BackgroundIncreases in the proportion of facility-based deliveries have been marginal in many low-income countries in the African region. Preliminary clinical and anthropological evidence suggests that one major factor inhibiting pregnant women from delivering at facility is disrespectful and abusive treatment by health care providers in maternity units. Despite acknowledgement of this behavior by policy makers, program staff, civil society groups and community members, the problem appears to be widespread but prevalence is not well documented. Formative research will be undertaken to test the reliability and validity of a disrespect and abuse (D&A) construct and to then measure the prevalence of disrespect and abuse suffered by clinic clients and the general population.Methods/designA quasi-experimental design will be followed with surveys at twelve health facilities in four districts and one large maternity hospital in Nairobi and areas before and after the introduction of disrespect and abuse (D&A) interventions. The design is aimed to control for potential time dependent confounding on observed factors.DiscussionThis study seeks to conduct implementation research aimed at designing, testing, and evaluating an approach to significantly reduce disrespectful and abusive (D&A) care of women during labor and delivery in facilities. Specifically the proposed study aims to: (i) determine the manifestations, types and prevalence of D&A in childbirth (ii) develop and validate tools for assessing D&A (iii) identify and explore the potential drivers of D&A (iv) design, implement, monitor and evaluate the impact of one or more interventions to reduce D&A and (v) document and assess the dynamics of implementing interventions to reduce D&A and generate lessons for replication at scale.

BackgroundKenya’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.MethodsNational 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.ResultsOf 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).ConclusionsAn 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.

The Kenya nursing database is a first step toward facilitating evidence-based decision making in HRH. This database is unique to developing countries in sub-Saharan Africa. Establishing an electronic workforce database requires long-term investment and sustained support by national and global stakeholders.

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.

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