Background Supportive supervision is pivotal for both health service providers and managers to improve the quality of services and health outcomes. Tanzania's digital supportive supervision system is called Afya Supportive Supervision System (AfyaSS ®). The latter was designed and developed using a human-centered approach called Collaborative Requirements Development Methodology (CRDM). This paper describes the experiences of building the digital supportive supervision system through CRDM in Tanzania, a transition from the paper-based supportive supervision system. Methods In 2018, with the support of PATH, the government of Tanzania adopted a participatory human-centered design by carrying out desk reviews of existing guidelines and tools, field visits, stakeholder workshops, and user advisory groups to gather information for developing a digital supportive supervision system. The gathered information was analyzed with the lens of identifying the common challenges and system requirements. Results AfyaSS was successfully developed using CRDM and deployed in all regions across the country. It has consolidated multiple checklists for distinct health domains, and dashboard functionalities to track progress toward health system indicators, objectives, and action plans. As part of the deployment, several resources were developed to aid in the deployment process, such as a comprehensive user manual, facilitator's guide, training slides, and video tutorials. Health workers and managers can be empowered and motivated to implement comprehensive and coherent supportive supervision by using the lessons learned from this digitalization process to transform the current supervision processes to improve the quality of care by offering instruments that promote evidence-based actions. Conclusion A human-centered approach has been shown to be useful in developing digital tools for use in Tanzania’s health system. Tanzania's lessons can be applied in other low- and middle- income countries (LMICs) with similar contexts when considering implementing digital health interventions. While using the human-centered approach, it is crucial to establish a system development roadmap, conduct appropriate training, provide sustained information and communication technology, and management support for unforeseen issues, and ensure ongoing maintenance.

The global digital health ecosystem is project-centric: point solutions are developed for vertical health programs and financed through vertical funding allocations. This results in data fragmentation and technology lock-in, compromising health care delivery. A convergence of trends enabled by interoperability and digital governance makes possible a shift towards person-focused health. Together, open Standards, open Technologies, open Architectures and open Content represent a next-generation 'full-STAC' remedy for digital health transformation. Local developers and implementers can avoid reinventing the wheel, and instead build digital tools suited to local needs-where data travels with an individual over time, evidence-based practice is easily integrated, and insights are gleaned from harmonized data. This is the culmination of the vision endorsed by 194 WHO Member States in the Global Strategy on Digital Health 2020 to 2025.

Global campaigns to control HIV, tuberculosis, malaria, and vaccine-preventable illnesses showed that large-scale impact can be achieved by using additional international financing to support selected, evidence-based, high-impact investment areas and to catalyse domestic resource mobilisation. Building on this paradigm, we make the case for targeting additional international funding for selected high-impact investments in primary health care. We have identified and costed a set of concrete, evidence-based investments that donors could support, which would be expected to have major impacts at an affordable cost. These investments are in: (1) individuals and communities empowered to engage in health decision making, (2) a new model of people-centred primary care, and (3) next generation community health workers. These three areas would be supported by strengthening two cross-cutting elements of national systems. The first is the digital tools and data that support facility, district, and national managers to improve processes, quality of care, and accountability across primary health care. The second is the educational, training, and supervisory systems needed to improve the quality of care. We estimate that with an additional international investment of between US$1·87 billion in a low-investment scenario and $3·85 billion in a high-investment scenario annually over the next 3 years, the international community could support the scale-up of this evidence-based package of investments in the 59 low-income and middle-income countries that are eligible for external financing from the World Bank Group's International Development Association.

Registries play an instrumental role in facilitating the transfer, aggregation, and analysis of standardized data in health information exchange (HIE). One such example is a health worker registry (HWR), a central, authoritative registry that maintains the unique identities of health workers according to a defined, minimum data set. Currently, data comprising workers’ information—such as education, licensure, and place of employment—are collected through disparate methods and maintained in a variety of information systems. Harmonization of these data via an HWR can support interoperability and comparability of worker information across systems, thereby facilitating efficient workforce enumeration, planning, regulation and deployment, verification of training and education, identification of workforce shortages, and rapid communication and coordination of emergency response. In fact, HWR technologies played a role in coordinating response to both Ebola in West Africa in 2014 and more recently in response to COVID-19, making a HWR integral to nations’ infrastructure upgrades postpandemic. This chapter identifies who is considered a “health worker” and why a registry of these individuals is a useful component of an HIE, especially in the wake of the COVID-19 pandemic. It also provides guidance on selection of data elements and standards to include in the development of an HWR.

From the short-term and long-term effects of the COVID-19 pandemic to the health insecurities brought about by climate change, health futures are unfolding in an era of accelerating economic, societal, technological, and environmental changes. Digital transformations, which we define as the multifaceted processes of integration of digital technologies and platforms into all areas of life, including health, are central to understanding—and shaping—many of these disruptive dynamics. Because large gaps remain in the current evidence base on the interface of digital technologies and health, taking a precautionary, mission-oriented, and value-based approach to its governance is crucial. Digital transformations are embedded into, and negotiated within, broader political, societal, and economic processes. Business models based on data extraction, concentrations of power, and viral spread of misinformation and disinformation represent defining features of the current phase of digital transformations. For both private actors and governments, digital tools also allow for unprecedented reach into people's everyday lives, and are being used in many countries for surveillance and political purposes. Within these wider processes of digital transformations, health is rapidly becoming a high-stake domain owing to dynamics such as the increasing economic relevance of health data and the growing appetite for digital solutions in the health-care sector, which have been substantially accelerated by the COVID-19 pandemic. Digital transformations have the potential to bring both enormous long-term benefits and substantial disruption in many different areas of health and health care—in fact, the effect of digital transformations has been so pervasive that it might soon become a dominant prism through which we can understand and address health and wellbeing dynamics. Digital technologies are already driving health transformations both directly (through their application in health systems, health care, and self-monitoring of health status and behaviours) and indirectly (through their influence on the social, commercial, and environmental determinants of health). Moreover, due to the influence that dynamics of digital access and literacy might have on health and wellbeing outcomes, we can consider the digital ecosystem itself as an increasingly important determinant of health. Digital transformations call for a new understanding of the concepts of public health and universal health coverage (UHC), which reflect the extent to which digital technologies are changing notions of health and wellbeing and offering new tools through which public health goals can be achieved. However, this does not mean that achieving UHC in a digital world will only depend on a rapid pace of adoption of new technologies in health care and health systems. On the contrary, it will be important for decision makers to adopt a mission-oriented approach to digital health innovation, which aims to diffuse the benefits of digital health technologies equitably, make their deployment economically feasible, and decentralise and democratise their control. Moreover, reimagining public health and UHC in the light of digital transformations will also mean rethinking the breadth of health services that are offered in health systems and included in the publicly financed UHC package, to better reflect those new dimensions of health and wellbeing that are directly dependent on digital technologies and their role as new determinants of health. To ensure that everyone benefits from digital transformations of health and health care, there is an urgent need to orient digital health priorities towards the establishment of strong health and wellbeing foundations early in life. This objective will especially require adapting the health services that are traditionally considered part of UHC to reflect the needs and priorities of children and young people, which are likely to vary across age groups, communities, and levels of digital literacy. There are several reasons for putting children and young people at the centre of this effort. First, addressing the role of digital technologies as determinants of health already in early childhood will be crucial for reducing the social and economic burdens of disease later in life. Second, the health and wellbeing outcomes of children and young people are likely to be a litmus test for the capacity of societies to harness digital transformations in support of UHC for all people. Third, although there is no universal experience of growing up in a digital world, children and young people are generally those with the highest exposure to digital technologies. As such, they are both particularly exposed to potential harms that might derive from them and uniquely equipped to shape positive health futures through codesign of digital health solutions and participatory research and decision making. The massive challenges and opportunities posed by digital transformations of health and health care constitute a powerful call for governance at multiple scales, which should be grounded in core Health for All values of democracy, equity, solidarity, inclusion, and human rights. Upholding Health for All values through governance will help ensure that digital technologies enable health benefits, including positive transformation of UHC, improved access to and quality of health services, and more effective prevention and management of public health crises. However, if these values are to play a central role in shaping health futures, they must be strengthened and updated to reflect their specific relevance for, and intersection with, digital transformations. The governance of digital technologies in health and health care must be driven by public purpose, not private profit. Its primary goals should be to address the power asymmetries reinforced by digital transformations, increase public trust in the digital health ecosystem, and ensure that the opportunities offered by digital technologies and data are harnessed in support of the missions of public health and UHC. To achieve these goals, we propose four action areas that we consider game-changers for shaping health futures in a digital world. First, we suggest that decision makers, health professionals, and researchers consider—and address—digital technologies as increasingly important determinants of health. Second, we emphasise the need to build a governance architecture that creates trust in digital health by enfranchising patients and vulnerable groups, ensuring health and digital rights, and regulating powerful players in the digital health ecosystem. Third, we call for a new approach to the collection and use of health data based on the concept of data solidarity, with the aim of simultaneously protecting individual rights, promoting the public good potential of such data, and building a culture of data justice and equity. Finally, we urge decision makers to invest in the enablers of digitally transformed health systems, a task that will require strong country ownership of digital health strategies and clear investment roadmaps that help prioritise those technologies that are most needed at different levels of digital health maturity.

As part of the work the Better Immunization Data (BID) Initiative undertook starting in 2013 to improve countries' collection, quality, and use of immunization data, PATH partnered with countries to identify the critical requirements for an electronic immunization registry (EIR). An EIR became the core intervention to address the data challenges that countries faced but also presented complexities during the development process to ensure that it met the core needs of the users. The work began with collecting common system requirements from 10 sub-Saharan African countries; these requirements represented the countries' vision of an ideal system to track individual child vaccination schedules and elements of supply chain. Through iterative development processes in both Tanzania and Zambia, the common requirements were modified and adapted to better fit the country contexts and users' needs, as well as to be developed with the technology available at the time. This process happened across four different software platforms. This paper outlines the process undertaken and analyzes similarities and differences across the iterations of the EIR in both countries, culminating in the development of a registry in Zambia that includes the most critical aspects required for initially deploying the registry and embodies what could be considered the minimum viable product for an EIR.

Citation for published version (APA): McQuide, P., Settle, D., Abubaker, W., Alsheikh, M., Regina Pierantonin, C., & de Vries, D. H. (2009). Use of administrative data sources for health workforce analysis: multicountry experience in implementation of human resources information systems. In M. R. Dal Poz, N. Gupta, E. Quain, & A. L. Soucat (Eds.), Handbook on Monitoring and Evaluation of Human Resources for Health with special applications for lowand middle-income countries (pp. 113-126). Geneva: World Health Organization.

Registries play an instrumental role in facilitating the transfer, aggregation, and analysis of standardized data in health information exchange (HIE). One such example is a health worker registry (HWR), a central, authoritative registry that maintains the unique identities of health workers according to a defined minimum data set. Currently, data comprising workers' information—such as education, licensure, and place of employment—are collected through disparate methods and maintained in a variety of information systems. Harmonization of these data via an HWR can support interoperability and comparability of worker information across systems, thereby facilitating efficient workforce planning, including verification of training and education, identification of workforce shortages, and coordination of emergency response. This chapter identifies who is considered a "health worker" and why a registry of these individuals is a useful component of an HIE. It also provides guidance on selection of data elements and standards to include in the development of an HWR.

Despite progress over the last decade, Uganda's achievement of key health indicators, including for HIV and AIDS, remains unsatisfactory and continues to represent leading causes of morbidity and mortality [1]. As the Government of Uganda works to improve healthcare across all service delivery areas, HIV and AIDS receives heightened attention because of the country's ranking in terms of the number of new HIV infections, people living with HIV (PLHIV), AIDS-related deaths, and adult HIV prevalence rate [2]. Intensive efforts in HIV prevention, care, and treatment led to a decrease in HIV prevalence from a high of 18% in the 1990s to 6.4% in 2002. After persisting at this level from 2002 to 2007, HIV prevalence rose to a national average of 7.3% (2011) [3,4]. Many regions experience an even higher burden of HIV, especially in central and mid-northern Uganda, with prevalence ranging from 8.3 to 10.6% [4]. Health workforce challenges undermine HIV service delivery Uganda's aim to strengthen and scale up its HIV and AIDS response to reduce new infections and achieve ‘a population free of HIV and its effects’ [5] is undermined by low utilization of health services and perceived low quality of healthcare [6]. A key element of quality service delivery and demand is a well performing and well trained health workforce [7]. Uganda's absolute shortage and inadequate geographic distribution of health workers with appropriate skill mix to provide services across the continuum hinders achievement of epidemic control. A national staff audit conducted by the Ministry of Health in 2009 found that 47% of established positions in government health facilities were vacant [8]. In addition, about 71% of doctors and 41% of nurses and midwives were working in urban areas, although 85% of the population reside in rural areas [9,10]. Factors contributing to high health worker vacancy and low retention include weak leadership and management, inadequate planning and human resources management systems, low levels of motivation, and poor working and living conditions in rural areas [6]. To address health workforce challenges affecting quality of care for HIV and AIDS, the United States Agency for International Development (USAID) and U.S. President's Emergency Plan for AIDS Relief-funded global CapacityPlus project and bilateral Uganda Capacity Program (UCP), both led by IntraHealth International, worked in close collaboration with the Ministry of Health to strengthen health workforce management to enable improved delivery of quality HIV and AIDS services. They also provided family planning, reproductive health and other health services with funding from PEPFAR and USAID's Population and Reproductive Health, Maternal and Child Health, and other programs. This field note describes selected interventions from a more comprehensive package of human resources management support provided to the Ministry of Health, to improve the utilization of data for evidence-based planning, deployment, and management of the health workforce. It also provides an example of how health workforce data can be analyzed alongside country-level HIV service statistics to ensure an adequate supply of human resources for health (HRH) where increased accessibility and scale-up of HIV services is needed to achieve 90–90–90 goals [11–13].

Background: In-service training of health workers plays a pivotal role in improving service quality. However, it is often expensive and requires providers to leave their posts. We developed and assessed a prototype mLearning system that used interactive voice response (IVR) and text messaging on simple mobile phones to provide in-service training without interrupting health services. IVR allows trainees to respond to audio recordings using their telephone keypad.Methods: In 2013, the CapacityPlus project tested the mobile delivery of an 8-week refresher training course on management of contraceptive side effects and misconceptions to 20 public-sector nurses and midwives working in Mekhe and Tivaouane districts in the Thies region of Senegal. The course used a spaced-education approach in which questions and detailed explanations are spaced and repeated over time. We assessed the feasibility through the system's administrative data, examined participants' experiences using an endline survey, and employed a pre- and post-test survey to assess changes in provider knowledge.Results: All participants completed the course within 9 weeks. The majority of participant prompts to interact with the mobile course were made outside normal working hours (median time, 5: 16 pm); average call duration was about 13 minutes. Participants reported positive experiences: 60% liked the ability to determine the pace of the course and 55% liked the convenience. The largest criticism (35% of participants) was poor network reception, and 30% reported dropped IVR calls. Most (90%) participants thought they learned the same or more compared with a conventional course. Knowledge of contraceptive side effects increased significantly, from an average of 12.6/20 questions correct before training to 16.0/20 after, and remained significantly higher 10 months after the end of training than at baseline, at 14.8/20, without any further reinforcement.Conclusions: The mLearning system proved appropriate, feasible, and acceptable to trainees, and it was associated with sustained knowledge gains. IVR mLearning has potential to improve quality of care without disrupting routine service delivery. Monitoring and evaluation of larger-scale implementation could provide evidence of system effectiveness at scale.

BACKGROUND:To address the need for timely and comprehensive human resources for health (HRH) information, governments and organizations have been actively investing in electronic health information interventions, including in low-resource settings. The economics of human resources information systems (HRISs) in low-resource settings are not well understood, however, and warrant investigation and validation.CASE DESCRIPTION:This case study describes Uganda's Human Resources for Health Information System (HRHIS), implemented with support from the US Agency for International Development, and documents perceptions of its impact on the health labour market against the backdrop of the costs of implementation. Through interviews with end users and implementers in six different settings, we document pre-implementation data challenges and consider how the HRHIS has been perceived to affect human resources decision-making and the healthcare employment environment.DISCUSSION AND EVALUATION:This multisite case study documented a range of perceived benefits of Uganda's HRHIS through interviews with end users that sought to capture the baseline (or pre-implementation) state of affairs, the perceived impact of the HRHIS and the monetary value associated with each benefit. In general, the system appears to be strengthening both demand for health workers (through improved awareness of staffing patterns) and supply (by improving licensing, recruitment and competency of the health workforce). This heightened ability to identify high-value employees makes the health sector more competitive for high-quality workers, and this elevation of the health workforce also has broader implications for health system performance and population health.CONCLUSIONS:Overall, it is clear that HRHIS end users in Uganda perceived the system to have significantly improved day-to-day operations as well as longer term institutional mandates. A more efficient and responsive approach to HRH allows the health sector to recruit the best candidates, train employees in needed skills and deploy trained personnel to facilities where there is real demand. This cascade of benefits can extend the impact and rewards of working in the health sector, which elevates the health system as a whole.

Background: Human resources for health are critical for effective health systems. In Africa, the number of doctors and nurses required to provide essential health services will be deficient by an estimated 800,000 in 2015.1 Numerous interventions have been implemented to mitigate these shortages, including educational reforms aimed at retaining medical graduates in areas of need by both increasing the number of graduates and by adapting training to match the needs of local populations.2 Tracking graduates from African universities is critical to determine whether interventions are effective. However, most African medical schools do not track their graduates; only 18% of Sub-Saharan African medical schools reported having a graduate tracking system in 2012,3 and the data obtained from these systems are generally inadequate.4,5 Intervention: Based on a community of practice theory, a Graduate Tracking Technical Working Group (GT-TWG) was established within the Medical Education Partnership Initiative (MEPI) network comprising representatives from MEPI schools and the MEPI Coordinating Center. The GT-TWG, with CapacityPlus, a USAID-funded health workforce strengthening project, developed graduate tracking requirements for MEPI institutions and countries through a collaborative process, including structured interviews of 12 key individuals from 11 MEPI schools. Interviewees included deans, physician leaders, and monitoring and evaluation program officers identified by their schools as being central to graduate tracking. The GT-TWG and CapacityPlus also convened a workshop in October 2013 where representatives from 10 MEPI schools and from various country ministries of health, education, and health professional councils explored the MEPI landscape for tracking. Outcomes: Tracking systems varied widely among schools and countries. Most were paper based, although five schools reported having tracking systems in electronic formats or using electronic resources such as e-mail or social networking for communication and data gathering from graduates. No country among the MEPI-sponsored network had a single collaborative tracking system that involved all key stakeholders. The workshop allowed participants to validate findings and define a way forward to develop systems. Underlying principles included (1) clear goals and objectives to ensure that systems and data elements match the needs of schools and health systems; (2) medical school systems should be integrated with other health professional tracking systems when possible to enhance cooperation and information sharing; (3) early and meaningful stakeholder engagement is needed to define goals and objectives, establish integrated systems, and ensure sustainability; and (4) tracking systems should be sufficiently flexible to match data collection to local contexts and available resources. Participants designed a framework to guide the establishment of graduate tracking systems consisting of seven core processes or elements: (1) general requirements; (2) locate graduates; (3) collect/update information; (4) search and view information; (5) create tracking survey tools; (6) manage tracking survey response data; and (7) generate reports. Objectives, business rules, triggers, and other elements were developed for each core process. Comment: The framework and its requirements may provide a tool for institutions developing graduate tracking systems of their own and highlight opportunities for partnerships nationally and globally to establish sustainable systems.

The International Telecommunication Union estimates that, in only four years (2007–2011), mobile broadband subscriptions in the developing world increased by more than tenfold: from 43 million to 458 million. Mobile de-vices and internet access are becoming increasingly necessary professional tools for health-care workers at all levels in developing countries. New fibre and wireless infrastructure, as well as the rapid growth of computer processing power, provide an unprecedented op-portunity to scale up health worker training and improve its quality, as well as to optimize health service delivery and strengthen health systems.Over the past 20 years, learning management systems have contributed greatly to the tremendous expansion of e-learning. The past five years have also seen an increase in massive open online courses. eHealth technologies, including electronic medical records, laboratory and pharmacy information systems, along with disease surveil-lance and supply chain information systems, are transforming health care. Mobile health (mHealth), which is the practice of medicine and public health supported by mobile devices, extends these systems to the most remote and inaccessible parts of the developing world. In addition, the same mobile devices used to optimize communica-tion and support front-line health-care workers can be used to deploy multi-media training programmes and clini -cal decision support tools. The social media and the development of com-munities of practice have yet to be fully mobilized to support health workforce capacity building. The use of the social media by health workers has several potential benefits. Some examples are crowdsourcing of educational content, translations and localization (i.e. ad-aptation of the content to a particular region), peer-to-peer learning, joint problem solving and reflective prac-tice. In addition, ICTs can strengthen communication between providers and patients, increase community support for health worker capacity building and heighten the demand for high-quality clinical services.E-learning tools can support cur-riculum development and course sched -uling and management in ways that are conducive to blended learning approaches and that take advantage of multiple learning environments. Such tools can also be linked with national health professional registration and licensure systems, as well as with health workforce planning, management and in-service training systems, to provide information and support to the health workforce throughout the health worker lifecycle. Following pre-service train-ing, ICTs can be used to optimize the work of a health-care provider – the use of electronic health records, clinical decision-making, supply chain manage -ment and service quality control are examples – and to facilitate mHealth communications, continuing education and the establishment of professional social networks.Training methods based on video conferencing, webcasting, recording, localization and playback of training can enable global access to the very best educators and are more cost-effective than standard face-to-face educational programmes. Interactive content pro-grammes that incorporate gaming and adaptive learning tools can also be used.

Over the last nine years the USAID-funded CapacityPlus global project and its predecessor the Capacity Project have worked with countries to adapt and implement human resources information systems (HRIS) to better track and support their health workforces. HRIS are only valuable however to the extent that stakeholders use them for policy and management decisions and can only be deemed successful if the decisions in turn lead to better health care. Both criteria wholly depend on the quality of data in the system. In the context of HRIS data quality is best defined as how well the data represent the real world. Poor data quality can adversely affect support for -- and even the livelihoods of -- the very health workers we want the systems to benefit. Low-quality data can also influence organizational project or donor indicators. A national HRIS typically involves numerous data collection and entry steps and many users countrywide all of which pose challenges to ensuring data quality. As countries move ahead with HRIS scale-up efforts it is important to establish and use standards (organizational national and international) to align and and harmonize the collection aggregation and analysis of human resources for health (HRH) data.