No-Show Rates in a Urogynecology Clinic.

IMPORTANCE: No-show appointments, or scheduled appointments that patients do not attend without giving notice of cancellation, are a prevalent problem in the outpatient setting. OBJECTIVE: The objective of this study was to compare the proportion of patients by decades of life who "no-show" to their urogynecology appointments. STUDY DESIGN: This retrospective cohort included women 20 years and older who did not show to their urogynecologic clinical encounters at an academic practice between January 1, 2022, and December 31, 2022. Demographics and visit history were recorded. The primary outcome was the proportion of patients by decade of age who were a "no-show" to their appointments. All decades were compared with women in their 70s, the decade with the most patients seen. Secondary outcomes included descriptive data of patients. Descriptive statistics and χ2 analyses were used. RESULTS: The cohort of 450 no-show encounters (composed of 391 patients), out of 6729 encounters, demonstrated an overall no-show rate of 6.7%. Baseline demographics of "no-show" patients were 67.3% White and 27.4% Black. The odds of women in their 20s-50s who no-show was 2-3 times higher than women in their 70s (P < 0.01). The highest no-show rates occurred in 20s (12.6%) and 40s (11.8%). Forty-six patients missed multiple appointments. The odds of a Black patient having multiple no-shows was 3.15 times higher than the odds of a White patient. CONCLUSIONS: No-show rates are low in this urogynecology practice. Younger women are more likely to no-show. This knowledge can facilitate potential double bookings necessary for urgent appointments and to maximize resource utilization.

Effect of Standardized Reminder Calls on Trauma Patient No-Show Rate.

BACKGROUND: Most patients who sustain a traumatic injury require outpatient follow-up. A common barrier to outpatient postadmission care is patient failure to follow-up. One of the most significant factors resulting in failure to follow-up is age more than 35 years. Recent work has shown that follow-up telephone calls reduce readmission rates. Our aim was to decrease no-show appointments by 10% in 12 months. STUDY DESIGN: The electronic medical records at our level I and II trauma centers were queried for all outpatient appointments for trauma between July 1, 2020, and June 9, 2021, and whether the patient attended their follow-up appointment. Patients with visits scheduled after August 1, 2021, received 24- and 48-hour previsit reminder calls. Patients with visits scheduled between July 1, 2020, and August 1, 2021, did not receive previsit calls. Both groups were compared using multivariable direct logistic regression models. RESULTS: A total of 1,822 follow-up opportunities were included in the study. During the pre-implementation phase, there was a no-show rate of 30.9% (329 of 1,064 visits). Postintervention, a 12.2% reduction in overall no-show rate occurred. A statistically significant 11.2% decrease (p < 0.001) was seen in elderly patients. Multivariate analysis showed standardized calls resulted in significantly decreased odds of failing to keep an appointment (adjusted odds ratio = 0.610, p < 0.001). CONCLUSIONS: Reminder calls led to a 12.2% reduction in no-show rate and were an independent predictor of a patient's likelihood of attending their appointment. Other predictors of attendance included insurance status and abdominal injury.

Policy-makers' conception of patient non-attendance fees in specialist healthcare: a qualitative document analysis.

OBJECTIVES: Patients missing their scheduled appointments in specialist healthcare without giving notice can undermine efficient care delivery. To reduce patient non-attendance and possibly compensate healthcare providers, policy-makers have noted the viability of implementing patient non-attendance fees. However, these fees may be controversial and generate public resistance. Identifying the concepts attributed to non-attendance fees is important to better understand the controversies surrounding the introduction and use of these fees. Patient non-attendance fees in specialist healthcare have been extensively debated in Norway and Denmark, two countries that are fairly similar regarding political culture, population size and healthcare system. However, although Norway has implemented a patient non-attendance fee scheme, Denmark has not. This study aimed to identify and compare how policy-makers in Norway and Denmark have conceptualised patient non-attendance fees over three decades. DESIGN: A qualitative document study with a multiple-case design. METHODS: A theory-driven qualitative analysis of policy documents (n=55) was performed. RESULTS: Although patient non-attendance fees were seen as a measure to reduce non-attendance rates in both countries, the specific conceptualisation of the fees differed. The fees were understood as a monetary disincentive in Norwegian policy documents. In the Danish documents, the fees were framed as an educative measure to foster a sense of social responsibility, as well as serving as a monetary disincentive. The data suggest, however, a recent change in the Danish debate emphasising fees as a disincentive. In both countries, fees were partly justified as a means of compensating providers for the loss of income. CONCLUSIONS: The results demonstrate how, as a regulative policy tool, patient non-attendance fees have been conceptualised and framed differently, even in apparently similar contexts. This suggests that a more nuanced and complex understanding of why such fees are debated is needed.

Factors Associated with No-Show Rates in a Pediatric Audiology Clinic.

OBJECTIVE: To evaluate factors associated with no-show rates in a pediatric audiology clinic. STUDY DESIGN: Retrospective review. SETTING: Tertiary referral center. PARTICIPANTS: All pediatric patients younger than 18 years whose parents/guardians scheduled an appointment at a tertiary Audiology Clinic between June 1, 2015, and July 1, 2017. MAIN OUTCOME MEASURES: Data included whether the patient came to their appointment, patient age, sex, race, insurance type, appointment type, location, season of appointment, and day of the week of the appointment. RESULTS: Of the 7,784 pediatric appointments scheduled with audiology, the overall no-show rate was 24.3% (n = 1893). Lower age was significantly associated with no-shows ( p = 0.0003). Black/African American children were more likely to no-show compared with White/Caucasians ( p = 0.0001). Compared with self-pay/military/other insurance, those with Medicaid were more likely to no-show ( p = 0.0001). The highest rate of no-shows occurred during summer (27%). On multivariate analysis, younger age, Black/African American race, and Medicaid insurance were associated with increased no-show rates. CONCLUSION: A variety of factors influence no-show rates in a pediatric audiology setting. No-shows can affect treatment quality and affect overall hearing outcomes. Further investigation is necessary to assess barriers to appointment adherence and to develop interventions to improve adherence and care.

To charge or not to charge: reducing patient no-show.

BACKGROUND: In order to reduce patient no-show, the Israeli government is promoting legislation that will allow Health Plans to require a co-payment from patients when reserving an appointment. It is hoped that this will create an incentive for patients to cancel in advance rather than simply not show up. The goal of this policy is to improve patient access to medical care and ensure that healthcare resources are utilized effectively. We explore this phenomenon to support evidence-based decision making on this issue, and to determine whether the proposed legislation is aligned with the findings of previous studies. MAIN BODY: No-show rates vary across countries and healthcare services, with several strategies in place to mitigate the phenomenon. There are three key stakeholders involved: (1) patients, (2) medical staff, and (3) insurers/managed care organizations, each of which is affected differently by no-shows and faces a different set of incentives. The decision whether to impose financial penalties for no-shows should take a number of considerations into account, such as the fine amount, service type, the establishment of an effective fine collection system, the patient's socioeconomic status, and the potential for exacerbating disparities in healthcare access. The limited research on the impact of fines on no-show rates has produced mixed results. Further investigation is necessary to understand the influence of fine amounts on no-show rates across various healthcare services. Additionally, it is important to evaluate the implications of this proposed legislation on patient behavior, access to healthcare, and potential disparities in access. CONCLUSION: It is anticipated that the proposed legislation will have minimal impact on attendance rates. To achieve meaningful change, efforts should focus on enhancing medical service availability and improving the ease with which appointments can be cancelled or alternatively substantial fines should be imposed. Further research is imperative for determining the most effective way to address the issue of patient no-show and to enhance healthcare system efficiency.

Intraday dynamic rescheduling under patient no-shows.

Patient no-shows are a major source of uncertainty for outpatient clinics. A common approach to hedge against the effect of no-shows is to overbook. The trade-off between patient's waiting costs and provider idling/overtime costs determines the optimal level of overbooking. Existing work on appointment scheduling assumes that appointment times cannot be updated once they have been assigned. However, advances in communication technology and the adoption of online (as opposed to in-person) appointments make it possible for appointments to be flexible. In this paper, we describe an intraday dynamic rescheduling model that adjusts upcoming appointments based on observed no-shows. We formulate the problem as a Markov Decision Process in order to compute the optimal pre-day schedule and the optimal policy to update the schedule for every scenario of no-shows. We also propose an alternative formulation based on the idea of 'atomic' actions that allows us to apply a shortest path algorithm to solve for the optimal policy more efficiently. Based on a numerical study using parameter estimates from existing literature, we find that intraday dynamic rescheduling can reduce expected cost by 15% compared to static scheduling.

Mapping out the arguments for and against patient non-attendance fees in healthcare: an analysis of public consultation documents.

BACKGROUND: Patients not attending their appointments without giving notice burden healthcare services. To reduce non-attendance rates, patient non-attendance fees have been introduced in various settings. Although some argue in narrow economic terms that behavioural change as a result of financial incentives is a voluntary transaction, charging patients for non-attendance remains controversial. This paper aims to investigate the controversies of implementing patient non-attendance fees. OBJECTIVE: The aim was to map out the arguments in the Norwegian public debate concerning the introduction and use of patient non-attendance fees at public outpatient clinics. METHODS: Public consultation documents (2009-2021) were thematically analysed (n=84). We used a preconceived conceptual framework based on the works of Grant to guide the analysis. RESULTS: A broad range of arguments for and against patient non-attendance fees were identified, here referring to the acceptability of the fees' purpose, the voluntariness of the responses, the effects on the individual character and institutional norms and the perceived fairness and comparative effectiveness of patient non-attendance fees. Whereas the aim of motivating patients to keep their appointments to avoid poor utilisation of resources and increased waiting times was widely supported, principled and practical arguments against patient non-attendance fees were raised. CONCLUSION: A narrow economic understanding of incentives cannot capture the breadth of arguments for and against patient non-attendance fees. Policy makers may draw on this insight when implementing similar incentive schemes. The study may also contribute to the general debate on ethics and incentives.

Telehealth as a Tool to Improve Access and Reduce No-Show Rates in a Large Safety-Net Population in the USA.

Low-income populations are at higher risk of missing appointments, resulting in fragmented care and worsening disparities. Compared to face-to-face encounters, telehealth visits are more convenient and could improve access for low-income populations. All outpatient encounters at the Parkland Health between March 2020 and June 2022 were included. No-show rates were compared across encounter types (face-to-face vs telehealth). Generalized estimating equations were used to evaluate the association of encounter type and no-show encounters, clustering by individual patient and adjusting for demographics, comorbidities, and social vulnerability. Interaction analyses were performed. There were 355,976 unique patients with 2,639,284 scheduled outpatient encounters included in this dataset. 59.9% of patients were of Hispanic ethnicity, while 27.0% were of Black race. In a fully adjusted model, telehealth visits were associated with a 29% reduction in odds of no-show (aOR 0.71, 95% CI: 0.70-0.72). Telehealth visits were associated with significantly greater reductions in probability of no-show among patients of Black race and among those who resided in the most socially vulnerable areas. Telehealth encounters were more effective in reducing no-shows in primary care and internal medicine subspecialties than surgical specialties or other non-surgical specialties. These data suggest that telehealth may serve as a tool to improve access to care in socially complex patient populations.

Estudo transversal sobre ausências de pacientes em consultas médicas agendadas em ambulatórios de hospital terciário / Cross-sectional Study On Patient Absences In Medical Consultations Scheduled In Outpatient Clinics Of Tertiary Hospital / Estudio Transversal Sobre Ausencias de Pacientes Em Citas Médicas Programadas Em Pacientes Ambulatorios de Hospitales Terciarios

Objetivo: Analisar variáveis relacionadas ao agendamento de consultas ambulatoriais que não se realizaram pela ausência dos pacientes. Métodos: Estudo transversal produzido em hospital público terciário de referência para o Sistema Único de Saúde. Foram sorteados aleatoriamente 493 pacientes, e a amostra final totalizou 317 pacientes que faltaram a consultas médicas. Variáveis investigadas: recebimento de mensagens via celular informando a data da consulta, intervalo entre a data do agendamento e da consulta e a realização de reagendamento. Os dados foram oriundos de relatórios informatizados de faltosos a consultas agendadas e entrevistas telefônicas. Análises estatísticas realizadas no programa SAS® for Windows, versão 9.3. Resultados: 49.8% dos pacientes informaram não terem recebido mensagem lembrando sobre a data da consulta. O tempo entre o agendamento e a data da consulta ficou entre 180 e 365 dias para 36,6% dos pacientes. Reagendaram a consulta 24,6% dos pacientes. Conclusão: É necessário ampliar procedimentos para prevenção de faltas às consultas, independentemente do tempo entre o agendamento e a consulta. (AU)

Objective: To analyze variables related to the scheduling of outpatient appointments that did not take place due to patient no-show. Methods: Cross-sectional study conducted in a tertiary public referral hospital providing services to the Brazilian Unified Health System. A total of 493 patients were randomly selected, and the final sample totaled 317 no-show patients. Variables investigated: receipt of messages via cell phones informing the appointment date, interval between the scheduling date and the appointment date, and rescheduling. Data were obtained from computerized reports regarding absenteeism from scheduled appointments and telephone interviews. Statistical analyses were performed using the SAS® for Windows software, version 9.3. Results: 49.8% of patients reported not having received a message reminding them of the appointment dates. The interval between scheduling and the appointment dates was from 180 to 365 days for 36.6% of patients. A total of 24.6% of patients rescheduled their appointments. Conclusion: It is necessary to expand procedures to prevent missed appointments regardless of the time between scheduling and the appointment. (AU)

Objetivo: Analizar variables relacionadas con la programación de consultas externas que no se realizaron por ausencia del paciente. Métodos: Estudio transversal realizado en un hospital público terciario de referencia del Sistema Único de Salud. Se seleccionó aleatoriamente a 493 pacientes y la muestra final fue de 317 pacientes que faltaron a las citas médicas. Variables investigadas: recepción de mensajes vía celular informando la fecha de la cita, intervalo entre la cita y la fecha de la cita y reprogramación. Los datos provienen de informes computarizados de ausencias n citas programadas y entrevistas telefónicas. Análisis estadísticos realizados en SAS® para Windows versión 9.3. Resultados: En el 49.8% de los pacientes informaron no haber recibido un mensaje recordando la fecha de la cita. Conclusión: Es necesario ampliar los procedimientos para evitar citas perdidas independientemente del tiempo entre citas y citas. (AU)

Appointment attendance behaviors in multiple sclerosis: Understanding the factors that differ between no shows, short notice cancellations, and attended appointments.

BACKGROUND: There has yet to be an examination of how appointment attendance behaviors in multiple sclerosis (MS) are related to scheduling metrics and certain demographic, clinical, and behavioral factors such as cognitive functioning and personality traits. This study aimed to examine the factors that differ between no shows (NS), short notice cancellations (SNC), and attended appointments. METHODS: Participants (n = 110) were persons with MS who were enrolled in a larger cross-sectional study, during which they completed a battery of neuropsychological measures. Data about their appointments in three MS-related clinics the year prior to their study evaluation were extracted from the medical record. Bivariate analyses were done, with post-hoc tests conducted with Bonferroni corrections if there was an overall group difference. RESULTS: A higher number of SNC were noted during the winter, with 22.4% being due to the weather. SNC were also more common on Thursdays, but less frequent during the early morning time slots (7am to 9am). In contrast, NS were associated with lower annual income, weaker healthcare provider relationships, lower self-efficacy, higher levels of neuroticism, depressive symptom severity, and health distress, and greater cognitive difficulties, particularly with prospective memory. CONCLUSIONS: While SNC are related to clinic structure and situational factors like the weather, NS may be more influenced by behavioral issues, such as difficulty remembering an appointment and high levels of distress. These findings highlight potential targets for reducing the number of missed appointments in the clinic, providing opportunities for improved healthcare efficiency and most importantly health.

Appointment Non-attendance for Telehealth Versus In-Person Primary Care Visits at a Large Public Healthcare System.

BACKGROUND: Appointment non-attendance has clinical, operational, and financial implications for patients and health systems. How telehealth services are associated with non-attendance in primary care is not well-described, nor are patient characteristics associated with telehealth non-attendance. OBJECTIVE: We sought to compare primary care non-attendance for telehealth versus in-person visits and describe patient characteristics associated with telehealth non-attendance. DESIGN: An observational study of electronic health record data. PARTICIPANTS: Patients with primary care encounters at 23 adult primary care clinics at a large, urban public healthcare system from November 1, 2019, to August 31, 2021. MAIN MEASURES: We analyzed non-attendance by modality (telephone, video, in-person) during three time periods representing different availability of telehealth using hierarchal multiple logistic regression to control for patient demographics and variation within patients and clinics. We stratified by modality and used hierarchal multiple logistic regression to assess for associations between patient characteristics and non-attendance in each modality. KEY RESULTS: There were 1,219,781 scheduled adult primary care visits by 329,461 unique patients: 754,149 (61.8%) in-person, 439,295 (36.0%) telephonic, and 26,337 (2.2%) video visits. Non-attendance for telephone visits was initially higher than that for in-person visits (adjusted odds ratio 1.04 [95% CI 1.02, 1.07]) during the early telehealth availability period, but decreased later (0.82 [0.81, 0.83]). Non-attendance for video visits was higher than for in-person visits during the early (4.37 [2.74, 6.97]) and later (2.02 [1.95, 2.08]) periods. Telephone visits had fewer differences in non-attendance by demographics; video visits were associated with increased non-attendance for patients who were older, male, had a primary language other than English or Spanish, and had public or no insurance. CONCLUSIONS: Telephonic visits may improve access to care and be more easily adoptable among diverse populations. Further attention to implementation may be needed to avoid impeding access to care for certain populations using video visits.

Effects of a brief pre-admission telephone reminder on no-show and dropout rates in substance use disorder treatment: a quasi-experimental study.

BACKGROUND: Appointment no-show and early dropout from treatment represent major challenges in outpatient substance use disorder treatment, adversely affecting clinical outcomes and health care productivity. In this quasi-experimental study, we examined how a brief reminder intervention for new patients before their first appointment affected treatment participation and retention. No-shows (not attending any sessions) and dropouts (discontinuation of initiated treatment because of three consecutively missed appointments) were compared between a period with pre-admission telephone calls (intervention) and a period without such reminders (non-intervention). METHODS: Participants were all eligible patients (N = 262) admitted to a Norwegian specialist clinic for substance use disorder treatment. We used the Chi-square test for the no-show analysis. Of the eligible patients, 147 were included in a subsequent dropout analysis. We used the number of visits up to 10 appointments as a measure for time to event. Group differences were analyzed using a Kaplan-Meier plot and the log-rank test. To control for relevant sociodemographic variables, as well as substance use and mental distress severity, we used Cox regression. RESULTS: No-show rates did not differ between the two periods (12% for non-intervention vs. 14% for intervention; χ2 = 0.20, p = 0.653). Of those consenting to participate in the dropout analysis (n = 147), 28 (19%) discontinued treatment within the time frame of 10 appointments, with no differences between the two periods (log-rank test = 0.328, p = 0.567). Controlling for baseline characteristics did not alter this finding. In fact, of the registered covariates at baseline, only higher education level was associated with attrition, linked to a reduced risk for dropout (hazard ratio = 0.85, 95% CI = 0.74-0.98, p = 0.025). CONCLUSION: These findings do not provide support for the systematic use of a brief pre-admission telephone reminder in the current treatment setting. TRIAL REGISTRATION: The study was retrospectively registered 13 Jan 2021 at ClinicalTrials.gov, NCT04707599.

Conversion of No-Show Patients to Telehealth in a Primary Medicine Clinic.

No-shows in primary care clinics prevent patients from receiving essential care and decrease clinic productivity. The COVID-19 pandemic forced physicians to adjust to telemedicine as a necessary method to provide care. In this study no-show patients were converted to telehealth visits thereby allowing physicians to care for their patients and maintain hospital revenue. The most common reasons for "no-shows" were found to be forgetting appointments and transportation issues.

Prospective Evaluation of a Machine-Learning Prediction Model for Missed Radiology Appointments.

The term "no-show" refers to scheduled appointments that a patient misses, or for which she arrives too late to utilize medical resources. Accurately predicting no-shows creates opportunities to intervene, ensuring that patients receive needed medical resources. A machine-learning (ML) model can accurately identify individuals at high no-show risk, to facilitate strategic and targeted interventions. We used 4,546,104 non-same-day scheduled appointments in our medical system from 1/1/2017 through 1/1/2020 for training data, including 631,386 no-shows. We applied eight ML techniques, which yielded cross-validation AUCs of 0.77-0.93. We then prospectively tested the best performing model, Gradient Boosted Regression Trees, over a 6-week period at a single outpatient location. We observed 123 no-shows. The model accurately identified likely no-show patients retrospectively (AUC 0.93) and prospectively (AUC 0.73, p < 0.0005). Individuals in the highest-risk category were three times more likely to no-show than the average of all other patients. No-show prediction modeling based on machine learning has the potential to identify patients for targeted interventions to improve their access to medical resources, reduce waste in the medical system and improve overall operational efficiency. Caution is advised, due to the potential for bias to decrease the quality of service for patients based on race, zip code, and gender.

Predicting Patient No-Shows in an Academic Pediatric Neurology Clinic.

Background: No-shows can negatively affect patient care. Efforts to predict high-risk patients are needed. Previously, our epilepsy clinic identified patients with 2 or more no-shows or late cancelations in the past 18 months as being at high risk for no-shows. Our objective was to develop a model to accurately predict the risk of no-shows among patients with epilepsy seen at our neurology clinic. Methods: Using electronic health record data, we developed a least absolute shrinkage and selection operator (LASSO)-regularized logistic regression model to predict no-shows and compared its performance with our neurology clinic's above-mentioned ad hoc rule. Results: The ad hoc rule identified 13% of patients seen at our neurology clinic as high-risk patients for no-shows and resulted in a positive predictive value of 38%. In comparison, our LASSO model resulted in a positive predictive value of 48%. Our LASSO model identified that lack of private insurance, inactive Epic MyChart, greater past no-show rates, fewer appointment changes before the appointment date, and follow-up appointments were more likely to result in no-shows. Conclusions: Our LASSO model outperformed the ad hoc rule used by our neurology clinic in predicting patients at high risk for no-shows. Social workers can use the no-show risk scores generated by our LASSO model to prioritize high-risk patients for targeted intervention to reduce no-shows at our neurology clinic.

Lost in Follow-Up: Predictors of Patient No-Shows to Clinic Follow-Up After Abdominal Injury.

BACKGROUND: The aim of this study is to evaluate risk factors for non-attendance to post-discharge, hospital follow-up appointments for traumatically injured patients who underwent exploratory laparotomy. METHODS: This is a retrospective chart review of patients who underwent exploratory laparotomy for traumatic abdominal injury at an urban, Midwestern, level I trauma center with clinic follow-up scheduled after discharge. Clinically, relevant demographic characteristics, patients' distance from hospital, and the presence of staples, sutures, and drains requiring removal were collected. Descriptive statistics of categorical variables were calculated as totals and percentages and compared with a chi-squared test or Fisher's exact when appropriate. RESULTS: The sample included 183 patients who were largely assaultive trauma survivors (68%), male (80%), and black (53%) with a mean age of 35.4 ± 14.9 years. Overall, 18.5% no-showed for their follow-up appointment. On multivariate analysis for clinic no-show; length of stay (odds ratio = 0.92 [0.84-0.99], P = 0.04) and the need for suture, staple, or drain removal were protective for clinic attendance (odds ratio = 5.59 [1.07-7.01], P = 0.04). Overall, 12 patients (6.4%) were readmitted. Forty patients (18.3%) had their follow-up in the emergency department (ED). On multivariate regression of risk factors for ED visits, the only statistically significant factors (P < 0.05) were clinic appointment no-show (OR = 2.81) and self-pay insurance (OR = 4.78). CONCLUSIONS: Abdominal trauma patients are at high risk of no-show for follow-up appointments and no-show visits are associated with ED visits. Future work is needed evaluating interventions to improve follow-up.

Factors Contributing to Non-Attendance of GI Endoscopic Procedures in a Tertiary Care Center in the Middle East.

INTRODUCTION: The cancer burden in the Middle East is high and growing. Colorectal cancer (CRC) is the second most common cancer for both men and women in the UAE. Although early diagnosis of malignancy reduces morbidity and increases the survival rates, non-attendance of gastroenterology (GI) endoscopic procedures is a significant global problem, which can lead to delay in cancer diagnosis and treatment. Several factors have been found to contribute to non-attendance behavior, including socioeconomic, cultural, and organizational related barriers. The purpose of this study was to identify factors contributing to non-attendance behavior among outpatients scheduled for GI endoscopic procedures in a tertiary hospital in the United Arab Emirates. We conclude with recommendations that can help in reducing the rate of patient no-shows for GI endoscopic procedures in the region. METHODS: In a tertiary medical center in the Middle East, we surveyed patients who did not attend their scheduled GI endoscopic procedures over a period of one year. The questionnaire sought to identify possible reasons for patient's non-attendance. Descriptive measures including means, standard deviation, frequencies, and percentages were used to analyze the demographic characteristics of the study participants. The chi-square test was performed to analyze gender differences. RESULTS: Of 314 outpatients who met study inclusion criteria, 168 agreed to participate (53.5% response rate). The majority of participants were women (n=96, 60.4 %), aged 18 to 73, with a mean of 42 years. The largest age group was between 35 and 44 (n=46, 28.9 %). Approximately equal numbers of non-attendance appointments were scheduled for combined colonoscopy and upper endoscopy (36.3 %), colonoscopy alone (31.3 %), or upper endoscopy alone (31.3 %). The most common causes for cancellation or non-attendance included concerns about the appointment (35.5%), inconvenient timing of the appointment (27.9%) and changes in medical status (26.4%). Gender differences were noted for non-attendance behaviors, with women significantly more likely than men to report feelings of embarrassment (Chi-square 6.261, df=1, p=.012). CONCLUSION: Our study has identified several barriers to patient attendance of endoscopic procedures, as well as opportunities to reduce the rate of patient no-shows, including patient education, scheduling options, and protocols to minimize discomfort and misconceptions around GI endoscopic procedures, particularly accommodating for same gender endoscopists, with the ultimate goal of increasing early cancer screening and prevention.

Association of Differences in Treatment Intensification, Missed Visits, and Scheduled Follow-up Interval With Racial or Ethnic Disparities in Blood Pressure Control.

Importance: Black patients with hypertension often have the lowest rates of blood pressure (BP) control in clinical settings. It is unknown to what extent variation in health care processes explains this disparity. Objective: To assess whether and to what extent treatment intensification, scheduled follow-up interval, and missed visits are associated with racial and ethnic disparities in BP control. Design, Setting, and Participants: In this cohort study, nested logistic regression models were used to estimate the likelihood of BP control (defined as a systolic BP [SBP] level <140 mm Hg) by race and ethnicity, and a structural equation model was used to assess the association of treatment intensification, scheduled follow-up interval, and missed visits with racial and ethnic disparities in BP control. The study included 16 114 adults aged 20 years or older with hypertension and elevated BP (defined as an SBP level ≥140 mm Hg) during at least 1 clinic visit between January 1, 2015, and November 15, 2017. A total of 11 safety-net clinics within the San Francisco Health Network participated in the study. Data were analyzed from November 2019 to October 2020. Main Outcomes and Measures: Blood pressure control was assessed using the patient's most recent BP measurement as of November 15, 2017. Treatment intensification was calculated using the standard-based method, scored on a scale from -1.0 to 1.0, with -1.0 being the least amount of intensification and 1.0 being the most. Scheduled follow-up interval was defined as the mean number of days to the next scheduled visit after an elevated BP measurement. Missed visits measured the number of patients who did not show up for visits during the 4 weeks after an elevated BP measurement. Results: Among 16 114 adults with hypertension, the mean (SD) age was 58.6 (12.1) years, and 8098 patients (50.3%) were female. A total of 4658 patients (28.9%) were Asian, 3743 (23.2%) were Black, 3694 (22.9%) were Latinx, 2906 (18.0%) were White, and 1113 (6.9%) were of other races or ethnicities (including American Indian or Alaska Native [77 patients (0.4%)], Native Hawaiian or Pacific Islander [217 patients (1.3%)], and unknown [819 patients (5.1%)]). Compared with patients from all racial and ethnic groups, Black patients had lower treatment intensification scores (mean [SD], -0.33 [0.26] vs -0.29 [0.25]; ß = -0.03, P < .001) and missed more visits (mean [SD], 0.8 [1.5] visits vs 0.4 [1.1] visits; ß = 0.35; P < .001). In contrast, Asian patients had higher treatment intensification scores (mean [SD], -0.26 [0.23]; ß = 0.02; P < .001) and fewer missed visits (mean [SD], 0.2 [0.7] visits; ß = -0.20; P < .001). Black patients were less likely (odds ratio [OR], 0.82; 95% CI, 0.75-0.89; P < .001) and Asian patients were more likely (OR, 1.13; 95% CI, 1.02-1.25; P < .001) to achieve BP control than patients from all racial or ethnic groups. Treatment intensification and missed visits accounted for 21% and 14%, respectively, of the total difference in BP control among Black patients and 26% and 13% of the difference among Asian patients. Conclusions and Relevance: This study's findings suggest that racial and ethnic inequities in treatment intensification may be associated with more than 20% of observed racial or ethnic disparities in BP control, and racial and ethnic differences in visit attendance may also play a role. Ensuring more equitable provision of treatment intensification could be a beneficial health care strategy to reduce racial and ethnic disparities in BP control.