Using business intelligence and data visualization to understand the characteristics of failed appointments in dental school clinics. Issue 4 (28th January 2021) - Weber, Kate; DaSilva, Alexandre F.; Dault, Jean T.; Eber, Robert; Huner, Kim; Jones, Darlene; Kornman, Kenneth; Ramaswamy, Vidya; Snyder, Mark; Ward, Brent B.; Nalliah, Romesh P.
Abstract: Purpose/Objectives: Broken appointments are an important cause of waste in health care. Patients who fail to attend incur costs to providers, deny trainees learning opportunities, and impact their own health as well as that of other patients who are waiting for care. Methods: A total of 410, 000 appointment records over 3 years were extracted from our electronic health record. We conducted exploratory data analysis and assessed correlations between appointment no‐shows and other attributes of the appointment and the patient. The University of Michigan Medical School's Committee on Human Research reviewed the study and deemed that no Institutional Review Board oversight was necessary for this quality improvement project that was, retrospectively, turned into a study with previously de‐identified data. Results: The patient's previous attendance record is the single most significant correlation with attendance. We found that patients who said they are "scared" of dental visits were 62% as likely to attend as someone reporting "no problem." Patients over 65 years of age have better attendance rates. There was a positive association between receiving email/text confirmation and attendance. A total of 94.9% of those emailed a reminder and 92.2% of those who were texted attended their appointment. Conclusion(s): We were able to identify relationships of several variables to failed and attended appointments that we were previously unknown to us. This knowledge enabled us to implement interventions to support better attendance at Dental Clinics at the University of Michigan, improving patient health, student training, and efficient use of resources.