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Mast Analytics was co-founded by Cristina Mannie and Stefan Strydom. We are a team passionate about combining the disciplines of health, artificial intelligence and analytics to improve public health which connects us all.
We refer to public health science in its true and broadest sense, to include issues related to health policy, public education and the protection of health, as well as the prevention, detection and treatment of disease, and the associated social, behavioural and environmental determinants of health.
Together we have 20 years’ experience performing advanced healthcare analytics including assessing the health status of populations and identifying individuals at risk of various healthcare events, developing risk stratification models, identifying significant risk factors to inform the design of effective initiatives (such as care management programmes or alternative payment models), and evaluating programmes or measuring the outcomes of the interventions implemented.
During this time, we have developed award-winning risk stratification models for care-management and we have been acknowledged locally and abroad for our contribution to designing innovative solutions.
With our combined expertise across sectors and disciplines – and a commitment to constantly pushing the boundaries using data science – we take a holistic and cutting-edge approach towards analysing and unlocking value from vast volumes of data. This enables us to design innovative and impactful data-driven solutions for clients, which we deliver in the form of user-friendly applications and tools. We have extensive experience in implementing and assessing the impact of these solutions in partnership with our clients.
Meet The Team
Cristina Mannie
Co-founder
Cristina’s qualifications include a degree in Pharmacy, a master’s degree in Public Health with graduate certificates in Global Health, and Health Finance and Management from the Johns Hopkins Bloomberg School of Public Health, and a certificate in Quantitative Methods in Clinical Public Health Research (in Biostatistics and Epidemiology).
Prior to co-founding Mast Analytics, Cristina gained diverse experience in the provision and funding of healthcare in the public and private healthcare sectors. Her early career includes specialised paediatric hospital pharmacy experience in a state paediatric academic tertiary hospital and providing and managing pharmaceutical services at a private multidisciplinary primary healthcare facility. She also worked in the managed healthcare environment within the private sector for 13 years where she held various roles including medicine utilisation review, training clinical staff on medicine treatment guidelines, clinical data warehousing and performing clinical statistical analyses – during which time she spent 8 years focusing primarily on healthcare and population health analytics, the identification of at-risk populations for clinical care management programmes, intervention design and outcomes measurement.
Stefan Strydom
Co-founder
Stefan has an honours degree in Mathematical Statistics and is currently completing an M.Sc. in Computer Science. He is also a qualified healthcare actuary, which has equipped him with the skills to conduct complex and long-term financial modelling. Additionally, he has completed graduate-level courses from Columbia University through edX in artificial intelligence, machine learning and robotics.
Stefan has over 8 years’ experience working on machine learning and advanced analytics projects. Prior to co-founding Mast Analytics, he spent more than7 years at a large third-party administrator and managed care organisation, where he was responsible for leading the technical development of their suite of hospital efficiency models. These are used to profile providers and negotiate prices and alternative reimbursement models with hospitals. In this position, he played an integral role in developing predictive models for identifying high and emerging risk patients and predicting future utilisation as well as models for early identification of individuals at risk of specific high cost events such as invasive back surgery.
Cristina’s qualifications include a degree in Pharmacy, a master’s degree in Public Health with graduate certificates in Global Health, and Health Finance and Management from the Johns Hopkins Bloomberg School of Public Health, and a certificate in Quantitative Methods in Clinical Public Health Research (in Biostatistics and Epidemiology).
Prior to co-founding Mast Analytics, Cristina gained diverse experience in the provision and funding of healthcare in the public and private healthcare sectors. Her early career includes specialised paediatric hospital pharmacy experience in a state paediatric academic tertiary hospital and providing and managing pharmaceutical services at a private multidisciplinary primary healthcare facility. She also worked in the managed healthcare environment within the private sector for 13 years where she held various roles including medicine utilisation review, training clinical staff on medicine treatment guidelines, clinical data warehousing and performing clinical statistical analyses – during which time she spent 8 years focusing primarily on healthcare and population health analytics, the identification of at-risk populations for clinical care management programmes, intervention design and outcomes measurement.
Stefan is a data scientist, machine learning engineer and healthcare actuary. He has extensive experience in the South African healthcare environment and has also worked on projects located in North America, Europe, Asia and other African countries outside of South Africa.
Stefan holds B.Sc. and B.Com. (Honours) degrees in mathematical
statistics and an M.Sc. (cum laude) in computer science from Stellenbosch
University. The title of his master’s thesis was “Automatic assignment of
diagnosis codes to free-form text medical notes.”
Stefan previously spent over 7 years at a large third-party administrator and managed care organization in South Africa where his last position was Advanced Specialist: Hospital Analytics. In this role, he was responsible for leading the
development of the organisation’s suite of hospital efficiency models which are
used to profile providers and negotiate prices and reimbursement models with
hospitals. Along with two colleagues, he was awarded the 2014
Starfield Award by the Johns Hopkins Bloomberg School of Public Health’s ACG
System® team for their work in identifying emerging risk individuals through
machine learning using administrative health data, designing an intervention
plan for the identified individuals and measuring clinical and financial
outcomes of the programme.