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A framework for explaining the role of values in health policy decision-making in Latin America: a critical interpretive synthesis.

ABSTRACT: BACKGROUND:Although values underpin the goals pursued in health systems, including how health systems benefit the population, it is often not clear how values are incorporated into policy decision-making about health systems. The challenge is to encompass social/citizen values, health system goals, and financial realities and to incorporate them into the policy-making process. This is a challenge for all health systems and of particular importance for Latin American (LA) countries. Our objective was to understand how and under what conditions societal values inform decisions about health system financing in LA countries. METHODS:A critical interpretive synthesis approach was utilised for this work. We searched 17 databases in December 2016 to identify articles written in English, Spanish or Portuguese that focus on values that inform the policy process for health system financing in LA countries at the macro and meso levels. Two reviewers independently screened records and assessed them for inclusion. One researcher conceptually mapped the included articles, created structured summaries of key findings from each, and selected a purposive sample of articles to thematically synthesise the results across the domains of agenda-setting/prioritisation, policy development and implementation. RESULTS:We identified 5925 references, included 199 papers, and synthesised 68 papers. We identified 116 values and developed a framework to explain how values have been used to inform policy decisions about financing in LA countries. This framework has four categories - (1) goal-related values (i.e. guiding principles of the health system); (2) technical values (those incorporated into the instruments adopted by policy-makers to ensure a sustainable and efficient health system); (3) governance values (those applied in the policy process to ensure a transparent and accountable process of decision-making); and (4) situational values (a broad category of values that represent competing strategies to make decisions in the health systems, their influence varying according to the four factors). CONCLUSIONS:It is an effort to consolidate and explain how different social values are considered and how they support policy decision-making about health system financing. This can help policy-makers to explicitly incorporate values into the policy process and understand how values are supporting the achievement of policy goals in health system financing. TRIAL REGISTRATION:The protocol was registered with PROSPERO, ID=CRD42017057049 .

SUBMITTER: Velez CM

PROVIDER: S-EPMC7487839 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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A framework for explaining the role of values in health policy decision-making in Latin America: a critical interpretive synthesis.

Vélez C Marcela CM Wilson Michael G MG Lavis John N JN Abelson Julia J Florez Ivan D ID

Health research policy and systems 20200907 1

<h4>Background</h4>Although values underpin the goals pursued in health systems, including how health systems benefit the population, it is often not clear how values are incorporated into policy decision-making about health systems. The challenge is to encompass social/citizen values, health system goals, and financial realities and to incorporate them into the policy-making process. This is a challenge for all health systems and of particular importance for Latin American (LA) countries. Our o ...[more]

PMID: 32894131

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Project description:BackgroundWhile calls for institutionalization of evidence-informed policy-making (EIP) have become stronger in recent years, there is a paucity of methods that governments and organizational knowledge brokers can use to sustain and integrate EIP as part of mainstream health policy-making. The objective of this paper was to conduct a knowledge synthesis of the published and grey literatures to develop a theoretical framework with the key features of EIP institutionalization.MethodsWe applied a critical interpretive synthesis (CIS) that allowed for a systematic, yet iterative and dynamic analysis of heterogeneous bodies of literature to develop an explanatory framework for EIP institutionalization. We used a "compass" question to create a detailed search strategy and conducted electronic searches to identify papers based on their potential relevance to EIP institutionalization. Papers were screened and extracted independently and in duplicate. A constant comparative method was applied to develop a framework on EIP institutionalization. The CIS was triangulated with the findings of stakeholder dialogues that involved civil servants, policy-makers and researchers.ResultsWe identified 3001 references, of which 88 papers met our eligibility criteria. This CIS resulted in a definition of EIP institutionalization as the "process and outcome of (re-)creating, maintaining and reinforcing norms, regulations, and standard practices that, based on collective meaning and values, actions as well as endowment of resources, allow evidence to become-over time-a legitimate and taken-for-granted part of health policy-making". The resulting theoretical framework comprised six key domains of EIP institutionalization that capture both structure and agency: (1) governance; (2) standards and routinized processes; (3) partnership, collective action and support; (4) leadership and commitment; (5) resources; and (6) culture. Furthermore, EIP institutionalization is being achieved through five overlapping stages: (i) precipitating events; (ii) de-institutionalization; (iii) semi-institutionalization (comprising theorization and diffusion); (iv) (re)-institutionalization; and (v) renewed de-institutionalization processes.ConclusionsThis CIS advances the theoretical and conceptual discussions on EIP institutionalization, and provides new insights into an evidence-informed framework for initiating, strengthening and/or assessing efforts to institutionalize EIP.

Project description:BackgroundThe pace of the COVID-19 pandemic poses an unprecedented challenge to the evidence-to-decision process. Latin American countries have responded to COVID-19 by introducing interventions to both mitigate the risk of infection and to treat cases. Understanding how evidence is used to inform government-level decision-making at a national scale is crucial for informing country and regional actors in ongoing response efforts.ObjectivesThis study was undertaken between February-May 2021 and aims to characterise the best available evidence (BAE) and assess the extent to which it was used to inform decision-making in 21 Latin American countries, in relation to pharmaceutical (PI) and non-pharmaceutical interventions (NPI) related to COVID-19, including the use of therapeutics (corticosteroids, hydroxychloroquine/chloroquine and ivermectin), facemask use in the community setting and the use of diagnostic tests as a requirement for international travel.MethodA three-phase methodology was used to; (i) characterise the BAE for each intervention using an umbrella review, (ii) identify government-level decisions for each intervention through a document review and (iii) assess the use of evidence to inform decisions using a novel adapted framework analysis.FindingsThe BAE is characterized by 17 living and non-living systematic reviews as evolving, and particularly uncertain for NPIs. 107 country-level documents show variation in both content and timing of decision outcomes across intervention types, with the majority of decisions taken at a time of evidence uncertainty, with only 5 documents including BAE. Seven out of eight key indicators of an evidence-to-decision process were identified more frequently among PIs than either NPI of facemask use or testing prior to travel. Overall evidence use was reported more frequently among PIs than either NPI of facemask use or travel testing (92%, 28% and 29%, respectively).InterpretationThere are limitations in the extent to which evidence use in decision-making is reported across the Latin America region. Institutionalising this process and grounding it in existing and emerging methodologies can facilitate the rapid response in an emergency setting.FundingNo funding was sourced for this work.

Project description:The financial implications of the increase in the prevalence of diabetes in middle-income countries represents one of the main challenges to health system financing and to the society as a whole. The objective of this study was to estimate the economic cost of diabetes in Latin America and the Caribbean (LAC) in 2015.The study used a prevalence-based approach to estimate the direct and indirect costs related to diabetes in 29 LAC countries in 2015. Direct costs included health care expenditures such as medications (insulin and oral hypoglycemic agents), tests, consultations, hospitalizations, emergency visits and treating complications. Two different scenarios (S1 and S2) were used to analyze direct cost. S1 assumed conservative estimates while S2 assumed broader coverage of medication and services. Indirect costs included lost resources due to premature mortality, temporary and permanent disabilities.In 2015 over 41 million adults (20 years of age and more) were estimated to have Diabetes Mellitus in LAC. The total indirect cost attributed to Diabetes was US$ 57.1 billion, of which US$ 27.5 billion was due to premature mortality, US$16.2 billion to permanent disability, and US$ 13.3 billion to temporary disability. The total direct cost was estimated between US$ 45 and US$ 66 billion, of which the highest estimated cost was due to treatment of complications (US$ 1?616 to US$ 26 billion). Other estimates indicated the cost of insulin between US$ 6 and US$ 11 billion; oral medication US$ 4 to US$ 6 billion; consultations between US$ 5 and US$ 6 billion; hospitalization US$ 10 billion; emergency visits US$ 1 billion; test and laboratory exams between US$ 1 and US$ 3 million. The total cost of diabetes in 2015 in LAC was estimated to be between US$ 102 and US$ 123 billion. On average, the annual cost of treating one case of diabetes mellitus (DM) in LAC was estimated between US$ 1088 and US$ 1818. Per capita National Health Expenditures averaged US$ 1061 in LAC.Diabetes represented a major economic burden to the countries of Latin America and the Caribbean in 2015. The estimates presented here are key information for decision-making that can be used in the formulation of policies and programs to achieve greater efficiency and effectiveness in the use of resources for diabetes prevention in the 29 countries of LAC.

Project description:BackgroundThe increasing prevalence of childhood obesity makes it essential to study the risk factors with a sample representative of the population covering more health topics for better preventive policies and interventions. It is aimed to develop an ensemble feature selection framework for large-scale data to identify risk factors of childhood obesity with good interpretability and clinical relevance.MethodsWe analyzed the data collected from 426,813 children under 18 during 2000-2019. A BMI above the 90th percentile for the children of the same age and gender was defined as overweight. An ensemble feature selection framework, Bagging-based Feature Selection framework integrating MapReduce (BFSMR), was proposed to identify risk factors. The framework comprises 5 models (filter with mutual information/SVM-RFE/Lasso/Ridge/Random Forest) from filter, wrapper, and embedded feature selection methods. Each feature selection model identified 10 variables based on variable importance. Considering accuracy, F-score, and model characteristics, the models were classified into 3 levels with different weights: Lasso/Ridge, Filter/SVM-RFE, and Random Forest. The voting strategy was applied to aggregate the selected features, with both feature weights and model weights taken into consideration. We compared our voting strategy with another two for selecting top-ranked features in terms of 6 dimensions of interpretability.ResultsOur method performed the best to select the features with good interpretability and clinical relevance. The top 10 features selected by BFSMR are age, sex, birth year, breastfeeding type, smoking habit and diet-related knowledge of both children and mothers, exercise, and Mother's systolic blood pressure.ConclusionOur framework provides a solution for identifying a diverse and interpretable feature set without model bias from large-scale data, which can help identify risk factors of childhood obesity and potentially some other diseases for future interventions or policies.

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A framework for explaining the role of values in health policy decision-making in Latin America: a critical interpretive synthesis.

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A framework for explaining the role of values in health policy decision-making in Latin America: a critical interpretive synthesis.

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