The development of task sharing policy and guidelines in Kenya.

BACKGROUND: The global critical shortage of health workers prevents expansion of healthcare services and universal health coverage. Like most countries in sub-Saharan Africa, Kenya's healthcare workforce density of 13.8 health workers per 10,000 population falls below the World Health Organization (WHO) recommendation of at least 44.5 doctors, nurses, and midwives per 10,000 population. In response to the health worker shortage, the WHO recommends task sharing, a strategy that can increase access to quality health services. To improve the utilization of human and financial health resources in Kenya for HIV and other essential health services, the Kenya Ministry of Health (MOH) in collaboration with various institutions developed national task sharing policy and guidelines (TSP). To advance task sharing, this article describes the process of developing, adopting, and implementing the Kenya TSP. CASE PRESENTATION: The development and approval of Kenya's TSP occurred from February 2015 to May 2017. The U.S. Centers for Disease Control and Prevention (CDC) allocated funding to Emory University through the United States President's Emergency Plan for AIDS Relief (PEPFAR) Advancing Children's Treatment initiative. After obtaining support from leadership in Kenya's MOH and health professional institutions, the TSP team conducted a desk review of policies, guidelines, scopes of practice, task analyses, grey literature, and peer-reviewed research. Subsequently, a Policy Advisory Committee was established to guide the process and worked collaboratively to form technical working groups that arrived at consensus and drafted the policy. The collaborative, multidisciplinary process led to the identification of gaps in service delivery resulting from health workforce shortages. This facilitated the development of the Kenya TSP, which provides a general orientation of task sharing in Kenya. The guidelines list priority tasks for sharing by various cadres as informed by evidence, such as HIV testing and counseling tasks. The TSP documents were disseminated to all county healthcare facilities in Kenya, yet implementation was stopped by order of the judiciary in 2019 after a legal challenge from an association of medical laboratorians. CONCLUSIONS: Task sharing may increase access to healthcare services in resource-limited settings. To advance task sharing, TSP and clinical practice could be harmonized, and necessary adjustments made to other policies that regulate practice (e.g., scopes of practice). Revisions to pre-service training curricula could be conducted to ensure health professionals have the requisite competencies to perform shared tasks. Monitoring and evaluation can help ensure that task sharing is implemented appropriately to ensure quality outcomes.

Success of a South-South collaboration on Human Resources Information Systems (HRIS) in health: a case of Kenya and Zambia HRIS collaboration.

BACKGROUND: Shortage of health workforce in most African countries is a major impediment to achieving health and development goals. Countries are encouraged to develop evidence-based strategies to scale up their health workforce in order to bridge the gap. South-South collaborations have gained popularity due to similarities in the challenges faced in the region. This strategy has been used in trade, education, and health sector among others. This paper is a road map of using a South-South collaboration to develop a Human Resources Information System (HRIS) to inform scale-up of the health workforce. CASE PRESENTATION: In the last decade, Kenya implemented one of the most comprehensive HRIS in Africa. The HRIS was funded by the US President's Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC) and implemented by Emory University. The Kenyan team collaborated with the Zambian team to establish a similar HRIS in Zambia. This case study describes the collaboration activities between Zambia and Kenya which included needs assessment, establishment of project office, stakeholders' sensitization, technical assistance and knowledge transfer, software reuse, documents and guidelines reuse, project structure and management, and project formative evaluation. Furthermore, it highlights the need for adopting effective communication strategies, collaborative planning, teamwork, willingness to learn, and having minimum technical skills from the recipient country as lessons learned from the collaboration. As a result of the collaboration, while Kenya took 5 years, Zambia was able to implement the project within 2 years which is less than half the time it took Kenya. CONCLUSIONS: This case presents a unique experience in the use of South-South collaboration in establishing a HRIS. It illustrates the steps and resources needed while identifying the successes and challenges in undertaking such collaboration.

Do interoperable national information systems enhance availability of data to assess the effect of scale-up of HIV services on health workforce deployment in resource-limited countries?

Sub-Saharan Africa (SSA) bears the heaviest burden of the HIV epidemic. Health workers play a critical role in the scale-up of HIV programs. SSA also has the weakest information and communication technology (ICT) infrastructure globally. Implementing interoperable national health information systems (HIS) is a challenge, even in developed countries. Countries in resource-limited settings have yet to demonstrate that interoperable systems can be achieved, and can improve quality of healthcare through enhanced data availability and use in the deployment of the health workforce. We established interoperable HIS integrating a Master Facility List (MFL), District Health Information Software (DHIS2), and Human Resources Information Systems (HRIS) through application programmers interfaces (API). We abstracted data on HIV care, health workers deployment, and health facilities geo-coordinates. Over 95% of data elements were exchanged between the MFL-DHIS and HRIS-DHIS. The correlation between the number of HIV-positive clients and nurses and clinical officers in 2013 was R2=0.251 and R2=0.261 respectively. Wrong MFL codes, data type mis-match and hyphens in legacy data were key causes of data transmission errors. Lack of information exchange standards for aggregate data made programming time-consuming.

Informing the scale-up of Kenya's nursing workforce: a mixed methods study of factors affecting pre-service training capacity and production.

BACKGROUND: Given the global nursing shortage and investments to scale-up the workforce, this study evaluated trends in annual student nurse enrolment, pre-service attrition between enrolment and registration, and factors that influence nurse production in Kenya. METHODS: This study used a mixed methods approach with data from the Regulatory Human Resources Information System (tracks initial student enrolment through registration) and the Kenya Health Workforce Information System (tracks deployment and demographic information on licensed nurses) for the quantitative analyses and qualitative data from key informant interviews with nurse training institution educators and/or administrators. Trends in annual student nurse enrolment from 1999 to 2010 were analyzed using regulatory and demographic data. To assess pre-service attrition between training enrolment and registration with the nursing council, data for a cohort that enrolled in training from 1999 to 2004 and completed training by 2010 was analyzed. Multivariate logistic regression was used to test for factors that significantly affected attrition. To assess the capacity of nurse training institutions for scale-up, qualitative data was obtained through key informant interviews. RESULTS: From 1999 to 2010, 23,350 students enrolled in nurse training in Kenya. While annual new student enrolment doubled between 1999 (1,493) and 2010 (3,030), training institutions reported challenges in their capacity to accommodate the increased numbers. Key factors identified by the nursing faculty included congestion at clinical placement sites, limited clinical mentorship by qualified nurses, challenges with faculty recruitment and retention, and inadequate student housing, transportation and classroom space. Pre-service attrition among the cohort that enrolled between 1999 and 2004 and completed training by 2010 was found to be low (6%). CONCLUSION: To scale-up the nursing workforce in Kenya, concurrent investments in expanding the number of student nurse clinical placement sites, utilizing alternate forms of skills training, hiring more faculty and clinical instructors, and expanding the dormitory and classroom space to accommodate new students are needed to ensure that increases in student enrolment are not at the cost of quality nursing education. Student attrition does not appear to be a concern in Kenya compared to other African countries (10 to 40%).

Kenya's emergency-hire nursing programme: a pilot evaluation of health service delivery in two districts.

OBJECTIVE: To assess the feasibility of utilizing a small-scale, low-cost, pilot evaluation in assessing the short-term impact of Kenya's emergency-hire nursing programme (EHP) on the delivery of health services (outpatient visits and maternal-child health indicators) in two underserved health districts with high HIV/AIDS prevalence. METHODS: Six primary outcomes were assessed through the collection of data from facility-level health management forms-total general outpatient visits, vaginal deliveries, caesarean sections, antenatal care (ANC) attendance, ANC clients tested for HIV, and deliveries to HIV-positive women. Data on outcome measures were assessed both pre-and post-emergency-hire nurse placement. Informal discussions were also conducted to obtain supporting qualitative data. FINDINGS: The majority of EHP nurses were placed in Suba (15.5%) and Siaya (13%) districts. At the time of the intervention, we describe an increase in total general outpatient visits, vaginal deliveries and caesarean sections within both districts. Similar significant increases were seen with ANC attendance and deliveries to HIV-positive women. Despite increases in the quantity of health services immediately following nurse placement, these levels were often not sustained. We identify several factors that challenge the long-term sustainability of these staffing enhancements. CONCLUSIONS: There are multiple factors beyond increasing the supply of nurses that affect the delivery of health services. We believe this pilot evaluation sets the foundation for future, larger and more comprehensive studies further elaborating on the interface between interventions to alleviate nursing shortages and promote enhanced health service delivery. We also stress the importance of strong national and local relationships in conducting future studies.

The public sector nursing workforce in Kenya: a county-level analysis.

BACKGROUND: Kenya's human resources for health shortage is well documented, yet in line with the new constitution, responsibility for health service delivery will be devolved to 47 new county administrations. This work describes the public sector nursing workforce likely to be inherited by the counties, and examines the relationships between nursing workforce density and key indicators. METHODS: National nursing deployment data linked to nursing supply data were used and analyzed using statistical and geographical analysis software. Data on nurses deployed in national referral hospitals and on nurses deployed in non-public sector facilities were excluded from main analyses. The densities and characteristics of the public sector nurses across the counties were obtained and examined against an index of county remoteness, and the nursing densities were correlated with five key indicators. RESULTS: Of the 16,371 nurses in the public non-tertiary sector, 76% are women and 53% are registered nurses, with 35% of the nurses aged 40 to 49 years. The nursing densities across counties range from 1.2 to 0.08 per 1,000 population. There are statistically significant associations of the nursing densities with a measure of health spending per capita (P value = 0.0028) and immunization rates (P value = 0.0018). A higher county remoteness index is associated with explaining lower female to male ratio of public sector nurses across counties (P value <0.0001). CONCLUSIONS: An overall shortage of nurses (range of 1.2 to 0.08 per 1,000) in the public sector countrywide is complicated by mal-distribution and varying workforce characteristics (for example, age profile) across counties. All stakeholders should support improvements in human resources information systems and help address personnel shortages and mal-distribution if equitable, quality health-care delivery in the counties is to be achieved.

Kenya's health workforce information system: a model of impact on strategic human resources policy, planning and management.

OBJECTIVE: Countries worldwide are challenged by health worker shortages, skill mix imbalances, and maldistribution. Human resources information systems (HRIS) are used to monitor and address these health workforce issues, but global understanding of such systems is minimal and baseline information regarding their scope and capability is practically non-existent. The Kenya Health Workforce Information System (KHWIS) has been identified as a promising example of a functioning HRIS. The objective of this paper is to document the impact of KHWIS data on human resources policy, planning and management. METHODS: Sources for this study included semi-structured interviews with senior officials at Kenya's Ministry of Medical Services (MOMS), Ministry of Public Health and Sanitation (MOPHS), the Department of Nursing within MOMS, the Nursing Council of Kenya, Kenya Medical Practitioners and Dentists Board, Kenya's Clinical Officers Council, and Kenya Medical Laboratory Technicians and Technologists Board. Additionally, quantitative data were extracted from KHWIS databases to supplement the interviews. Health sector policy documents were retrieved from MOMS and MOPHS websites, and reviewed to assess whether they documented any changes to policy and practice as having been impacted by KHWIS data. RESULTS: Interviews with Kenyan government and regulatory officials cited health workforce data provided by KHWIS influenced policy, regulation, and management. Policy changes include extension of Kenya's age of mandatory civil service retirement from 55 to 60 years. Data retrieved from KHWIS document increased relicensing of professional nurses, midwives, medical practitioners and dentists, and interviewees reported this improved compliance raised professional regulatory body revenues. The review of Government records revealed few references to KHWIS; however, documentation specifically cited the KHWIS as having improved the availability of human resources for health information regarding workforce planning, management, and development. CONCLUSION: KHWIS data have impacted a range of improvements in health worker regulation, human resources management, and workforce policy and planning at Kenya's ministries of health.

The impact of out-migration on the nursing workforce in Kenya.

OBJECTIVE: To examine the impact of out-migration on Kenya's nursing workforce. STUDY SETTING: This study analyzed deidentified nursing data from the Kenya Health Workforce Informatics System, collected by the Nursing Council of Kenya and the Department of Nursing in the Ministry of Medical Services. STUDY DESIGN: We analyzed trends in Kenya's nursing workforce from 1999 to 2007, including supply, deployment, and intent to out-migrate, measured by requests for verification of credentials from destination countries. PRINCIPLE FINDINGS: From 1999 to 2007, 6 percent of Kenya's nursing workforce of 41,367 nurses applied to out-migrate. Eighty-five percent of applicants were registered or B.Sc.N. prepared nurses, 49 percent applied within 10 years of their initial registration as a nurse, and 82 percent of first-time applications were for the United States or United Kingdom. For every 4.5 nurses that Kenya adds to its nursing workforce through training, 1 nurse from the workforce applies to out-migrate, potentially reducing by 22 percent Kenya's ability to increase its nursing workforce through training. CONCLUSIONS: Nurse out-migration depletes Kenya's nursing workforce of its most highly educated nurses, reduces the percentage of younger nurses in an aging nursing stock, decreases Kenya's ability to increase its nursing workforce through training, and represents a substantial economic loss to the country.

Geospatial distribution and determinants of child mortality in rural western Kenya 2002-2005.

OBJECTIVE: To describe local geospatial variation and geospatial risk factors for child mortality in rural western Kenya. METHODS: We calculated under-5 mortality rates (U5MR) in 217 villages in a Health and Demographic Surveillance System (HDSS) area in western Kenya from 1 May 2002 through 31 December 2005. U5MRs by village were mapped. Geographical positioning system coordinates of residences at the time of death and distances to nearby locations were calculated. Multivariable Poisson regression accounting for clustering at the compound level was used to evaluate the association of geospatial factors and mortality for infants and children aged 1-4 years. RESULTS: Among 54 057 children, the overall U5MR was 56.5 per 1000 person-years and varied by village from 21 to 177 per 1000 person-years. High mortality villages occurred in clusters by location and remained in the highest mortality quintile over several years. In multivariable analysis, controlling for maternal age and education as well as household crowding, higher infant mortality was associated with living closer to streams and further from public transport roads. For children 1-4 years, living at middle elevations (1280-1332 metres), living within lower population densities areas, and living in the northern section of the HDSS were associated with higher mortality. CONCLUSIONS: Childhood mortality was significantly higher in some villages. Several geospatial factors were associated with mortality, which might indicate variability in access to health care or exposure and transmission of infectious diseases. These results are useful in prioritising areas for further study and implementing directed public health interventions.