Self-scheduling Medical Visits in a Multispecialty, Multisite Medical Practice: Complexity, Challenges, and Successes.

Background: Self-scheduling of medical visits is becoming more common but the complexity of applying multiple requirements for self-scheduling has hampered implementation. Mayo Clinic implemented self-scheduling in 2019 and has been increasing its portfolio of self-schedulable visits since then. Our aim was to show measures quantifying the complexity associated with medical visit scheduling and to describe how opportunities and challenges of scheduling complexity apply in self-scheduling. Methods: We examined scheduled visits from January 1, 2022, through August 24, 2023. For seven visit categories, we counted all unique visit types that were scheduled, for both staff-scheduled and self-scheduled. We examined counts of self-scheduled visit types to identify those with highest uptake during the study period. Results: There were 9555 unique visit types associated with 20.8 M (million) completed visits. Self-scheduled visit types accounted for 4.0% (838,592/20,769,699) of the completed total visits. Of seven visit categories, self-scheduled established patient visits, testing visits, and procedure visits accounted for 93.5% (784,375/838,592) of all self-scheduled visits. Established patient visits in primary care (10 visit types) accounted for 273,007 (32.6%) of all self-scheduled visits. Testing visits (blood and urine testing, 2 visit types) accounted for 183,870 (21.9%) of all self-scheduled visits. Procedure visits for screening mammograms, bone mineral density, and immunizations (8 visit types) accounted for 147,358 (17.6%) of all self-scheduled visits. Conclusion: Large numbers of unique visit types comprise a major challenge for self-scheduling. Some visit types are more suitable for self-scheduling. Guideline-based procedure visits such as screening mammograms, bone mineral density exams, and immunizations are examples of visits that have high volumes and can be standardized for self-scheduling. Established patient visits and laboratory testing visits also can be standardized for self-scheduling. Despite the successes, there remain thousands of specific visit types that may need some staff-scheduler intervention to properly schedule.

Self-scheduling in a Large Multispecialty and Multisite Clinic: A Retrospective, Longitudinal Examination of Multiple Self-Scheduled Visit Types.

Background: Self-scheduling of medical visits is becoming available at many medical institutions. We aimed to examine the self-scheduled visit counts and rate of growth of self-scheduled visits in a multispecialty practice. Methods: For 85 weeks extending from January 1, 2022 through August 24, 2023, we examined self-scheduled visit counts for over 1500 self-scheduled visit types. We compared completed self-scheduled visit counts to all scheduled completed visit counts for the same visit types. We collected counts of the most frequently self-scheduled visit types for each week and examined the change over time. We also determined the proportion that each visit type was self-scheduled. Results: There were 20,769 699 completed visits during the course of the study that met the criteria for inclusion. Self-scheduled visits accounted for 4.0% of all completed visits (838 592/20,769 699). Over the 85-week span, self-scheduled visits rose from 3.0% to 5.3% of the total. There were 1887 unique visit types that were associated with completed visits. There were just 6 appointment visit types of the total 1887 self-scheduled visit types that accounted for 50.7% of the total 838 592 self-scheduled visits. Those 6 visit types were a lab blood test visit (19.5%, 163 K visits), two Family Medicine office visit types (13.0%, 109 K visits), a screening mammogram visit type (6.6%, 55 K visits), a scheduled express care visit type (6%, 50 K visits) and a COVID immunization visit type (5.7%, 48 K visits). Twenty-one visit types that were self-scheduled accounted for 75% of the total self-scheduled visits. Four seasonal visits, accounting for 10.6% of the total self-scheduled visits, were responsible for almost all the non-linear change in self-scheduling. Conclusion: Self-scheduling accounted for a small but growing percent of all outpatient scheduled visits in a multispecialty, multisite practice. A wide range of visit types can be successfully self-scheduled.

Self-Triage Use, Subsequent Healthcare Utilization, and Diagnoses: A Retrospective Study of Process and Clinical Outcomes Following Self-Triage and Self-Scheduling for Ear or Hearing Symptoms.

Background: Self-triage is becoming more widespread, but little is known about the people who are using online self-triage tools and their outcomes. For self-triage researchers, there are significant barriers to capturing subsequent healthcare outcomes. Our integrated healthcare system was able to capture subsequent healthcare utilization of individuals who used self-triage integrated with self-scheduling of provider visits. Methods: We retrospectively examined healthcare utilization and diagnoses after patients had used self-triage and self-scheduling for ear or hearing symptoms. Outcomes and counts of office visits, telemedicine interactions, emergency department visits, and hospitalizations were captured. Diagnosis codes associated with subsequent provider visits were dichotomously categorized as being associated with ear or hearing concerns or not. Nonvisit care encounters of patient-initiated messages, nurse triage calls, and clinical communications were also captured. Results: For 2168 self-triage uses, we were able to capture subsequent healthcare encounters within 7 days of the self-triage for 80.5% (1745/2168). In subsequent 1092 office visits with diagnoses, 83.1% (891/1092) of the uses were associated with relevant ear, nose and throat diagnoses. Only 0.24% (4/1662) of patients with captured outcomes were associated with a hospitalization within 7 days. Self-triage resulted in a self-scheduled office visit in 7.2% (126/1745). Office visits resulting from a self-scheduled visit had significantly fewer combined non-visit care encounters per office visit (fewer combined nurse triage calls, patient messages, and clinical communication messages) than office visits that were not self-scheduled (-0.51; 95% CI, -0.72 to -0.29; P < .0001). Conclusion: In an appropriate healthcare setting, self-triage outcomes can be captured in a high percentage of uses to examine for safety, patient adherence to recommendations, and efficiency of self-triage. With the ear or hearing self-triage, most uses had subsequent visit diagnoses relevant to ear or hearing, so most patients appeared to be selecting the appropriate self-triage pathway for their symptoms.

Online Self-Triage of Ear or Hearing Concerns in a Patient Portal: Comparison of Subsequent Diagnoses and Hospitalizations to National Emergency Department and National Ambulatory Ear or Hearing Visits.

Background: Although online self-triage is easily accessible, little is known about the patients who use self-triage or their subsequent diagnoses. We compared ear/hearing self-triage subsequent diagnoses to ear/hearing visit diagnoses in emergency departments (ED) and ambulatory clinics across the United States. Methods: We compared International Classification of Diseases version 10 (ICD10) coded diagnoses following online self-triage for ear/hearing concerns with those from national ED and ambulatory clinic samples. We used data from the Centers for Disease Control (CDC) National Hospital Ambulatory Medical Care Survey (NHAMCS) and National Ambulatory Medical Care Survey (NAMCS) for comparison. Using matched ear/hearing diagnostic categories for those aged 1 and over, we compared self-triage diagnosis frequencies with national ED and ambulatory diagnosis frequencies. Results: Following ear/hearing self-triage, there were 1092 subsequent office visits with a primary diagnosis code. For five frequently diagnosed ear/hearing conditions (i.e., suppurative and nonsuppurative otitis media [OM], otalgia, otitis externa, and cerumen impaction), there was a strong correlation between diagnosis counts made following self-triage and estimated counts of national ED visit diagnoses (r = 0.94; CI 95% [0.37 to 0.99]; p = .016, adjusted r2 = 0.85). Seven diagnoses were available to compare with the national ambulatory sample; correlation was r = 0.79; CI 95% [0.08 to 0.97]; p = .037, adjusted r2 = 0.54. For ages 1 and over, estimated hospital admissions from the national ED visits for ear/hearing were 0.76%, CI 95% [0.28-2.1%]; estimated total national ear/hearing ED visits were 7.5 million (for 4 years, 2016 through 2019). Conclusion: The strong correlation of ear-related self-triage diagnoses with national ED diagnoses and the low hospitalization risk for these diagnoses suggests that there is an opportunity for self-triage of ear/hearing concerns to decrease ED visits for these symptoms.

Self-Scheduling Process Efficiency and Utilization of Online Self-Scheduling of Lab Tests: A Retrospective Analysis of Self-Scheduled Appointments for COVID Testing.

Introduction: The COVID 19 pandemic increased the need for rapid and accurate diagnostic testing for COVID. When testing became available, a systems response was needed to efficiently accommodate the high-volume flow of patients who needed testing. Self-scheduling of COVID testing was developed to help patients safely and efficiently schedule their COVID testing online or with a mobile app. Methods: We captured the counts of COVID test appointments, time patients spent in scheduling COVID test appointments, appointment lead times, and no-shows for COVID test appointments. For 17 months of self-scheduling, we retrospectively compared self-scheduling with the concurrent staff scheduling of COVID tests. Results: From November 2020 through March 2022 there were 619 104 scheduled appointments for COVID testing with 22% (136 252) being self-scheduled. For asymptomatic self-scheduled COVID tests, accounting for 10.3% (63 605/619 104) of total COVID tests scheduled, median time to self-schedule was 3.1 min, interquartile range (IQR) [2.4,4.7]. For symptomatic self-schedulers accounting for 11.7% (72 647/619 104) of total COVID tests scheduled, the median time to self-triage and self-schedule was 5.8 min, IQR[4.3,8.9]. Self-scheduled COVID appointments increased to 44% (42 387/97 086) of the total COVID appointments during the peak month of January 2022. Median appointment lead time for symptomatic self-scheduled COVID test appointments was 6.6 h compared to 2.9 h (P < .0001) for symptomatic staff scheduled appointments. However, adjusting for the 24% (32 194/135 252) that self-scheduled during hours when testing was unavailable, the median appointment lead time for symptomatic self-scheduled patients dropped to 3.6 h. No-shows were 2.5% for self-scheduled appointments compared to 3.0% no-shows that were staff scheduled (odds ratio 0.83, P < .0001). Conclusion: COVID testing was self-scheduled for a large percent of scheduled COVID tests, taking patients only a few minutes to complete. Self-scheduling use increased over time, associated with a decreasing use of staff scheduled appointments and lower no-shows.

The Effect of Automated Mammogram Orders Paired With Electronic Invitations to Self-schedule on Mammogram Scheduling Outcomes: Observational Cohort Comparison.

BACKGROUND: Screening mammography is recommended for the early detection of breast cancer. The processes for ordering screening mammography often rely on a health care provider order and a scheduler to arrange the time and location of breast imaging. Self-scheduling after automated ordering of screening mammograms may offer a more efficient and convenient way to schedule screening mammograms. OBJECTIVE: The aim of this study was to determine the use, outcomes, and efficiency of an automated mammogram ordering and invitation process paired with self-scheduling. METHODS: We examined appointment data from 12 months of scheduled mammogram appointments, starting in September 2019 when a web and mobile app self-scheduling process for screening mammograms was made available for the Mayo Clinic primary care practice. Patients registered to the Mayo Clinic Patient Online Services could view the schedules and book their mammogram appointment via the web or a mobile app. Self-scheduling required no telephone calls or staff appointment schedulers. We examined uptake (count and percentage of patients utilizing self-scheduling), number of appointment actions taken by self-schedulers and by those using staff schedulers, no-show outcomes, scheduling efficiency, and weekend and after-hours use of self-scheduling. RESULTS: For patients who were registered to patient online services and had screening mammogram appointment activity, 15.3% (14,387/93,901) used the web or mobile app to do either some mammogram self-scheduling or self-cancelling appointment actions. Approximately 24.4% (3285/13,454) of self-scheduling occurred after normal business hours/on weekends. Approximately 9.3% (8736/93,901) of the patients used self-scheduling/cancelling exclusively. For self-scheduled mammograms, there were 5.7% (536/9433) no-shows compared to 4.6% (3590/77,531) no-shows in staff-scheduled mammograms (unadjusted odds ratio 1.24, 95% CI 1.13-1.36; P<.001). The odds ratio of no-shows for self-scheduled mammograms to staff-scheduled mammograms decreased to 1.12 (95% CI 1.02-1.23; P=.02) when adjusted for age, race, and ethnicity. On average, since there were only 0.197 staff-scheduler actions for each finalized self-scheduled appointment, staff schedulers were rarely used to redo or "clean up" self-scheduled appointments. Exclusively self-scheduled appointments were significantly more efficient than staff-scheduled appointments. Self-schedulers experienced a single appointment step process (one and done) for 93.5% (7553/8079) of their finalized appointments; only 74.5% (52,804/70,839) of staff-scheduled finalized appointments had a similar one-step appointment process (P<.001). For staff-scheduled appointments, 25.5% (18,035/70,839) of the finalized appointments took multiple appointment steps. For finalized appointments that were exclusively self-scheduled, only 6.5% (526/8079) took multiple appointment steps. The staff-scheduled to self-scheduled odds ratio of taking multiple steps for a finalized screening mammogram appointment was 4.9 (95% CI 4.48-5.37; P<.001). CONCLUSIONS: Screening mammograms can be efficiently self-scheduled but may be associated with a slight increase in no-shows. Self-scheduling can decrease staff scheduler work and can be convenient for patients who want to manage their appointment scheduling activity after business hours or on weekends.

Impact of Web-Based Self-Scheduling on Finalization of Well-Child Appointments in a Primary Care Setting: Retrospective Comparison Study.

BACKGROUND: Web-booking of flights, hotels, and sports events has become commonplace in the travel and entertainment industry, but self-scheduling of health care appointments on the web is not yet widely used. An electronic health record that integrates appointment scheduling and patient web-based access to medical records creates an opportunity for patient self-scheduling. The Mayo Clinic developed and implemented a feature in its Patient Online Services (POS) web and mobile platform that allows software-managed self-scheduling of well-child visits. OBJECTIVE: This study aims to examine the use of a new self-scheduling appointment feature within POS in both web and mobile formats and determine the use characteristics, outcomes, and efficiency of self-scheduling compared with staff scheduling. METHODS: Within a primary care setting, we collected 13 months of all appointment activity for the well-child visit for children aged 2-12 years. As these specific appointment types are for minors, self-scheduling is performed by parents or other proxies. We compared the appointment actions of scheduling and cancelling for both self-scheduled and staff-scheduled appointments. The frequency in which patients were using self-scheduling outside of normal business hours was quantified, and we compared no-show outcomes of finalized appointments. RESULTS: Of the 1099 patients who performed any self-scheduling actions, 73.1% (803/1099) exclusively used self-scheduling and self-cancelling software. For those with access to self-scheduling (patients registered with the Mayo Clinic POS), 4.92% (1201/24,417) of all well-child appointment-scheduling actions were self-scheduled. Staff scheduling required more than a single appointment step (eg, schedule, cancel, reschedule) in 28.32% (3729/13,168) compared with only 6.93% (53/765) of self-scheduled appointments (P<.001). Self-scheduling appointment actions took place outside of regular business hours 29.5% (354/1201) of the time. No-shows accounted for 3.07% (28/912) of the self-scheduled finalized appointments compared with 4.12% (693/16,828) of staff-scheduled appointments, which is a nonsignificant difference (P=.12). Staff-scheduled finalized appointments (that allowed for scheduling appointments for more than 12 weeks in the future) revealed a potential demand of 11.15% (1876/16,828) for appointments with longer lead times. CONCLUSIONS: Self-scheduling can generate a significant number of finalized appointments, decreasing the need for staff scheduler time. We found that 29.5% (354/1201) of the self-scheduling activity took place outside of the usual staff scheduler hours, adding convenience value to the scheduling process. For exclusive self-schedulers, 93.1% (712/765) finalized the appointment in a single step. The no-show rates were not adversely affected by the self-scheduling.