Integrating digital solutions into national health data systems through public-private collaboration: An early experience of the SPICE platform in Kenya.

Public-private collaborative efforts to address healthcare challenges in low- and middle-income countries have been the focus of digital initiatives to improve both access and quality of health services. We report the early feasibility, experience, and learnings of migrating healthcare data generated from a proprietary, privately owned cloud-based environment into an on-premises National Health Data Center (NHDC) in compliance with Kenya's data management legislation. In 2018, Medtronic LABS entered into a partnership with the Kenya Ministry of Health and other stakeholders to improve access to quality services and data availability for non-communicable diseases (diabetes and hypertension), anchored on the SPICE digital health platform. Data migration from SPICE to the NHDC necessitated the establishment of multi-stakeholder coordination structures, alignment on system configuration requirements, provisioning of on-premises servers, data replication and monitoring. The data replication process showed consistency in format and content with no evidence of data loss. The monitoring of the server uptime and availability, however, exposed overall downtime of 15% of the total time tracked between April and December 2022 caused by Internet Protocol address configuration issues, power outages, firewall rule changes, and unscheduled system maintenance. Monthly tracked downtime however reduced from a high of 28% in April 2022 to 5% in December 2022. Our early experience shows that data migration from proprietary host environments to public "one-stop-shop" national data warehouses are feasible provided investments are made in the requisite infrastructure, software and human resource capacity to ensure long-term sustainability, maintenance, and scale to match cloud-based data hosting. Further, digital health solutions developed in collaboration with non-state actors can be integrated into national data systems, saving Governments the cost and efforts of building similar tools while leveraging private sector capacity.

Recommendations for the use of mathematical modelling to support decision-making on integration of non-communicable diseases into HIV care.

INTRODUCTION: Integrating services for non-communicable diseases (NCDs) into existing primary care platforms such as HIV programmes has been recommended as a way of strengthening health systems, reducing redundancies and leveraging existing systems to rapidly scale-up underdeveloped programmes. Mathematical modelling provides a powerful tool to address questions around priorities, optimization and implementation of such programmes. In this study, we examine the case for NCD-HIV integration, use Kenya as a case-study to highlight how modelling has supported wider policy formulation and decision-making in healthcare and to collate stakeholders' recommendations on use of models for NCD-HIV integration decision-making. DISCUSSION: Across Africa, NCDs are increasingly posing challenges for health systems, which historically focused on the care of acute and infectious conditions. Pilot programmes using integrated care services have generated advantages for both provider and user, been cost-effective, practical and achieve rapid coverage scale-up. The shared chronic nature of NCDs and HIV means that many operational approaches and infrastructure developed for HIV programmes apply to NCDs, suggesting this to be a cost-effective and sustainable policy option for countries with large HIV programmes and small, un-resourced NCD programmes. However, the vertical nature of current disease programmes, policy financing and operations operate as barriers to NCD-HIV integration. Modelling has successfully been used to inform health decision-making across a number of disease areas and in a number of ways. Examples from Kenya include (i) estimating current and future disease burden to set priorities for public health interventions, (ii) forecasting the requisite investments by government, (iii) comparing the impact of different integration approaches, (iv) performing cost-benefit analysis for integration and (v) evaluating health system capacity needs. CONCLUSIONS: Modelling can and should play an integral part in the decision-making processes for health in general and NCD-HIV integration specifically. It is especially useful where little data is available. The successful use of modelling to inform decision-making will depend on several factors including policy makers' comfort with and understanding of models and their uncertainties, modellers understanding of national priorities, funding opportunities and building local modelling capacity to ensure sustainability.

Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey.

INTRODUCTION: non-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors. METHODS: we performed a secondary analysis of the STEPS 2015 data to determine prevalence and correlation between diabetes, hypertension, harmful alcohol use, smoking, obesity and injuries across age, gender, residence and socio-economic strata. RESULTS: tobacco use prevalence was 13.5% (males 19.9%, females 0.9%, p<0.001); harmful alcohol use was 12.6% (males 18.1%, females 2.2%, p<0.001); central obesity was 27.9% (females 49.5%, males 32.9%, p=0.017); type 2 diabetes prevalence 3.1% (males 2.0%, females 2.8%, p=0.048); elevated blood pressure prevalence was 23.8% (males 25.1%, females 22.6%, p<0.001), non-use of helmets 72.8% (males 89.5%, females 56.0%, p=0.031) and seat belts non-use 67.9% (males 79.8%, females 56.0%, p=0.027). Respondents with <12 years of formal education had higher prevalence of non-use of helmets (81.7% versus 54.1%, p=0.03) and seat belts (73.0% versus 53.9%, p=0.039). Respondents in the highest wealth quintile had higher prevalence of type II diabetes compared with those in the lowest (5.2% versus 1.6%,p=0.008). Rural dwellers had 35% less odds of tobacco use (aOR 0.65, 95% CI 0.49, 0.86) compared with urban dwellers, those with ≥12 years of formal education had 89% less odds of tobacco use (aOR 0.11, 95% CI 0.07, 0.17) compared with <12 years, and those belonging to the wealthiest quintile had 64% higher odds of unhealthy diets (aOR 1.64, 95% CI 1.26, 2.14). Only 44% of respondents with type II diabetes and 16% with hypertension were aware of their diagnosis. CONCLUSION: prevalence of NCD risk factors is high in Kenya and varies across socio-demographic attributes. Socio-demographic considerations should form part of multi-sectoral, integrated approach to reduce the NCD burden in Kenya.

Prevalence and determinants of heavy episodic drinking among adults in Kenya: analysis of the STEPwise survey, 2015.

BACKGROUND: Globally, alcohol consumption contributes to 3.3 million deaths and 5.1% of Disability Adjusted Life Years (DALYs), and its use is linked with more than 200 disease and injury conditions. Our study assessed the frequency and patterns of Heavy Episodic Drinking (HED) in Kenya. HED is defined as consumption of 60 or more grams of pure alcohol (6+ standard drinks in most countries) on at least one single occasion per month. Understanding the burden and patterns of heavy episodic drinking will be helpful to inform strategies that would curb the problem in Kenya. METHODS: Using the WHO STEPwise approach to surveillance (STEPS) tool, a nationally representative household survey of 4203 adults aged 18-69 years was conducted in Kenya between April and June 2015. We used logistic regression analysis to assess factors associated with HED among both current and former alcohol drinkers. We included the following socio-demographic variables: age, sex, and marital status, level of education, socio-economic status, residence, and tobacco as an interaction factor. RESULTS: The prevalence of HED was 12.6%. Men were more likely to engage in HED than women (unadjusted OR 9.9 95%, CI 5.5-18.8). The highest proportion of HED was reported in the 18-29-year age group (35.5%). Those currently married/ cohabiting had the highest prevalence of HED (60%). Respondents who were separated had three times higher odds of HED compared to married counterparts (OR 2.7, 95% CI 1.3-5.7). Approximately 16.0% of respondents reported cessation of alcohol use due to health reasons. Nearly two thirds reported drinking home-brewed beers or wines. Tobacco consumption was associated with higher odds of HED (unadjusted OR 6.9, 95% CI 4.4-10.8); those that smoke (34.4%) were more likely to engage in HED compared to their non-smoking counterparts. CONCLUSION: Our findings highlight a significant prevalence of HED among alcohol drinkers in Kenya. Young males, those with less education, married people, and tobacco users were more likely to report heavy alcohol use, with male sex as the primary driving factor. These findings are novel to the country and region; they provide guidance to target alcohol control interventions for different groups in Kenya.