Estimating the return on investment of selected infection prevention and control interventions in healthcare settings for preparing against novel respiratory viruses: modelling the experience from SARS-CoV-2 among health workers.

Background: Insufficient infection prevention and control (IPC) practices in healthcare settings increase the SARS-CoV-2 infection risk among health workers. This study aimed to examine the level of preparedness for future outbreaks. Methods: We modelled the experience from the COVID-19 pandemic and assessed the return on investment on a global scale of three IPC interventions to prevent SARS-CoV-2 infections among health workers: enhancing hand hygiene; increasing access to personal protective equipment (PPE); and combining PPE, with a scale-up of IPC training and education (PPE+). Our analysis covered seven geographic regions, representing a combination of World Health Organization (WHO) regions and the Organisation for Economic Co-operation and Development (OECD) countries. Across all regions, we focused on the first 180 days of the pandemic in 2020 between January 1st and June 30th. We used an extended version of a susceptible-infectious-recovered compartmental model to measure the level of IPC preparedness. Data were sourced from the WHO COVID-19 Detailed Surveillance Database. Findings: In all regions, the PPE + intervention would have averted the highest number of new SARS-CoV-2 infections compared to the other two interventions, ranging from 6562 (95% CI 4873-8779) to 38,170 (95% CI 33,853-41,901) new infections per 100,000 health workers in OECD countries and in the South-East Asia region, respectively. Countries in the South-East Asia region and non-OECD countries in the Western Pacific region were poised to achieve the highest level of savings by scaling up the PPE + intervention. Interpretation: Our results not only support efforts to make an economic case for continuing investments in IPC interventions to halt the COVID-19 pandemic and protect health workers, but could also contribute to efforts to improve preparedness for future outbreaks. Funding: This work was funded by WHO, with support by the German Federal Ministry of Health for the WHOResearch and Development Blueprint for COVID-19.

A comparative assessment of action plans on antimicrobial resistance from OECD and G20 countries using natural language processing.

Following the launch of the Global Action Plan on antimicrobial resistance (AMR-GAP) in 2015, most OECD and G20 countries developed their own national action plans (AMR-NAPs). This is the first paper that deploys natural language processing (NLP) techniques to systematically measure and compare the extent to which AMR-NAPs from 21 OECD and G20 countries align with the AMR-GAP in terms of the strategic objectives and interventions. We quantify the extent of alignment based on two NLP metrics: term-frequency (TF) and term-frequency-inverse document frequency (TF-IDF). Quantifying TF allows us to compare the relative prominence of strategic objectives and interventions, whereas quantifying TF-IDF enables us to identify interventions that occur more frequently in each AMR-NAP. Similar to the AMR-GAP, in our sample, terms associated with optimizing antimicrobial use in human and animal health have the highest frequency (TF = 0. 287), whereas terms linked to raising AMR awareness and education have the lowest frequency (TF = 0.066). Substantial cross-country variation exists in the distribution of interventions that are distinctly frequent in each AMR-NAP. We also report new evidence on the selected policy design and monitoring and evaluation features of these documents. Our results suggest a high degree of congruence between the AMR-GAP and AMR-NAPs, with notable diversity in the spate of interventions that OECD and G20 countries discuss in their action plans.

Financial strategies targeting healthcare providers to promote the prudent use of antibiotics: a systematic review of the evidence.

Improving prudent use of antibiotics is one way to limit the spread of antimicrobial resistance (AMR). The objective of this systematic review was to assess the effects of financial strategies targeting healthcare providers on the prudent use of antibiotics. A systematic review of the literature was conducted searching PubMed, Embase and Cochrane databases, and the grey literature. Search terms related to antibacterial agents, drug resistance, financial strategies, and healthcare providers and/or prescribers. Twenty-two articles were included in the review, reporting on capitation and salary reimbursement, cost containment interventions, pay-for-performance initiatives, penalties, and a one-off bonus payment. There was substantial variation in the reported outcomes describing prescribing behaviours, including proportion of patients prescribed antibiotics, antibiotic prescriptions per patient, and number of cases treated with recommended antibiotic therapy. All financial strategies were associated with improvements in the appropriate prescription of antibiotics in the short-term, although the magnitude of observed effects varied across financial strategies. Financial penalties were associated with the greatest decreases in inappropriate antibiotic prescriptions, followed by capitation models and pay-for-performance schemes that paid bonuses upon achievement of performance targets. However, the risk of bias across studies must be noted. Findings point to the viability of financial strategies to promote the prudent use of antibiotics. Measuring the downstream impact of prescriber behaviour changes is key to estimating the true value of such interventions to tackle AMR. Research efforts should continue to build the evidence on causal mechanisms driving provider prescribing patterns for antibiotics and the long-term impact on antibiotic prescriptions.

A Comparative Case Study: Does the Organization of Primary Health Care in Brazil and Turkey Contribute to Reducing Disparities in Access to Care?

Brazil and Turkey are among the few high-middle-income countries that explicitly chose to strengthen their primary health care (PHC) systems as the centerpiece of much broader health system reforms aiming to narrow inequities in access to care. This comparative case study reviews the organization of Brazil and Turkey's PHC systems to derive lessons that can apply to other countries that may consider reforming the organization of PHC systems as a way to address health inequities. The analysis uses the Flagship Framework to investigate how the organization of PHC delivery in Brazil and Turkey can lead to measurable improvements in access to care. It compares (1) the degree of decentralization in PHC service delivery responsibilities, (2) the use of multi-professional PHC teams, and (3) patient impanelment strategies. The comparative analysis offers three important lessons. First, changes in the organization of PHC systems can contribute to observable improvements in the level and distribution of health outcomes, but organizational strategies do not guarantee eliminating disparities in access. Second, PHC systems can operate in health systems with varying degrees of decentralization, but the level of decentralization may influence implementation. Third, relying on multi-professional PHC teams that serve geographically empaneled populations can improve equitable access to care, but course corrections may be needed to address evolving health demands.

Assessing the performance of beneficiary targeting in Brazil's More Doctors Programme.

Many countries employ strategies that rest on the use of an explicitly defined set of criteria to identify underserved communities. Yet, we know relatively little about the performance of community-level targeting in large-scale health programmes. To address this gap, we examine the performance of community targeting in the More Doctors Programme (MDP). Our analysis covers all 5570 municipalities in the period between 2013 and 2017 using publicly available data. We first calculate the rate at which vulnerable municipalities enrolled in the MDP. Next, we consider two types of mistargeting: (1) proportion of vulnerable municipalities that did not have any MDP physicians (i.e. under-coverage municipalities) and (2) proportion of MDP enrolees that did not fit the vulnerability criteria (i.e. non-target municipalities). We found that almost 70% of vulnerable municipalities received at least one MDP physician between 2013 and 2017; whereas non-target municipalities constituted 33% of beneficiaries. Targeting performance improved over time. Non-target municipalities had the highest levels of socioeconomic development and greater physician availability. The poverty rate among under-coverage municipalities was almost six times that in non-target municipalities. Under-coverage municipalities had the lowest primary care physician availability. They were also smaller and more sparsely populated. We also found small differences in the political party alignments of mayors and the President between under-coverage and non-target municipalities. Our results suggest that using community-level targeting approaches in large-scale health programmes is a complex process. Programmes using these approaches may face substantial challenges in beneficiary targeting. Our results highlight that policymakers who consider using these approaches should carefully study various municipal characteristics that may influence the implementation process, including the level of socioeconomic development, health supply factors, population characteristics and political party alignments.

Impact of Brazil's More Doctors Program on hospitalizations for primary care sensitive cardiovascular conditions.

Globally, cardiovascular diseases are the leading cause of disease burden and death. Timely and appropriate provision of primary care may lead to sizeable reductions in hospitalizations for a range of chronic and acute health conditions. In this paper, we study the impact of Brazil's More Doctors Program (MDP) on hospitalizations due to cerebrovascular disease and hypertension. We exploit the geographic variation in the uptake of the MPD and combine coarsened exact matching and difference-in-difference methods to construct valid counterfactual estimates. We use data from the Hospital Information System in Unified Health System, the MDP administrative records, the Brazilian Regulatory Agency, the Ministry of Health, and the Brazilian Institute of Geography and Statistics, covering the years from 2009 to 2017. Our analysis resulted in estimated coefficients of -1.47 (95%CI: -4.04,1.10) for hospitalizations for cerebrovascular disease and -1.20 (95%CI: -5.50,3.11) for hypertension, suggesting an inverse relationship between the MDP and hospitalizations. For cerebrovascular disease, the estimated MDP coefficient was -0.50 (95%CI: -2.94,1.95) in the year of program introduction, -5.21 (95%CI: -9.43,-0.99) and -8.21 (95%CI: -13.68,-2.75) in its third and fourth year of implementation, respectively. Our results further suggest that the beneficial impact of MDP on hospitalizations due to cerebrovascular disease became discernable in urban municipalities starting from the fourth year of implementation. We found no evidence that the MDP led to reductions in hospitalizations due to hypertension. Our results highlight that increased investment in resources devoted to primary care led to improvements in hospitalizations for selected cardiovascular conditions. However, it took time for the beneficial effects of the MDP to become discernable and the Program did not guarantee declines in hospitalizations for all cardiovascular conditions, suggesting that further improvements may be needed to enhance the beneficial impact of the MDP on the level and distribution of population health in Brazil.

Applying Inverse Probability Weighting to Measure Contraceptive Prevalence Using Data from a Community-Based Reproductive Health Intervention in Pakistan.

CONTEXT: Many community-based reproductive health programs use their program data to monitor progress toward goals. However, using such data to assess programmatic impact on outcomes such as contraceptive use poses methodological challenges. Inverse probability weighting (IPW) may help overcome these issues. METHODS: Data on 33,162 women collected in 2013-2015 as part of a large-scale community-based reproductive health initiative were used to produce population-level estimates of the contraceptive prevalence rate (CPR) and modern contraceptive prevalence rate (mCPR) among married women aged 15-49 in Pakistan's Korangi District. To account for the nonrandom inclusion of women in the sample, estimates of contraceptive prevalence during the study's four seven-month intervention periods were made using IPW; these estimates were compared with estimates made using complete case analysis (CCA) and the last observation carried forward (LOCF) method-two approaches for which modeling assumptions are less flexible. RESULTS: In accordance with intervention protocols, the likelihood that women were visited by intervention personnel and thus included in the sample differed according to their past and current contraceptive use. Estimates made using IPW suggest that the CPR increased from 51% to 64%, and the mCPR increased from 34% to 53%, during the study. For both outcomes, IPW estimates were higher than CCA estimates, were generally similar to LOCF estimates and yielded the widest confidence intervals. CONCLUSION: IPW offers a powerful methodology for overcoming estimation challenges when using program data that are not representative of the population in settings where cost impedes collection of outcome data for an appropriate control group.

RESUMEN Contexto: Muchos programas comunitarios de salud reproductiva usan los datos de su programa para monitorear el progreso hacia sus metas. Sin embargo, el uso de tales datos para evaluar el impacto programático en resultados tales como el uso de anticonceptivos plantea desafíos metodológicos. La ponderación de probabilidad inversa (PPI) podría ayudar a superar estos problemas. Métodos: Se usaron datos de 33,162 mujeres recolectados entre 2013 y 2015 como parte de una iniciativa comunitaria de salud reproductiva a gran escala para producir estimaciones de la tasa de prevalencia de anticonceptivos (TPA) y la tasa de prevalencia de anticonceptivos modernos (TPAm) a nivel de la población, entre mujeres casadas de 15 a 49 años de edad en el distrito de Korangi, Pakistán. Para tener en cuenta la inclusión no aleatoria de mujeres en la muestra, se hicieron estimaciones de la prevalencia del uso de anticonceptivos durante los cuatro períodos de siete meses de intervención del estudio utilizando PPI; estas estimaciones se compararon con las estimaciones realizadas utilizando el análisis de caso completo (ACC) y el método de la última observación llevada adelante (UOLA)­dos enfoques cuyos supuestos de modelado son menos flexibles. Resultados: De conformidad con los protocolos de intervención, la probabilidad de que las mujeres fueran visitadas por el personal de intervención y por lo tanto incluidas en la muestra difería de acuerdo con su uso anticonceptivo pasado y actual. Las estimaciones realizadas con la PPI sugieren que, durante el estudio, la TPA aumentó del 51% al 64%; y que la TPAm aumentó del 34% al 53%. Para ambos resultados, las estimaciones fueron más altas que las estimaciones de ACC, en general fueron similares a las estimaciones de UOLA y produjeron intervalos de confianza más amplios. Conclusiones: La PPI ofrece una metodología poderosa para superar los desafíos relacionados con las estimaciones, cuando se utilizan datos de programas que no son representativos de la población en entornos donde el costo impide la recolección de datos de resultados para un grupo de control apropiado.

RÉSUMÉ Contexte: De nombreux programmes de santé reproductive à base communautaire utilisent leurs données pour suivre le progrès vers la réalisation de leurs objectifs. L'emploi de ces données pour évaluer l'impact programmatique sur les résultats tels que la pratique contraceptive pose cependant des problèmes de méthode. La pondération par l'inverse de la probabilité (PIP) peut être utile à la résolution de ces difficultés. Méthodes: Les données relatives à 33 162 femmes, collectées en 2013­2015 dans le cadre d'une initiative de santé reproductive à base communautaire à grande échelle, ont servi à produire des estimations au niveau de la population du taux de prévalence contraceptive (TPC) et du taux de prévalence contraceptive moderne (TPCm) parmi les femmes mariées âgées de 15 à 49 ans dans le district pakistanais de Korangi. Pour rendre compte de l'inclusion non aléatoire des femmes dans l'échantillon, les estimations de la prévalence pendant les quatre périodes d'intervention de sept mois de l'étude ont été calculées selon la méthode PIP. Ces estimations ont été comparées à celles obtenues par analyse de cas complète (ACC) et selon la méthode de la dernière observation rapportée (LOCF) ­ deux approches à hypothèses de modélisation moins souples. Résultats: Conformément aux protocoles d'intervention, la probabilité que les femmes aient reçu la visite du personnel d'intervention et soient donc incluses dans l'échantillon diffère suivant leur pratique passée et actuelle de la contraception. Les estimations obtenues selon la méthode PIP portent à croire que le TPC est passé de 51% à 64%, et le TPCm de 34% à 53%, pendant l'étude. Pour les deux résultats, les estimations PIP étaient supérieures à celles calculées selon la méthode ACC; elles étaient généralement similaires aux estimations LOCF et elles produisaient les plus larges intervalles de confiance. Conclusions: La PIP offre une méthode efficace de résolution des difficultés d'estimation lors de l'utilisation de données de programme non représentatives de la population, dans les contextes où le coût entrave la collecte de données de résultat pour un groupe témoin approprié.

Political Economy Analysis for Health Financing Reform.

Health financing reform is an inherently political process that alters the distribution of entitlements, responsibilities and resources across the health sector and beyond. As a result, changes in health financing policy affect a range of stakeholders and institutions in ways that can create political obstacles and tensions. As countries pursue health financing policies that support progress towards Universal Health Coverage, the analysis and management of these political concerns must be incorporated in reform processes. This article proposes an approach to political economy analysis to help policy makers develop more effective strategies for managing political challenges that arise in reform. Political economy analysis is used to assess the power and position of key political actors, as a way to develop strategies to change the political feasibility of desired reforms. Applying this approach to recent health financing reforms in Turkey and Mexico shows the importance of political economy factors in determining policy trajectories. In both cases, reform policies are analyzed according to the roles and positions of major categories of influential stakeholders: interest group politics, bureaucratic politics, budget politics, leadership politics, beneficiary politics, and external actor politics. The strategic responses to each political economy factor stress the connectedness of technical and political processes. Applying the approach to the two cases of Turkey and Mexico retrospectively shows its relevance for understanding reform experiences and its potential for helping decision makers manage reform processes prospectively. Moving forward, explicit political economy analysis can become an integral component of health financing reform processes to inform strategic responses and policy sequencing.