Company: Mediclinic International plc
Company background: We are a diversified international private healthcare services group, established in South Africa in 1983, with divisions in Switzerland, Southern Africa (South Africa and Namibia) and the Middle East. We place science at the heart of our care process by striving to provide evidence-based care of the highest standard. The group operates over 80 facilities with over 11 000 beds and employees over 37 000 people. Mediclinic is focused on providing specialist-orientated, multi-disciplinary services across the continuum of care in such a way that the Group will be regarded as the most respected and trusted provider of healthcare services by patients, medical practitioners, funders and regulators of healthcare in each of its markets. Mediclinic takes a sustainable, long-term approach to business, putting patients at the heart of its operations and consistently delivering high-quality healthcare services. In order to deliver on these priorities, the Group upholds the highest standards of clinical governance and ethical behaviour across its divisions; invests significant time and resources in recruiting and retaining skilled employees; makes considerable investment into its facilities and equipment; and respects the communities and environment in the areas in which it operates. The Data Science and Information Management department (based in Stellenbosch, South Africa) is responsible for delivering data and analytics solutions across all of the company's operating divisions. We have been SAS customers for almost 10 years
Contact: Shravan Lalbahadur
Title: Group Manager: Data Science and Visualization
Country: South Africa
Award Category: ROI Rock Star
What was the business need/presented problem you were faced with?
- Our centralized architecture brought all the data to South Africa and for analysis and reporting. This approach was slowing us down as the team was struggling to produce reports on SAS 9.4 in a timely manner because data was only being refreshed 1-2 times per month.
- New data privacy laws in Switzerland and the UAE were promulgated that prohibited the transfer of healthcare data outside their borders
- We want to deliver predictive and prescriptive analytics to doctors and nurses at the patient bedside but this would be difficult to implement with out SAS 9.4 deployment
- Our existing SAS environment was running on aging hardware which required replacing. However, our ICT department was not going to buy new hardware and prescribed that all new deployments needed to be made on the cloud.
How did you use SAS to increase revenue/save money for your organization?
We increased our SAS investment so that we could use the software in all of our divisions. We then decided to deploy Viya 4 (instead of 9.4) in Azure and migrated our old workloads to Viya 4 on Azure. It took us almost 3 months to setup our new SAS environments and migrate our existing workloads to the new environments on Viya 4. This allowed us to get near realtime access to patient data for ingestion into SAS, comply with local data privacy regulations and provided us with a platform to bring machine learning to the patient bedside.
The scalability of Viya on Kubernetes will allow us to match compute demand to supply in a cost-effective manner which will result in net savings for the company (versus running Viya 3.5 or SAS 9.4 on fixed hardware 24/7).
What SAS products did you use and how did you use them?
We migrated our previous jobs from SAS Enterprise Guide on SAS 9.4 to SAS Viya Enterprise which was deployed on our own Virtual Private Cloud in Azure(in the UAE and Switzerland). SAS Studio was used to migrate the old process flows from SAS Enterprise Guide in a matter of days rather than weeks. The deployment was accelerated by the fact that Mediclinic is using several Microsoft/Azure products which are supported by SAS.
The large amount SAS resources available on github and SAS communities were invaluable in assisting us with the design and deployment of our new SAS environments.
What were your results? Please quantify.
We immediately saw 40% to 60% reduction workload times after migrating to SAS Viya on Azure. Workloads that took 24-30 hours to run now complete in 10-13 hours. The flexible compute configurations & scalability available as part of Kubernetes and Viya will allow us to save 30%-50% on compute costs on an annual basis.
