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Predictive Scheduling Solutions May Save Healthcare Providers Billions of Dollars

October 31, 2017 No Comments

Featured article by Marc Kaplan, Founder and CEO of Save Rite Medical

Incidents of patient no show are more common than you might think, and they can come with a hefty price tag for healthcare providers. As many as 15 percent of appointments that are made result in a no show and it’s been suggested that as many as 40 percent of a day’s bookings can result in a missed appointment. Not only does this pose an enormous inconvenience to providers who already have to put in substantial effort to keep appointments in order, but the ultimate loss of revenue can be enormous.

Fortunately for those many providers who struggle daily with patient no shows and late cancellations, a new scheduling solution has arrived on the scene. Known as Sibyl, this technology allows practices to better manage those times during the day when patients miss their appointments.

Sibyl was developed as a scheduling solution by Macro-Eyes, a company who’s work centers around providing personalized healthcare technologies. The CEO of Macro-Eyes, Benjamin Fels, believes that patient no shows can be a big problem for healthcare providers for a number of reasons. Along with costing billions of dollars in losses, missed appointments can be a huge drain on clinic morale. Not only this, but no shows can also cause significant strain on practice operations and could even impact a provider’s ability to save lives when called upon.

Since 2013, Seattle-based Macro-Eyes has been creating helpful products designed to simplify and streamline patient care for healthcare providers throughout the country. Sibyl is one of the company’s newest technologies and works by harnessing the power of artificial intelligence and putting it to work for providers looking for an effective scheduling solution. Sibyl is a predictive solution that is able to “learn” the best times to schedule patients in order to improve scheduling and provider and/or clinic utilization. According to Fels, the healthcare world has become increasingly dependent upon computers and data. However, scheduling was not “keeping up” with all of these advances. Sibyl was developed, according to Fels, as a means of melding scheduling with state-of-the-art predictive analytics and technology.

The predictive solution is able to adapt to the individual practice or provider and to learn which appointment times are not only best for the provider, but for the patient. Based on learned statistics, Sibyl can determine which times of the day are most likely to result in a successful appointment as opposed to a patient no show. This allows the tool to maximize the number of patients who are successfully seen in a day. The software can be easily added to existing scheduling solutions and provides helpful suggestions when an individual goes to schedule an appointment for a patient.

The development of Sibyl has taken many years and countless tests. The software has been put to the test throughout a number of premier medical centers in both California and New York. The data that was collected was analyzed according to many different data points, ranging from type of provider, patient demographics, as well as times of visits. These and a number of other helpful factors and variables were considered in order to get the biggest picture possible. These other variables included things like weather patterns, area traffic patterns, availability of public transportation, and even air quality. Believe it or not, all of these individual factors can have a significant impact on patient no shows and cancellations.

Once all of this data had been analyzed and conclusions drawn, Sibyl was launched in twenty clinics throughout the United States. Macro-Eyes worked closely with each of these facilities and reviewed upwards of two million anonymous appointments. Sibyl was given the task of analyzing each of the appointments and determining whether the appointment was missed or not. Sibyl was able to correctly predict the outcome in 76 percent of instances.

Results like these show that technological advances can be used to benefit all areas of healthcare, and companies like Macro-Eyes have made it clear that patient scheduling is yet another crucial task that can be made easier and more efficient with data solutions.

Link to news coverage:

-Marc Kaplan

CEO, Save Rite Medical

Marc 150x150 Predictive Scheduling Solutions May Save Healthcare Providers Billions of Dollars

Marc Kaplan is founder and CEO of Save Rite Medical — the leading provider of wholesale medical supplies. A salesman by day and educator by night, Marc enjoys providing valuable ways and alternatives to living a healthier lifestyle.


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