The paediatrician workforce and its role in addressing neonatal, child and adolescent healthcare in Kenya

Public service motivation, public sector preference and employment of Kenyan medical doctor interns: a cross-sectional and prospective study

BACKGROUND

Kenya grapples with a paradox; severe public sector workforce shortages co-exist with rising unemployment among healthcare professionals. Medical schools have increased trainee outputs, but only 45% of newly qualified/registered doctors were absorbed by the public sector during 2015-2018. In such a context, we explore what influences doctors' career choices at labour market entry, specifically understanding the role of public service motivation (PSM).

METHODS

We conducted a cross-sectional and prospective study of interns and recently graduated doctors to examine PSM, their intention to work in the public sector and their final employment sector and status. We surveyed them on their PSM and job intentions and conducted a prospective follow-up survey of the interns, around one year later, to understand their employment status.

FINDINGS

We recruited 356 baseline participants and followed up 76 out of 129 eligible interns. The overall PSM score was high among all participants (rated 4.50/5.00) irrespective of sector preferences. 48% (171/356) of the participants preferred to work in the public sector immediately after internship, alongside 16% (57/356) preferring direct entry into specialist training-commonly in the public sector. Only 13% (46/356) and 7% (25/365) preferred to work in the private or faith-based sector. Despite the high proportion of interns preferring public sector jobs, only 17% (13/76) were employed in the public sector at follow-up and 13% (10/76) were unemployed, due to lack of job availability.

CONCLUSION

High PSM scores irrespective of sector preferences suggest that doctors are generally committed to serving the 'public good'. Many intended to work in the public sector but were unable to due to lack of job opportunities. Policymakers have an opportunity to tackle workforce gaps in the public sector as young doctors continue to express a preference for such work. To do this they should prioritise creating adequate and sustainable job opportunities.

Feasibility and acceptability of a novel biomedical device to prevent neonatal hypothermia and augment Kangaroo Mother Care in Kenya: Qualitative analysis of focus group discussions and key Informant Interviews

Hypothermia is a leading newborn complication, especially among premature and/or low birth weight infants. Within low/middle-income countries where incubators and radiant warmers are often in short supply, leading to gaps in the thermal care chain, neonatal hypothermia underlies high rates of newborn morbidity and mortality. Kangaroo Mother Care/Skin-to-skin care is an effective method for prevention of hypothermia in premature and low birthweight babies but can be very burdensome for families and healthcare providers. Our international multidisciplinary team has developed a prototype for a wearable biomedical device ("NeoWarm") to provide continuous thermal care and augment kangaroo mother care practices in low-resource settings. The objective of this study was to assess the feasibility and acceptability of NeoWarm and to obtain user design feedback for an early prototype from among adult end-users in Western Kenya. We performed key informant interviews (n = 17) among healthcare providers and 5 focus group discussions (FGDs) among 3 groups of adult stakeholders of premature babies, including: (1) parents/family members of premature babies aged 6 weeks or less (3 FGDs); (2) healthcare providers of newborns (e.g., nurses; physicians; 1 FGD); (3) community opinion leaders and stakeholders (e.g., traditional birth attendants; pastors; village elders; 1 FGD). Content and thematic analyses of transcripts indicate that NeoWarm is acceptable and feasible in promoting facility-based kangaroo mother care in the Kenyan setting. Novel findings derived from respondents include (1) the ability of the device to potentially overcome several barriers to traditional kangaroo mother care methods and (2) user-driven encouragement to expand the use case of the device to potentially include community-based kangaroo mother care and neonatal transport. User design feedback obtained during the interviews informed several key design iterations for subsequent prototypes of the device.

The NeoRoo mobile app: Initial design and prototyping of an Android-based digital health tool to support Kangaroo Mother Care in low/middle-income countries (LMICs)

Premature birth and neonatal mortality are significant global health challenges, with 15 million premature births annually and an estimated 2.5 million neonatal deaths. Approximately 90% of preterm births occur in low/middle income countries, particularly within the global regions of sub-Saharan Africa and South Asia. Neonatal hypothermia is a common and significant cause of morbidity and mortality among premature and low birth weight infants, particularly in low/middle-income countries where rates of premature delivery are high, and access to health workers, medical commodities, and other resources is limited. Kangaroo Mother Care/Skin-to-Skin care has been shown to significantly reduce the incidence of neonatal hypothermia and improve survival rates among premature infants, but there are significant barriers to its implementation, especially in low/middle-income countries (LMICs). The paper proposes the use of a multidisciplinary approach to develop an integrated mHealth solution to overcome the barriers and challenges to the implementation of Kangaroo Mother Care/Skin-to-skin care (KMC/STS) in LMICs. The innovation is an integrated mHealth platform that features a wearable biomedical device (NeoWarm) and an Android-based mobile application (NeoRoo) with customized user interfaces that are targeted specifically to parents/family stakeholders and healthcare providers, respectively. This publication describes the iterative, human-centered design and participatory development of a high-fidelity prototype of the NeoRoo mobile application. The aim of this study was to design and develop an initial ("A") version of the Android-based NeoRoo mobile app specifically to support the use case of KMC/STS in health facilities in Kenya. Key functions and features are highlighted. The proposed solution leverages the promise of digital health to overcome identified barriers and challenges to the implementation of KMC/STS in LMICs and aims to equip parents and healthcare providers of prematurely born infants with the tools and resources needed to improve the care provided to premature and low birthweight babies. It is hoped that, when implemented and scaled as part of a thoughtful, strategic, cross-disciplinary approach to reduction of global rates of neonatal mortality, NeoRoo will prove to be a useful tool within the toolkit of parents, health workers, and program implementors.

Examining the absorption of post-internship medical officers into the public sector at county-level in devolved Kenya: a qualitative case study

BACKGROUND

After Kenya's decentralization and constitutional changes in 2013, 47 devolved county governments are responsible for workforce planning and recruitment including for doctors/medical officers (MO). Data from the Ministry of Health suggested that less than half of these MOs are being absorbed by the public sector between 2015 and 2018. We aimed to examine how post-internship MOs are absorbed into the public sector at the county-level, as part of a broader project focusing on Kenya's human resources for health.

METHODS

We employed a qualitative case study design informed by a simplified health labour market framework. Data included interviews with 30 MOs who finished their internship after 2018, 10 consultants who have supervised MOs, and 51 county/sub-county-level managers who are involved in MOs' planning and recruitment. A thematic analysis approach was used to examine recruitment processes, outcomes as well as perceived demand and supply.

RESULTS

We found that Kenya has a large mismatch between supply and demand for MOs. An increasing number of medical schools are offering training in medicine while the demand for MOs in the county-level public sector has not been increasing at the same pace due to fiscal resource constraints and preference for other workforce cadres. The local Department of Health put in requests and participate in interviews but do not lead the recruitment process and respondents suggested that it can be subject to political interference and corruption. The imbalance of supply and demand is leading to unemployment, underemployment and migration of post-internship MOs with further impacts on MOs' wages and contract conditions, especially in the private sector.

CONCLUSION

The mismatched supply and demand of MO accompanied by problematic recruitment processes led to many MOs not being absorbed by the public sector and subsequent unemployment and underemployment. Although Kenya has ambitious workforce norms, it may need to take a more pragmatic approach and initiate constructive policy dialogue with stakeholders spanning the education, public and private health sectors to better align MO training, recruitment and management.

Improving facility-based care: eliciting tacit knowledge to advance intervention design

Attention has turned to improving the quality and safety of healthcare within health facilities to reduce avoidable mortality and morbidity. Interventions should be tested in health system environments that can support their adoption if successful. To be successful, interventions often require changes in multiple behaviours making their consequences unpredictable. Here, we focus on this challenge of change at the mesolevel or microlevel. Drawing on multiple insights from theory and our own empirical work, we highlight the importance of engaging managers, senior and frontline staff and potentially patients to explore foundational questions examining three core resource areas. These span the physical or material resources available, workforce capacity and capability and team and organisational relationships. Deficits in all these resource areas may need to be addressed to achieve success. We also argue that as inertia is built into the complex social and human systems characterising healthcare facilities that thought on how to mobilise five motive forces is needed to help achieve change. These span goal alignment and ownership, leadership for change, empowering key actors, promoting responsive planning and procurement and learning for transformation. Our aim is to bridge the theory-practice gap and offer an entry point for practical discussions to elicit the critical tacit and contextual knowledge needed to design interventions. We hope that this may improve the chances that interventions are successful and so contribute to better facility-based care and outcomes while contributing to the development of learning health systems.

Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol

BACKGROUND

Medication errors are likely common in low- and middle-income countries (LMICs). In neonatal hospital care where the population with severe illness has a high mortality rate, around 14.9% of drug prescriptions have errors in LMICs settings. However, there is scant research on interventions to improve medication safety to mitigate such errors. Our objective is to improve routine neonatal care particularly focusing on effective prescribing practices with the aim of achieving reduced gentamicin medication errors.

METHODS

We propose to conduct an audit and feedback (A&F) study over 12 months in 20 hospitals with 12 months of baseline data. The medical and nursing leaders on their newborn units had been organised into a network that facilitates evaluating intervention approaches for improving quality of neonatal care in these hospitals and are receiving basic feedback generated from the baseline data. In this study, the network will (1) be expanded to include all hospital pharmacists, (2) include a pharmacist-only professional WhatsApp discussion group for discussing prescription practices, and (3) support all hospitals to facilitate pharmacist-led continuous medical education seminars on prescription practices at hospital level, i.e. default intervention package. A subset of these hospitals (n = 10) will additionally (1) have an additional hospital-specific WhatsApp group for the pharmacists to discuss local performance with their local clinical team, (2) receive detailed A&F prescription error reports delivered through mobile-based dashboard, and (3) receive a PDF infographic summarising prescribing performance circulated to the clinicians through the hospital-specific WhatsApp group, i.e. an extended package. Using interrupted time series analysis modelling changes in prescribing errors over time, coupled with process fidelity evaluation, and WhatsApp sentiment analysis, we will evaluate the success with which the A&F interventions are delivered, received, and acted upon to reduce prescribing error while exploring the extended package's success/failure relative to the default intervention package.

DISCUSSION

If effective, these theory-informed A&F strategies that carefully consider the challenges of LMICs settings will support the improvement of medication prescribing practices with the insights gained adapted for other clinical behavioural targets of a similar nature.

TRIAL REGISTRATION

PACTR, PACTR202203869312307 . Registered 17th March 2022.

Characterising Kenyan hospitals' suitability for medical officer internship training: a secondary data analysis of a cross-sectional study

OBJECTIVE

To characterise the capacity of Kenya internship hospitals to understand whether they are suitable to provide internship training for medical doctors.

DESIGN

A secondary data analysis of a cross-sectional health facility assessment (Kenya Harmonized Health Facility Assessment (KHFA) 2018).

SETTING AND POPULATION

We analysed 61 out of all 74 Kenyan hospitals that provide internship training for medical doctors.

OUTCOME MEASURES

Comparing against the minimum requirement outlined in the national guidelines for medical officer interns, we filtered and identified 166 indicators from the KHFA survey questionnaire and grouped them into 12 domains. An overall capacity index was calculated as the mean of 12 domain-specific scores for each facility.

RESULTS

The average overall capacity index is 69% (95% CI 66% to 72%) for all internship training centres. Hospitals have moderate capacity (over 60%) for most of the general domains, although there is huge variation between hospitals and only 29 out of 61 hospitals have five or more specialists assigned, employed, seconded or part-time-as required by the national guideline. Quality and safety score was low across all hospitals with an average score of 40%. As for major specialties, all hospitals have good capacity for surgery and obstetrics-gynaecology, while mental health was poorest in comparison. Level 5 and 6 facilities (provincial and national hospitals) have higher capacity scores in all domains when compared with level 4 hospitals (equivalent to district hospitals).

CONCLUSION

Major gaps exist in staffing, equipment and service availability of Kenya internship hospitals. Level 4 hospitals (equivalent to district hospitals) are more likely to have a lower capacity index, leading to low quality of care, and should be reviewed and improved to provide appropriate and well-resourced training for interns and to use appropriate resources to avoid improvising.

Pairwise joint modeling of clustered and high-dimensional outcomes with covariate missingness in pediatric pneumonia care

Multiple outcomes reflecting different aspects of routine care are a common phenomenon in health care research. A common approach of handling such outcomes is multiple univariate analyses, an approach which does not allow for answering research questions pertaining to joint inference. In this study, we sought to study associations among nine pediatric pneumonia care outcomes spanning assessment, diagnosis and treatment domains of care, while circumventing the computational challenge posed by their clustered and high-dimensional nature and incompletely recorded covariates. We analyzed data from a cluster randomized trial conducted in 12 Kenyan hospitals. There were varying degrees of missingness in the covariates of interest, and these were multiply imputed using latent normal joint modeling. We used the pairwise joint modeling strategy to fit a correlated random effects joint model for the nine outcomes. This entailed fitting 36 bivariate generalized linear mixed models and deriving inference for the joint model using pseudo-likelihood theory. We also analyzed the nine outcomes separately before and after multiple imputation. We observed joint effects of patient-, clinician- and hospital-level factors on pneumonia care indicators before and after multiple imputation of missing covariates. In both pairwise joint modeling and separate univariate analysis methods, enhanced audit and feedback improved documentation and adherence to recommended clinical guidelines over time in six and five pneumonia care indicators, respectively. Additionally, multiple imputation improved precision of parameter estimates compared to complete case analysis. The strength and direction of association among pneumonia outcomes varied within and across the three domains of pneumonia care.

Task-sharing to support paediatric and child health service delivery in low- and middle-income countries: current practice and a scoping review of emerging opportunities

BACKGROUND

Demographic and epidemiological changes have prompted thinking on the need to broaden the child health agenda to include care for complex and chronic conditions in the 0-19 years (paediatric) age range. Providing such services will be undermined by general and skilled paediatric workforce shortages especially in low- and middle-income countries (LMICs). In this paper, we aim to understand existing, sanctioned forms of task-sharing to support the delivery of care for more complex and chronic paediatric and child health conditions in LMICs and emerging opportunities for task-sharing. We specifically focus on conditions other than acute infectious diseases and malnutrition that are historically shifted.

METHODS

We (1) reviewed the Global Burden of Diseases study to understand which conditions may need to be prioritized; (2) investigated training opportunities and national policies related to task-sharing (current practice) in five purposefully selected African countries (Kenya, Uganda, Tanzania, Malawi and South Africa); and (3) summarized reported experience of task-sharing and paediatric and child health service delivery through a scoping review of research literature in LMICs published between 1990 and 2019 using MEDLINE, Embase, Global Health, PsycINFO, CINAHL and the Cochrane Library.

RESULTS

We found that while some training opportunities nominally support emerging roles for non-physician clinicians and nurses, formal scopes of practices often remain rather restricted and neither training nor policy seems well aligned with probable needs from high-burden complex and chronic conditions. From 83 studies in 24 LMICs, and aside from the historically shifted conditions, we found some evidence examining task-sharing for a small set of specific conditions (circumcision, some complex surgery, rheumatic heart diseases, epilepsy, mental health).

CONCLUSION

As child health strategies are further redesigned to address the previously unmet needs careful strategic thinking on the development of an appropriate paediatric workforce is needed. To achieve coverage at scale countries may need to transform their paediatric workforce including possible new roles for non-physician cadres to support safe, accessible and high-quality care.

Neonatal mortality in Kenyan hospitals: a multisite, retrospective, cohort study

BACKGROUND

Most of the deaths among neonates in low-income and middle-income countries (LMICs) can be prevented through universal access to basic high-quality health services including essential facility-based inpatient care. However, poor routine data undermines data-informed efforts to monitor and promote improvements in the quality of newborn care across hospitals.

METHODS

Continuously collected routine patients' data from structured paper record forms for all admissions to newborn units (NBUs) from 16 purposively selected Kenyan public hospitals that are part of a clinical information network were analysed together with data from all paediatric admissions ages 0-13 years from 14 of these hospitals. Data are used to show the proportion of all admissions and deaths in the neonatal age group and examine morbidity and mortality patterns, stratified by birth weight, and their variation across hospitals.

FINDINGS

During the 354 hospital months study period, 90 222 patients were admitted to the 14 hospitals contributing NBU and general paediatric ward data. 46% of all the admissions were neonates (aged 0-28 days), but they accounted for 66% of the deaths in the age group 0-13 years. 41 657 inborn neonates were admitted in the NBUs across the 16 hospitals during the study period. 4266/41 657 died giving a crude mortality rate of 10.2% (95% CI 9.97% to 10.55%), with 60% of these deaths occurring on the first-day of admission. Intrapartum-related complications was the single most common diagnosis among the neonates with birth weight of 2000 g or more who died. A threefold variation in mortality across hospitals was observed for birth weight categories 1000-1499 g and 1500-1999 g.

INTERPRETATION

The high proportion of neonatal deaths in hospitals may reflect changing patterns of childhood mortality. Majority of newborns died of preventable causes (>95%). Despite availability of high-impact low-cost interventions, hospitals have high and very variable mortality proportions after stratification by birth weight.

Employing learning health system principles to advance research on severe neonatal and paediatric illness in Kenya

We have worked to develop a Clinical Information Network (CIN) in Kenya as an early form of learning health systems (LHS) focused on paediatric and neonatal care that now spans 22 hospitals. CIN's aim was to examine important outcomes of hospitalisation at scale, identify and ultimately solve practical problems of service delivery, drive improvements in quality and test interventions. By including multiple routine settings in research, we aimed to promote generalisability of findings and demonstrate potential efficiencies derived from LHS. We illustrate the nature and range of research CIN has supported over the past 7 years as a form of LHS. Clinically, this has largely focused on common, serious paediatric illnesses such as pneumonia, malaria and diarrhoea with dehydration with recent extensions to neonatal illnesses. CIN also enables examination of the quality of care, for example that provided to children with severe malnutrition and the challenges encountered in routine settings in adopting simple technologies (pulse oximetry) and more advanced diagnostics (eg, Xpert MTB/RIF). Although regular feedback to hospitals has been associated with some improvements in quality data continue to highlight system challenges that undermine provision of basic, quality care (eg, poor access to blood glucose testing and routine microbiology). These challenges include those associated with increased mortality risk (eg, delays in blood transfusion). Using the same data the CIN platform has enabled conduct of randomised trials and supports malaria vaccine and most recently COVID-19 surveillance. Employing LHS principles has meant engaging front-line workers, clinical managers and national stakeholders throughout. Our experience suggests LHS can be developed in low and middle-income countries that efficiently enable contextually appropriate research and contribute to strengthening of health services and research systems.

Programme theory and linked intervention strategy for large-scale change to improve hospital care in a low and middle-income country - A Study Pre-Protocol

In low and middle-income countries (LMIC) general hospitals are important for delivering some key acute care services. Neonatal care is emblematic of these acute services as averting deaths requires skilled care over many days from multiple professionals with at least basic equipment. However, hospital care is often of poor quality and large-scale change is needed to improve outcomes. In this manuscript we aim to show how we have drawn upon our understanding of contexts of care in Kenyan general hospital NBUs, and on social and behavioural theories that offer potential mechanisms of change in these settings, to develop an initial programme theory guiding a large scale change intervention to improve neonatal care and outcomes.  Our programme theory is an expression of our assumptions about what actions will be both useful and feasible.  It incorporates a recognition of our strengths and limitations as a research-practitioner partnership to influence change. The steps we employ represent the initial programme theory development phase commonly undertaken in many Realist Evaluations. However, unlike many Realist Evaluations that develop initial programme theories focused on pre-existing interventions or programmes, our programme theory informs the design of a new intervention that we plan to execute. Within this paper we articulate briefly how we propose to operationalise this new intervention. Finally, we outline the quantitative and qualitative research activities that we will use to address specific questions related to the delivery and effects of this new intervention, discussing some of the challenges of such study designs. We intend that this research on the intervention will inform future efforts to revise the programme theory and yield transferable learning.

Programme theory and linked intervention strategy for large-scale change to improve hospital care in a low and middle-income country - A Study Pre-Protocol

In low and middle-income countries (LMIC) general hospitals are important for delivering some key acute care services. Neonatal care is emblematic of these acute services as averting deaths requires skilled care over many days from multiple professionals with at least basic equipment. However, hospital care is often of poor quality and large-scale change is needed to improve outcomes. In this manuscript we aim to show how we have drawn upon our understanding of contexts of care in Kenyan general hospital NBUs, and on social and behavioural theories that offer potential mechanisms of change in these settings, to develop an initial programme theory guiding a large scale change intervention to improve neonatal care and outcomes.  Our programme theory is an expression of our assumptions about what actions will be both useful and feasible.  It incorporates a recognition of our strengths and limitations as a research-practitioner partnership to influence change. The steps we employ represent the initial programme theory development phase commonly undertaken in many Realist Evaluations. However, unlike many Realist Evaluations that develop initial programme theories focused on pre-existing interventions or programmes, our programme theory informs the design of a new intervention that we plan to execute. Within this paper we articulate briefly how we propose to operationalise this new intervention. Finally, we outline the quantitative and qualitative research activities that we will use to address specific questions related to the delivery and effects of this new intervention, discussing some of the challenges of such study designs. We intend that this research on the intervention will inform future efforts to revise the programme theory and yield transferable learning.