Evaluation Of Public Health Policies Research Articles

On the measurement of cause of death inequality.

Attempts at assessing heterogeneity in countries' mortality profiles often rely on measures of cause of death (CoD) diversity. Unfortunately, such indicators fail to take into consideration the degree of (dis)similarity among pairs of causes (e.g. 'transport injuries' and 'unintentional injuries' are implicitly assumed to be as dissimilar as 'transport injuries' and 'Alzheimer's disease')－an unrealistic and unduly restrictive assumption. We extend diversity indicators proposing a broader class of heterogeneity measures that are sensitive to the similarity between the causes of death one works with. The so-called 'CoD inequality' measures are defined as the average expected 'dissimilarity between any two causes of death'. A strength of the approach is that such measures are decomposable, so that users can assess the contribution of each cause to overall CoD heterogeneity levels-a useful property for the evaluation of public health policies. We have applied the method to 15 low-mortality countries between 1990 and 2019, using data from the Global Burden of Disease project. CoD inequality and CoD diversity generally increase over time across countries and sex, but with some exceptions. In several cases (notably, Finland), both indicators run in opposite directions. CoD inequality and diversity indicators capture complementary information about the heterogeneity of mortality profiles, so they should be analysed alongside other population health metrics, such as life expectancy and lifespan inequality.

Fine-grained mathematical modeling for cost-effectiveness evaluation of public health policies for cervical cancer, with application to a Colombian case study

BackgroundCervical cancer (CC) is globally ranked fourth in terms of incidence and mortality among women. Vaccination against Human Papillomavirus (HPV) and screening programs can significantly reduce CC mortality rates. Hence, executing cost-effective public health policies for prevention and surveillance is crucial. However, defining policies that make the best use of the available resources is not easy, as it requires predicting the long-term costs and results of interventions on a changing population. Since the simpler task of predicting the results of public health policies is difficult, devising those that make the best usage of available resources is an arduous challenge for decision-makers.MethodsThis paper proposes a fine-grained epidemiological simulation model based on differential equations, to effectively predict the costs and effectiveness of CC public health policies that include vaccination and screening. The model represents population dynamics, HPV transmission within the population, likelihood of infection clearance, virus-induced appearance of precancerous lesions and eventually CC, as well as immunity gained with vaccination and early detection with screening.ResultsWe offer a compartmentalized modeling approach that separates population, epidemics, and intervention concerns. We instantiate models with actual data from a Colombian case study and analyze their results to show how our modeling approach can support CEA studies. Moreover, we implement models in an open-source software tool to simultaneously define and evaluate multiple policies. With the support of the tool, we analyze 54 policies within a 30-year time horizon and use as a comparator the CC policy that has been used until recently. We identify 8 dominant policies, the best one with an ICER of 6.3 million COP (Colombian Pesos) per averted DALY. We also validate the modeling approach against the available population and HPV epidemic data. The effects of uncertainty in the values of key parameters (discount rate, sensitivity of screening tests) is evaluated through one-way sensitivity analysis.ConclusionsOur modeling approach can provide valuable support for healthcare decision-makers. The implementation into an automated tool allows customizing the analysis with country-specific data, flexibly defining public health policies to be evaluated, and conducting disaggregate analyses of their cost and effectiveness.

Explaining transmission rate variations and forecasting epidemic spread in multiple regions with a semiparametric mixed effects SIR model.

The transmission rate is a central parameter in mathematical models of infectious disease. Its pivotal role in outbreak dynamics makes estimating the current transmission rate and uncovering its dependence on relevant covariates a core challenge in epidemiological research as well as public health policy evaluation. Here, we develop a method for flexibly inferring a time-varying transmission rate parameter, modeled as a function of covariates and a smooth Gaussian process (GP). The transmission rate model is further embedded in a hierarchy to allow information borrowing across parallel streams of regional incidence data. Crucially, the method makes use of optional vaccination data as a first step toward modeling of endemic infectious diseases. Computational techniques borrowed from the Bayesian spatial analysis literature enable fast and reliable posterior computation. Simulation studies reveal that the method recovers true covariate effects at nominal coverage levels. We analyze data from the COVID-19 pandemic and validate forecast intervals on held-out data. User-friendly software is provided to enable practitioners to easily deploy the method in public healthresearch.

Perceptions and experiences on data sharing and linkage for research and the evaluation of public health policy.

ObjectivesThis research seeks to understand viewpoints on the use of data containing personally identifiable information by a range of organizations for divergent purposes, focusing on the sharing and linkage of administrative data for the purposes of conducting research and evaluating public policies in Brazil.
 ApproachAn exploratory approach was employed to perceive how the concepts relevant to this subject are understood, experienced and expressed by our interlocutors. A semi-structured interview technique was chosen to establish a base of scripted questions capable of building on and adapting to discussions with the participants, as well as addressing the questions that emerged during interviews. The interviewees were divided into three groups: data subjects (patients and beneficiaries of social welfare programs), researchers, and managers with experience in public policy in the areas of health and social protection. Specific scripts were elaborated for each group of respondents.
 ResultsGroups and individuals are constantly balancing risks and benefits with regard to exposing and sharing their data; risks weigh more heavily depending on the individual’s socioeconomic context, which is permeated by intersectionality. The processing of personal data by the government raises more fears than actions taken by large technology companies. Individuals and social groups want to receive feedback on research carried out in their communities, and also desire to participate in the design of scientific research and the analysis of evidence used to guide public policies which directly affect them. Data governance is indispensable, requiring not only data management but also specific conditions on data sharing and linkage, principally regarding the sharing of administrative data aligned with legitimate public interests.
 ConclusionRaising awareness and providing information on individual and collective rights on personal and sensitive data collection, as well as informing the public about the purposes of data sharing and linkage, is of utmost importance for responsible data management. Administrative data governance should be planned and implemented to foster trust and transparency among all involved and interested parties.

A Modelling Framework for Evidence-Based Public Health Policy Making.

It is widely recognised that the process of public health policy making (i.e., the analysis, action plan design, execution, monitoring and evaluation of public health policies) should be evidenced based, and supported by data analytics and decision-making tools tailored to it. This is because the management of health conditions and their consequences at a public health policy making level can benefit from such type of analysis of heterogeneous data, including health care devices usage, physiological, cognitive, clinical and medication, personal, behavioural, lifestyle data, occupational and environmental data. In this paper we present a novel approach to public health policy making in a form of an ontology, and an integrated platform for realising this approach. Our solution is model-driven and makes use of big data analytics technology. More specifically, it is based on public health policy decision making (PHPDM) models that steer the public health policy decision making process by defining the data that need to be collected, the ways in which they should be analysed in order to produce the evidence useful for public health policymaking, how this evidence may support or contradict various policy interventions (actions), and the stakeholders involved in the decision-making process. The resulted web-based platform has been implemented using Hadoop, Spark and HBASE, developed in the context of a research programme on public health policy making for the management of hearing loss called EVOTION, funded by the Horizon 2020.

The Impact of School Closure on Adolescents' Wellbeing, and Steps towards to a New Normal: The Need for an Assessment Tool Update?

Close to 200 countries have implemented school closures to decrease the spread of the COVID-19 coronavirus. Though the closures have seemed necessary, their effects on the wellbeing of children and adolescents have raised serious concerns. To truly understand the impact of such disruption on young people's wellbeing, and their views on how to move towards a new normal, we must adopt different approaches to gather the data to secure children's and adolescents' rights to be heard in the issues that concern their lives. Current ways to examine the impacts of school closure have been dominated by gathering information concerning the children and adolescents, using mainly existing wellbeing indicators and related questionnaire surveys. Although such sources of information are important, they provide limited understanding of how children and adolescents have experienced school closures, especially if they have been produced using measures developed purely by adults. There is a need for information produced by children and adolescents themselves, which may require going beyond existing and pre-COVID theoretical wellbeing frameworks. By capturing information produced by children and adolescents, we can more effectively guide the development and evaluation of public health policies and identify solutions to mitigate the negative impacts of school closure, or to acknowledge the possible positive effects, and respond accordingly.

Ethics of vaccination: Should capability measures be used to inform SARS-CoV-2 vaccination strategies?

Proposals for SARS‐CoV‐2 virus vaccination priorities in the UK and in many other countries are heavily influenced by epidemiological models, which use outcome measures such as deaths or hospitalisation. Limiting the values under consideration to those attributable to the direct effects of infection has the advantage of simplifying the models and the process of decision‐making. However, the consequences of the pandemic extend beyond outcomes directly attributable to SARS‐CoV‐2 infection, and include restrictions on educational and work opportunities, access to services, recreational activities, affiliations and relationships with others, freedom of movement (including escaping abusive relationships), and other determinants of human experience.Capability theory gives emphasis to the freedoms that individuals have to express themselves (in doings and beings). Restrictions on freedoms restrict our capabilities. Capability theory has been used to provide a framework for the evaluation and comparison of international development approaches and in the evaluation of public health policy. There is a clustering of disadvantages associated with this pandemic that adds to pre‐existing inequalities. Much of the disadvantage engendered in the SARS‐CoV‐2 pandemic is left out when public health policy is based on a limited range of metrics. Acknowledging the impact of policy across the range of human freedoms at both a national and international level has the potential to improve policy, facilitate the mitigation of direct and indirect adverse consequences, and improve public confidence and the effectiveness of vaccine deployment strategies.

French Health big data experience: The evolution of the national health insurance information system

Abstract The French national health insurance information system created in 1999 is one of the largest global data warehouse of medico-administrative data, covering nearly 66 million inhabitants and containing more than 160 billion records, including all outpatient health expenditures. Recent legislation has enlarged the scope of information and access to the data warehouse. Initially created to reimburse patients, the national health insurance data warehouse has developed into a powerful tool for conducting public health research. Public health researchers and epidemiologists have long studied population health determinants, including access to and impact of health care interventions, through hypothesis driven investigations based on experimental (randomized controlled trials) or quasi-experimental designs (e.g. cohort or case control studies). In such studies, efforts are centred on data validity rather than scope or volume. Nowadays the availability of medical claims and electronic health records (eHR) allows users not only to address similar research questions at no or little cost for data collection, but also to extend the scope of research questions to the analysis of care pathways, the evaluation of public health policies, the impact of interventions in real-life conditions. Striding away from the conventional hypothesis driven research paradigm, public health researchers have started exploring the power of applying data mining approaches on eHR. As demonstrated in the omics revolution, data driven approaches are discovery-generating tools with explanatory and predictive power. Could data mining methods applied to eHR deliver similar breakthroughs in Health Services Research? What new knowledge and tools must the public health research community acquire to embrace this new research paradigm? These are the issues that we will discuss, with illustrations, during this presentation.

Modeling the Puzzle of Hepatitis C Epidemiology in Romania: A Pathway to Control.

To combat hepatitis C virus (HCV) and achieve its elimination by 2030, the emphasis should be on public health policies. In this study, we investigated the dynamics of epidemiology of HCV in Romanian risk groups that are characterized by higher occurrence densities with the aid of The Let's End HepC (LEHC) project. The LEHC project addressed the modelling of HCV epidemiology, being applied in several countries, one of which is Romania. The model comprised an integrated solution of public health policies focused on the disease, using Adaptive Conjoint Analysis and Markov chains systems. This tool allowed the quantitative evaluation of public health policies' impact, for every year until 2030, in five population groups: people who inject drugs (PWID), prisoners, individuals who have received blood products, children at risk for vertical transmission, and the remnant population. It appears that Romania was already making great efforts in the context of public policies, allowing the achievement of HCV elimination by 2028 if current policies were maintained. Through additional work and greater efforts in further implementing public policies, the LEHC model estimated the possibility of anticipating this outcome to 2026. The LEHC model estimated an anticipation of the HCV elimination year in Romania to be 2026 if the twenty-four health policies in the study are fully implemented and consistently maintained over the years.

A methodology for small area prevalence estimation based on survey data

BackgroundBrazil conducts many health surveys to provide estimates by national level, macro-regions, states, metropolitan regions and capitals. However, estimates for smaller areas are lacking due to their high cost. The Health Vulnerability Index (in Portuguese, Índice de Vulnerabilidade em Saúde, IVS) is a measure that combines socioeconomic and environmental variables in the same indicator and allows for the analysis of the characteristics of population groups residing in census tracts, grouping them into four health risk areas (low, medium, high and very high risk) in addition to showing inequalities in the epidemiological profile of different social groups. This index was developed by the Municipal Health Secretariat of Belo Horizonte to guide health planning.ObjectiveThe aim of the study is to produce a methodology for obtaining reliable estimates for tobacco smoking in small areas for which the IVS was not designed.MethodsThe Vigitel dataset from 2006 to 2013 was used to obtain estimates of the prevalence of smokers based on the IVS employing small area estimation methods that use data from a larger domain to obtain estimates in smaller areas. For indirect estimates, the covariates included were sanitation, housing, education, income, and social and health factors. Post-stratification weights were used according to the IVS based on the population of the 2010 census.ResultsFrom 2006 to 2009, 16.2% (95% CI: 13.6–14.8%) of the adult population in Belo Horizonte were smokers, and 14.8% (95% CI: 14.0–15.6%) were smokers between 2010 and 2013. The very high-risk population maintained a high prevalence over the same period of 21.1% (95% CI: 17.1–25.0%) between 2006 and 2009 and 20.8% (95% CI: 17.0–24.6%) between 2010 and 2013, while in the low-risk group, the prevalence in the same period fell from 14.9% (95% CI: 13.7–16.2%) to 11.8% (95% CI, 10.6–13.1%).ConclusionsThe present study identified differences in the profile of smokers by the IVS in the city of Belo Horizonte. While the smoking prevalence declined in richer areas, it remained high in poor areas. This methodology can be used to produce reliable estimates for subgroups with greater vulnerability in small areas and thus subsidize the formulation, monitoring and evaluation of public health policies and programmes aimed at smoking.

Modelling and Evaluation of Policies.

NCDs (non-communicable diseases) are considered an important social issue and a financial burden to the health care systems in the EU which can be decreased if cost-effective policies are implemented, along with proactive interventions. The CrowdHEALTH project recognizes that NCD poses a burden for the healthcare sector and society and aims at focusing on NCDs' public health policies. The aim of this paper is to present the concept of Public Health Policy (PHP), elaborate on the state-of-the-art of PHPs development, and propose a first approach to the modeling and evaluation of PHPs used in a toolkit that is going to support decision making, the Policy Development Toolkit (PDT). The policy creation module is a part of the PDT aiming to integrate the results of the rest of the health analytics and policy components. It is the module that selects, filters, and aggregates all relevant information to help policy-makers with the decision making process. The policies creation component is connected to the visualization component to provide the final users with data visualization on different PHPs, including outcomes from data-driven models, such as risk stratification, clinical pathways mining, forecasting or causal analysis models, outcomes from cost-benefit analysis, and suggestions and recommendations from the results of different measured KPIs, using data from the Holistic Health Records (HHRs). In the context of CrowdHEALTH project, PHP can be defined as the decisions taken for actions by those responsible in the public sector that covers a set of actions or inactions that affect a group of public and private actors of the health care system. In the CrowdHEALTH project, the Policy Development Toolkit works as the main interface between the final users and the whole system in the CrowdHEALTH platform. The three components related to policy creation are: (i) the policy modeling component, (ii) the population identification component and (iii) the policy evaluation component. In policy evaluation, KPIs are used as measurable indicators to help prevent ambiguity problems in the interpretation of the model and the structure. This initial Policy creation component design might be modified during the project life circle according to the concept complexity.

Mudança no perfil de causas de morte após investigação de óbitos hospitalares em Belo Horizonte, 2017

Deaths certified with ill-defined causes or garbage codes (GC) compromise the analysis of mortality and its use for planning and evaluation of public health policies. The hospital investigation of these causes is one of the strategies qualifying the profile of mortality in the country. To evaluate the change in the hospital mortality profile after investigation of deaths certified with GC in 2017 in Belo Horizonte, Brazil. A sample of hospital deaths reported with GC in the Mortality Information System (SIM) of Belo Horizonte in 2017 was investigated and subsequently certified by a physician to compare the mortality profile before and after investigation. After investigating 1,395 deaths out of 3,038 reported with GC, a reduction of 35.5% of these causes was observed. Groups of all ages presented decreases in GC occurrence. A higher proportional increase was observed for deaths due to ischemic heart diseases, Alzheimer's disease, chronic obstructive pulmonary disease, ischemic and hemorrhagic stroke, and external causes of death (accidental falls, homicides and traffic/transport accidents). The investigation on reported hospital deaths is one of the strategies to improve mortality statistics, reducing the occurrence of GC among reported deaths and changing the mortality profile in these facilities. The importance of continuous physician training in cause-of-death certification is emphasized.

Barriers to the evaluation of evidence-based public health policy.

Public health policy has the potential to produce great benefits for individuals and communities. There is growing demand that such efforts be rigorously evaluated to ensure that the expected benefits are, in fact, realised. Commonly, public health policy is evaluated by consumer acceptability, reach, or changes in knowledge and attitudes. Non-robust research designs are often used. But these approaches to evaluation do not answer three critical questions: Has a change in the desired outcome occurred? Was it a consequence of the policy and not some extraneous factor? Was the size of the change considered significant and cost-effective? We, a team of government and academic scholars working in research and evaluation, have examined some of the more common impediments to robust evaluation: political impediments, a lack of investment in evaluation capacity within bureaucracy, and the failure of academic researchers to understand the need for the evaluation of public health policy.

Smoothed Temporal Atlases of Age-Gender All-Cause Mortality in South Africa.

Most mortality maps in South Africa and most contried of the sub-Saharan region are static, showing aggregated count data over years or at specific years. Lack of space and temporral dynamanics in these maps may adversely impact on their use and application for vigorous public health policy decisions and interventions. This study aims at describing and modeling sub-national distributions of age–gender specific all-cause mortality and their temporal evolutions from 1997 to 2013 in South Africa. Mortality information that included year, age, gender, and municipality administrative division were obtained from Statistics South Africa for the period. Individual mortality level data were grouped by three ages groups (0–14, 15–64, and 65 and over) and gender (male, female) and aggregated at each of the 234 municipalities in the country. The six age-gender all-cause mortality rates may be related due to shared common social deprivation, health and demographic risk factors. We undertake a joint analysis of the spatial-temporal variation of the six age-gender mortality risks. This is done within a shared component spatial model construction where age-gender common and specific spatial and temporal trends are estiamted using a hierarchical Bayesian spatial model. The results show municipal and temporal differentials in mortality risk profiles between age and gender groupings. High rates were seen in 2005, especially for the 15–64 years age group for both males and females. The dynamic geographical and time distributions of subnational age-gender all-cause mortality contribute to a better understanding of the temporal evolvement and geographical variations in the relationship between demographic composition and burden of diseases in South Africa. This provides useful information for effective monitoring and evaluation of public health policies and programmes targeting mortality reduction across time and sub-populations in the country.

Evaluation of Public Health Policies Addressing Childhood Obesity in The EU 28

Evaluation of Public Health Policies Addressing Childhood Obesity in The EU 28

POLE.VAULT: A Semantic Framework for Health Policy Evaluation and Logical Testing.

The major goal of our study is to provide an automatic evaluation framework that aligns the results generated through semantic reasoning with the best available evidence regarding effective interventions to support the logical evaluation of public health policies. To this end, we have designed the POLicy EVAlUation & Logical Testing (POLE.VAULT) Framework to assist different stakeholders and decision-makers in making informed decisions about different health-related interventions, programs and ultimately policies, based on the contextual knowledge and the best available evidence at both individual and aggregate levels.

Ethical Frameworks in Public Health Decision-Making: Defending a Value-Based and Pluralist Approach.

A number of ethical frameworks have been proposed to support decision-making in public health and the evaluation of public health policy and practice. This is encouraging, since ethical considerations are of paramount importance in health policy. However, these frameworks have various deficiencies, in part because they incorporate substantial ethical positions. In this article, we discuss and criticise a framework developed by James Childress and Ruth Bernheim, which we consider to be the state of the art in the field. Their framework distinguishes aims, such as the promotion of public health, from constraints on the pursuit of those aims, such as the requirement to avoid limitations to liberty, or the requirement to be impartial. We show how this structure creates both theoretical and practical problems. We then go on to present and defend a more practical framework, one that is neutral in avoiding precommitment to particular values and how they ought to be weighted. We believe ethics is at the very heart of such weightings and our framework is developed to reflect this belief. It is therefore both pluralist and value-based. We compare our new framework to Childress and Bernheim's and outline its advantages. It is justified by its impetus to consider a wide range of alternatives and its tendency to direct decisions towards the best alternatives, as well as by the information provided by the ranking of alternatives and transparent explication of the judgements that motivate this ranking. The new framework presented should be useful to decision-makers in public health, as well as being a means to stimulate further reflection on the role of ethics in public health.

Elevating the impact of nutrition and obesity policy research and evaluation.

Increasingly, public policy is recognized as a high-impact and robust approach for accelerating progress toward reducing and managing nutrition-related chronic diseases such as obesity (1). In various jurisdictions, policy makers enact courses of action, regulatory measures, laws, and policies and set funding priorities designed to improve access to healthier food and beverage options (2). Public policy, however, is often the least understood strategy for creating supportive nutrition environments for population health impact. Research has predominantly focused on understanding individual behavior change rather than evaluating approaches to environmental, policy, and system-level change (1,3,4). More attention has been given recently to approaches that could potentially strengthen our understanding of policy including empirical public health law and policy; research, dissemination, and implementation of science; and public health policy evaluation and research (5). Nevertheless, little is known about whether or how nutrition and obesity policy research and evaluation findings influence policy pathways or whether these findings are consistently and systematically used in formulating public policy.

Conflict and compromise in public health policy: analysis of changes made to five competitive food legislative proposals prior to adoption.

Competitive foods in schools have historically been scrutinized for their ubiquity and poor nutritional quality, leading many states to enact legislation limiting the availability and accessibility of these items. Evaluations of these policy approaches show their promise in improving the healthfulness of school food environments, considered an important strategy for reducing childhood obesity. Yet little is known about the decision-making processes by which such legislation is formed and adopted. Using a comparative case study design, this study describes and analyzes the policy formation processes surrounding five state-level competitive food bills introduced in 2009-2010. Data for each case were drawn from multiple key informant interviews and document reviews. Case studies were conducted, analyzed, and written independently using a standard protocol and were subsequently compared for recurring and unique themes. Abbreviated case studies and summary tables are provided. Results indicate that bill cost is a major barrier to achieving strong, health-promoting policy change. Additionally, findings reveal that supporters of stronger competitive food policies often concede to changes that weaken a bill in order to neutralize opposition and achieve stakeholder buy-in. These challenges suggest that continued research on the development, implementation, and evaluation of public health policies can contribute to the advancement of new strategies for effective health promotion.

Take-home naloxone to prevent fatalities from opiate-overdose: Protocol for Scotland’s public health policy evaluation, and a new measure to assess impact

Aims: Scotland was the first country to adopt take-home naloxone (THN) as a funded public health policy. We summarise the background and rigorous set-up for before/after monitoring to assess the impact on high-risk opiate-fatalities. Methods: Evidence-synthesis of prospectively monitored small-scale THN schemes led to a performance indicator for distribution of THN-kits relative to opiate-related deaths. Next, we explain the primary outcome and statistical power for Scotland’s before/after monitoring. Results: Fatality-rate at opiate overdoses witnessed by THN-trainees was 6% (9/153, 95% CI: 2–11%). National THN-schemes should aim to issue 20 times as many THN-kits as there are opiate-related deaths per annum; and at least nine times as many. Primary outcome for evaluating Scotland’s THN policy is reduction in the percentage of all opiate-related deaths with prison-release as a 4-week antecedent. Scotland’s baseline period is 2006–10, giving a denominator of 1970 opiate-related deaths. A priori plausible effectiveness was 20–30% reduction, relative to baseline, in the proportion of opiate-related deaths that had prison-release as a 4-week antecedent. A secondary outcome was also defined. Conclusion: If Scotland’s THN evaluation shifts the policy ground seismically, our new performance measure may prove useful on how many THN-kits nations should provide annually.