By 2021, healthcare providers and consumers are expected to spend more than six billion dollars annually on artificial intelligence solutions and platforms.
Major investments are being made across a range of healthcare technologies – from consumer health applications by technology giants such as Apple and Fitbit, to cognitive computing solutions analyzing diagnostic, clinical and workflow applications. The AI/Bot revolution is already shaping the healthcare sector, and will likely see major growth over the next decade. However, while these advances offer exciting possibilities, now is the time to consider the impact they will have on another aspect of care delivery highly valued by patients and caregivers alike: human contact.
For all of us as patients, the idea of receiving treatment from a “robot” may be unsettling. Can AI really understand us as individuals, the way our family doctor does? On the provider front, care facilities also face a number of logistical hurdles when integrating these technologies into their practice. Moreover, some physicians are hesitant to trust automated results from a machine over their own methods. In order to resolve these issue, care providers need to recognize and protect the importance of the human experience while embracing the potential of AI – this does not have to be an all-or-nothing choice. Hospitals should be working to better understand the optimal balance between hands-on staff and technology, and applying the growing range of AI solutions to enhance the patient-provider experience, not to displace it.
Perhaps one of the most widely-recognized applications of AI in healthcare is in the field of computer-aided diagnostics. Advanced AI and machine learning technologies like IBM Watson and the SAP Foundation for Health have started assisting clinics and doctors in the study, diagnosis and treatment of cancer and other serious illnesses. As the development of new applications and cheaper solutions allow AI to expand into the everyday operations of hospitals, those rapid analytics capabilities will add an additional layer of decision support for physicians to more quickly and accurately diagnose and treat patients.
Rather than acting as the sole decision-maker, cognitive technologies will be another tool for doctors and nurses, running through lists of symptoms and conditions far faster than a human could and displaying these “decisions” for the care provider to review. Working collaboratively with the new technology, clinicians can blend the information offered with their own clinical knowledge and experience to make a final determination. In this way, the centrality of the patient-provider relationship is maintained, while improving the quality and accuracy of care.
In fact, there are many routine tasks in healthcare that are well suited to AI. Every patient visit generates a great deal of administrative work. Staff are required to record patients’ admission information, coordinate their rooms, assign staff to their care schedule and continually track and update their health records throughout their stay. This can take a lot of time and resources when performed by hospital personnel – but it is one of the premier applications of automated bots and machine learning systems. Bots can be programmed to interact with patients upon entering the facility, recording their information and answering any basic admittance questions – then things are handed off to staff who are trusted to guide patients through the process and resolve any lingering concerns. In that way, machine systems can be an excellent support option for clinicians, removing mundane tasks and standard explanations, and letting them focus on the particular concerns and questions that arise for each individual patient. We readily trust digital technology to give us facts and information, but when we seek comfort or reassurance, we reach for the human touch. Once again, hospitals can balance the patient’s machine-based interaction with flesh-and-blood staff depending on the nature of the task at hand.
Finally, although AI and machine learning are still relative newcomers to the field of healthcare, hospitals have for years been collecting the massive amounts of data required for those systems from wireles tags, sensors, and other connected devices used throughout their facilities. In turn, by running that data through a cognitive computing system, hospitals will dramatically simplify the analytics process, collecting new insights which the AI system can use to design more efficient staff workflow, operational procedures, asset utilization and even the facility layout. For instance, by gathering individual patient data, the system can learn each person’s habits and preferences, and coordinate that with staff shifts and workflow patterns to design an optimal patient experience while ensuring efficient staff flow and throughput. In doing so, doctors and nurses are relieved of these coordination tasks, allowing them to focus on the aspects of their work that require (or are best suited to) a human touch. That means more time interacting with patients and staff, faster and more efficient delivery of equipment throughout the facility, and ensuring a clean, secure and welcoming environment.
The age of artificial intelligence is here, but that doesn’t have to mean we’ll be scheduling our next checkup with Dr. Robot. The potential of futuristic technologies like AI is real, especially with its promise of reduced workloads and better care coordination, but hospitals and their staff of dedicated caregivers will need to use this technology to support, and not supplant, the human experience that is at the core of caring for one another.
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