Predictive Analytics Brings Greater Efficiencies to the Healthcare Industry

In the healthcare industry, data scientists have made strides in the scheduling of patient appointments by applying predictive analytics. An article called "Data-driven scheduling predicts patient no-shows" from The Boston Globe by Michael B. Farrell expresses the problem of constant patient overbooking and rescheduling. Many people wait long periods of time for their doctor's appointment even though they may have arrived on time.

Gabriel Belfort, a former postdoctoral student at MIT, challenged this issue: "What if you could use data science to determine which patients are likely to show up and which ones will be no-shows and manage office appointments around those tendencies?"

At a healthcare hackathon, Belfort pursued a solution to this challenge with a team who developed a startup named Smart Scheduling Inc. With data, the scheduling histories of patients are mined and revealed to the scheduling programs. For those tagged as "high-risk," they are given calls to remind them of their appointments. If they can't be reached, they most likely will not show – so doctors book other patients to keep the schedule full.

As the program has developed, more variables are being examined to make sure that predictions on patient no-shows are more accurate. View the whole article to read about how the program has taken off.

Be part of the progress in applying predictive analytics to the healthcare industry in aspects of patient scheduling and beyond by attending Predictive Analytics World for Healthcare in Boston, October 6 – 7, 2014.

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