Hospitals and healthcare providers worldwide are increasingly leveraging cloud technology to resolve some of their most pressing problems, including population health, care coordination and data security.
Cloud technology has had a palpable impact on healthcare efficiencies and outcomes across the world during what has been seen as the most severe health crisis for a generation – and, still, healthcare is only “scratching the surface” of what is achievable with the technology, say experts at Amazon Web Services (AWS), the cloud-computing services arm of Amazon.
In examples taken from India, the Netherlands, the UK and the US, cloud has proved invaluable in many healthcare settings. For example, ESanjeevani, a browser-based telemedicine platform developed to improve access to healthcare services in India has enabled patients to access clinical consultations 12 hours a day, seven days a week, as COVID swept the country. Now, over 1 billion people are able to seek care using the platform – over 80% of the Indian population – with 4000 doctors engaged and over 150 synchronous outpatient consultations taking place.
Support for earlier detection
Advanced cloud computing has also enabled innovation in medical research by allowing researchers access to relevant, de-identified datasets under strict controls. Genomics England worked with technology partner, Lifebit, to create secure access to a cohort of sequenced genomes from 20,000 patients with severe COVID-19 infection and 15,000 patients with milder cases (with reference data from the 100,000 Genomes Project). Leading research organizations and pharmaceutical companies leveraged these data to help develop novel diagnostics, treatment and vaccine programs.
Radboud University Medical Centre, an EMRAM Stage 7 hospital in the Netherlands, meanwhile, launched its Grand Challenge for AI developers and clinicians to build solutions to classify lung abnormalities in the fight against COVID. Over 45,000 researchers have now signed up to the platform worldwide, demonstrating the scale that can be achieved through cloud-enabled research.
Cloud has also proved a powerful tool in hospital settings. In the US, for example, Beth Israel Deaconess Medical Centre, a teaching hospital of Harvard Medical School, is working with AWS to tackle inefficiencies and make process improvements, including optimising the schedules of its operating rooms and aligning them to improve patient flow.
Improved access to care and engagement
Dr Rowland Illing, international healthcare director and chief medical officer at AWS said, “Cloud computing has had a tangible positive impact on health outcomes, during what is the worst global health crisis for a generation. However, while the foundations to use cloud are in place, we are still only scratching the surface of what is achievable for healthcare systems with cloud technology.”
“Advanced compute, database and storage capability, coupled with machine learning and AI tools, can help healthcare technology partners, consulting partners and healthcare systems build solutions and services that serve patients,” said Dr Illing. “Even greater levels of trust will be placed in systems that can be seen to democratise access to care, allow best in class decision making and access to relevant medical research,” he continued.
Preventative care becoming a reality
And at a recent AWS Innovation Day, Andrea Fiumicelli, CEO of Italy-based healthcare and diagnostics software provider, Dedalus, spoke of how cloud technology can be used to create a digital healthcare ecosystem to enable continuity of care services, addressing the fragmentation and lack of standardisation of data and accelerating patient-centric care models.
“Advanced computing power and improved database capabilities mean that preventative population health analytics are now becoming a reality,” said AWS’ Dr Illing, citing a recent publication in arXiv.org by Mallya et al. In this study, patients who went on to develop congestive heart failure were identified with a high degree of accuracy up to 15 months in advance, using 12 month observational data.
