By Dr Nicolai Baldin
Even before the Covid-19 pandemic affected the world, AI was already making its impact on the healthcare industry.
In the last year alone, the UK’s National Health Service (NHS) invested £250 million into a national AI laboratory to enhance the care of patients, while U.S. company Cigna has deployed AI-driven technology to check if patients are taking their medications. Pre-pandemic it was estimated that over $4 billion was poured into companies pioneering AI in healthcare in 2019, according to CB Insights.
Since then, Covid-19 has been the accelerator for a number of unprecedented and near-overnight changes on healthcare providers and patients. The most notable change brought on by the pandemic has been the swift and sudden pivot to telehealth services as a way to deliver healthcare. Adoption has reached record levels, from just 11% in 2019 to 46% of consumers relying on telehealth to replace in-person healthcare visits. Additionally, consumers’ overall willingness to use telehealth in the future has elevated as well. A McKinsey study found that only 11% were open to the idea of telehealth last year, while during the pandemic that number has jumped to 76%. Finally, in less than six months, over 10 million Medicare beneficiaries have used telehealth, compared to just 13,000 weekly appointments for services prior to the onset of the pandemic.
As demonstrated by the technology deployed by Cigna, AI already plays a major role in this shift to telehealth. However, the benefits of AI will become more pivotal to the success of telehealth as more providers continue to share data. Before Covid-19, the healthcare sector had become a clear target for those attempting to siphon sensitive data, with the industry sustaining the second-highest number of security breaches last year. AI can be used to prevent such breaches and protect data by helping healthcare providers to put a coherent data strategy in place.
Currently, many healthcare providers are relying on either anonymous or original data in order to offer their patients treatment, both of which pose security risks. Original data contains Personally Identifiable Information (PII), while anonymous data holds transactional information, leaving patients vulnerable to fraud. Using AI, telehealth companies can now look toward the so-called synthetic or synthesized data. Synthesized data is able to remove characteristics that could leave patients identifiable, as the AI technology is able to make randomized changes to the original data while maintaining the same results. By its very nature, synthesized data is automatically compliant with HIPAA, GDPR, and other government privacy regulations.
At Synthesized, we’ve created a platform that is able to provision synthetic data for millions of records in just ten minutes. This not only saves companies from spending money and time on collecting, managing, and provisioning data (it’s estimated that up to $250 billion of healthcare spending in the U.S. could be virtualized), but also this on-demand approach allows for more personalized treatment than telehealth can currently offer.
Though the recent pivot to telehealth was born out of necessity during the pandemic, there now lies a great opportunity for the healthcare industry to conquer challenges for provisioning data using the most advanced AI advancements.