In her white paper, Silpa Saladi, Client Operations Director, discusses the financial consequences of no-show revenue loss and how it can be avoided. In particular, Silpa’s white paper reviews Vee Technologies’ innovative solutions that prevent no-shows and no-show revenue loss.
Please click on the video to the right to learn more about Silpa, her paper’s key takeaways, and her motivation for writing on this subject.
To discuss this white paper at length, please contact the author using her information provided at the bottom of the article.
In healthcare, a no-show is a patient that misses a scheduled appointment without proper cancellation. Reducing no-shows can have a tremendous, positive impact on a practice resulting in improved efficiency, reduced costs, and improved patient outcomes. Machine learning and artificial intelligence (AI) strategies offer reliable solutions to manage this unwelcomed issue.
Missed appointments disrupt the continuity of an organization’s workflow and lead to inefficient resource allocation. When a patient misses a scheduled appointment, two patients miss the opportunity for care; the patient that did not attend their original appointment and the other patient who could have been scheduled at that time.
For the patients, they risk a delay in preventive services, acute issues shifting to chronic conditions, complications in recovery, and increased health consequences. For the practice, revenue deficits can increase in parallel to no-show rates. Understanding the underlying causes of no-shows is the best means of correction; prevention is the treatment.
Research studies have shown that no-shows result in a total loss of revenue of over $150B a year in the United States alone. At most healthcare facilities and practices, the typical no-show rate ranges between 23% to 34%. In New York, this rate extends closer to 40%, averaging one in every three patients.
Each represents a non-reimbursable visit for that day, reflecting a loss of approximately $200 per patient. The consequence of these missed opportunities become unnecessarily pricey as they accumulate, endangering an organization’s profit margin, and ultimately, even their bottom line.
Unfortunately, patients may not understand the financial impact of a missed, scheduled appointment. Many believe that this is standard practice, and the administrative staff takes no-shows into consideration when reserving the time slot for an appointment, as airline carriers often overbook to compensate for missed travelers. Unlike airline carriers, however, if clinics overbook, the wait times will be increased for patients, leading to patient dissatisfaction and physician burnout.
Although the excuses may be plenty, most of the reasons that patients miss their appointments fall under the following categories:
Preventive options include:
Studying recurring patients’ appointments, Vee Technologies can use artificial intelligence (AI) to provide a solution through machine learning. We look at patient variable data to predict the probability of patient absenteeism.
Combining historical data, demographic data, and population health metrics provides a more accurate assessment of the risk of a no-show. With this information at hand, we can suggest appropriate action before a patient’s appointment date to help increase the likelihood of attendance.
For example, if a patient has a 33% no-show rate, the clinic can use text message reminders, suggest a more convenient location, or provide transportation options to help the patient get to his or her appointment.
Social Determinants of Health (SDOH) data is an influential variable in the prediction of a patient’s no-show probability. Based on this historical, geographic, and demographic information, algorithms are used to determine the likelihood of the patient missing an appointment.
With this readily available data, we can ensure that patients are satisfied with their appointment, increasing their attendance probability as we take into consideration the roadblocks preventing patients from attending appointments. Our tools are then able to support customers to adjust their services to meet individual patient needs.
A significant benefit of this technology is its ability to create data-supported recommendations for overbooking appointments. Machine learning technology can analyze thousands of data entries in real-time. The algorithm identifies which patients are at the highest risk of absenteeism and make recommendations on whether time slots should be staggered. With this technology in place, the providers can fully maximize their time to provide the most significant value to their patients.
Adopting the right technology is critical for patient success. By engaging AI, clinics can reduce no-show costs while increasing overall patient satisfaction.
By teaming up with Vee Technologies, your organization can gain an in-depth analysis of three to five years’ worth of data extracted from your scheduling system. This analysis can focus on recent and high-volume trending no-shows and can isolate future appointments at high risk of resulting in a no-show. The results will provide the information needed to take measures to prevent no-shows and reduce their net, negative impact. The integration of a customized machine learning process within a practice’s internal scheduler, or combination with an external interface to the existing system, can also allow patients to book their appointments online.
This technology collects patient demographics, insurance information, schedule/cancel/reschedule requests and provides the ability for real-time communications with patients. Patients that schedule or can reschedule their visits online are much less likely to no-show or cancel; patients interested in earlier appointments with short notice can be alerted the day of and remain on standby. Alternatively, patients unable to keep appointments may be amenable to telemedicine options.
Additionally, rescheduling within a unified scheduling system that is integrated into your EHR will allow administrative staff to utilize their time to concentrate on essential tasks and reduce the duplication of work. Implementation of a machine learning algorithm to predict no-shows and cancellations before they happen can eliminate gaps in the schedule.
Vee Technologies has the capability to enhance your organization a step further with a customized tool that provides an alert if a patient cancels at the last minute on the day of their visit.
At this time, the patient is offered the choice of having a HIPAA compliant virtual appointment through our very own telemedicine platform, systematically lowering the no-show rates.
By teaming up with Vee Technologies’ expert IT consultants, your practice can benefit from being equipped with the information it needs, to act on no-shows before they happen, and have robust options of adapting to sudden changes available via our scheduling assistants and telemedicine platforms. Remember, prevention is the best treatment.