AI in itself is not a solution but a tool that needs to be integrated into the workflow and designed with a human-AI collaboration in mind.
Artificial intelligence can help us become faster and better at fighting diseases, living healthier lives, and lowering the costs of healthcare. However, applying AI to real-world healthcare problems is a tricky process that involves a range of obstacles. Healthcare organizations are under tremendous pressure, now more so than ever with the COVID-19 pandemic and the increasing levels of aging populations and lifestyle-related chronic diseases.
Simultaneously, digital transformation is driving a tremendous increase in health data. Healthcare providers are now more capable than ever to gather information about individual and population health. But, putting that data to use is another challenge altogether.
Just because doctors have access to a lot of data, doesn’t mean they want to be bombarded with the data. What they require is relevant and precise information, at the point of decision making. Artificial intelligence can help with that by providing the right data and the right time and enabling clinicians to make the best use of all the available data. Turning data into actionable insights for precision health will allow precise and personalized healthcare to flourish across the health continuum.
AI can also help make the entire experience of medical care more human by freeing up the time of doctors and enabling them to spend more time on patient care. AI can take away the burden of poring over data and medical records from physicians, who can then allocate their time to doing what they know best; treating patients in a more precise and personalized manner.
Clinicians and AI have different strengths that complement and augment each other. Although AI is a powerful tool, it is not a replacement for human capabilities. A lot of the decisions that clinicians make are complex in nature and need more than an AI-assisted approach. What makes the real difference when it
comes to effective patient management is the augmented intelligence and support for decision making at the appropriate time.
The post-COVID world will likely see an increase in the use of wearable technology and remote monitoring tools as well. Such technology is also well suited to monitor patients with chronic conditions from the comfort of their home. It also enables the use of predictive analytics to predict which patients may need additional care.
AI definitely has the capacity to bring about huge improvements in healthcare. But to have a truly transformative impact, it has to be integrated deeply into the workflow of clinical staff and the daily routines of patients. Those who design the AI systems must ensure that their systems fit smoothly into the workflow of the busiest of health care professionals. If an AI system is designed to add extra steps to a clinical procedure and take up more time than before, it will not be useful to healthcare providers. It is important to remember that AI in itself is not a solution. It’s a tool that needs to be integrated into the workflow and designed with a human-AI collaboration in mind.