Development of a master of science in digital health program at Muhimbili University of Health and Allied Sciences, Tanzania: a mixed-methods curriculum development study.

BACKGROUND: The rapid expansion of digital technologies is transforming health systems and creating increasing demand for a workforce with competencies in health informatics, data science, artificial intelligence (AI), cybersecurity, digital health governance, and implementation. However, digital health training remains fragmented in many low- and middle-income countries (LMICs), including Tanzania. This study describes the systematic, evidence-based process used to develop an MSc Digital Health program at Muhimbili University of Health and Allied Sciences (MUHAS), Tanzania.

METHODS: A mixed-methods curriculum development approach was undertaken, comprising document review and benchmarking, a quantitative stakeholder survey, qualitative interviews with alumni of the MSc Health Information Management program, and a stakeholder consultative workshop. Nine higher-education and competency-framework sources were reviewed to identify gaps and emerging competency domains. A structured survey was administered to 48 stakeholders purposively selected from government, non-governmental, private-sector, and start-up organizations. Qualitative data from alumni interviews and open-ended survey responses were analyzed thematically using manual coding by two independent coders. A two-day consultative workshop involving 22 stakeholders from academia, professional associations, non-governmental organizations, government, and clinical practice reviewed and validated the proposed curriculum.

RESULTS: Benchmarking demonstrated substantial variability in digital health curriculum content, with no single program comprehensively covering all priority competency domains. Stakeholders identified AI and machine learning (48.0%) and big data and analytics (41.7%) as prominent emerging technology competencies, while data science and predictive analytics, health information systems and interoperability, cybersecurity and data privacy, and epidemiology and biostatistics were also emphasized. Overall, 81.3% of survey respondents considered digital health competencies highly important to their organizations, while 89.6% indicated willingness to employ MUHAS MSc Digital Health graduates. Qualitative findings emphasized five priority areas: advanced computing and emerging technologies; applied health data science and analytics; health systems architecture and interoperability; experiential learning and program delivery; and governance, cybersecurity, leadership, and professional ethics. Workshop participants endorsed the proposed curriculum and recommended stronger practical learning, field attachment, innovation-oriented projects, and alignment of course content with emerging workforce needs. The resulting program was structured as a two-year, full-time MSc Digital Health program with three specialization tracks: Digital Health Leadership, Digital Health Systems Development, and Health Data Science and AI.

CONCLUSION: The MUHAS MSc Digital Health curriculum was developed through an iterative, evidence-informed, and stakeholder-driven process that integrates multidisciplinary digital health competencies with practical, implementation-oriented learning. The approach provides a potentially adaptable model for curriculum development in LMIC settings. Future evaluation should assess program implementation, graduate competencies, employment outcomes, employer satisfaction, and contribution to national digital health transformation.