Microsoft’s latest AI tool can predict missed doctor’s appointments

Between the scarcity of trained doctors, the shortage of nursing staff, and the general attrition among healthcare workers, getting a doctor’s appointment is no easy task in the modern clinical landscape. Indeed, the time value of appointments has never been so high.

This piece is exactly what Microsoft’s latest artificial intelligence (AI) tool is trying to solve: reduce missed medical appointments. Merav Davidson, Vice President of Microsoft Industry AI, wrote in Microsoft Industry Blogs: “The annual cost of missed appointments in healthcare is over $150 billion in the United States alone. United. Missed appointments not only lead to deteriorating patient health, but the economic effects of patient no-shows significantly affect clinic operations and fixed cost calculations, leading to overstaffing and downtime unforeseen events, ultimately leaving healthcare providers struggling with day-to-day operations.

Davidson highlights an important phenomenon. Missed appointments are not only detrimental to the patient, but also to the entire clinical ecosystem. For example, if a patient does not show up for their assigned slot, that room will now be unused for that time. In most situations it can’t just be refilled with the next person in line, since it’s an appointment-based service, and the next person probably won’t arrive. not before his allotted time. While one or two missed appointment slots may be negligible, viewed from a holistic perspective, this unused time costs the system billions of dollars per year. Perhaps more importantly, the fact that a lost appointment is a missed opportunity for someone else who really needed to see a doctor but couldn’t get in. Given that current wait lists for primary care physicians result in months-long wait times nationwide, this is a very real problem.

Microsoft’s tool is integrated with its robust Cloud for Healthcare platform and has an easy learning curve: “The model is easily deployable and can be trained in just two hours, leaving the healthcare provider ready to use the solution in just one day. This offer benefits both clinicians and patients. With a user-friendly and familiar interface, Missed Appointment Forecasting allows office staff and clinicians to predict patient absences without data science training or staff.

Davidson further explains that “Various types of input data have been shown to be important in predicting missed appointments in healthcare. Demographics, historical patterns, social determinants, and appointment data such as type and time of day are examples of inputs that care teams can use to train the model. The intricacies behind the software have been explained in detail by Microsoft, which also insists that “the model is not pre-trained and will need to be trained by a healthcare provider’s user.”

Notably, clinics and ambulatory care facilities aren’t the only places where this tool could potentially benefit. There could possibly be an important role for this software in almost any clinical setting, ranging from the emergency department to hospital care situations.

Indeed, while this AI engine likely needs more work and testing before its full potential can be fully realized, the concept holds promise for using objective data and metrics to improve clinical outcomes. .

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