How healthcare data will make or break healthcare AI
October 15, 2019
The single most important thing that a medical team does before a surgery is cleaning the tools. Fully functional and clean instruments are critical to successful outcomes. Without adequate cleaning, patient safety is at risk.
The same is true for your digital operations. As organizations prepare to forge into a future with artificial intelligence (AI), they must also “clean” their tools—that is, their processes and data. Otherwise, they too risk poor outcomes on their AI journey, in the form of low-quality outputs and reduced value of AI.
Accenture research shows that AI has the potential to boost the world’s economic output by $14 trillion and increase corporate profitability by an average of 38 percent. But while companies across industries are seeing the benefits of implementing AI technologies, its usage is fragmented, leading to significant untapped potential.
When compared to other industries, healthcare is leading the way in the use of AI. But its usage is still significantly low. The reason? In a recent Accenture survey, 18 percent of health executives say that one of the main obstacles to broad-scale AI implementation is organizational structure, namely lack of available, clean data.
By now, we’ve all heard the mantra, “data is the new currency.” The ability to make sense of data—and linking it to your AI efforts—is what will distinguish the winners and the losers in this race to provide more affordable and productive healthcare, as well as a positive patient experience.
So, where’s the challenge? Even if the drive to integrate AI exists, hospitals and clinics struggle with content validity and management of their current data processes and storage.
Squeezed by government payments, insurance payments and consumer choice, AI can help health providers continue to deliver services at the pace and quality expected by the consumer. But to even begin the AI journey, organizations need better control over their data. Only with clear insights, derived from clean data, can you differentiate yourself.
Without clean data, AI will be a hinderance, if not an absolute failure. It’s just like the surgical instruments referenced above. There’s no doubt that these tools will do what they’re intended to do. But if they’re not cleaned, they could infect the patient, causing other systems and functions to break down. Similarly, “messy” data will make your artificial intelligence outputs meaningless.
Data cleansing requires a lot of effort—and it may not be fun. But it’s not something you can just ignore. If you want to stay in business and drive positive business growth, you’ll eventually have to tackle your data sets.
AI is the future. In the healthcare industry, Accenture estimates that 25 percent of today’s tasks will be automated and 50 percent of services will be provided virtually by 2030.
But before the journey can begin, clean data should be a business and strategic priority. You don’t want to be delayed whenever you’re ready to employ AI just because your data sets aren’t ready.
Investing the time and resources now to tackle this cleanup will allow for a faster and easier transition to automated, analytical and AI-centered business strategies. And that means a more direct path toward delivering operational efficiency, patient satisfaction and better access to care.
Are you ready to start cleaning your data and processes?