When patients miss appointments, it costs providers money and has serious health impacts on patients. Analytics can help improve scheduling processes for more effective use of resources and to ensure patients receive the care they need.

In isolation, it doesn’t seem that missing a doctor’s appointment is that big of a deal—a minor inconvenience for all concerned, at worst. That couldn’t be farther from the truth. And fighting the negative impacts of no-shows on both health organizations and patients themselves is a top focus of Predictive Health Services (PHS), a company created by N.J.’s Children’s Specialized Hospital and longtime SAS Partner, Pinnacle Solutions, Inc.

No-shows – appointments that are neither cancelled nor attended – create a ripple effect through the health system, affecting the quality of patient care, health outcomes, resource allocation and the bottom line. Each no-show costs three appointments:

  • The missed appointment itself.
  • The slot taken up by rescheduling
  • And the missed opportunity to see another patient on the waitlist.

“Today’s medical offices have a backlog of patients stuck on long waiting lists, while valuable appointments go unused because patients cancel too late for appointments to be backfilled, or they simply don’t show up at all,” says Dj Penix, Pinnacle’s President and Chief Executive Officer.

The health impacts of missed appointments (for whichever of the three reasons) can be more serious than our blasé attitude toward them suggests. Worsening health outcomes can be traced to patterns of missed appointments, especially for those with multiple long-term conditions. The reasons are many: lack of continuity of care, challenges assessing the effectiveness of medication, missed screening opportunities, and the fact that missed appointments lead to more missed appointments (one study found that patients were 70 percent less likely to return within 18 months after missing just one appointment).

Then there are the operational and bottom line impacts of those unfilled slots. Just because a patient doesn’t show up doesn’t mean support staff goes unpaid, office infrastructure costs disappear and equipment maintenance and depreciation stop. Expenses continue to accumulate, even when revenues are depleted by no-shows. In fact, one 2017 study found that no-shows cost the US health care system more than $150 billion a year and individual physicians an average of $200 per unused time slot.

Tactics and techniques

There are time-honored techniques for reducing the number of no-shows, each with its own pros and cons. Telephone reminders are still one of the most effective tactics; the Robert Wood Johnson University Medical Group found that 23 percent of patients missed their appointments if they didn’t get a phone reminder. That number dropped to 17 percent when they received automated phone reminders of their appointments and 13 percent with personal phone calls. But those calls consume staff time and telephone resources. Prepaid appointments might help the health center’s bottom line, but they can discourage vulnerable patient populations from seeking help in the first place. Similarly, imposing financial penalties for missed appointments can provide a disincentive for patients but often disproportionately impacts the less fortunate.

Other solutions revolve around scheduling. Patients are more likely to show up for quick-turnaround follow-ups within one to three days, but limited bandwidth can make this difficult. Overbooking is another strategy; having patients available to fill those no-show slots reduces the length of wait lists while avoiding wasted time and money. But blindly overbooking can result in an overwhelming workload, meaning less time with the patient and a decline in quality of care, as well as ironically increasing the cost of support staff with overtime.

Rather than focusing on these interventions themselves, PHS focuses on the why of the missed appointment. If a health center can accurately predict the likelihood of a missed appointment, patients can be prioritized for quick appointment turnaround, even same-day, and the hospital can have a strategic guide to the best windows for overbooking. A 2018 Duke University study successfully predicted more than 5,000 no-shows by modeling data from electronic health records.

Understanding why

Predicting no-shows depends on understanding their underlying causes. Griffin Hospital in Derby, Conn., interviewed patients who had missed appointments. The free text data from these interviews were analyzed using SAS and more than 30 percent said they had simply forgotten their appointments (another case for telephone reminders), the study found several other causes for missed appointments: lack of transportation, inability to afford co-pay or a lack of insurance altogether, illness, and family or work-related issues.

The PHS solution bundles this patient historical data with other data sources such as demographics, lifestyle information, type of insurance, commute and transportation circumstances (traffic and transit delays, roadwork and closures, etc.), appointment time of day, and even weather conditions, to provide simple red-yellow-green dashboards. These visualizations help identify appointments that are likely to be missed, allowing hospital or clinic staff to drill down into the possible solutions.

Pinnacle brought its decades of analytics experience to the table. Children’s Specialized Hospital brought operational insight to the partnership. “If it’s not meaningful in the context of patient interactions, the data can’t drive process improvements,” says Michael Dribbon, Vice President of Business Development and Chief Innovation Officer for the hospital’s Center for Discovery, Innovation, and Development (CDID).

Presenting the information in an accessible dashboard for users with varying technical and process skills allows the hospital to tailor interventions to the individual patient, from managing overbookings to providing transportation for the transit challenged.

The hospital can drill down into the performance enhancements of various strategies by practice type. Aside from driving efficiencies, it also bolsters staff morale and fights burnout.

“Provider stress has been on the rise for years and has become an even more significant issue with the impact of COVID,” Dribbon says.

No appointments translate to no care, no revenue, and no productivity, he puts it bluntly, and that increases stress for staff who want great outcomes for their patients, and who also have metrics to achieve. Avoiding last-minute scurrying to fill empty appointment slots plays into not just staff morale, but the quality of care.

“We all want to do the best for our patients and, when we do, staff feels really good,” he says.

To learn more about PHS’s No-Show Predictor solution, tune into the half-hour on-demand webinar Predicting Patient No-Shows, part of the SAS Analytics In 20 series.


About Author

Alex Coop

Senior Communications Specialist

Alex Coop manages internal and external communications for the Canadian business, helps create stories with our incredible customers and subject matter experts, and prior to joining SAS, was an editor and community reporter.

Comments are closed.

Back to Top