5L.

Economic evaluations of treatments help to inform decisions on allocating health care resources. These evaluations involve comparing costs and effectiveness in terms of quality of life. To calculate quality-adjusted life years, generic health related quality of life is often used, but is criticized for not being sensitive to change in mental health populations. Another approach, using experienced well-being measured through capabilities with the ICECAP-A, has been proposed as an alternative. The aim of this study was to investigate whether changes in individuals with eating disorder (ED) symptoms can be better captured using health related quality of life (EQ-5D-5L) or well-being (ICECAP-A). Measurements at two time points with an interval of 1 year were used from a sample of 233 participants with self-reported ED symptoms. An analysis of variance was used to test whether the EQ-5D-5L and ICECAP-A differed in sensitivity to change over time. In order to compare the two questionnaires in terms of clinically significant outcome, the reliable change index and clinical cut-off score were calculated. The two questionnaires did not differ in sensitivity to change. More individuals had recovered but also more had deteriorated according to the EQ-5D-5L compared to the ICECAP. The present study revealed no differences in sensitivity to change in health-related quality of life or well-being in individuals with ED symptoms in the context of mild clinical change. Results corroborated the pervasiveness of low quality of life in this population, even after alleviation of ED symptoms. Measuring treatment benefits in terms of improvements in quality of life is an integral part of economic evaluations in health care. It was expected that these treatment benefits would be better captured as changes in well-being (measured with the ICECAP-A) than as changes in health-related quality of life (measured with the EQ-5D-5L) for individuals with ED symptoms. Based on the results of this study, no preference for one of the two approaches was found.

Standardising workforce cost estimates across Australian jurisdictions: genomic testing as a use case.

IntroductionLabour costs are a key driver of healthcare costs and a key component of economic evaluations in healthcare. We undertook the current study to collect information about workforce costs related to clinical genomic testing in Australia, identifying key components of pay scales and contracts, and incorporating these into a matrix to enable modelling of disaggregated costs.MethodsWe undertook a microcosting study of health workforce labour costs in Australia, from a health services perspective. We mapped the genomic testing processes, identifying the relevant workforce. Data was collected on the identified workforce from publicly available pay scales. Estimates were used to model the total cost from a public health services employer perspective, undertaking deterministic and probabilistic sensitivity analyses.ResultsWe identified significant variability in the way in which pay scales and related conditions are both structured and the levels between jurisdictions. The total costs (2023-2024 Australian dollars) ranged from 160,794 (113,848-233,350) for administrative staff to 703,206 (548,011-923,661) for pathology staff (full-time equivalent). Deterministic sensitivity analysis identified that the base salary accounts for the greatest source of uncertainty, from 24.8% (20.0-32.9%) for laboratory technicians to 53.6% (52.8-54.4%) for medical scientists.ConclusionVariations in remuneration levels and conditions between Australian jurisdictions account for considerable variation in the estimated cost of labour and may contribute significantly to the uncertainty of economic assessments of genomic testing and other labour-intensive health technologies. We outline an approach to standardise the collection and estimation of uncertainty for Australian health workforce costs and provide current estimates for labour costs.

Impact of stoma site marking on healthcare costs in patient care

Objective: To analyze the impact of stoma site marking on healthcare costs for patients who underwent marking and those who did not, as well as the subsequent outcomes. Method: We conducted an economic evaluation in healthcare based on retrospective primary data. We obtained the data from the medical records of patients treated at the Health Care Service for Ostomy Patients in Belo Horizonte, Minas Gerais, Brazil, between 2015 and 2021. The sample consisted of 40 patients, with 20 who underwent stoma site marking and 20 who did not. We applied the Mann-Whitney test for independent samples and analyzed the effect size, which was adjusted using Hedge’s g test, considering the risk of low sample power. Results: The study identified an average cost of R$5,201.47 (US$938.19) for the group of patients who did not undergo stoma site marking, which was 23.88% higher than the cost of R$3,959.27 (US$938.19) for the group who did. Most patients were female, with an average age of 60.7 years, married, and of mixed race. Colorectal cancer was the most common cause of stoma creation, while dermatitis was the most frequent complication. We observed that complications led to increased costs. Conclusion: Stoma site marking significantly affects the healthcare costs for individuals with elimination stomas.

EE298 Process and Results of the Third Update of the Dutch Guideline for Economic Evaluations in Healthcare: Evolution Instead of Revolution

EE298 Process and Results of the Third Update of the Dutch Guideline for Economic Evaluations in Healthcare: Evolution Instead of Revolution

Healthcare costs of different treatment options for condylar fractures

ObjectiveAs treatment options for condylar fractures have comparable outcomes, getting insight into associated costs is a first step towards implementing value-based healthcare (VBH). Therefore, we described the actual costs of the different treatment options (surgical, conservative, and expectative treatment) for condylar fractures. We expected surgical treatment to be the most expensive treatment. Study designThis is a cost-of-illness study, based on estimates from the literature. Firstly, care pathways of all treatment options were described. Secondly, the costs per step were calculated based on the literature and Dutch guidelines for economic evaluations in health care. ResultsThe direct treatment costs of surgical treatment (€3721 to €4040) are three to five times higher than conservative treatment (€730 to €1332). When lost productivity costs during the recovery period are included, costs of surgical treatment remain 1.5 times higher (€9511 to €9830 for surgical treatment and €6224 to €6826 for conservative treatment). The costs of expectative treatment (€5436) are lower than both other treatments. ConclusionThe costs for surgical treatment are considerably higher than those for conservative or expectative treatment, mainly related to direct treatment cost. Future research should focus on the patients’ perspective, to support implementation of VBH in treating condylar fractures.

Mapping of disease-specific Oxford Knee Score onto EQ-5D-5L utility index in knee osteoarthritis

BackgroundEQ5D is a generic measure of health. It provides a single index value for health status that can be used in the clinical and economic evaluation of healthcare. Oxford Knee Score (OKS) is a joint-specific outcome measure tool designed to assess symptoms and function in osteoarthritis patients after joint replacement surgery. Though widely used, it has the disadvantage of lacking health index value. To fill the gap between functional and generic questionnaires with economic value, we linked generic EQ-5D-5L to the specific OKS to give a single index value for health status in KOA patients.Questions/purposesDeveloping and evaluating an algorithm to estimate EuroQoL generic health utility scores (EQ-5D-5L) from the disease-specific OKS using data from patients with knee osteoarthritis (KO).Patients and methodsThis is a cross-sectional study of 571 patients with KO. We used four distinct mapping algorithms: Cumulative Probability for Ordinal Data, Penalized Ordinal Regression, CART (Classification and Regression Trees), and Ordinal random forest. We compared the resultant models’ degrees of accuracy.ResultsMobility was best predicted by penalized regression with pre-processed predictors, usual activities by random forest, pain/discomfort by cumulative probability with pre-processed predictors, self-care by random forest with RFE (recursive feature elimination) predictors, and anxiety/depression by CART with RFE predictors. Model accuracy was lowest with anxiety/depression and highest with mobility and usual activities. Using available country value sets, the average MAE was 0.098 ± 0.022, ranging from 0.063 to 0.142; and the average MSE was 0.020 ± 0.008 ranging from 0.008 to 0.042.ConclusionsThe current study derived accurate mapping techniques from OKS to the domains of EQ-5D-5L, allowing for the computation of QALYs in economic evaluations. A machine learning-based strategy offers a viable mapping alternative that merits further exploration.

Making visible the cost of informal caregivers’ time in Latin America: a case study for major cardiovascular, cancer and respiratory diseases in eight countries

BackgroundInformal care is a key element of health care and well-being for society, yet it is scarcely visible and rarely studied in health economic evaluations. This study aims to estimate the time use and cost associated with informal care for cardiovascular diseases, pneumonia and ten different cancers in eight Latin American countries (Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Mexico and Peru).MethodsWe carried out an exhaustive literature review on informal caregivers’ time use, focusing on the selected diseases. We developed a survey for professional caregivers and conducted expert interviews to validate this data in the local context. We used an indirect estimate through the interpolation of the available data, for those cases in which we do not found reliable information. We used the proxy good method to estimate the monetary value of the use of time of informal care. National household surveys databases were processed to obtain the average wage per hour of a proxy of informal caregiver. Estimates were expressed in 2020 US dollars.ResultsThe study estimated approximately 1,900 million hours of informal care annually and $ 4,300 million per year in average informal care time cost for these fifteen diseases and eight countries analyzed. Cardiovascular diseases accounted for an informal care burden that ranged from 374 to 555 h per year, while cancers varied from 512 to 1,825 h per year. The informal care time cost share on GDP varied from 0.26% (Mexico) to 1.38% (Brazil), with an average of 0.82% in the studied American countries. Informal care time cost represents between 16 and 44% of the total economic cost (direct medical and informal care cost) associated with health conditions.ConclusionsThe study shows that there is a significant informal care economic burden -frequently overlooked- in different chronic and acute diseases in Latin American countries; and highlights the relevance of including the economic value of informal care in economic evaluations of healthcare.

Healthcare utilization and costs among intracranial meningioma patients during long-term follow-up

PurposeFew studies have reported on healthcare utilization and costs for intracranial meningioma patients, while the tumor and its treatment profoundly affect patients’ functioning and well-being. Here we evaluated healthcare utilization and costs, including their determinants.MethodsA multicenter cross-sectional study of adult meningioma patients ≥ 5 years after intervention. Patients completed three validated patient-reported outcome measures (PROMs) assessing patients ‘functioning and wellbeing (SF-36, EORTC QLQ-BN20, and HADS) and a study-specific questionnaire assessing healthcare utilization over the previous twelve months. Healthcare costs of the twelve months prior were calculated using reported healthcare utilization ≥ 5 years after intervention by the Dutch Manual for Economic Evaluation in Healthcare. Determinants for healthcare utilization and costs were determined with regression analyses.ResultsWe included 190 patients with WHO grade I or II meningioma after a mean follow-up since intervention of 9.2 years (SD 4.0). The general practitioner (80.5%), physiotherapist (37.9%), and neurologist (25.4%) were visited most often by patients. Median annual healthcare costs were €871 (IQR €262–€1933). Main contributors to these costs were medication (45.8% of total costs, of which anti-seizure medication was utilized most [21.6%]), specialist care (17.7%), and physiotherapy (15.5%). Lower HRQoL was a significant determinant for higher healthcare utilization and costs.ConclusionIn patients with meningioma, medication costs constituted the largest expenditure of total healthcare costs, in particular anti-seizure medication. Particularly a lower HRQoL was a determinant for healthcare utilization and costs. A patient-specific approach aimed at improving patients’ HRQoL and needs could be beneficial in reducing disease burden and functional recovery.

PP88 Bayesian Joint Models For Cost-Effectiveness Analyses Based On Clustered Participant Data, With Implementation In Stan

IntroductionCost-effectiveness analyses of empirical participant data are frequently complicated by irregularly distributed and correlated observations, which are not well approximated by normal distributions. Things get even more difficult when observations are clustered within higher level units (for example, hospitals) or the participant (that is, multiple measurements at different timepoints). Therefore, we developed a flexible Bayesian approach to jointly model costs and effects of two competing interventions with a multilevel structure.MethodsOur new model is presented in mathematical form and discussed in detail. We model costs and Quality-Adjusted Life-Years effects through Gamma and Beta distributions, and account for the dependency between costs and effects by adding the effects as a predictor for the costs. We further include hurdle models to account for costs of for the presence of zero costs and perfect health scores.The full model is implemented in the probabilistic programming language Stan. To compare the performance of our Bayesian model to a frequentist approach (linear mixed model combined with bootstrapping), we simulate 1000 datasets consisting of 400 participants and 20 clusters. Performance of both models is assessed in terms of variance, bias and coverage probability with respect to the costs and effects defined in the simulation.ResultsWe ran a preliminary simulation with high intraclass correlation, strong negative correlation for patient-level costs and effects, and positive correlation of cluster effects on both outcomes. The analysis shows that the Bayesian model exhibits a slightly larger bias for estimated costs, but smaller errors and higher coverage probability compared to the frequentist alternative. We will explore different scenarios where we vary the parameters of the simulations and assess whether the results are robust to change.ConclusionsIt is very important that economic evaluations in health care produce precise and reliable results. Our Bayesian approach is able to handle multiple statistical complexities at once and performs better than a comparable frequentist model. Whether this conclusion holds for different simulation scenarios will be explored in further stages of this study.

Updated guidelines of reporting pharmacoeconomics and health technology assessment results from 2022 ISPOR (CHEERS 2022)

In 2022, ISPOR released an updated checklist on economic evaluation of health care, since the latter several years have passed, the circumstances have changed, and science has progressed that it demanded fresh relevant changes. To support decision-making in accordance with the principles of evidence-based medicine, expanding participants, the involvement of as many sides as possible for more coordinated and high-quality work. The paper contains the main principles included into the ISPOR CHEERS 2022 check-list.

Value Insider Season 1 Episode 4: How are Costs Measured, and How are CEAs Constructed and Used? (CEA) [Podcast

How is a cost-effectiveness analysis constructed and used? In this episode of the Value Insider podcast, host Mike Chambers speaks with Prof. Maureen Rutten-van Mölken about economic evaluations in healthcare and how value is considered in these evaluations. Prof. Rutten-van Mölken is professor of Economic Evaluation of Innovations for Health at the Erasmus University Rotterdam in the Netherlands. She leads the Erasmus HTA department and is Scientific Director of the Institute for Medical Technology Assessment (iMTA). Prof Rutten-van Mölken explains how comparative assessments can help us understand which treatments offer the best value-for-money as reimbursement can only be allocated to a selection of all possible treatments.

Estimating Societal Cost of Illness and Patients’ Quality of Life of Duchenne Muscular Dystrophy in Egypt

ObjectivesDuchenne muscular dystrophy (DMD) is a rare neuromuscular disease that causes substantial economic burden. This study aims to measure the DMD cost from societal perspective and the quality of life (QOL) of the Egyptian patients. MethodsWe conducted interviews with caregivers of patients with DMD. The questionnaire included demographics, healthcare resource use, and nonmedical and indirect costs. Total disease burden was estimated with a bottom-up approach. QOL was measured with a disease-specific tool. Costs and utilities were stratified by the disease stage. ResultsCaregivers of 97 patients with DMD were interviewed. The mean annual per-patient cost of $17 485 (SD ± 9240) was estimated resulting in a total burden of $138 217 043 in Egypt. Nonmedical costs made up the largest category representing 54% followed by medical then indirect costs. Informal care made the greatest contribution of nonmedical costs whereas physiotherapy was the largest medical subcategory. Nonmedical costs were highest in stage 3 and lowest at early stages whereas medical costs were almost steady among all stages with differences in individual subcategories. Of all medical costs, 95% were out of pocket. The mean utility score was 0.43 (± 0.31), which decreases with disease progression. ConclusionOur study quantified the huge economic burden of DMD on the society and how it differs in different stages. Almost the whole burden is paid by households resulting in catastrophic expenditures, which leads to reduced compliance and quality of care. QOL is also severely compromised. Our findings can inform future healthcare policies and economic evaluation of new DMD therapies.

The Primary Process and Key Concepts of Economic Evaluation in Healthcare.

Economic evaluations in the healthcare are used to assess economic efficiency of pharmaceuticals and medical interventions such as diagnoses and medical procedures. This study introduces the main concepts of economic evaluation across its key steps: planning, outcome and cost calculation, modeling, cost-effectiveness results, uncertainty analysis, and decision-making. When planning an economic evaluation, we determine the study population, intervention, comparators, perspectives, time horizon, discount rates, and type of economic evaluation. In healthcare economic evaluations, outcomes include changes in mortality, the survival rate, life years, and quality-adjusted life years, while costs include medical, non-medical, and productivity costs. Model-based economic evaluations, including decision tree and Markov models, are mainly used to calculate the total costs and total effects. In cost-effectiveness or cost-utility analyses, cost-effectiveness is evaluated using the incremental cost-effectiveness ratio, which is the additional cost per one additional unit of effectiveness gained by an intervention compared with a comparator. All outcomes have uncertainties owing to limited evidence, diverse methodologies, and unexplained variation. Thus, researchers should review these uncertainties and confirm their robustness. We hope to contribute to the establishment and dissemination of economic evaluation methodologies that reflect Korean clinical and research environment and ultimately improve the rationality of healthcare policies.

An EQ-5D-5L Value Set for Belgium.

ObjectiveThis study aimed to establish a Belgian EQ-5D-5L value set based on the preferences of the adult Belgian general population.MethodsThe most recent EuroQol Valuation Technology (EQ-VT 2.1) protocol for EQ-5D-5L valuation studies was followed. Computer-assisted personal interviews were carried out in a representative sample of the adult Belgian population. Potential respondents were randomly selected from the National Register using a multistage, stratified, cluster sampling with unequal probability design. Each respondent valued 10 or 11 health states using composite time trade-off (cTTO) and 14 health states in seven paired choice tasks using a discrete choice experiment (DCE). Different model specifications were explored and assessed based on logical consistency, goodness of fit, predictive accuracy and theoretical considerations.ResultsA total of 892 respondents were included in the analyses. The sample was representative of the Belgian adult population in terms of age, sex, region of residence, educational attainment, labour market status, self-assessed health status and health-related quality of life (HRQoL). The preferred model specification was a hybrid (DCE and cTTO data combined) multiplicative eight-coefficient model with intercept random effects and correction for heteroskedasticity. Values range from − 0.532 to 1. Loss of HRQoL is highest in the dimension pain/discomfort, closely followed by anxiety/depression.ConclusionsThis study developed a Belgian EQ-5D-5L value set, based on the preferences of the Belgian adult general population. It provides opportunities for future clinical and economic evaluations in healthcare, for the measurement of patient-reported outcomes and for population health assessments.Supplementary InformationThe online version contains supplementary material available at 10.1007/s41669-022-00353-3.

SA3 Utility of Artificial Intelligence in Systematic Literature Reviews for Health Technology Assessment Submissions

The use of artificial intelligence (AI) may alleviate additional time and effort needed to conduct robust, fully comprehensive systematic literature reviews (SLRs) intended for submission to health technology assessment (HTA) bodies. This study aimed to determine the ability of AI to accurately identify relevant studies on costs, healthcare resource use (HCRU), economic evaluations (EE), and patient-reported outcomes (PRO).

Economic studies in medical research: ‘Importance, targets, outcome evaluation’

Economic studies in healthcare are used to measure the cost and effectiveness of an intervention and are valuable in determining how healthcare resources can be distributed to achieve the greatest overall gain. Most economic studies in healthcare are cost-benefit analyses, cost-effectiveness analyses (CEAs), or cost-utility analyses (CUAs). CEAs and CUAs compare alternative interventions based on cost and effectiveness but are influenced by different methodologies and assumptions employed by researchers. The perspective from which an economic study is evaluated (the patient, the provider, the payor, or the society) should be carefully considered. The incremental cost effectiveness ratio (ICER) describes the difference between two interventions in cost and health outcomes and can be expressed in dollars per quality-adjusted life year (QALY). A threshold ICER <$50,000/QALY is often used to determine whether an intervention is cost-effective, in conjunction with patient factors, healthcare system factors, and opportunity cost associated with the intervention. The Consolidated Health Economic Evaluating Reporting Standards (CHEERS) statement provides guidelines for reporting healthcare economic studies. Key elements to be reported include the study design, target population and subgroups, time horizon, health outcomes, perspectives, comparison group, and sensitivity analyses performed. Economic studies are particularly important in orthopedics given the prevalence of musculoskeletal disease, high upfront costs, and potential quality of life improvements associated with orthopedic surgical procedures. An understanding of economic evaluations in healthcare is important to critically review the available literature.

Nothing to Cheer About: Endorsing Imaginary Economic Evaluations and Value Claims with CHEERS 22

One of the more unfortunate features of health technology assessment is the tenacity with which leaders in the field and organizations such as the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Institute for Clinical and Economic Review (ICER) cling to an evaluation framework that fails to meet the standards of normal science. Believers subscribe to a meme that is clearly non-science (metaphysics and pseudoscience) and one that should have been discarded over 30 years ago. Certainly, subscribing to an impossible belief is not unusual; indeed it may make the belief that much stronger. Yet the meme is non-sustainable; it is also pointless as the economic evaluation claims are non-evaluable. There is no acknowledgement of the standards of normal science or the limitations imposed by the axioms of fundamental measurement. The purpose of this commentary is to make the case that the recent release of the Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 22) checklist is misleading; CHEERS 22 fails to address the manifest deficiencies in the approach to economic evaluations endorsed by ISPOR and ICER. Instead, it continues to promote economic evaluations in healthcare that invent evidence and non-empirically evaluable value claims. Given the widespread publicity that has accompanied the release of CHEERS 22, the purpose of this commentary is to detail the deficiencies in CHEERS 22 and propose an alternative framework for economic evaluation in health care to meet the information needs of formulary committees. This means abandoning the standards for economic evaluations that have dominated health technology assessment for 30 years, notably the key role assigned to the mathematically impossible quality adjusted life year (QALY). The proposed new start recommends single attribute evaluable value claims that meet ratio or interval measurement standards and are supported by evaluation protocols.