The role of National Immunization Technical Advisory Groups (NITAG) in strengthening health system governance: Lessons from three middle-income countries—Argentina,Jordan, and South Africa (2017–2018)

IntroductionToward the Global Vaccine Action Plan 2020 goal, almost 90% of countries have established a National Immunization Technical Advisory Group (NITAG). However, little is known about NITAG's contributions to governance.MethodsIn 2017–2018, a two-step, qualitative retrospective study was conducted. Jordan (JO), Argentina (AR), and South Africa (SA) were selected owing to government-financed NITAGs from middle-income countries (MICs), geographic diversity, and a vaccine introduction with NITAG support. Country case studies were developed, collecting data through desk review and face-to-face key informant interviews (KIIs) from Ministry of Health (MoH) and NITAG. Case studies were analyzed together, to assess governance applying the European Observatory on Health Systems and Policies framework focusing on transparency, accountability, participation, integrity, and policy capacity (TAPIC).ResultsDocument review and 53 KII (22 AR, 20 SA, 11 JO) showed NITAGs played a pivotal role as advisors promoting a culture of evidence-informed policies. NITAGs strengthened governance, although practices varied among countries. Meetings were conducted behind-closed-doors, participation restricted to members, only in one country agendas, and recommendations were public (AR). To increase participation, policy capacity, and transparency, countries considered adding experts in communications, advocacy, and economics. AR and SA contemplated including community members. NITAGs functioned autonomously from the government, with no established internal or external monitoring or supervision. NITAG meeting minutes allowed the review of integrity, adherence to terms of reference, standard operating procedures, and conflict of interest (CoI). For the most part, NITAGs abided by their mandates. Significant issues were related to the level of MoH support and oversight of CoI declaration and documentation.ConclusionsSystematically implementing governance approaches could improve processes, better tailor policies, and implementation. The long-term survival and resilience of NITAGs in these countries showed they play a significant role in strengthening governance. Lessons learned could be useful to those promoting country-driven evidence-informed decision-making.     

Hacia el buen gobierno por la salud: incorporación de la diversidad de percepciones en salud urbana

ObjectiveTo analyse the similarities and differences in the discourse surrounding the conceptualisation of health and the perceived health assets and needs in the neighborhoods and city of Bilbao in a participatory process.MethodParticipatory workshops were held with professionals, neighbors and associated citizens. The differences in perceptions of the three content blocks were analysed on the basis of the health model referred, as well as the typologies —of a more individual or structural nature— of identified health needs and assets.ResultsThe conceptualisation of health from a biopsychosocial perspective was clearer among professionals, although both profiles pointed to the importance of its social determinants. The formulation of needs and assets in health by the neighbors was made from the impact on their daily life and from a position of users with respect to a service provider administration. Among the associated citizens and professionals, intermediate and structural determinants were more frequently mentioned, as well as issues related to the administration's scope of action.ConclusionsThe inclusion of the multiplicity and diversity of perceptions in planning is key to good local government for health. To address their contradictions, a commitment by governments to effectively incorporate citizen participation is needed.     

论谓项量化、主项质化理论在语言逻辑中的价值与影响

哈米尔顿的谓项量化理论揭示了量化命题中的简单换位规律 ,突破了原有三段论的规则 ,增加了大量新的三段论式。德摩根的主项质化理论给传统的逻辑方阵增添了新的内容 ,八个命题之间存在着紧密的内在联系 ,谓项量化、主项质化命题有着广泛的思维空间和运用价值 ,且语言表达灵活多样。哈米尔顿和德摩根都对联项“是”作了深入研究、赋予新的内涵 ,给逻辑注入了新的活力。     

忘却我国公立医院应对变革的有效选择

从"忘却型医院"的概念入手,分析了我国公立医院"忘却"的必要性,并重点阐述了当前我国公立医院迫切需要忘却的主要因素,而后对忘却与学习的关系进行了辨析.     

Understanding vaccine hesitancy in polio eradication in northern Nigeria

BackgroundVaccine hesitancy constitutes a major threat to the Global Polio Eradication Initiative (GPEI), and to further expansion of routine immunisation. Understanding hesitancy, leading in some cases to refusal, is vital to the success of GPEI. Re-emergence of circulating wild poliovirus in northern Nigeria in mid-2016, after 24 months polio-free, gives urgency to this. But it is equally important to protect and sustain the global gains available through routine immunisation in a time of rising scepticism and potential rejection of specific vaccines or immunisation more generally.Methods and findingsThis study is based on a purposive sampling survey of 1653 households in high- and low-performing rural, semiurban and urban areas of three high-risk states of northern Nigeria in 2013–14 (Sokoto, Kano and Bauchi). The survey sought to understand factors at household and community level associated with propensity to refuse polio vaccine.Wealth, female education and knowledge of vaccines were associated with lower propensity to refuse oral polio vaccine (OPV) among rural households. But higher risk of refusal among wealthier, more literate urban household rendered these findings ambiguous. Ethnic and religious identity did not appear to be associated with risk of OPV refusal.Risk of vaccine refusal was highly clustered among households within a small sub-group of sampled settlements. Contrary to expectations, households in these settlements reported higher levels of expectation of government as service provider, but at the same time lesser confidence in the efficacy of their relations with government.ConclusionsResults suggest that strategies to address the micro-political dimension of vaccination – expanding community-level engagement, strengthening the role of local government in public health, and enhancing public participation of women – should be effective in reducing non-compliance, as an important set of strategies complementary to conventional didactic/educational approaches and working through religious and traditional ‘influencers’.     

Integrating multiple-domain rules for disease classification

In psychiatry, clinicians use criteria sets from the Diagnostic and Statistical Manual of Mental Disorders to diagnose mental disorders. Most criteria sets have several symptom domains, and in order to be diagnosed, an individual must meet the minimum number of symptoms required by each domain. Some efforts are now focused on adding biomarkers to these symptom domains to facilitate the detection of and highlight the neurobiological basis of psychiatric disorders. Thus, a new criteria set may consist of both clinical symptom counts in several domains and continuous biomarkers. In this paper, we propose a method to integrate classification rules from multiple data sources to estimate an optimal criteria set. Each domain-specific rule can be counts of symptoms, a linear function of symptoms, or even nonparametric. The overall classification rule is the intersection of these domain-specific rules. Based on examining the expected population loss function, we propose two iterative algorithms using either support vector machines or logistic regression to fit intersection rules consistent with the Diagnostic and Statistical Manual of Mental Disorders. In simulation studies, these proposed methods are comparable with the true decision rule. The methods are applied to the motivating study to construct a criteria set for complicated grief. The developed criteria set shows a substantial improvement in sensitivity and specificity compared to the current standards on an independent validation study.     

The promises and perils of hospital autonomy: Reform by decree in Viet Nam

This article investigates impacts of hospital autonomization in Viet Nam employing a “decision-space” framework that examines how hospitals have used their increased discretion and to what effect. Analysis suggests autonomization is associated with increased revenue, increasing staff pay, and greater investment in infrastructure and equipment. But autonomization is also associated with more costly and intensive treatment methods of uncertain contribution to the Vietnamese government's stated goal of quality healthcare for all. Impacts of autonomization in district hospitals are less striking. Despite certain limitations, the analysis generates key insights into early stages of hospital autonomization in Viet Nam.     

A Quantum Probability Perspective on Borderline Vagueness

The term “vagueness” describes a property of natural concepts, which normally have fuzzy boundaries, admit borderline cases, and are susceptible to Zeno's sorites paradox. We will discuss the psychology of vagueness, especially experiments investigating the judgment of borderline cases and contradictions. In the theoretical part, we will propose a probabilistic model that describes the quantitative characteristics of the experimental finding and extends Alxatib's and Pelletier's ( 2011 ) theoretical analysis. The model is based on a Hopfield network for predicting truth values. Powerful as this classical perspective is, we show that it falls short of providing an adequate coverage of the relevant empirical results. In the final part, we will argue that a substantial modification of the analysis put forward by Alxatib and Pelletier and its probabilistic pendant is needed. The proposed modification replaces the standard notion of probabilities by quantum probabilities. The crucial phenomenon of borderline contradictions can be explained then as a quantum interference phenomenon.     

Relational machine learning for electronic health record-driven phenotyping

ObjectiveElectronic health records (EHR) offer medical and pharmacogenomics research unprecedented opportunities to identify and classify patients at risk. EHRs are collections of highly inter-dependent records that include biological, anatomical, physiological, and behavioral observations. They comprise a patient’s clinical phenome, where each patient has thousands of date-stamped records distributed across many relational tables. Development of EHR computer-based phenotyping algorithms require time and medical insight from clinical experts, who most often can only review a small patient subset representative of the total EHR records, to identify phenotype features. In this research we evaluate whether relational machine learning (ML) using inductive logic programming (ILP) can contribute to addressing these issues as a viable approach for EHR-based phenotyping.MethodsTwo relational learning ILP approaches and three well-known WEKA (Waikato Environment for Knowledge Analysis) implementations of non-relational approaches (PART, J48, and JRIP) were used to develop models for nine phenotypes. International Classification of Diseases, Ninth Revision (ICD-9) coded EHR data were used to select training cohorts for the development of each phenotypic model. Accuracy, precision, recall, F-Measure, and Area Under the Receiver Operating Characteristic (AUROC) curve statistics were measured for each phenotypic model based on independent manually verified test cohorts. A two-sided binomial distribution test (sign test) compared the five ML approaches across phenotypes for statistical significance.ResultsWe developed an approach to automatically label training examples using ICD-9 diagnosis codes for the ML approaches being evaluated. Nine phenotypic models for each ML approach were evaluated, resulting in better overall model performance in AUROC using ILP when compared to PART (p = 0.039), J48 (p = 0.003) and JRIP (p = 0.003).DiscussionILP has the potential to improve phenotyping by independently delivering clinically expert interpretable rules for phenotype definitions, or intuitive phenotypes to assist experts.ConclusionRelational learning using ILP offers a viable approach to EHR-driven phenotyping.