Looking to the clinic of tomorrow
Artificial intelligence (AI) and new technologies are set to transform healthcare—by making it more efficient, preventive, personalized and accessible. They will enhance the capabilities of healthcare providers, save time, improve patient outcomes and offer innovative solutions to complex medical challenges.
At least, that is the hope and the promise. There are already many examples of these technologies improving efficiencies and patient care, many more in the pipeline and still others a glimmer in the eyes of visionaries and entrepreneurs.
This AI revolution is happening in tandem with forces that both inform it and give it urgency: an aging population, a rising burden of disease, health workforce shortages, overcrowded hospitals, health access inequities, burned-out physicians and increasingly informed and demanding patients.
AI is already being utilized in areas such as diagnostics, patient monitoring, surgery and the development of personalized treatment plans.
“There are many areas where I think AI can help, but we have to step back and say, what are areas that actually need help?” said Muhammad Mamdani, vice-president of data science and advanced analytics at Unity Health Toronto and a public health expert.
Admin work halved?
For many clinicians and their staff, the most tantalizing promise of AI is to reduce manual, time-consuming tasks like scheduling appointments, processing insurance claims, referrals and managing patient records. AI scribes promise to reduce note taking during visits and will be especially helpful when they are fully integrated into EMR systems. Once integrated, EMRs will order tests, process referrals, make diagnoses and recommend treatments. “Studies are suggesting that it’s going to cut the administrative work by half and that’s going to take a lot of pressure off. Now what do they do with that additional time? That’s a whole other story,” said Mamdani.
A major force of AI in healthcare is its machine learning models that access so much data from a wide swath of patients that it can predict the likelihood of diseases, leading to earlier and more precise diagnoses. From there it can analyze an individual patient’s age, medical history, comorbidities, genetic data, current condition, lifestyle and environment and recommend personalized treatment.
“There’s so much that we have high hopes for, but I think also it’s going to be a culture and a mindset change,” said Mamdani. “Either we change or it will change us, it is inevitable.”