The transition of human resources for health information systems from the MDGs into the SDGs and the post-pandemic era: reviewing the evidence from 2000 to 2022.

BACKGROUND: This review paper offers a policy-tracing trend analysis of national experiences among low- and middle-income countries in strengthening human resources for health information systems (HRHIS). This paper draws on evidence from the last two decades and applies a modified Bardach's policy analysis framework. A timely review of the evidence on HRHIS and underlying data systems is needed now more than ever, given the halfway mark of the Global Strategy on Human Resources for Health: Workforce 2030 and the protracted COVID-19 pandemic and other global health emergencies, over and above the increasing need for health and care workers to provide essential health services. MAIN TEXT: Considering World Health Assembly resolutions and HRH-related global developments between 2000 and 2022, we targeted peer-reviewed and gray literature covering the inception, impact, bottlenecks, and gaps of HRHIS. We also considered results from a Bill and Melinda Gates Foundation-funded project that assessed HRH data systems in 21 countries and the use of HRH data and information for policy, planning, and management. Aligned with the National Health Workforce Accounts (NHWA), we identify priority themes related to digital priorities for HRHIS and governance/leadership and present case studies of five countries that pursued different pathways to successfully develop their HRHIS. Over the last two decades, considerable progress has been achieved through a scaled-up implementation of HRHIS combined with the skills needed to analyze and use data, sustain systems functionality, and make systematic improvements over time. Global health development aid investments and technical innovations have led to advancements in HRHIS, district health information software (DHIS2), and partner collaborations during the HIV/AIDS, Ebola, and COVID-19 crises. Although the progressive implementation of NHWA continues to steer country-level efforts through standardized indicators and regular reporting, traditional challenges remain, such as data systems fragmentation, lack of interoperability between systems, and underutilization of reported data. Encouragingly, some countries demonstrate strong governance and leadership capacities and others strong HRHIS digital capacities. Both HRH and health service data are needed to inform on-demand decisions during times of emergencies and pandemics as well as during routine essential health services delivery. Evidence-based examples from distinctive countries demonstrate that reliable HRHIS is achievable for better planning and management of the health and care workforce.

Applying WHO COVID-19 workforce estimate tools remotely in an African context: a case report from Mali and Kenya.

BACKGROUND: The COVID-19 pandemic has increased the burden on health systems, particularly in low- and middle-income countries, where health systems already struggle. To meet health workforce planning needs during the pandemic, IntraHealth International used two tools created by the World Health Organization (WHO) Regional Office for Europe. The Health Workforce Estimator (HWFE) allows the estimation of the quantity of health workers needed to treat patients during a surge, and the Adaptt Surge Planning Support Tool helps to predict the timing of a surge in cases and the number of health workers and beds needed for predicted caseload. These tools were adapted to fit the African context in a rapid implementation over 5 weeks in one region in Mali and one region in Kenya with the objective to test the feasibility of adapting these tools, which use a Workload Indicators of Staffing Need (WISN)-inspired human resources management methodology, to obtain daily and surge projections of COVID-19 human resources for health needs. CASE PRESENTATION: Using a remote team in the US and in-country teams in Mali and Kenya, IntraHealth enacted a phased plan to gather stakeholder support, collect data related to health systems and COVID-19 cases, populate data into the tools, verify modeled results with results on the ground, enact policy measures to meet projected needs, and conduct national training workshops for the ministries of health. CONCLUSIONS: This phased implementation in Mali and Kenya demonstrated that the WISN approach applied to the Health Workforce Estimator and Adaptt tools can be readily adapted to the local context for African countries to rapidly estimate the number of health workers and beds needed to respond to the predicted COVID-19 pandemic caseload. The results may also be used to give a proxy estimate for needed health supplies-e.g., oxygen, medications, and ventilators. Challenges included accurate and timely data collection and updating data. The success of the pilot can be attributed to the adapted WHO tools, the team composition in both countries, access to human resources data, and early support of the ministries of health, with the expectation that this methodology can be applied to other country contexts.

Applying the workload indicators of staffing need (WISN) method in Namibia: challenges and implications for human resources for health policy.

INTRODUCTION: As part of ongoing efforts to restructure the health sector and improve health care quality, the Ministry of Health and Social Services (MoHSS) in Namibia sought to update staffing norms for health facilities. To establish an evidence base for the new norms, the MoHSS supported the first-ever national application of the Workload Indicators of Staffing Need (WISN) method, a human resource management tool developed by the World Health Organization. APPLICATION: The WISN method calculates the number of health workers per cadre, based on health facility workload. It provides two indicators to assess staffing: (1) the gap/excess between current and required number of staff, and (2) the WISN ratio, a measure of workload pressure. Namibian WISN calculations focused on four cadres (doctors, nurses, pharmacists, pharmacy assistants) and all four levels of public facilities (clinics, health centers, district hospitals, intermediate hospitals). WISN steps included establishing a task force; conducting a regional pilot; holding a national validation workshop; field verifying data; collecting, uploading, processing, and analyzing data; and providing feedback to policy-makers. CHALLENGES: The task force faced two challenges requiring time and effort to solve: WISN software-related challenges and unavailability of some data at the national level. FINDINGS: WISN findings highlighted health worker shortages and inequities in their distribution. Overall, staff shortages are most profound for doctors and pharmacists. Although the country has an appropriate number of nurses, the nurse workforce is skewed towards hospitals, which are adequately or slightly overstaffed relative to nurses' workloads. Health centers and, in particular, clinics both have gaps between current and required number of nurses. Inequities in nursing staff also exist between and within regions. Finally, the requirement for nurses varies greatly between less and more busy clinics (range = 1 to 7) and health centers (range = 2 to 57). POLICY IMPLICATIONS: The utility of the WISN health workforce findings has prompted the MoHSS to seek approval for use of WISN in human resources for health policy decisions and practices. The MoHSS will focus on revising staffing norms; improving staffing equity across regions and facility types; ensuring an appropriate skill mix at each level; and estimating workforce requirements for new cadres.

Tracking and monitoring the health workforce: a new human resources information system (HRIS) in Uganda.

BACKGROUND: Health workforce planning is important in ensuring that the recruitment, training and deployment of health workers are conducted in the most efficient way possible. However, in many developing countries, human resources for health data are limited, inconsistent, out-dated, or unavailable. Consequently, policy-makers are unable to use reliable data to make informed decisions about the health workforce. Computerized human resources information systems (HRIS) enable countries to collect, maintain, and analyze health workforce data. METHODS: The purpose of this article is twofold. First, we describe Uganda's transition from a paper filing system to an electronic HRIS capable of providing information about country-specific health workforce questions. We examine the ongoing five-step HRIS strengthening process used to implement an HRIS that tracks health worker data at the Uganda Nurses and Midwives Council (UNMC). Secondly, we describe how HRIS data can be used to address workforce planning questions via an initial analysis of the UNMC training, licensure and registration records from 1970 through May 2009. RESULTS: The data indicate that, for the 25 482 nurses and midwives who entered training before 2006, 72% graduated, 66% obtained a council registration, and 28% obtained a license to practice. Of the 17 405 nurses and midwives who obtained a council registration as of May 2009, 96% are of Ugandan nationality and just 3% received their training outside of the country. Thirteen per cent obtained a registration for more than one type of training. Most (34%) trainings with a council registration are for the enrolled nurse training, followed by enrolled midwife (25%), registered (more advanced) nurse (21%), registered midwife (11%), and more specialized trainings (9%). CONCLUSION: The UNMC database is valuable in monitoring and reviewing information about nurses and midwives. However, information obtained from this system is also important in improving strategic planning for the greater health care system in Uganda. We hope that the use of a real-world example of HRIS strengthening provides guidance for the implementation of similar projects in other countries or contexts.

Making non-discrimination and equal opportunity a reality in Kenya's health provider education system: results of a gender analysis.

IntraHealth International's USAID-funded Capacity Kenya project conducted a performance needs assessment of the Kenya health provider education system in 2010. Various stakeholders shared their understandings of the role played by gender and identified opportunities to improve gender equality in health provider education. Findings suggest that occupational segregation, sexual harassment and discrimination based on pregnancy and family responsibilities present problems, especially for female students and faculty. To grow and sustain its workforce over the long term, Kenyan human resource leaders and managers must act to eliminate gender-based obstacles by implementing existing non-discrimination and equal opportunity policies and laws to increase the entry, retention and productivity of students and faculty. Families and communities must support girls' schooling and defer early marriage. All this will result in a fuller pool of students, faculty and matriculated health workers and, ultimately, a more robust health workforce to meet Kenya's health challenges.