Gender-responsive monitoring and evaluation (M&E) for health and health systems interventions and programs is vital to improve health, health systems, and gender equality outcomes. It can be used to identify and address gender disparities in program participation, outcomes, and benefits, as well as ensure that programs are designed and implemented in a way that is inclusive and accessible for all. While gender-responsive M&E is most effective when interventions and programs intentionally integrate a gender lens, it is relevant for all health systems programs and interventions. Within the literature, gender-responsive M&E is defined in different and diverse ways, making it difficult to operationalize. This is compounded by the complexity and multi-faceted nature of gender. Within this methodological musing, we present our evolving approach to gender-responsive M&E which we are operationalizing within the Monitoring for Gender and Equity (MAGE) project. We define gender-responsive M&E as intentionally integrating the needs, rights, preferences, and power relations among women and girls, men and boys, and gender minority individuals, as well as across social, political, economic, and health systems, in M&E processes. This is done through the integration of different types of gender data and indicators, including: sex or gender specific, sex or gender disaggregated, sex or gender specific/disaggregated which incorporate needs, rights and preferences, and gender power relations and systems indicators. Examples of each of these are included within the paper. Active approaches can also enhance the gender-responsiveness of any M&E activities, including incorporating an intersectional lens and tailoring the types of data and indicators included and processes used to the specific context. Incorporating gender into the programmatic cycle, including M&E, can lead to more fit-for-purpose, effective, and equitable programs and interventions. The framework presented in this paper provides an outline of how to do this, enabling the uptake of gender-responsive M&E.

Among many by-products of Web 2.0 come the wide range of potential image and text datasets within social media and content sharing platforms that speak of how people live, what they do, and what they care about. These datasets are imperfect and biased in many ways, but those flaws make them complementary to data derived from conventional social science methods and thus potentially useful for triangulation in complex decision-making contexts. Yet the online environment is highly mutable, and so the datasets are less reliable than censuses or other standard data types leveraged in social impact assessment. Over the past decade, we have innovated numerous methods for deploying Instagram datasets in investigating management or development alternatives. This article synthesizes work from three Canadian decision contexts - hydroelectric dam construction or removal; dyke realignment or wetland restoration; and integrating renewable energy into vineyard landscapes - to illustrate some of the methods we have applied to social impact assessment questions using Instagram that may be transferrable to other social media platforms and contexts: thematic (manual coding, machine vision, natural language processing/sentiment analysis, statistical analysis), spatial (hotspot mapping, cultural ecosystem modeling), and visual (word clouds, saliency mapping, collage). We conclude with a set of cautions and next steps for the domain.
Parmi les nombreux sous-produits du Web 2.0 figure un large éventail de données provenant d’images et de textes, de contenus de médias sociaux et de plateformes numériques, qui révèlent comment les gens vivent, ce qu’ils font et les questions qui les préoccupent. Ces ensembles de données sont imparfaits et biaisés à bien des égards, mais nombre de leurs lacunes les rendent complémentaires des informations collectées par les sciences sociales à l’aide de méthodes conventionnelles. D’où leur utilité potentielle pour la triangulation dans des contextes décisionnels complexes. Cet article synthétise le travail de trois études de cas menées au Canada pour illustrer certaines des méthodes que nous avons développées et qui pourraient être utiles à d’autres chercheurs en EIS: thématiques (codage, apprentissage automatique, analyse sémantique, association statistique), spatiales (cartographie des points chauds, modélisation du transfert des bénéfices) et visuelles (cartes de saillance, collage).
Entre los muchos subproductos de la Web 2.0 se encuentra una amplia gama de datos de imágenes y texto, contenidos en redes sociales y plataformas digitales, que hablan de cómo vive, qué hace y por qué cuestiones se preocupa la gente. Estos conjuntos de datos son imperfectos y sesgados en muchos sentidos, pero muchos de sus defectos los hacen complementarios a la información recogida por las ciencias sociales con métodos convencionales. De ahí su potencial utilidad para la triangulación en contextos complejos de toma de decisiones. Este artículo sintetiza el trabajo de tres estudios de caso llevados a cabo en Canadá para ilustrar algunos de los métodos que hemos desarrollado y pueden resultar útiles para otros investigadores en EIS: temáticos (codificación, machine learning, análisis semántico, asociación estadística), espaciales (mapeo de puntos críticos, modelización de transferencia de beneficios) y visuales (mapas de saliencia, collage).

Emergency obstetric care (EmOC) signal functions are a shortlist of key clinical interventions capable of averting deaths from the five main direct causes of maternal mortality; they have been used since 1997 as a part of an EmOC monitoring framework to track the availability of EmOC services in low- and middle-income settings. Their widespread use and proposed adaptation to include other types of care, such as care for newborns, is testimony to their legacy as part of the measurement architecture within reproductive health. Yet, much has changed in the landscape of maternal and newborn health (MNH) since the initial introduction of EmOC signal functions. As part of a project to revise the EmOC monitoring framework, we carried out a meta-narrative inspired review to reflect on how signal functions have been developed and conceptualised over the past two decades, and how different narratives, which have emerged alongside the evolving MNH landscape, have played a role in the conceptualisation of the signal function measurement. We identified three overarching narrative traditions: 1) clinical 2) health systems and 3) human rights, that dominated the discourse and critique around the use of signal functions. Through an iterative synthesis process including 19 final articles selected for the review, we explored patterns of conciliation and areas of contradiction between the three narrative traditions. We summarised five meta-themes around the use of signal functions: i) framing the boundaries; ii) moving beyond clinical capability; iii) capturing the woods versus the trees; iv) grouping signal functions and v) measurement challenges. We intend for this review to contribute to a better understanding of the discourses around signal functions, and to provide insight for the future roles of this monitoring approach for emergency obstetric and newborn care.

UNASSIGNED: Many digital health interventions (DHIs), including mobile health (mHealth) apps, aim to improve both client outcomes and efficiency like electronic medical record systems (EMRS). Although interoperability is the gold standard, it is also complex and costly, requiring technical expertise, stakeholder permissions, and sustained funding. Manual data linkage processes are commonly used to \"integrate\" across systems and allow for assessment of DHI impact, a best practice, before further investment. For mHealth, the manual data linkage workload, including related monitoring and evaluation (M&E) activities, remains poorly understood.
UNASSIGNED: As a baseline study for an open-source app to mirror EMRS and reduce healthcare worker (HCW) workload while improving care in the Nurse-led Community-based Antiretroviral therapy Program (NCAP) in Lilongwe, Malawi, we conducted a time-motion study observing HCWs completing data management activities, including routine M&E and manual data linkage of individual-level app data to EMRS. Data management tasks should reduce or end with successful app implementation and EMRS integration. Data was analysed in Excel.
UNASSIGNED: We observed 69:53:00 of HCWs performing routine NCAP service delivery tasks: 39:52:00 (57%) was spent completing M&E data related tasks of which 15:57:00 (23%) was spent on manual data linkage workload, alone.
UNASSIGNED: Understanding the workload to ensure quality M&E data, including to complete manual data linkage of mHealth apps to EMRS, provides stakeholders with inputs to drive DHI innovations and integration decision making. Quantifying potential mHealth benefits on more efficient, high-quality M&E data may trigger new innovations to reduce workloads and strengthen evidence to spur continuous improvement.

This article uses reflective practice and social interdependence theory to unpack the ways in which our practice as internal evaluators was impacted by the COVID-19 pandemic, using the development of a monitoring and evaluation framework as a case study. The reflections are separated into six stages: description, feelings, evaluation, analysis, conclusion and action plan. Initial reflections on the impact of COVID-19 drew out the negative effects of the pandemic and associated restrictions, which limited our ability to build rapport and stretched our capacity to balance work and home commitments. Deeper investigation revealed that the disaster pushed us to develop new ways of working that will augment and improve our future efforts. We foresee that these learnings will enable a future with greater ability to offer hybrid online/face-to-face collaborative opportunities that will enhance inclusion and active participation, thereby promoting monitoring and evaluation with greater collective ownership and relevance to a wider audience.

Sound urban water management relies on extensive and reliable monitoring of water infrastructure. As low-cost sensors and networks have become increasingly available for environmental monitoring, urban water researchers and practitioners must consider the benefits and disadvantages of such technologies. In this perspective paper, we highlight six technical and socio-technological considerations for low-cost monitoring technology to reach its full potential in the field of urban water management, including: technical barriers to implementation, complementarity with traditional sensing technologies, low-cost sensor reliability, added value of produced information, opportunities to democratize data collection, and economic and environmental costs of the technology. For each consideration, we present recent experiences from our own work and broader literature and identify future research needs to address current challenges. Our experience supports the strong potential of low-cost monitoring technology, in particular that it promotes extensive and innovative monitoring of urban water infrastructure. Future efforts should focus on more systematic documenting of experiences to lower barriers to designing, implementing, and testing of low-cost sensor networks, and on assessing the economic, social, and environmental costs and benefits of low-cost sensor deployments.

BACKGROUND: Seasonal Malaria Chemoprevention (SMC) is a highly effective intervention for preventing malaria, particularly in areas with highly seasonal transmission. Monitoring and evaluating (M&E) SMC programmes are complex due to the scale, time-sensitive delivery of the programme, and influence of external factors. This paper describes the process followed to develop a comprehensive M&E framework tailored specifically for the SMC context.
METHODS: The Framework was developed through a literature and programme review, and stakeholder dialogues across three implementing countries-Burkina Faso, Chad, and Nigeria. Expert consultation further refined the Framework through an iterative approach drawing upon data collected through the three sources. The Framework was designed using the Logical Framework Approach incorporating external factors and intentionally aligned with global malaria M&E standards.
RESULTS: An overall aim and seven programme objectives were developed measured by 70 indicators. The indicators also capture the causal links between the implementation and results of the programme. The Framework leverages the use of current data sources and existing mechanisms, ensuring efficient data use without requiring a significant increase in resources for overall programme optimization. It also promotes the use of data triangulation, and stratification for a more nuanced understanding of factors affecting programme performance and timely data informed decision-making.
CONCLUSIONS: The SMC M&E Framework presented here provides a standardized approach for programme implementers to enhance decision-making for optimal programme performance. This is an essential tool as the scope of SMC programmes expands to new geographies and target age groups.

A national medicine policy (NMP), formerly referred to as a national drug policy (NDP) is a document that serves as a political commitment and guide for action by the government to provide safe, efficacious, quality assured, available, affordable and rationally used medicines. This is the first study to review the implemented components of the NMPs of the 16 South African Development Community (SADC) countries over the past ten years (2011-2021). Information published between 2011 and 2021 of each country such as pharmaceutical profiles, official government documents, WHO/HAI/World Bank datasets and research studies on the implemented components were appraised. Significant progress has been made by 16 SADC countries over the period 2011-2021 in implementing the NMP. The most commonly implemented components included the concept of essential medicines, pricing, and regulation. Though traditional and herbal medicines component is yet to be implemented by the majority. The pharmacist-patient ratio of 1:2300 was below the target for all countries, prompting the need to strengthen the pharmacy personnel in the healthcare systems. Medicine pricing, affordability, and availability studies are necessary to develop equitable pricing policies that will improve the accessibility of medicines in all countries and the SADC region. With the exception of the Republic of Tanzania, SADC countries need to urgently revise their NMPs, thus adopting progressive processes such as incorporating Health Technology Assessment (HTA) in the NMP. All SADC countries require a strong, internationalistic evaluation culture built-in their policy formulation. As the first study to investigate the implemented NMPs in the SADC region, it could serve as a springboard for the countries to address their common pharmaceutical challenges thus improving their readiness for universal health coverage (UHC). Future in-depth cross-country studies in the SADC region are necessary to comprehensively evaluate the implemented components of NMPs.

Individual and community-level COVID-19 mitigation policies can have effects beyond direct COVID-19 health outcomes, including social, behavioral, and economic outcomes. These social, behavioral, and economic outcomes can extend beyond the pandemic period and have disparate effects on populations. Public Health-Seattle & King County (PHSKC) built on the Centers for Disease Control and Prevention\'s community mitigation strategy framework to create a local project tracking near-real-time data to understand factors affected by mitigation approaches, inform decision-making, and monitor and evaluate community-level disparities during the pandemic. This case study describes the framework and lessons learned from PHSKC\'s collation, use, and dissemination of local data from 20 data sources to guide community and public health decision-making. Social, behavioral, economic, and health indicators were regularly updated and disseminated through interactive dashboards and products that examined data in the context of applicable policies. Data disaggregated by demographic characteristics and geography highlighted inequities, but not all datasets contained the same details; local surveys or qualitative data were used to fill gaps. Project outcomes included informing city and county emergency response planning related to implementation of financial and food assistance programs. Key lessons learned included the need to (1) build on existing processes and use automated processes and (2) partner with other sectors to use nontraditional public health data for active dissemination and data disaggregation and for real-time data contextualized by policy changes. This project provided programs and communities with timely, reliable data to understand where to invest recovery funding. A similar framework could position other health departments to examine social and economic effects during future public health emergencies.

BACKGROUND: Differentiated service delivery (DSD) increases antiretroviral therapy (ART) access in sub-Saharan Africa by moving clients out of congested ART clinics to communities for care. However, DSD settings challenge provider adherence to complex, chronic care treatment guidelines and have burdensome systems for client monitoring and evaluation (M&E), reducing data for decision-making. Electronic medical record systems (EMRS) improve client outcomes and reduce M&E workload. Traditional EMRS cannot operate in most DSD settings with unreliable power and poor connectivity.
OBJECTIVE: This study aims to detail the human-centered design (HCD) process of developing a mobile EMRS for community-based DSD services in Lilongwe, Malawi.
METHODS: Lighthouse Trust (LT) operates 2 Ministry of Health (MoH) clinics in Lilongwe, Malawi, with a combined total of >35,000 ART clients. LT\'s real-time, point-of-care EMRS collects complex client M&E data and provides decision-making support, ensuring adherence to integrated HIV and tuberculosis guidelines that optimize client and program outcomes. LT\'s EMRS scaled to all large MoH ART clinics. LT also implements a nurse-led community-based ART program (NCAP), a DSD model to provide ART and rapid assessment for 2400 stable LT clients in the community. LT, alongside collaborators, from the University of Washington\'s International Training and Education Center for Health and technology partner, Medic, used the open-source Community Health Toolkit (CHT) and HCD to develop an open-source, offline-first, mobile EMRS-like app, \"community-based ART retention and suppression\" (CARES). CARES aims to bring EMRS-like provider benefits to NCAP\'s DSD clients.
RESULTS: CARES design took approximately 12 months and used an iterative process of highly participatory feedback sessions with provider, data manager, and M&E team inputs to ensure CARES optimization for the NCAP and LT settings. The CARES mobile EMRS prototype supports NCAP providers with embedded prompts and alerts to ensure adherence to integrated MoH ART guidelines, aiming to improve the quality of client care. CARES facilitates improved data quality and flow for NCAP M&E, aiming to reduce data gaps between community and clinic settings. The CARES pilot demonstrates the potential of a mobile, point-of-care EMRS-like app that could benefit NCAP clients, providers, and program teams with integrated client care and complete M&E data for decision-making. CARES challenges include app speed, search features to align longitudinal records, and CARES to EMRS integration that supports timely care alerts.
CONCLUSIONS: Leveraging the CHT and HCD processes facilitated the design of a locally specified and optimized mobile app with the promise to bring EMRS-like benefits to DSD settings. Moving from the CARES prototype to routine NCAP implementation should result in improved client care and strengthened M&E while reducing workload. Our transparent and descriptive process shares the progress and pitfalls of the CARES design and development, helping others in this digital innovation area to learn from our experiences at this stage.