The goal of healthcare has always been to deliver the best outcomes for patients in the most efficient and effective way possible. But the road to achieving that goal is often filled with challenges, many of which seem to be outside of our scope of control.
One of the chief challenges that fits this bill is scheduling. While providers understand the importance of treatment and have found ways to mitigate distractions in their lives, the same can’t always be said about patients. And when patients miss treatment, it not only affects the quality of their treatment, but it affects the provider’s ability to offer services to other patients who might be more prepared to take the process more seriously.
Unfortunately, other people’s reliability is something outside of our scope of control, right? In some cases, yes. However, artificial intelligence (AI) may offer some solutions to give healthcare scheduling the revolutionary boost it needs. The potential results?—Increased patient attendance, enhanced provider productivity, and yes, improved patient outcomes.
It Starts With Why
Before we can address the ways that AI is poised to change the game, we need to take a quick look at the reasons patients miss treatment. For some, it’s a lack of buy-in. With some treatment regimens requiring a lot of visits that may feel repetitive to the patient, motivation and prioritization may be issues. For other patients, the issues may be logistical. It may be an issue with means of transportation, an issue with funding those transportation costs, or comorbidities or the very issue they’re being treated for causing challenges. By compassionately understanding these challenges, we set the framework to be able to start looking for ways to help.
The Provider’s Responsibility?
A healthcare provider’s specialty is treating the patient and delivering quality outcomes. Obviously, this can only happen if the patient actually shows up and sticks to the treatment regimen laid out. So, does that mean that it’s the provider’s responsibility to ensure patients show up for treatment?
Yes and no. On the one hand, it directly affects the quality of the outcome, so it seems like a logical responsibility. However, let’s be real. While it would be great if providers had the time to dig into every patient’s personal challenges, the time to research their socioeconomic status, and the ability to assess their reliability and buy-in—that’s just not feasible.
How AI is Poised to Assist
This is where AI has the opportunity to shine. What if we were able to utilize readily available data to accurately predict the likelihood that a patient is going to miss treatment or is going to be late? If we knew ahead of time which patients were more likely to self-discharge, forget completely about their appointments, or struggle to arrive on time, imagine the changes we could make to improve our scheduling.
We’d be able to do things like double book high cancellation risk patients. We’d be able to send additional reminders prior to appointments to the patients that need them most. Ultimately, we’d be able to keep our schedules full, our revenue maximized, and the quality of our patient outcomes sky high.
Here’s the bottom line. As providers, we can debate whether or not patient reliability is our responsibility. However, as business owners, there’s no question that maximizing revenue by keeping the schedule full is 100% our responsibility. Thankfully, artificial intelligence is poised to offer solutions that don’t detract from our time with patients and our ability to deliver high-quality care.
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