Strengthening primary care for diabetes and hypertension in Eswatini: study protocol for a nationwide cluster-randomized controlled trial.

BACKGROUND: Diabetes and hypertension are increasingly important population health challenges in Eswatini. Prior to this project, healthcare for these conditions was primarily provided through physician-led teams at tertiary care facilities and accessed by only a small fraction of people living with diabetes or hypertension. This trial tests and evaluates two community-based healthcare service models implemented at the national level, which involve health care personnel at primary care facilities and utilize the country's public sector community health worker cadre (the rural health motivators [RHMs]) to help generate demand for care. METHODS: This study is a cluster-randomized controlled trial with two treatment arms and one control arm. The unit of randomization is a primary healthcare facility along with all RHMs (and their corresponding service areas) assigned to the facility. A total of 84 primary healthcare facilities were randomized in a 1:1:1 ratio to the three study arms. The first treatment arm implements differentiated service delivery (DSD) models at the clinic and community levels with the objective of improving treatment uptake and adherence among clients with diabetes or hypertension. In the second treatment arm, community distribution points (CDPs), which previously targeted clients living with human immunodeficiency virus, extend their services to clients with diabetes or hypertension by allowing them to pick up medications and obtain routine nurse-led follow-up visits in their community rather than at the healthcare facility. In both treatment arms, RHMs visit households regularly, screen clients at risk, provide personalized counseling, and refer clients to either primary care clinics or the nearest CDP. In the control arm, primary care clinics provide diabetes and hypertension care services but without the involvement of RHMs and the implementation of DSD models or CDPs. The primary endpoints are mean glycated hemoglobin (HbA1c) and systolic blood pressure among adults aged 40 years and older living with diabetes or hypertension, respectively. These endpoints will be assessed through a household survey in the RHM service areas. In addition to the health impact evaluation, we will conduct studies on cost-effectiveness, syndemics, and the intervention's implementation processes. DISCUSSION: This study has the ambition to assist the Eswatini government in selecting the most effective delivery model for diabetes and hypertension care. The evidence generated with this national-level cluster-randomized controlled trial may also prove useful to policy makers in the wider Sub-Saharan African region. TRIAL REGISTRATION: NCT04183413. Trial registration date: December 3, 2019.

Accelerating the Front End of Medicine: Three Digital Use Cases and HCI Implications.

Digital applications in health care are a concurrent research and management question, where implementation experiences are a core field of information systems research. It also contributes to fighting pandemic crises like COVID-19 because contactless information flow and speed of diagnostics are improved. This paper presents three digital application case studies from emergency medicine, administration management, and cancer diagnosis with AI support from the University Medical Centers of Münster and Göttingen in Germany. All cases highlight the potential of digitalization to increase speed and efficiency within the front end of medicine as the crucial phase before patient treatment starts. General challenges for health care project implementations and human-computer interaction (HCI) concepts in health care are derived and discussed, including the importance of specific processes together with user analysis and adaption. A derived concept for HCI includes the criteria speed, accuracy, modularity, and individuality to achieve sustainable improvements within the front end of medicine.

Relevant Aspects for Sustainable Open Source Pandemic Apps and Platform Deployment with Focus on Community Building.

The global COVID-19 pandemic revealed the necessity for mobile and web-based solutions for a variety of medical processes, e.g., individual risk calculation, communication of health information and contact tracing. Many such solutions are provided in form of open source software. However, there are major obstacles to the sustainable long-term continuation of such projects. As the topic of sustainability strategies is complex, a classification would be useful to help new projects to identify relevant sustainability factors. Based on a literature review a classification for long-term success of open source software was created. This paper presents a classification focusing on five unique categories: (1) structural decision, (2) revenue generation, (3) user focus, (4) openness and (5) community building. It was developed within the NUM-COMPASS project, focusing content-wise on pandemic apps and structure-wise on open-source provision. We provide some insights into the community building dimension by discussing factors that go into building sustainable communities.