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.

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.

What Can Apologies in the Electronic Health Record Tell Us About Health Care Quality, Processes, and Safety?

INTRODUCTION: Apologizing to patients is an encouraged practice, yet little is known about how and why providers apologize and what insights apologies could provide in improving quality and safety. OBJECTIVE: The aim of the study was to determine whether provider apologies in the electronic health record could identify patient safety concerns and opportunities for improvement. METHODS: After performing a free-text search, we randomly selected 100 clinical notes from 1685 available containing terminology related to apology. We categorized the reason for apology, presence and classification of medical error, level of patient harm, and practice improvement opportunities. We compared patient events discovered from apologies in the medical record to standard patient incident report logs. RESULTS: Of 100 randomly selected apologies, 37 were related to a delay in care, 14 to misunderstanding, 11 to access to care, and 8 to information technology. For apologies related to delay, the median delay was 6 days (mean = 8.9, range = 0-41). Twenty-four (65%) of the 37 delays were related to diagnostic testing.Medical errors were associated with 46 (46%) of the 100 apologies. Sixty-four (64%) of the 100 apologies were associated with actionable opportunities for improvement. These opportunities were classified into 37 discrete issues across 8 broad categories. When apology review was compared with standard incident report logs, 27 (73%) of the 37 discrete issues identified by patient apology review were not found in incident reporting; both methods identified similar rates of patient harm. CONCLUSIONS: Review of apologies in the electronic health record can identify patient safety concerns and improvement opportunities not apparent through standard incident reporting.

Population health challenges in primary care: What are the unfinished tasks and who should do them?

BACKGROUND: There are numerous recommendations from expert sources that help guide primary care providers in cancer screening, infectious disease screening, metabolic screening, monitoring of drug levels, and chronic disease management. Little is known about the potential effort needed for a healthcare system to address these recommendations, or the patient effort needed to complete the recommendations. METHODS: For 73 recommended population healthcare items, we examined each of 28,742 patients in a primary care internal medicine practice to determine whether they were up-to-date on recommended screening, immunizations, counseling, and chronic disease management goals. We used a rule-based software tool that queries the medical record for diagnoses, dates, laboratory values, pathology reports, and other information used in creating the individualized recommendations. We counted the number of uncompleted recommendations by age groups and examined the healthcare staff needed to address the recommendations and the potential patient effort needed to complete the recommendations. RESULTS: For the 28,742 patients, there were 127,273 uncompleted recommendations identified for population health management (mean recommendations per patient 4.36, standard deviation of 2.65, range of 0-17 recommendations per patient). The age group with the most incomplete recommendations was age of 50-65 years with 5.5 recommendations per patient. The 18-35 years age group had the fewest incomplete recommendations with 2.6 per patient. Across all age groups, initiation of these recommendations required high-level input (physician, nurse practitioner, or physician's assistant) in 28%. To completely adhere to recommended services, a 1000-patient cross-section cohort would require a total of 464 procedures and 1956 lab tests. CONCLUSION: Providers and patients face a daunting number of tasks necessary to meet guideline-generated recommendations. We will need new approaches to address the burgeoning numbers of uncompleted recommendations.

Uses of Mobile Device Digital Photography of Dermatologic Conditions in Primary Care.

BACKGROUND: PhotoExam is a mobile app that incorporates digital photographs into the electronic health record (EHR) using iPhone operating system (iOS, Apple Inc)-based mobile devices. OBJECTIVE: The aim of this study was to describe usage patterns of PhotoExam in primary care and to assess clinician-level factors that influence the use of the PhotoExam app for teledermatology (TD) purposes. METHODS: Retrospective record review of primary care patients who had one or more photos taken with the PhotoExam app between February 16, 2015 to February 29, 2016 were reviewed for 30-day outcomes for rates of dermatology consult request, mode of dermatology consultation (curbside phone consult, eConsult, and in-person consult), specialty and training level of clinician using the app, performance of skin biopsy, and final pathological diagnosis (benign vs malignant). RESULTS: During the study period, there were 1139 photo sessions on 1059 unique patients. Of the 1139 sessions, 395 (34.68%) sessions documented dermatologist input in the EHR via dermatology curbside consultation, eConsult, and in-person dermatology consult. Clinicians utilized curbside phone consults preferentially over eConsults for TD. By clinician type, nurse practitioners (NPs) and physician assistants (PAs) were more likely to utilize the PhotoExam for TD as compared with physicians. By specialty type, pediatric clinicians were more likely to utilize the PhotoExam for TD as compared with family medicine and internal medicine clinicians. A total of 108 (9.5%) photo sessions had a biopsy performed of the photographed site. Of these, 46 biopsies (42.6%) were performed by a primary care clinician, and 27 (25.0%) biopsies were interpreted as a malignancy. Of the 27 biopsies that revealed malignant findings, 6 (22%) had a TD consultation before biopsy, and 10 (37%) of these biopsies were obtained by primary care clinicians. CONCLUSIONS: Clinicians primarily used the PhotoExam for non-TD purposes. Nurse practitioners and PAs utilized the app for TD purposes more than physicians. Primary care clinicians requested curbside dermatology consults more frequently than dermatology eConsults.

Controlled Substance Agreements for Opioids in a Primary Care Practice.

BACKGROUND: Opioids are widely prescribed for chronic non cancer pain (CNCP). Controlled substance agreements (CSAs) are intended to increase adherence and mitigate risk with opioid prescribing. We evaluated the demographic characteristics of and opioid dosing for patients with CNCP enrolled in CSAs in a primary care practice. METHODS: We conducted a retrospective cohort study of 1066 patients enrolled in CSAs between May 9, 2013 and August 15, 2016 for CNCP in a Midwest primary care practice. RESULTS: Patients were prescribed an average of 40.8 (SD ± 57.0) morphine milligram equivalents per day (MME/day), and 21.5% of patients were receiving ≥50 MME/day and 9.7% were receiving ≥90 MME/day. Patients who were younger in age (≥ 65 vs. < 65 years, P < 0.0001), male gender (P = 0.0001), and used tobacco (P = 0.0002) received significantly higher MME/day. Patients with more co-morbidities (Charlson Comorbidity Index, CCI) received higher MME/day (CCI > 3 vs. CCI ≤ 3, P = 0.03), and reported higher average pain (CCI > 3 mean 5.8 [SD ± 2.1] vs. CCI ≤ 3 mean 5.3 [SD ± 2.0], P = 0.0011). Patients on an identified tapering plan (6.9%) had higher MME/day than patients not on a tapering plan (P = 0.0002). CONCLUSIONS: CSAs present an opportunity to engage patients taking higher doses of opioids in discussions about opioid safety, appropriate dosing and tapering. CSAs could be leveraged to develop a population health management approach to the care of patients with CNCP.

Patient question set proliferation: scope and informatics challenges of patient question set management in a large multispecialty practice with case examples pertaining to tobacco use, menopause, and Urology and Orthopedics specialties.

BACKGROUND: Health care institutions have patient question sets that can expand over time. For a multispecialty group, each specialty might have multiple question sets. As a result, question set governance can be challenging. Knowledge of the counts, variability and repetition of questions in a multispecialty practice can help institutions understand the challenges of question set proliferation. METHODS: We analyzed patient-facing question sets that were subject to institutional governance and those that were not. We examined question variability and number of repetitious questions for a simulated episode of care. In addition to examining general patient question sets, we used specific examples of tobacco questions, questions from two specialty areas, and questions to menopausal women. RESULTS: In our analysis, there were approximately 269 institutionally governed patient question sets with a mean of 74 questions per set accounting for an estimated 20,000 governed questions. Sampling from selected specialties revealed that 50 % of patient question sets were not institutionally governed. We found over 650 tobacco-related questions in use, many with only slight variations. A simulated use case for a menopausal woman revealed potentially over 200 repeated questions. CONCLUSIONS: A group practice with multiple specialties can have a large volume of patient questions that are not centrally developed, stored or governed. This results in a lack of standardization and coordination. Patients may be given multiple repeated questions throughout the course of their care, and providers lack standardized question sets to help construct valid patient phenotypes. Even with the implementation of a single electronic health record, medical practices may still have a health information management gap in the ability to create, store and share patient-generated health information that is meaningful to both patients and physicians.

Effect of visit length and a clinical decision support tool on abdominal aortic aneurysm screening rates in a primary care practice.

RATIONALE, AIMS AND OBJECTIVES: In 2005, the US Preventive Services Task Force issued recommendations for one-time abdominal aortic aneurysm (AAA) screening using abdominal ultrasonography in men aged 65 to 75 years with a history of smoking. However, despite a mortality rate of up to 80% for ruptured AAAs, providers order the screening for a minority of patients. We examined AAA screening rates among providers and investigated the role of visit duration and other factors in whether patients received screening. We also looked for potential interventions to improve compliance. METHODS: We retrospectively reviewed the records of patients who visited our clinic over a 4-month period and met the US Preventive Services Task Force criteria for AAA screening when our practice had a real-time decision support tool implemented to identify patients due for the screening. We also surveyed our clinic's providers about their knowledge and attitudes regarding AAA screening. RESULTS: Despite the use of physician reminders, providers ordered screening for only 12.9% of eligible patients. Screening was more likely to be ordered during longer visits versus shorter ones (24% vs. 6%). When surveyed, most providers (70.6%) indicated that a nurse-directed ordering system would improve compliance. CONCLUSIONS: This study illustrates that physician reminders alone are not sufficient to improve care and that more time is needed for preventive services. This provides additional support for the use of a multidisciplinary approach to preventive screening, as in a patient-centred medical home. In a patient-centred medical home, a care team of physicians, nurses and office staff use technology such as clinical decision support to provide comprehensive, coordinated patient care.

A pilot study to assess smokeless tobacco use reduction with varenicline.

INTRODUCTION: Long-term smokeless tobacco (ST) use is known to increase the risk for oropharyngeal cancer, heart attack, and stroke. Extant literature on cigarette smokers suggests that smoking reduction increases smoking abstinence among smokers not interested in quitting. Similarly, a reduction strategy may reduce ST exposure and increase ST abstinence rates among ST users not interested in quitting. METHODS: We conducted a pilot study to obtain preliminary data on the use of 12 weeks of varenicline as a tobacco reduction strategy among ST users not interested in quitting. RESULTS: We enrolled 20 male ST users with a mean age of 42.8 ± 11.7 years who used an average of 3.9 ± 1.7 cans/pouches per week for 18.6 ± 8.6 years. At end of treatment (12 weeks), 60% (12/20) of subjects reduced their ST use by ≥ 50% and 15% (3/20) were biochemically confirmed abstinent from tobacco. At end of study (6 months), 50% (10/20) reduced by ≥ 50% of baseline use and 10% (2/20) were biochemically confirmed abstinent from tobacco. Varenicline reduced ST satisfaction, reward, and craving. Among subjects able to reduce ST, all subjects reported that reduction increased motivation and confidence in being able to maintain reduction and quit. The most common side effects were sleep disturbance (25%) and nausea (15%). DISCUSSION: Varenicline may be effective in reducing ST use and achieving ST abstinence among ST users with no plans to quit but who are interested in reducing their ST use.

Trial design: blood pressure control and weight gain prevention in prehypertensive and hypertensive smokers: the treatment and prevention study.

BACKGROUND: Cigarette smokers with elevated blood pressure (BP) are at substantially higher risk for cardiovascular events compared to normotensive smokers. Although smoking cessation should be a primary treatment goal for these patients, increases in body weight accompanying smoking abstinence may further increase BP. Intervention strategies that facilitate smoking cessation and modify adverse changes in body weight and BP are needed. METHODS: We describe an ongoing multi-site, two-phase, five-year randomized clinical trial. Participants are cigarette smokers with Prehypertension or Stage I Hypertension. In the first phase, participants receive a smoking cessation intervention combining behavioral counseling and nicotine replacement in an open-label fashion. In the second phase, participants who successfully quit smoking are randomly assigned to one of three lifestyle interventions: 1) weight gain prevention, 2) blood pressure control, or 3) usual lifestyle. Participants are followed for one year to assess changes in blood pressure, body weight, dietary intake, and physical activity. CONCLUSIONS: Results from the proposed study will provide important insights into the efficacy of various approaches to lifestyle modification in smokers at increased risk for cardiovascular events.