Application of economic evidence in health technology assessment and decision-making for the allocation of health resources in Latin America: Seven key topics and a preliminary proposal for implementation

This technical note1 discusses the application of economic evidence in health technology assessments for decision-making on the allocation of health resources. There is already recognition in Latin America that the economic dimensions of health interventions, such as cost-effectiveness and budgetary impact, are critical dimensions that should always be considered when making decisions about the coverage or inclusion of technologies in benefits packages. However, there are still barriers and constraints that prevent the evaluation of economic evidence in the region from being an integral part of all decision- making processes, with serious implications for the equity and efficiency with which health resources are allocated. The purpose of this technical note is to provide elements and tools that contribute, in a practical way, to overcoming these barriers, answering the questions asked by health systems that are beginning to apply economic evidence in their evaluation and decision-making processes. How do we know if a technology or intervention is cost-effective in our context? What cost-effectiveness threshold should be applied? How might non-economic criteria and dimensions influence our cost-effectiveness threshold? What limit should be considered when a technology implies a high budgetary impact in a particular health system? Given the existing difficulties in generating local economic evidence, what can the economic evidence generated in other jurisdictions tell us? How can economic evidence be taken into account in a fragmented health system? Consideration of these aspects is key to ensuring fairer, more transparent allocation of health resources and thus achieving more efficient and equitable health systems in Latin America

A systematic review of value criteria for next-generation sequencing/ comprehensive genomic profiling to inform value framework development

Objectives: To comprehensively identify and map an exhaustive list of value criteria for the assessment of next-generation sequencing/comprehensive genomic profiling (NGS/CGP), to be used as an aid in decision making. Methods: We conducted a systematic review to identify existing value frameworks (VFs) applicable to any type of healthcare technology. VFs and criteria were mapped to a previously published Latin American (LA) VF to harmonize definitions and identify additional criteria and or subcriteria. Based on this analysis, we extracted a comprehensive, evidence-based list of criteria and subcriteria to be considered in the design of a NGS/CGP VF. Results: A total of 42 additional VFs were compared with the LA VF, 88% were developed in high-income countries, 30% targeted genomic testing, and 16% specifically targeted oncology. A total of 242 criteria and subcriteria were extracted; 227 (94%) were fully/partially included in the LA VF; and 15 (6%) were new. Clinical benefit and economic aspects were the most common criteria. VFs oriented to genomic testing showed significant overlap with other VFs. Considering all criteria and subcriteria, a total of 18 criteria and 36 individual subcriteria were identified. Conclusions: Our study provides an evidence-based set of criteria and subcriteria for healthcare decision making useful for NGS/CGP as well as other health technologies. The resulting list can be beneficial to inform decision making and will serve as a foundation to co-create a multistakeholder NGS/CGP VF that is aligned with the needs and values of health systems and could help to improve patient access to high-value technologies

Challenges faced in transferring economic evaluations to middle income countries

BACKGROUND: Decision makers in middle income countries are using economic evaluations (EEs) in pricing and reimbursement decisions for pharmaceuticals. However, whilst many of these jurisdictions have local submission guidelines and local expertise, the studies themselves often use economic models developed elsewhere and elements of data from countries other than the jurisdiction concerned. The objectives of this study were to describe the current situation and to assess the challenges faced by decision makers in transferring data and analyses from other jurisdictions. METHODS: Experienced health service researchers in each region conducted an interview survey of representatives of decision making bodies from jurisdictions in Asia, Central and Eastern Europe, and Latin America that had at least one year’s experience of using EEs. RESULTS: Representatives of the relevant organizations in 12 countries were interviewed. All 12 jurisdictions had developed official guidelines for the conduct of EEs. All but one of the organizations evaluated studies submitted to them, but 9 also conducted studies and 7 commissioned them. Nine of the organizations stated that, in evaluating EEs submitted to them, they had consulted a study performed in a different jurisdiction. Data on relevant treatment effect was generally considered more transferable than those on prices/unit costs. Views on the transferability of epidemiological data, data on resource use and health state preference values were more mixed. Eight of the respondents stated that analyses submitted to them had used models developed in other jurisdictions. Four of the organizations had a policy requiring models to be adapted to reflect local circumstances. The main obstacles to transferring EEs were the different patterns of care or wealth of the developed countries from which most economic evaluations originate. CONCLUSIONS: In middle income countries it is commonplace to deal with the issue of transferring analyses or data from other jurisdictions. Decision makers in these countries face several challenges, mainly due to differences in current standard of care, practice patterns or GDP between the developed countries where the majority of the studies are conducted and their own jurisdiction

Lives Versus Livelihoods: The Epidemiological, Social, And Economic Impact Of COVID-19 In Latin America And The Caribbean

During the COVID-19 pandemic, Latin American and Caribbean countries implemented stringent public health and social measures that disrupted economic and social activities. This study used an integrated model to evaluate the epidemiological, economic, and social trade-offs in Argentina, Brazil, Jamaica, and Mexico throughout 2021. Argentina and Mexico displayed a higher gross domestic product (GDP) loss and lower deaths per million compared with Brazil. The magnitude of the trade-offs differed across countries. Reducing GDP loss at the margin by 1 percent would have increased daily deaths by 0.5 per million in Argentina but only 0.3 per million in Brazil. We observed an increase in poverty rates related to the stringency of public health and social measures but no significant income-loss differences by sex. Our results indicate that the economic impact of COVID-19 was uneven across countries as a result of different pandemic trajectories, public health and social measures, and vaccination uptake, as well as socioeconomic differences and fiscal responses. Policy makers need to be informed about the trade-offs to make strategic decisions to save lives and livelihoods

La costo-efectividad de las intervenciones y políticas para el control de las enfermedades no transmisibles y sus factores de riesgo en América Latina y el Caribe: revisión sistemática

Las enfermedades no transmisibles (ENT) son la principal causa de muerte en las Américas; entre ellas, las enfermedades cardiovasculares (ECV) ocasionan 45% de las defunciones (Hospedales, Barcelo, Luciani y colaboradores 2012). Se calcula que en América Latina y el Caribe (ALC), las defunciones atribuibles a las ECV, en particular la enfermedad coronaria (EC), aumentarán en alrededor de 145%, tanto en los hombres como en las mujeres, entre 1990 y el año 2020. Estas cifras contrastan con un aumento de 28% en las mujeres y de 50% en los hombres durante el mismo periodo en los países desarrollados (Yusuf, Hawken, Ounpuu y colaboradores 2004).Fil: Watkin, David. No especifíca;Fil: Poggio, Rosana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Augustovski, Federico Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Brouwer, Elizabeth. No especifíca;Fil: Pichon Riviere, Andrés. No especifíca;Fil: Rubinstein, Adolfo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Nugent, Rachel. No especifíca

Burden of smoking in Brazil and potential benefit of increasing taxes on cigarettes for the economy and for reducing morbidity and mortality

The prevalence of smoking in Brazil has decreased considerably in recent decades, but the country still has a high burden of disease associated with this risk factor. The study aimed to estimate the burden of mortality, morbidity, and costs for society associated with smoking in 2015 and the potential impact on health outcomes and the economy based on price increases for cigarettes through taxes. Two models were developed: the first is a mathematical model based on a probabilistic microsimulation of thousands of individuals using hypothetical cohorts that considered the natural history, costs, and quality of life of these individuals. The second is a tax model applied to estimate the economic benefit and health outcomes in different price increase scenarios in 10 years. Smoking was responsible for 156,337 deaths, 4.2 million years of potential life lost, 229,071 acute myocardial infarctions, 59,509 strokes, and 77,500 cancer diagnoses. The total cost was BRL 56.9 billion (USD 14.7 billion), with 70% corresponding to the direct cost associated with healthcare and the rest to indirect cost due to lost productivity from premature death and disability. A 50% increase in cigarette prices would avoid 136,482 deaths, 507,451 cases of cardiovascular diseases, 64,382 cases of cancer, and 100,365 cases of stroke. The estimated economic benefit would be BRL 97.9 billion (USD 25.5 billion). In conclusion, the burden of disease and economic losses associated with smoking is high in Brazil, and tax increases are capable of averting deaths, illness, and costs to society

Essential parameters for use in epidemiological models of COVID-19 in Argentina: a rapid review

INTRODUCCIÓN: Los modelos de simulación para COVID-19 requieren una serie de parámetros epidemiológicos que varían en base a cuestiones propias de cada región y al momento de la pandemia que se esté atravesando. OBJETIVO: Esta revisión rápida presenta los parámetros epidemiológicos esenciales potencialmente utilizables en Argentina. MÉTODOS: Se realizó una búsqueda en las principales bases de datos y en buscadores de artículos en estado de preimpresión (preprints) de parámetros relacionados con la propagación del virus y evolución de la enfermedad, y el uso del sistema de salud. Para revisar los artículos seleccionados se utilizó una herramienta de evaluación de calidad apropiada al diseño del estudio. RESULTADOS: De las variables relacionadas con la propagación y evolución; el período de incubación es de 5,8 días (intervalos de confianza [IC95%]: 4,83-6,85), el período de infecciosidad es de 6,25 días (IC95%: 5,09-7,51), el número básico de reproducción es de 3,32 (IC95%: 3,24-3,39), y la tasa de fatalidad en pacientes infectados fue de 0,64% (IC95%: 0,5-0,78). De las variables relacionadas con el uso del sistema de salud, el tiempo de internación hospitalaria es de 5 días (rango intercuartílico [RIC]: 3-9), el tiempo de internación en una unidad de cuidados intensivos (UCI) es de 7 días (RIC: 4-11), el porcentaje de pacientes internados que requieren de UCI es de 26% (IC95%: 20-33) y, de estos, el porcentaje que requieren de ventilación mecánica es de 69% (IC95%: 61-75). DISCUSIÒN: Estudios recientes y datos de acceso públicos a nivel nacional muestran valores distintos a los relevados de la bibliografía internacional. La información recolectada en este trabajo puede contribuir a informar futuros modelamientos y tableros de control para predecir la dinámica de la epidemia en Argentina.INTRODUCTION: Simulation models for COVID-19 require a set of epidemiological parameters that vary according to regional issues and the timing of the pandemic. OBJECTIVE: This rapid review presents the essential epidemiological parameters potentially usable in Argentina. METHODS: A search of the main databases and search engines for articles in preprint status (preprints) of parameters related to the spread of the virus and evolution of the disease, and the use of the health system was carried out. A quality assessment tool appropriate to the study design was used to review the selected articles. RESULTS: Of the variables related to the spread and evolution; the incubation period is 5.8 days (confidence intervals [CI95%]: 4.83-6.85), the infectious period is 6.25 days (CI95%: 5.09-7.51), the basic reproduction number is 3.32 (CI95%: 3.24-3.39), and the fatality rate in infected patients was 0.64% (CI95%: 0.5-0.78). Of the variables related to health system use, the length of hospital stay was 5 days (interquartile range [IQR]: 3-9), the length of stay in an intensive care unit (ICU) was 7 days (IQR: 4-11), the percentage of hospitalized patients requiring ICU was 26% (CI95%: 20-33) and, of these, the percentage requiring mechanical ventilation was 69% (CI95%: 61-75). DISCUSSION: Recent studies and publicly available data at the national level show values different from those reported in the international literature. The information collected in this work may contribute to inform future modeling and dashboards to predict the dynamics of the epidemic in Argentina.Fil: Argento, Fernando Javier. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Rodriguez Cairoli, Federico. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Perelli, Lucas. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Augustovski, Federico Ariel. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pichon Riviere, Andrés. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Bardach, Ariel Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentin