Effectiveness of text message reminders on paediatric appointment adherence: a systematic review and meta-analysis.

Attending health appointments is important for the paediatric population, as it allows for earlier detection of health issues and subsequent necessary treatments. It also ensures timely immunisations while also allowing patients or their parents to raise health concerns. Hence, it is crucial to take steps to ensure that such medical appointments are attended. To evaluate the effectiveness of text message reminders (TMRs) in improving paediatric patients' adherence to their appointments. A systematic review and meta-analysis were conducted. The search spanned across eight online databases from their inception dates to January 2024. The random-effects model was utilised to conduct the meta-analysis, where risk ratio was used as the effect measure. Subgroup analyses were conducted for age, number of TMRs sent, and type of appointments attended. In total, 13 studies were included. Compared to standard care (involving non-text message reminders or no reminders), TMRs were significantly more effective in improving appointment attendance among the paediatric population. Significant subgroup differences were found in the type of appointments attended, where TMRs were more effective for medical appointments compared to vaccination appointments. No differences in adherence to appointments were found across age groups or the number of TMRs sent.   Conclusion: Sending TMRs can be a potentially cost-effective way to improve the attendance rate of paediatric medical appointments, given the ease of implementation and the extensive mobile phone usage globally. Future studies should compare TMRs to other modes of automated reminders such as telephone messages or emails, to identify the most optimal method of delivery.   Trial registration: PROSPERO (CRD42023464893).

Non-adherence to appointment follow-up and its associated factors among hypertensive patients in follow-up clinics in South Gondar hospitals.

Hypertension is a persistent systemic Blood Pressure reading of 140/90 mm Hg or greater which is a preventable cause of cardiovascular disease morbidity and mortality. To assess non-adherence to appointment follow-up and its associated factors among Hypertensive patients in the follow-up clinics in South Gondar Hospitals 2023. Institutional-based cross-sectional study design was employed in hospitals in South Gondar from January to February to assess missed appointment follow-up and its associated factors among Hypertensive patients in follow-up clinics. There is one comprehensive specialized hospital and 9 primary hospitals in this zone. Using simple random methods four hospitals were selected by lottery method. The sample was calculated by using the single population proportion formula. The collected data was entered into Epi data version 3.1 and exported to Statistical Package for Social Sciences version 26 for analysis. Bivariate and multivariable logistic regression analysis was performed to determine the association factors. A total of 401 hypertensive patients on hypertensive follow-up were involved with a response rate of 95.02%. Age ranged from 25 to 86 years with a median age of 58.47 years. Of the total of participants, 211 (52.6.) were rural residents. Among the total hypertensive patients in the hypertensive follow-up clinic, 39.2% were non-adherent for their appointment follow-up. Living far from follow-up health facility (AOR: 2.53; 95% CI 1.349-4.743), absence of perceived symptoms (AOR: 4.98; 95% CI 2.888-8.590), patient complaints Pill burdens (AOR: 3.50; 95% CI 2.108-5.825), and poor Awareness about complication of hypertension (AOR: 2.62; 95% CI 1.471-4.673) were significantly associated with missing of their appointment follow-up for the most hypertensive patients. The prevalence of non-adherence to medical follow-up in hypertension is high as compared to different national health policy recommendations. Distance from the health facility, absence of perceived symptoms, Pill burdens, and lack of knowledge about complications of hypertension were significantly associated with Missed appointment follow-up in Hypertensive patient.

Implementation of Virtual Yoga Shared Medical Appointment (VYSMA) Pilot at an Academic Medical Center Within a Mixed-Diagnosis Oncology Population.

Yoga is highly sought after by people seeking oncology care, endorsed by clinical practice guidelines, and supported by leading cancer organizations, yet barriers related to access, time, cost, and availability of quality providers remain. Shared medical appointments (SMA), a group healthcare model where patients with similar medical conditions participate in a collective appointment with healthcare providers, are associated with increased access to quality care, patient satisfaction, and clinician satisfaction. We piloted a unique insurance-covered virtual yoga SMA series to assess feasibility and acceptability in a mixed-diagnosis population. In this prospective cohort pilot, a trauma-informed Hanna Somatic Yoga instructor and an integrative medicine physician co-led yoga SMAs via live web-based conferencing. SMA content included conscious self-regulation through mind-body practices including breathing, movement, visualization, meditation, chanting, and guided relaxation. Qualitative and quantitative data were gathered to assess satisfaction with the 88 sessions offered over 33 months. Sixty-nine participants with diverse demographics attended a total of 500 visits. Class attendance ranged from 2-11 participants (mean 6 participants). Participants attended a mean of 7 sessions (range 1-63 sessions), with 63% attending > 1 session. Participants' diagnoses/symptoms included cancer (77%), anxiety/depression (38%), and pain (38%). Preseries, participants reported pain, weakness, neuropathy, lymphedema, insomnia, and fatigue. Postseries survey results suggested improvements in anxiety/fear, pain, fatigue, poor sleep, neuropathy, brain fog, isolation, weakness, inflexibility, and poor balance. Postseries, participants also reported incorporating mindfulness, breathing techniques, somatic skills, weight training, and yoga into their daily routines, with 91% reporting that their goals had been met. Participants appreciated remote delivery, learning new skills, community, and the instructors. This virtual yoga SMA series in a diverse population with mixed diagnoses was feasible, acceptable to participants, and showed promising positive impact. A larger randomized controlled trial with longer follow-up is recommended.

Factors Associated With Patient Failure To Attend Dental Appointments: A Retrospective Analysis.

Nonattendance at scheduled dental appointments has a significant impact on healthcare systems worldwide. This study examines the factors associated with missed appointments at the Dental Center in the Department of Oral and Dental Health in Riyadh, Saudi Arabia, through a retrospective secondary data analysis. Existing medical records from January 1, 2024, to May 1, 2024 were analyzed to identify patterns or factors contributing to nonattendance. Data were collected using a standardized sheet and analyzed with statistical methods, including correlation analysis, ANOVA, and chi-square tests, to determine significant associations and factors affecting nonattendance. The results indicated that the majority of nonattendees were single (56.2%), with a higher proportion of females (60.7%) compared to males (39.3%). Only 3.8% of those who missed their appointments were over 55 years old. Tuesdays had the highest incidence of nonattendance (331 cases). No significant association was found between age groups and the time (F = 0.224, p = 0.925) or date (F = 0.840, p = 0.500) of appointments. Patients were less likely to attend morning appointments compared to evening ones. The high rate of missed appointments reduces the effectiveness and efficiency of the Dental Center's resources. The identified patterns and factors can guide managers and policymakers in developing strategies to reduce missed appointments and improve overall appointment adherence.

Exploring the Feasibility and Acceptability of Telehealth Qi Gong Shared Medical Appointments: A Novel Approach to Expand Access.

Background: Research on Qi Gong (QG) supports promising health benefits. Both interest and use of QG in U.S. adults has increased over the past decade. Shared Medical Appointments (SMAs) are a novel, cost-effective, and time efficient health care delivery approach associated with patient and clinician satisfaction. Objectives: A telehealth delivered QG SMA was pilot tested among a diverse demographic population within an integrative medicine practice at an academic medical center to assess feasibility and acceptability. Methods: This was a feasibility/acceptability pilot study conducted at a large New York City academic medical center's Integrative Health and Wellness center from January to July 2023. A QG instructor-acupuncturist and an integrative medicine physician-acupuncturist co-led 3 separate series (5 Element QG, Eight-Section Brocade, and Joint-Mobilizing/Sinew Strengthening exercises) of weekly 30-45-minute sessions of QG SMA on a weekday afternoon via telemedicine. The first session included an overview of QG and Traditional Chinese Medicine (TCM) research while follow-up sessions included a check-in, didactic demonstration followed by QG practice, and a debrief to answer questions. Video links were provided for home practice. Surveys assessing satisfaction were sent pre/post series. Results: 18 sessions of QG SMA were offered over a 6-month period. A total of 40 unique participants from diverse demographics (gender, race/ethnicity, primary residence) attended, for a total of 197 virtual visits. A total of 20 participants enrolled in Series 1 (8 weeks), 23 enrolled in Series 2 (7 weeks), and 16 enrolled in Series 3 (3cweeks). For each session, group attendance ranged from 8-16 with an average of 11 participants. Attendance was high with participants attending an average of 72% of the sessions. Participants attended 88% of the first 8-week series, 54% of the second 7-week series, and 60% of the third series. Participant interest persisted over time with 35% of the 40 participants attending more than 1 series, and 12.5% attending all 3 series. Participants' diagnoses and health symptoms included pain (62.5%), cancer (45%) anxiety/depression (40%), cardiovascular disease (CVD) or metabolic conditions (32.5%), gastrointestinal (GI) symptoms/diagnoses (27.5%), stress (22.5%), osteopenia/osteoporosis (17.5%), and insomnia (17.5%). Pre-series [n = 27] participants endorsed symptoms including sleep disturbances, fatigue, pain, stress, weakness, GI symptoms, psychological symptoms, hot flashes, and brain fog. Post-program survey results [n = 11] suggested QG program addressed common symptoms including fatigue, insomnia, anxiety, stress, pain, weakness, and gastrointestinal symptoms. Participants reported incorporating QG, breathing techniques, and meditation into their daily routine. All participants reported their goals were met and that they would recommend the program to others. Regarding delivery preferences, 73% preferred telehealth, 27% hybrid, and none preferred in-person. Participants appreciated the format, new skills, community, and instructors. Conclusion: While the Virtual QG SMA series provided to diverse demographic population with mixed diagnoses is feasible, acceptable, and shows promising positive impact in this pilot, caution in interpreting the data is advised due to the low response rate of the post-program survey. Robust studies with longer follow-ups are recommended.

Prevalence of financial hardship and health-related social needs among patients with missed radiology appointments.

PURPOSE: We aimed to evaluate the prevalence of financial hardship and Health-Related Social Needs (HRSN) among patients who missed their radiology appointment. METHODS: English-speaking adult patients, with a missed outpatient imaging appointment at any of a tertiary care imaging centers between 11/2022 and 05/2023 were eligible. We measured self-reported general financial worry using Comprehensive Score for Financial Toxicity (COST), imaging hardship (worry that the current imaging is a financial hardship to patient and their family), material hardship (e.g., medical debt), cost-related care nonadherence, and HRSNs including housing instability, food insecurity, transportation problems, and utility help needs. RESULTS: 282 patients were included (mean age 54.7 ± 15.0 years; 70.7 % female). Majority were non-Hispanic White (52.4 %), followed by Asian (23.0 %) and Hispanic (16.0 %) racial/ethnic background. Most missed appointments were patient-initiated (74.8 %); 13.5 % due to cost or insurance coverage and 6.4 % due to transportation and parking. Mean COST score was 26.8 with 44.4 % and 28.8 % reporting their illness and imaging as a source of financial hardship. 18.3 % and 35.2 % endorsed cost-related care nonadherence and material hardship. 32.7 % had at least one HRSNs with food insecurity the most common (25.4 %). Only 12.5 % were previously screened for financial hardship or HRSNs. Having comorbidity and living in more disadvantaged neighborhoods was associated with higher report of financial hardship and HRSNs. CONCLUSION: Financial hardship and HRSNs are common among those who miss radiology appointments. There needs to be more rigorous screening for financial hardship and HRSNs at every health encounter and interventions should be implemented to address these.

Wait times for scheduling appointments with hospital affiliated dermatologists in New York City.

Patients' experience accessing dermatologic care is understudied. The purpose of this cross-sectional study was to examine current wait times for new patients to receive dermatological care in NYC. Websites at 58 accredited private and public hospitals in the five boroughs of NYC were reviewed to identify dermatology practices. Office telephone numbers listed on each website were called to collect information pertaining to whether the physician was accepting new patients, type of insurance accepted (public, private, both, or none), and the number of days until a new patient could be seen for an appointment. Data pertaining to the time kept on hold and availability of web-based booking were also collected. Mean waiting time for an appointment was 50 days [standard deviation, SD 66] - nearly 2 months, but the distribution was considerably skewed. The median waiting time was 19.5 days [Interquartile range, IQR 4-60]. The time kept on hold to make the appointment was negligible at about 1 min (63 s, SD = 77) but could take up to ~ 7 min. Two-thirds of dermatologists accepted private, Medicare, and Medicaid insurance (n = 228, 66%); a small number accepted only private insurance (n = 12, 4%) or no insurance at all (n = 16, 5%). The median waiting time for an appointment for the 228 providers that accepted Medicaid was 30.5 days (IQR = 5.0-73.25) while for providers who did not accept Medicaid (n = 116) the median wait time for an appointment was 13.0 days (IQR = 3.0-38.0). Just over half (56%) of the dermatologists allowed for appointments to be booked on their website (n = 193). This research highlights the necessity of incorporating new strategies into routine dermatology appointments in order to increase treatment availability and decrease healthcare inequality.

Adopting academic rank in a rural community practice affiliated with an academic medical center.

BACKGROUND: United States rural community-based practices are increasingly participating in undergraduate and graduate medical education to train the workforce of the future, and are required or encouraged to provide academic appointments to physicians who have typically not held an academic appointment. Mechanisms to identify faculty and award academic appointments across an entire health system have not been reported. METHODS: Our rural community regional practice identified academic appointments as important for participating in medical education. Over a three-year period, our regional leadership organized a formal education committee that led a variety of administrative changes to promote the adoption of academic rank. Data on attainment of academic appointments was obtained from our Academic Appointment and Promotion Committee, and cross referenced with data from our regional human resources department using self-reported demographic data. RESULTS: We describe a successful adoption strategy for awarding academic rank in a rural regional practice in which the percentage of physician staff with academic rank increased from 41.1 to 92.8% over a 3-year period. CONCLUSIONS: Our experience shows that process changes can rapidly increase and then sustain academic appointments for physicians over time. More rural health systems may want to consider the use of academic rank to support educational programs while enhancing physician satisfaction, recruitment and retention.

Patient Opportunities to Self-Schedule in a Large Multisite, Multispecialty Medical Practice: Program Description and Uptake of 7 Unique Processes for Patients to Successfully Self-Schedule (and Reschedule) Their Medical Appointments.

Introduction: Patient self-scheduling of medical appointments is becoming more common in many medical institutions. However, the complexity of scheduling multiple specialties, following scheduling guidelines, and managing appointment access requires a variety of processes for a diverse inventory of self-schedulable appointment types. Methods: From 7 unique patient self-scheduling methods, we captured counts of successfully self-scheduled and completed appointments. A process map was created to show the paths of 5 different primary self-scheduling processes (new appointment self-scheduling) and 2 secondary self-scheduling processes (existing appointment self-rescheduling). Results: There were 7 unique processes that led to 733,651 successfully self-scheduled completed visits from January 1 to December 31, 2023 at a multisite, multispecialty clinic. The self-scheduling processes consisted of the following: (1) Ticket offer (appointment "ticket" offers for specific visits generated by a provider order or system rules), the software "ticket" sent to the patient permits "admission" to self-schedule calendar templates (341,591 uses, 46.6%); (2) direct self-scheduled visit for prequalified visit types (203,593 uses, 27.6%); (3) self-reschedule option (patient option to reschedule existing appointment, 79,706 uses, 10.9%); (4) new patient self-scheduled visit via clinic website (does not require portal access, 54,367 uses, 7.4%). (5) automated waitlist self-rescheduled visit (38,649 uses, 5.3%); (6) automated waitlist self-scheduled visit of previously unscheduled visit (10,939 uses, 1.5%); and (7) self-triage self-scheduled visit (4806 uses, 0.7%). Conclusion: The processes for self-scheduling are expanding. Our multispecialty clinic has implemented 7 different processes to help patients successfully self-schedule medical appointments. Some of the processes occur before initial scheduling (such as self-triage), and some are implemented after successful scheduling has already occurred (self-rescheduling option and self-rescheduling aided by an automated waitlist). Continued research is needed to look for measures of success beyond the ability to complete a self-scheduled visit, including the accuracy of the booking (right provider, location, and length of visit).

[Prioritized appointment allocation in new patients, what is really decisive? : Comparative analysis of manual appointment allocation with automated and AI-assisted approaches]. / Priorisierte Terminvergabe bei Neuvorstellungen: Was ist wirklich entscheidend? : Vergleichende Analyse manueller Terminallokation mit automatisierten und KI-gestützten Ansätzen.

BACKGROUND: The timely allocation of appointments for new patients is a daily challenge in rheumatological practice, which can be supported by digital solutions. The question is to find the simplest and most effective possible method for prioritization when allocating appointments. METHODS: Using a registration form for new patients, standardized symptoms and laboratory results were collated. After reviewing this information by a medical specialist the allocation of appointments was carried out in three categories: a) < 6 weeks, b) 6 weeks up to 3 months and c) > 3 months. The waiting time between the time of registration and the presentation appointment was calculated and compared between patients with and without a diagnosis of an inflammatory rheumatic disease (IRD). In addition a decision tree (DT), a method taken from the field of supervised learning within artificial intelligence (AI), was established and the resulting classification was compared with respect to the accuracy and calculated saving in waiting time. RESULTS: In this study 800 appointments between 2020 and 2023 (including 555 women, 69.4%, median age 53 years, interquartile range, IQR 39-63 years) were analyzed. An IRD could be confirmed in 409 (51.1%) cases with a waiting time of 58 vs. 93 days for non-IRD cases (-38%, p < 0.01). An AI-based stratification resulted in an accuracy of 67% for IRD and a predicted saving of 19% waiting time. The accuracy increased up to 78% with a time saving for IRD cases of up to 31%, when all basic laboratory results were known. Simplified algorithms, e.g., stratification by the use of laboratory findings alone, resulted in a lower accuracy and time savings. CONCLUSION: Manual allocation of appointments by a medical specialist is effective and significantly reduces the waiting times for patients with IRD. An automated categorization can lead to a reduction in waiting times for appointments when taking complete laboratory results and a lower sensitivity into consideration.

Implementation of a patient reminder system in Haiti in a socio-political crisis context: evaluation of outcomes.

BACKGROUND: In Haiti, patient's adherence to treatment and compliance with medical appointments are very challenging due to different local factors. We aimed to assess the effectiveness of a reminder system implemented in health facilities in Haiti in a context of socio-political crisis. METHODS: We used appointment data from patients aged 15 years and older between January 2021 and November 2023 from four healthcare centers in the Port-au-Prince metropolitan area. We performed descriptive analysis, crossing covariates with appointment attendance. We performed Pearson's Chi-squared test, and multivariate regression analysis using a mixed-effect logistic regression model in order to explore the association between sending reminders and appointment attendance, with and without adjustment for other patient-level covariates. RESULTS: A total of 14 108 appointments were registered on the reminder systems, with 2 479 (17.6%) attendances. Among those to whom reminders were sent, the number of attendances was 167 (17.4%) for email recipients only, 199 (36.7%) for SMS recipients only, and 19 (42.2%) for both SMS and email recipients - versus 2 094 (16.7%) for non-reminders. After adjusting on all other covariates, we found that patients to whom a reminder was sent via email (aOR: 1.45; CI: 1.08, 1.94), SMS (aOR: 2.95; CI: 2.41, 3.60), and both SMS and email (aOR: 2.86, CI: 1.37, 5.96) were more likely to show up on their appointment day compared to those who did not receive any reminder. Other socio-demographic factors such as being 50 years and older (aOR: 1.31; CI: 1.10, 1.56) compared to under 30 years, living as couple (aOR: 1.23; CI: 1.10, 1.37), and not having children (aOR: 1.21; CI: 1.07, 1.37) were significantly associated with appointment attendance. CONCLUSIONS: Our study suggests that patient reminder systems may be used to reduce non-attendance in Haiti, even in a context of socio-political crisis.

Outcome evaluation of technical strategies on reduction of patient waiting time in the outpatient department at Kilimanjaro Christian Medical Centre-Northern Tanzania.

BACKGROUND: The Tanzania healthcare system is beset by prolonged waiting time in its hospitals particularly in the outpatient departments (OPD). Previous studies conducted at Kilimanjaro Christian Medical Centre (KCMC) revealed that patients typically waited an average of six hours before receiving the services at the OPD making KCMC have the longest waiting time of all the Zonal and National Referral Hospitals. KCMC implemented various interventions from 2016 to 2021 to reduce the waiting time. This study evaluates the outcome of the interventions on waiting time at the OPD. METHODS: This is an analytical cross-sectional mixed method using an explanatory sequential design. The study enrolled 412 patients who completed a structured questionnaire and in-depth interviews (IDI) were conducted among 24 participants (i.e., 12 healthcare providers and 12 patients) from 3rd to 14th July, 2023. Also, a documentary review was conducted to review benchmarks with regards to waiting time. Quantitative data analysis included descriptive statistics, bivariable and multivariable. All statistical tests were conducted at 5% significance level. Thematic analysis was used to analyse qualitative data. RESULTS: The findings suggest that post-intervention of technical strategies, the overall median OPD waiting time significantly decreased to 3 h 30 min IQR (2.51-4.08), marking a 45% reduction from the previous six-hour wait. Substantial improvements were observed in the waiting time for registration (9 min), payment (10 min), triage (14 min for insured patients), and pharmacy (4 min). Among the implemented strategies, electronic medical records emerged as a significant predictor to reduced waiting time (AOR = 2.08, 95% CI, 1.10-3.94, p-value = 0.025). IDI findings suggested a positive shift in patients' perceptions of OPD waiting time. Problems identified that still need addressing include, ineffective implementation of block appointment and extension of clinic days was linked to issues of ownership, organizational culture, insufficient training, and ineffective follow-up. The shared use of central modern diagnostic equipment between inpatient and outpatient services at the radiology department resulted in delays. CONCLUSION: The established technical strategies have been effective in reducing waiting time, although further action is needed to attain the global standard of 30 min to 2 h OPD waiting time.

Dynamic Price Application to Prevent Financial Losses to Hospitals Based on Machine Learning Algorithms.

Hospitals that are considered non-profit take into consideration not to make any losses other than seeking profit. A model that ensures that hospital price policies are variable due to hospital revenues depending on patients with appointments is presented in this study. A dynamic pricing approach is presented to prevent patients who have an appointment but do not show up to the hospital from causing financial loss to the hospital. The research leverages three distinct machine learning (ML) algorithms, namely Random Forest (RF), Gradient Boosting (GB), and AdaBoost (AB), to analyze the appointment status of 1073 patients across nine different departments in a hospital. A mathematical formula has been developed to apply the penalty fee to evaluate the reappointment situations of the same patients in the first 100 days and the gaps in the appointment system, considering the estimated patient appointment statuses. Average penalty cost rates were calculated based on the ML algorithms used to determine the penalty costs patients will face if they do not show up, such as 22.87% for RF, 19.47% for GB, and 14.28% for AB. As a result, this study provides essential criteria that can help hospital management better understand the potential financial impact of patients missing appointments and can be considered when choosing between these algorithms.

Investigating Patient Use and Experience of Online Appointment Booking in Primary Care: Mixed Methods Study.

BACKGROUND: Online appointment booking is a commonly used tool in several industries. There is limited evidence about the benefits and challenges of using online appointment booking in health care settings. Potential benefits include convenience and the ability to track appointments, although some groups of patients may find it harder to engage with online appointment booking. We sought to understand how patients in England used and experienced online appointment booking. OBJECTIVE: This study aims to describe and compare the characteristics of patients in relation to their use of online appointment booking in general practice and investigate patients' views regarding online appointment booking arrangements. METHODS: This was a mixed methods study set in English general practice comprising a retrospective analysis of the General Practice Patient Survey (GPPS) and semistructured interviews with patients. Data used in the retrospective analysis comprised responses to the 2018 and 2019 GPPS analyzed using mixed-effects logistic regression. Semistructured interviews with purposively sampled patients from 11 general practices in England explored experiences of and views on online appointment booking. Framework analysis was used to allow for comparison with the findings of the retrospective analysis. RESULTS: The retrospective analysis included 1,327,693 GPPS responders (2018-2019 combined). We conducted 43 interviews with patients with a variety of experiences and awareness of online appointment booking; of these 43 patients, 6 (14%) were from ethnic minority groups. In the retrospective analysis, more patients were aware that online appointment booking was available (581,224/1,288,341, 45.11%) than had experience using it (203,184/1,301,694, 15.61%). There were deprivation gradients for awareness and use and a substantial decline in both awareness and use in patients aged >75 years. For interview participants, age and life stage were factors influencing experiences and perceptions, working patients valued convenience, and older patients preferred to use the telephone. Patients with long-term conditions were more aware of (odds ratio [OR] 1.43, 95% CI 1.41-1.44) and more likely to use (OR 1.65, 95% CI 1.63-1.67) online appointment booking. Interview participants with long-term conditions described online appointment booking as useful for routine nonurgent appointments. Patients in deprived areas were clustered in practices with low awareness and use of online appointment booking among GPPS respondents (OR for use 0.65, 95% CI 0.64-0.67). Other key findings included the influence of the availability of appointments online and differences in the registration process for accessing online booking. CONCLUSIONS: Whether and how patients engage with online appointment booking is influenced by the practice with which they are registered, whether they live with long-term conditions, and their deprivation status. These factors should be considered in designing and implementing online appointment booking and have implications for patient engagement with the wider range of online services offered in general practice.

Appointment Blitz: Optimizing Patient-Therapist Rehab Scheduling.

Taiwan has a well-structured healthcare insurance system that offers accessible medical resources to the public through nominal health insurance fees. Consequently, individuals in need of care willingly pay nominal charges for medical services, including rehabilitation treatment. This study delves into the rehabilitation department of a medical center in southern Taiwan. Despite offering comprehensive traditional rehabilitation services covering neurological, musculoskeletal, pediatric, cardiopulmonary, communication, and swallow disorders, the demand for appointments significantly surpasses the number of available therapists. Therefore, this paper proposes an efficiently method to optimize patient-therapist appointment. With a Complex Conditional Logic that we have designed in this paper, we aim to simplify the scheduling processing for patient seeking appointment either online or via phone calls. More than 50,000 cases have been treated since the system's launch within a year, facilitates hospital resource allocation and enhancing patient medical experiences.

Implementation of a virtual, shared medical appointment program that focuses on food as medicine principles in a population with obesity: the SLIM program.

Background: Multimodal lifestyle interventions, employing food as medicine, stand as the recommended first-line treatment for obesity. The Shared Medical Appointment (SMA) model, where a physician conducts educational sessions with a group of patients sharing a common diagnosis, offers an avenue for delivery of comprehensive obesity care within clinical settings. SMAs, however, are not without implementation challenges. We aim to detail our experience with three implementation models in launching a virtual integrative health SMA for weight management. Methods: Eligible patients included individuals 18 years of age or older, having a body mass index (BMI) of 30 kg/m2 or 27 kg/m2 or greater with at least one weight related comorbidity. The Practical, Robust Implementation and Sustainability Model (PRISM), Plan, Do, Study, Act (PDSA), and the Framework for Reporting Adaptations and Modifications-Enhanced (FRAME) models were applied to guide the implementation of the Supervised Lifestyle Integrative Medicine (SLIM) program, a virtually delivered, lifestyle medicine focused SMA program, in a weight management clinic within a major health system. We describe how these models, along with attendance for the initial cohorts, were used for decision-making in the process of optimizing the program. Results: 172 patients completed the SLIM program over two years. Attendance was lowest for sessions held at 8:00 AM and 4:00 PM compared to sessions at 10:00 AM, 1:00 PM, and 3:00 PM, leading to only offering midday sessions (p = 0.032). Attendance data along with feedback from patients, facilitators, and administrative partners led to changes in the curriculum, session number and frequency, session reminder format, and intake visit number. Conclusion: The use of implementation and quality improvement models provided crucial insight for deployment and optimization of a virtual, lifestyle medicine focused SMA program for weight management within a large healthcare system.

Personal, health system, and geosocial disparities in appointment nonadherence at family medicine clinics in southcentral Pennsylvania, United States.

Background: To assess the relationship between patients' demographic, health system-related, and geosocial characteristics and the risk of missed appointments among patients in family medicine practice. Methods: The study was based on a retrospective cross-sectional design using electronic health records and neighborhood-level social determents of health metrics linked by geocoded patients' home address. The study population consisted of patients who had a primary care provider and at least one appointment at 14 family medicine clinics in rural and suburban areas in January-December 2022. Negative binomial regression was utilized to examine the impact of personal, health system, and geosocial effects on the risk of no-shows and same-day cancellations. Results: A total of 258,614 appointments were made from 75,182 patients during the study period, including 7.8% no-show appointments from 20,256 patients. The analysis revealed that individuals in the ethnic minority groups were 1.24-1.65 times more likely to miss their appointments than their White counterpart. Females and English speakers had 14% lower risk for no-show. A significant increase (32%-64%) in the odds of no-shows was found among individuals on Medicaid and uninsured. Persons with prior history of no-shows or same day cancellations were 6%-27% more likely to miss their appointments. The no-show risk was also higher among people living in areas experiencing socioeconomic disadvantage. Conclusion: The risk of missed appointments is affected by personal, health system, and geosocial contexts. Future efforts aiming to reduce no-shows could develop personalized interventions targeting the at-risk populations identified in the analysis.

Factors Associated with Nonreturn after Loss to Follow-Up from Glaucoma Care: An IRIS® Registry Retrospective Analysis.

PURPOSE: Loss to follow-up (LTFU) in primary open-angle glaucoma (POAG) can lead to undertreatment, disease progression, and irreversible vision loss. Patients who become LTFU either eventually re-establish glaucoma care after a lapse or never return to the clinic. The purpose of this study is to examine a large population of patients with POAG who became LTFU to determine the proportion that return to care and to identify demographic and clinical factors associated with nonreturn after LTFU. DESIGN: Retrospective longitudinal cohort study. PARTICIPANTS: Patients with a diagnosis of POAG with a clinical encounter in 2014 in the IRIS® Registry (Intelligent Research in Sight). METHODS: We examined follow-up patterns for 553 663 patients with POAG who had an encounter in the IRIS Registry in 2014 by following their documented clinic visits through 2019. LTFU was defined as exceeding 1 calendar year without an encounter. Within the LTFU group, patients were classified as returning after a lapse in care (return after LTFU) or not (nonreturn after LTFU). MAIN OUTCOME MEASURES: Proportion of patients with nonreturn after LTFU and baseline demographic and clinical characteristics associated with nonreturn among LTFU patients with POAG. RESULTS: Among 553 663 patients with POAG, 277 019 (50%) had at least 1 episode of LTFU over the 6-year study period. Within the LTFU group, 33% (92 471) returned to care and 67% (184 548) did not return to care. Compared to those who returned to care, LTFU patients with nonreturn were more likely to be older (age >80 years; relative risk [RR] = 1.48; 95% confidence interval [CI]: 1.47-1.50), to have unknown/missing insurance (RR = 1.31; 95% CI: 1.30-1.33), and to have severe-stage POAG (RR = 1.13; 95% CI: 1.11-1.15). Greater POAG severity and visual impairment were associated with nonreturn with a dose-dependent relationship in the adjusted model that accounted for demographic characteristics. Among those with return after LTFU, almost all returned within 2 years of last appointment (82 201; 89%) rather than 2 or more years later. CONCLUSIONS: Half of patients with POAG in the IRIS Registry had at least 1 period of LTFU, and two thirds of LTFU patients with POAG did not return to care. More effort is warranted to re-engage the vulnerable patients with POAG who become LTFU. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

BRIDGE to liver health: implementation of a group telehealth psychoeducational program through shared medical appointments for MASLD management.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a significantly costly and increasingly prevalent disease, with treatment focused on lifestyle intervention. Integrating education and behavioral health into clinical care offers opportunities to engage and empower patients to prevent progression of liver disease. We describe the design and implementation of Behavioral Resources and Intervention through Digital Group Education (BRIDGE), a 6-session group telehealth program led by advanced practice providers (APPs) in 90-min shared medical appointments (SMAs) with small groups of MASLD patients in an academic outpatient hepatology clinic. The program contains multi-component group interventions, with didactic education and behavioral coaching, while leveraging peer-based learning and support. METHODS: A mixed-methods exploratory pilot study was conducted. Feasibility and acceptability of the clinical intervention were assessed by tracking recruitment, attendance, and retention of BRIDGE participants, patient interviews, and debriefing of clinician and staff views of the clinical program. Implementation metrics included program development time, workflow and scheduling logistics, and billing compliance for sustainability. Finally, patient parameters including changes in liver enzymes, FIB-4, weight, and BMI from pre- to post-BRIDGE were retrospectively analyzed. RESULTS: We included 57 participants (median age 57, interquartile range (IQR) 50 - 65 years), 38 (67%) female, 38 (67%) white, and 40% had public insurance. Thirty-three (58%) participants completed all six sessions, while 43 (75%) attended at least five sessions. Patients who completed all sessions were older (median age 61 vs 53.5; p = 0.01). Gender, race/ethnicity, and insurance type were not significantly associated with missed sessions, and patients had similar rates of completion regardless of weight, BMI, or stage of liver disease. Barriers to completion included personal illness, family reasons, work commitments, or insurance issues. Prior to BRIDGE, median BMI was 31.9 (SD 29 - 36), with a median weight loss of 2 pounds (IQR -2 - 6) after BRIDGE. CONCLUSION: The BRIDGE telehealth SMA program was feasible, well-attended, and positively reviewed. This pilot study informs future iterations of program development and evaluation of outcome measures.