Globally, the stakeholders of the healthcare industry are aware of two important priorities. First, the time taken for medical research to result in meaningful changes in clinical practice must reduce. Second, for concepts such as population health management and precision medicine to become a reality, it is critical to develop personalized medicine techniques underpinned by stratification of risk-based population groups. This means the traditional “one size fits all” approach will not be effective in promoting better quality outcomes while reducing the healthcare cost burden at the same time. Many healthcare stakeholders believe that these priorities can be achieved only by making full use of huge repositories of clinical, patient, and genomic data.
The analysis of disparate data types reduces the time for medical research to translate into benefits for patients in clinical practice; and enables the development of personalized, evidence-based medicine techniques for at-risk population groups. The key implementation challenges are handling data from disparate sources, regulatory compliance, and information governance.
African nations have a significant amount of healthcare data, including patients’ history, symptoms, pathology results, and radiology results. Making these data readily accessible can not only save time but also compensate for the shortage of medical personnel, especially in the rural and remote regions. Using such advancements, clinicians can analyse the available data to offer diagnosis and consultation more quickly and at lower cost; and can also combine those with tools such as video telemedicine to serve patients in remote, rural villages without spending time and effort on travelling.
However, high investments in infrastructure, logistics, and technology are essential, together with sustained support from national and local governments.
The Government of South Africa has released national eHealth strategies and national mHealth strategies to address the nation’s healthcare needs. Hospitals in South Africa are also gradually moving toward electronic filing of health records (EHRs) to collate patients’ data in a more structured and productive manner; thereby deriving quality insights.
A data intelligence specialist company called Keyrus SA delivers data-driven solutions in South Africa, using Data Science and Data Discovery Technologies (such as Alteryx, Qlik, and Tableau Software). These solutions assist with patient costing, profit analysis, readmission, clinical pathways, clinical variations, and metrics on average length of stay; across hospitals and healthcare entities. Keyrus is currently working toward offering an Electronic Patient Management System (EPMS) that would integrate the entire range of patients’ data into a single, secure repository. The system will work through enhanced collaboration between doctors and reduce duplication of pathology and radiology tests. It also can help to reduce the prevalence of non-communicable diseases by allowing patients to track their health information and make better lifestyle choices for preventive care.
Another South African organisation, BroadReach Healthcare (a social enterprise) is working toward a user-friendly, integrated dashboard to assist in comparing key metrics across multiple public health medical centres, to identify the ones displaying the best and worst performance in providing care. BroadReach is prominently popular for offering its analytical and consulting services to pharmaceutical manufacturers. It works in almost 20 nations in Africa, and integrates demographic and clinical data available from state and private providers. This dashboard, called the Health Command Centre (HCC), has been launched in South Africa as a Software as a Service (SaaS) analytics service with Tibco Spotfire analytics, together with a real-time data visualisation package. HCC provides automated data which are gathered and presented in spread-sheets. HCC also displays the geographic distribution of clinics, pharmacies, schools, consultation rooms, staffing statistics, nurses’ training and qualifications, children’s health metrics, TB and HIV treatment preferences, access to clean water, and employment statistics. Collating these numbers will assist decision-making authorities in scrutinising the social, logistical, political, and economic factors affecting the performance of medical centres. With support from the accelerating coverage of mobile phones, HCC is serving a large percentage of the population, especially in the rural regions.
Thus data analytics is paving a brighter future of healthcare in South Africa; however, it is essential to ensure that data are gathered from reliable, authentic sources and are updated on a regular basis to present a true picture of the nation’s healthcare status. This will drive the necessary change in healthcare, especially in remote, rural regions that rely on public healthcare facilities for their preventive and curative needs.
