1142 GMT November 20, 2018
There’s an irrational fear that by embracing AI in healthcare our health ecosystem will be ‘run by robots,’ making humans redundant. But this couldn’t be further from the truth, healthcareit.com.au wrote.
A McKinsey report released in February this year found AI and robotics present huge opportunities for both the pharma and healthcare industries. The report found big data strategies could save the US healthcare system alone up to $100 billion a year thanks to AI-assisted efficiencies in trials, research and clinical practice.
Automation and streamlining processes
Embracing the power of big data and machine learning can free up healthcare professionals’ time to do less mundane tasks and focus on more personalized patient care. More health businesses around the world are also now leveraging the power of AI to automate decision-making, create financial and administrative efficiencies, automate parts of their supply chains, or streamline regulatory compliance functions.
A PWC report released earlier this year revealed how AI is already being leveraged by back offices and supply chains to generate quiet efficiencies. The report highlighted how repetitive tasks in particular may benefit from the introduction of AI and machine learning to replace or supplement human interaction.
This is because unlike human interaction AI doesn’t forget, tire, get bored with tasks, or develop repetitive strain injury or carpal tunnel syndrome.
Driving efficiency and better diagnostic outcomes
One of the ways AI is streamlining medical processes is by helping primary doctors fund and refer patients to specialists faster, and offer faster, more accurate and actionable insights for doctors and their patients. According to the PWC report, healthcare providers can also leverage AI tools to help their staff analyze routine pathology or radiology results more quickly and accurately, allowing them to see more patients and realize greater revenues.
Meanwhile, AI and deep learning is already being used to increase efficiency with healthcare image classification. This process enables extracting information from multiple images to help healthcare providers like radiologists mark and file X-rays, making the process quicker, easier and more accurate.
In the UK researchers at Oxford Hospital are already using AI technology to help improve diagnosis for heart disease and lung cancer.
Wellness wearables and machine learning
Leveraging data and insights from ‘wellness wearables’ can also aid diagnosis and treatment in healthcare. A recent study revealed wearable devices like Apple Watch and FitBit are already able to gather sophisticated data to enable detection of health conditions such as hypertension and sleep apnea. Machine learning is able to sift the reams of biometric information and maximize the insights.
According to MedicalDirector’s CEO Matt Bardsley, technology is now not only giving people incentive to become more deeply involved and interested in their own health, but they can easily share these data sets with their health practitioners in a far more accurate and structured way.
“In the short to mid-term, patients that can easily share this wellness data with their practitioners can help save a lot of time in diagnosis and monitoring their health,” he said.
“This can leaving open more time for medical professionals to spend on more complex medical issues, while opening up more resources to be spent on chronic health, which is currently a significant cost burden on the healthcare sector.”
In the long-term, Bardsley said increased education in the healthcare sector about how patients and practitioners can better leverage technology to optimize and share wellness data can open up a fresh wave of opportunities to enable more ideal healthcare and a more patient-centric approach.
“The future looks promising,” he said. “The digitally enabled practitioner will be able to see their next patient well-equipped with the same wealth of data that the patient has on their own wellness apps and devices, and more. The clinical visit will be more open, accurate and efficient, while the patient and practitioner relationship will become more trusting, personalized and transparent.”