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Objectives: Missed appointments can lead to treatment delays and adverse outcomes. Telemedicine may improve appointment completion because it addresses barriers to in-person visits, such as childcare and transportation. This study compared appointment completion for appointments using telemedicine versus in-person care in a large cohort of patients at an urban academic health sciences center. Materials and Methods: We conducted a retrospective cohort study of electronic health record data to determine whether telemedicine appointments have higher odds of completion compared to in-person care appointments, January 1, 2021, and April 30, 2023. The data were obtained from the University of South Florida (USF), a large academic health sciences center serving Tampa, FL, and surrounding communities. We implemented 1:1 propensity score matching based on age, gender, race, visit type, and Charlson Comorbidity Index (CCI). Results: The matched cohort included 87 376 appointments, with diverse patient demographics. The percentage of completed telemedicine appointments exceeded that of completed in-person care appointments by 9.2 points (73.4% vs 64.2%, P < .001). The adjusted odds ratio for telemedicine versus in-person care in relation to appointment completion was 1.64 (95% CI, 1.59-1.69, P < .001), indicating that telemedicine appointments are associated with 64% higher odds of completion than in-person care appointments when controlling for other factors. Discussion: This cohort study indicated that telemedicine appointments are more likely to be completed than in-person care appointments, regardless of demographics, comorbidity, payment type, or distance. Conclusion: Telemedicine appointments are more likely to be completed than in-person healthcare appointments.

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BACKGROUND: SMS texting systems have been considered a potential solution to reduce missed appointments in primary care. Existing research in this area focuses on qualitative studies investigating the attitudes of SMS text users and receivers. OBJECTIVE: This study aimed to examine appointment data from an independent general practitioner (GP) surgery in Wrexham, United Kingdom, with approximately 15,000 patients, to determine the impact of text messaging systems on reducing missed appointments. The objective of this study was to investigate whether the use of text messages can effectively reduce missed appointments. METHODS: To collect data for the study, SQL reports were run on EMIS Web, the United Kingdom's most widely used clinical system. The data spanned 10 years, from September 1, 2010, to March 31, 2020. Data accuracy was verified by cross-referencing with appointment diary records. Mann-Whitney and Kruskal-Wallis tests, chosen for their suitability in comparing groups in nonparametric settings, were conducted in Microsoft Excel due to its accessibility. RESULTS: Statistical analyses were conducted to compare data before and after implementation of the text messaging system. The results revealed a significant 42.8% reduction in missed appointments (before: 5848; after: 3343; P<.001). Further analysis of demographic characteristics revealed interesting trends, with no significant difference in missed appointments between genders, and variations observed across different age groups. The median number of missed appointments was not significantly different between genders (women: 1.55, IQR 1.11-2.16; men: 1.61, IQR 1.08-2.12; P=.73). Despite the prevalence of mobile phone use among young adults aged 20-25 years, the highest rates of missed appointments (848/7256, 11.7%) were noted in this group, whereas the lowest rates were noted in the 75-80 years age group (377/7256; 5.2%; P<.001). Analysis by age and gender indicated inconsistencies: women aged 20-25 years (571/4216) and men aged 35-40 years (306/3040) had the highest rates of missed appointments, whereas women aged 70-75 years (177/4216) and men aged 75-80 years (129/3040) had the lowest rates (P<.001 for both). CONCLUSIONS: This study demonstrates that SMS text messaging in primary care can significantly reduce missed appointments. Implementing technology such as SMS text messaging systems enables patients to cancel appointments on time, leading to improved efficiency in primary care settings.

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BACKGROUND: Childcare needs are an understudied social determinant of health. The effect of childcare needs on access to healthcare must be understood to inform health system interventions and policy reform. This study sought to characterize childcare needs, access to childcare, and prior experience with navigating childcare needs in healthcare settings among women in a safety-net population. METHODS: We conducted a cross-sectional study of patient-reported survey data collected in-person between April and October 2019. Surveys were administered in waiting rooms of ambulatory services in a large, urban safety-net health system in Dallas, Texas. Survey respondents were derived from a random convenience sample of women waiting for outpatient appointments. Participants were screened for having children under the age of 13 and/or childcare responsibilities for inclusion in the sample. Outcomes of interest included self-reported delayed or missed care, reasons for delayed or missed care, perceived difficulty in accessing childcare, prior methods for managing childcare during healthcare appointments, and prior experience with childcare centers. RESULTS: Among the 336 respondents (96.7% response rate), 121 (36.0%) reported delaying or missing a mean 3.7 appointments/year. Among women with delayed or missed care, 54.5% reported childcare barriers as the primary reason for deferral of care, greater than transportation (33%) or insurance (25%) barriers. Respondents rated childcare access as more difficult than healthcare access. Delayed or missed care due to childcare was more common among White (68.8%) and Black (55.0%) women compared to Hispanic women (34.3%). Common methods of navigating childcare needs during scheduled appointments included bringing children to appointments (69.1%) and re-scheduling or missing the scheduled appointment (43.0%). 40.6% of patients reported leaving an appointment before completion due to childcare needs. CONCLUSIONS: Childcare needs are a leading barrier to healthcare among women accessing care in safety-net settings. Unmet childcare needs result in deferral of care, which may impact health outcomes. Childcare access is perceived as more challenging than healthcare access itself. Health system and policy interventions are needed to address childcare as a social determinant of health.

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BACKGROUND: Although missed appointments in healthcare have been an area of concern for policy, practice and research, the primary focus has been on reducing single 'situational' missed appointments to the benefit of services. Little attention has been paid to the causes and consequences of more 'enduring' multiple missed appointments in primary care and the role this has in producing health inequalities. METHODS: We conducted a realist review of the literature on multiple missed appointments to identify the causes of 'missingness.' We searched multiple databases, carried out iterative citation-tracking on key papers on the topic of missed appointments and identified papers through searches of grey literature. We synthesised evidence from 197 papers, drawing on the theoretical frameworks of candidacy and fundamental causation. RESULTS: Missingness is caused by an overlapping set of complex factors, including patients not identifying a need for an appointment or feeling it is 'for them'; appointments as sites of poor communication, power imbalance and relational threat; patients being exposed to competing demands, priorities and urgencies; issues of travel and mobility; and an absence of choice or flexibility in when, where and with whom appointments take place. CONCLUSIONS: Interventions to address missingness at policy and practice levels should be theoretically informed, tailored to patients experiencing missingness and their identified needs and barriers; be cognisant of causal domains at multiple levels and address as many as practical; and be designed to increase safety for those seeking care.

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Non-attendance at hospital appointments is an extremely prevalent issue impacting healthcare systems on a daily basis. This phenomenon adversely affects patient health and healthcare providers, leading to delays in diagnosis and treatment, inefficient resource utilization, and increased healthcare expenses. The detrimental impact of non-attendance is not limited to patients who miss appointments, the knock-on effects of extended waiting times and reduced appointment availability are felt throughout healthcare systems. The purpose of this narrative review is to explore the factors underlying appointment non-attendance in hospital settings, to improve healthcare delivery and patient adherence. An extensive review of the existing global literature was conducted. Quantitative studies that explored the relationship between appointment non-attendance and patient characteristics, such as age, gender, marital status, education level, distance from the hospital, and source of referral, were included. Younger patients, males, individuals with lower levels of education, and those living farther from hospitals were more likely to miss appointments. Marital status was significant, with married patients showing better attendance, as was referral source, with general practitioner referrals associated with higher non-attendance. Qualitative studies identifying both patient-centered and hospital-specific reasons, such as forgetfulness, appointment time, protracted waiting times, patient-physician relationship, and patients' knowledge and perception of their health condition, were also included in the review. Lack of appointment reminders, difficulties in managing appointments, and inadequate patient-physician communication were significant hospital-specific reasons given for non-attendance. Patients' lack of awareness regarding the importance of attending appointments and limited understanding of their health conditions were also identified as patient-centered contributors. Non-attendance at hospital appointments is a multifaceted issue influenced by a range of socioeconomic, personal, and systemic factors. Addressing these factors requires a holistic approach that includes patient education, improved communication, and tailored healthcare delivery strategies, especially for vulnerable populations in rural areas. Enhanced reminder systems and streamlined appointment management could serve as pivotal interventions to reduce non-attendance rates, ultimately improving healthcare outcomes and resource utilization.

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PURPOSE: Preanesthesia screening is critical to evaluate the patient's medical and surgical history before any procedure or surgery to assess for risks and to optimize outcomes during the perioperative period. The purpose of this quality improvement project was to decrease the number of missed appointments in the outpatient preanesthesia and surgical screening clinic and the impact on provider satisfaction. DESIGN: The design of this quality improvement project was pre and post design. Automated and live phone calls reminders were provided for patients scheduled in the outpatient preanesthesia. Data were collected to compare missed appointment rates from a 3-month period before the project implementation and a 3-month period afterward. METHODS: Predata collection included the number of no-shows in the electronic health record system from the previous 3 months. Participants included all adult patients who are scheduled for a preanesthesia surgical screening appointment. Provider satisfaction was assessed using a 5-question survey, pre and postinnovation. FINDINGS: Reminder systems had a statistically significant impact on reducing the number of no-shows in the preanesthesia and surgical screening clinic. No significant impact was shown in provider satisfaction. CONCLUSIONS: Implementation of a reminder system can help to reduce no-show rates in clinics. Patient no-shows overload the health system by reducing the productivity of providers and waste resources including use of clinic staff, longer wait times for other patients, and the timing providers put into chart preparation.

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OBJECTIVE: Patients who miss screening mammogram appointments without notifying the health care system (no-show) risk care delays. We investigate sociodemographic characteristics of patients who experience screening mammogram no-shows at a community health center and whether and when the missed examinations are completed. METHODS: We included patients with screening mammogram appointments at a community health center between January 1, 2021, and December 31, 2021. Language, race, ethnicity, insurance type, residential ZIP code tabulation area (ZCTA) poverty, appointment outcome (no-show, same-day cancelation, completed), and dates of completed screening mammograms after no-show appointments with ≥1-year follow-up were collected. Multivariable analyses were used to assess associations between patient characteristics and appointment outcomes. RESULTS: Of 6,159 patients, 12.1% (743 of 6,159) experienced no-shows. The no-show group differed from the completed group by language, race and ethnicity, insurance type, and poverty level (all P < .05). Patients with no-shows more often had: primary language other than English (32.0% [238 of 743] versus 26.7% [1,265 of 4,741]), race and ethnicity other than White non-Hispanic (42.3% [314 of 743] versus 33.6% [1,595 of 4,742]), Medicaid or means-tested insurance (62.0% [461 of 743] versus 34.4% [1,629 of 4,742]), and residential ZCTAs with ≥20% poverty (19.5% [145 of 743] versus 14.1% [670 of 4,742]). Independent predictors of no-shows were Black non-Hispanic race and ethnicity (adjusted odds ratio [aOR], 1.52; 95% confidence interval [CI], 1.12-2.07; P = .007), Medicaid or other means-tested insurance (aOR, 2.75; 95% CI, 2.29-3.30; P < .001), and ZCTAs with ≥20% poverty (aOR, 1.76; 95% CI, 1.14-2.72; P = .011). At 1-year follow-up, 40.6% (302 of 743) of patients with no-shows had not completed screening mammogram. DISCUSSION: Screening mammogram no-shows is a health equity issue in which socio-economically disadvantaged and racially and ethnically minoritized patients are more likely to experience missed appointments and continued delays in screening mammogram completion.

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BACKGROUND: Healthcare accessibility and utilization are important social determinants of health. Lack of access to healthcare, including missed or no-show appointments, can have negative health effects and be costly to patients and providers. Various office-based approaches and community partnerships can address patient access barriers. OBJECTIVES: (1) To understand provider perceptions of patient barriers; (2) to describe the policies and practices used to address late or missed appointments, and (3) to evaluate access to patient support services, both in-clinic and with community partners. METHODS: Mailed cross-sectional survey with online response option, sent to all Nebraska primary care clinics (n = 577) conducted April 2020 and January through April 2021. Chi-square tests compared rural-urban differences; logistic regression of clinical factors associated with policies and support services computed odds ratios (OR) and 95% confidence intervals (CI). RESULTS: Response rate was 20.3% (n = 117), with 49 returns in 2020. Perceived patient barriers included finances, higher among rural versus urban clinics (81.6% vs. 56.1%, p =.009), and time (overall 52.3%). Welcoming environment (95.5%), telephone appointment reminders (74.8%) and streamlined admissions (69.4%) were the top three clinic practices to reduce missed appointments. Telehealth was the most commonly available patient support service in rural (79.6%) and urban (81.8%, p =.90) clinics. Number of providers was positively associated with having a patient navigator/care coordinator (OR = 1.20, CI = 1.02-1.40). For each percent increase in the number of privately insured patients, the odds of providing legal aid decreased by 4% (OR = 0.96, CI = 0.92-1.00). Urban clinics were less likely than rural clinics to provide social work services (OR = 0.16, CI = 0.04-0.67) or assist with applications for government aid (OR = 0.22, CI = 0.06-0.90). CONCLUSIONS: Practices to reduce missed appointments included a variety of reminders. Although finances and inability to take time off work were the most frequently reported perceived barriers for patients' access to timely healthcare, most clinics did not directly address them. Rural clinics appeared to have more community partnerships to address underlying social determinants of health, such as transportation and assistance applying for government aid. Taking such a wholistic partnership approach is an area for future study to improve patient access.

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BACKGROUND: No-show to medical appointments has significant adverse effects on healthcare systems and their clients. Using machine learning to predict no-shows allows managers to implement strategies such as overbooking and reminders targeting patients most likely to miss appointments, optimizing the use of resources. METHODS: In this study, we proposed a detailed analytical framework for predicting no-shows while addressing imbalanced datasets. The framework includes a novel use of z-fold cross-validation performed twice during the modeling process to improve model robustness and generalization. We also introduce Symbolic Regression (SR) as a classification algorithm and Instance Hardness Threshold (IHT) as a resampling technique and compared their performance with that of other classification algorithms, such as K-Nearest Neighbors (KNN) and Support Vector Machine (SVM), and resampling techniques, such as Random under Sampling (RUS), Synthetic Minority Oversampling Technique (SMOTE) and NearMiss-1. We validated the framework using two attendance datasets from Brazilian hospitals with no-show rates of 6.65% and 19.03%. RESULTS: From the academic perspective, our study is the first to propose using SR and IHT to predict the no-show of patients. Our findings indicate that SR and IHT presented superior performances compared to other techniques, particularly IHT, which excelled when combined with all classification algorithms and led to low variability in performance metrics results. Our results also outperformed sensitivity outcomes reported in the literature, with values above 0.94 for both datasets. CONCLUSION: This is the first study to use SR and IHT methods to predict patient no-shows and the first to propose performing z-fold cross-validation twice. Our study highlights the importance of avoiding relying on few validation runs for imbalanced datasets as it may lead to biased results and inadequate analysis of the generalization and stability of the models obtained during the training stage.

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INTRODUCTION: Non-attendance for radiology outpatient appointments is a global issue and is associated with adverse clinical outcomes and operational inefficiencies. This paper aims to understand the underlying factors influencing outpatient radiology attendances based on the Health Belief Model (HBM). METHODS: Purposive sampling was used to recruit patients (n=30) for in-depth semi-structured telephone interviews. Inclusion criteria comprised participants who were above 21 years old and fluent in English, while participants reliant on third-party assistance (e.g., nursing homes and prison services), to attend the appointment were excluded. The interviews were recorded and transcribed verbatim. The COREQ (Consolidated Criteria for Reporting Qualitative Research) was utilised to guide the reporting of this study. The data analysis involved a hybrid thematic analysis approach using NVivo. RESULTS: Six key themes associated with appointment adherence in radiology were identified. These themes included: 1) prioritising health and acceptance of current medical conditions; 2) the impact of perceived severity on non-attendance; 3) perceived benefits of attending appointments; 4) perceived barriers to attendance; 5) influential prompts; and 6) confidence in attendance. CONCLUSION: This is the first study of its kind to utilise the HBM to examine factors influencing attendance adherence among radiology outpatients in Singapore. Costs, prompts, and the perceived severity of the condition play pivotal roles in shaping the health-seeking behaviours of these outpatients while professionalism of healthcare staff and barriers to attendance present opportunities for providers to address patients' lack of interest towards their appointments. IMPLICATIONS FOR PRACTICE: Findings of this study will contribute to the development of personalised, targeted interventions for improving patient engagement and attendance in radiology settings.

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BACKGROUND: Missed colonoscopy appointments delay screening and treatment for gastrointestinal disorders. Prior nonadherence with other care components may be associated with missed colonoscopy appointments. OBJECTIVE: To assess variability in prior adherence behaviors and their association with missed colonoscopy appointments. DESIGN: Retrospective cohort study. PARTICIPANTS: Patients scheduled for colonoscopy in an integrated healthcare system between January 2016 and December 2018. MAIN MEASURES: Prior adherence behaviors included: any missed outpatient appointment in the previous year; any missed gastroenterology clinic or colonoscopy appointment in the previous 2 years; and not obtaining a bowel preparation kit pre-colonoscopy. Other sociodemographic, clinical, and system characteristics were included in a multivariable model to identify independent associations between prior adherence behaviors and missed colonoscopy appointments. KEY RESULTS: The median age of the 57,590 participants was 61 years; 52.8% were female and 73.4% were white. Of 77,684 colonoscopy appointments, 3,237 (4.2%) were missed. Individuals who missed colonoscopy appointments were more likely to have missed a previous primary care appointment (62.5% vs. 38.4%), a prior gastroenterology appointment (18.4% vs. 4.7%) or not to have picked up a bowel preparation kit (42.4% vs. 17.2%), all p < 0.001. Correlations between the three adherence measures were weak (phi < 0.26). The rate of missed colonoscopy appointments increased from 1.8/100 among individuals who were adherent with all three prior care components to 24.6/100 among those who were nonadherent with all three care components. All adherence variables remained independently associated with nonadherence with colonoscopy in a multivariable model that included other covariates; adjusted odds ratios (with 95% confidence intervals) were 1.6 (1.5-1.8) for outpatient appointments, 1.9 (1.7-2.1) for gastroenterology appointments, and 3.1 (2.9-3.4) for adherence with bowel preparation kits, respectively. CONCLUSIONS: Three prior adherence behaviors were independently associated with missed colonoscopy appointments. Studies to predict adherence should use multiple, complementary measures of prior adherence when available.

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Objective: Missed patient appointments have a substantial negative impact on patient care, child health and well-being, and clinic functioning. This study aims to identify health system interface and child/family demographic characteristics as potential predictors of appointment attendance in a pediatric outpatient neuropsychology clinic. Method: Pediatric patients (N = 6,976 across 13,362 scheduled appointments) who attended versus missed scheduled appointments at a large, urban assessment clinic were compared on a broad array of factors extracted from the medical record, and the cumulative impact of significant risk factors was examined. Results: In the final multivariate logistic regression model, health system interface factors that significantly predicted more missed appointments included a higher percentage of previous missed appointments within the broader medical center, missing pre-visit intake paperwork, assessment/testing appointment type, and visit timing relative to the COVID-19 pandemic (i.e. more missed appointments prior to the pandemic). Demographic characteristics that significantly predicted more missed appointments in the final model included Medicaid (medical assistance) insurance and greater neighborhood disadvantage per the Area Deprivation Index (ADI). Waitlist length, referral source, season, format (telehealth vs. in-person), need for interpreter, language, and age were not predictive of appointment attendance. Taken together, 7.75% of patients with zero risk factors missed their appointment, while 22.30% of patients with five risk factors missed their appointment. Conclusions: Pediatric neuropsychology clinics have a unique array of factors that impact successful attendance, and identification of these factors can help inform policies, clinic procedures, and strategies to decrease barriers, and thus increase appointment attendance, in similar settings.

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Missed cases of child physical abuse (CPA) persist despite known risk factors. Prior studies have not evaluated missed medical appointments as a risk factor for CPA. The objective of this study was to determine if an association exists between missed appointments and hospitalization for CPA. We conducted a 20-year, single health system, retrospective chart review of hospitalized patients ≤36 months of age meeting International Classification of Diseases (ICD) 9/10 criteria for CPA with ≥1 scheduled appointment in our system prior to their admission. Cases were categorized as definite CPA, high likelihood, or no concern for CPA/unable to be determined. Cases identified as definite or high likelihood of CPA were matched (5:1) with controls based on age, distance to primary care provider's (PCP's) office, sex, prior hospitalization, and race. Missed appointments were compared between cases (n = 146) and controls (n = 730). A significant difference was identified between cases and controls (26 % vs 9 %, p < 0.001) for the median proportion of missed appointments. After adjusting for matched and significant covariates, there was a 3 % increase in a patient's odds of admission for CPA for every 1 % increase in missed appointments. We found an association between missed appointments and future admission for CPA. This finding has potential to assist clinicians with CPA risk stratification and future child abuse research. Limitations include single healthcare system, ICD criteria determined by research team, and narrow definition of definite CPA.

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Purpose: While missed patient appointments reduce clinic efficiency and limit effective resource allocation, factors predictive of "no shows" are poorly understood in radiation oncology. Methods and materials: A prospective data registry of consecutive patients referred for initial consultation from October 2,018 to April 2022 was reviewed. Demographic characteristics recorded included age, gender, race, language preference, living situation, and insurance status. Zip code data linked to a patient's residential address was used to determine socioeconomic status (SES) based on publicly available data on median household income. No show encounters were defined as all encounters where the patient failed to cancel their visit and did not sign-in to their scheduled appointment. Descriptive statistics were presented to identify factors predictive of missed appointments. Results: A total of 9,241 consecutive patients were referred and logged into the database during the 4-year period, of which 5,755 were successfully scheduled and registered. A total of 523 patients (9%) failed to show for their appointments. Missed appointments were associated with low-income status, homeless living situation, and Black or Latino race (p < 0.05, for all). The proportion of White, Latino, Asian, and Black patients who missed appointments was 6%, 14%, 9%, and 12%, respectively (p < 0.001). Patient characteristics independently associated with higher odds of appointment non-adherence included low-income status ((OR) = 2.90, 95% CI (1.44-5.89) and Black or Latino race [(OR) = 3.31, 95% CI: 1.22-7.65]. Conclusions: Our results highlight the influence of demographic, financial, and racial disparities on proper health care utilization among patients with cancer. Future interventions aimed at reducing appointment no shows could channel resources to the at risk-populations identified in this analysis, improving access to care, and optimize clinic efficiency.

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BACKGROUND: The global outbreak of the COVID-19 pandemic resulted in significant changes in the delivery of health care services such as attendance of scheduled outpatient hospital appointments. This study aimed to evaluate the impact of COVID-19 on the rate and predictors of missed hospital appointment in the Sultanate of Oman. METHODS: A retrospective single-centre analysis was conducted to determine the effect of COVID-19 on missed hospital appointments at various clinics at The Royal Hospital (tertiary referral hospital) in Muscat, Sultanate of Oman. The study population included scheduled face-to-face and virtual appointments between January 2019 and March 2021. Logistic regression models were used with interaction terms (post COVID-19) to assess changes in the predictors of missed appointments. RESULTS: A total of 34, 3149 scheduled appointments was analysed (320,049 face-to-face and 23,100 virtual). The rate of missed face-to-face hospital appointments increased from 16.9% pre to 23.8% post start of COVID-19, particularly in early pandemic (40.5%). Missed hospital appointments were more frequent (32.2%) in virtual clinics (post COVID-19). Increases in missed face-to-face appointments varied by clinic (Paediatrics from 19.3% pre to 28.2% post; Surgery from 12.5% to 25.5%; Obstetrics & Gynaecology from 8.4% to 8.5%). A surge in the frequency of missed appointments was seen during national lockdowns for face-to-face and virtual appointments. Most predictors of missed appointments did not demonstrate any appreciable changes in effect (i.e., interaction term not statistically significant). Distance of patient residence to the hospital revealed no discernible changes in the relative effect pre and post COVID-19 for both face-to-face and virtual clinic appointments. CONCLUSION: The rate of missed visits in most clinics was directly impacted by COVID-19. The case mix of patients who missed their appointments did not change. Virtual appointments, introduced after start of the pandemic, also had substantial rates of missed appointments and cannot be viewed as the single approach that can overcome the problem of missing hospital appointments.

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BACKGROUND: Approximately one-third of patient appointments in Danish health care result in failures, leading to patient risk and sizable resource waste. Existing interventions to alleviate no-shows often target the patients. The underlying reason behind these interventions is a view that attendance or nonattendance is solely the patient's problem. However, these interventions often prove to be ineffective and can perpetuate social biases and health inequalities, leaving behind patients who are more vulnerable or disadvantaged (in terms of social, economical, and linguistic factors, etc). A more holistic understanding of no-shows is needed to optimize processes, reduce waste, and support patients who are vulnerable. OBJECTIVE: This study aims to gain a deep and more comprehensive understanding of the causes, mechanisms, and recurring patterns and elements contributing to nonattendance at Danish hospitals in the Region of Southern Denmark. It emphasizes the patient perspective and analyzes the relational and organizational processes surrounding no-shows in health care. In addition, the study aims to identify effective communicative strategies and organizational processes that can support the development and implementation of successful interventions. METHODS: The study uses mixed quantitative-qualitative methods, encompassing 4 analytical projects focusing on nonattendance patterns, patient knowledge and behavior, the management of hospital appointments, and in situ communication. To address the complexity of no-shows in health care, the study incorporates various data sources. The quantitative data sources include the electronic patient records, Danish central registries, Danish National Patient Registry, and Register of Medicinal Product Statistics. Baseline characteristics of patients at different levels are compared using chi-square tests and Kruskal-Wallis tests. The qualitative studies involve observational data, individual semistructured interviews with patients and practitioners, and video recordings of patient consultations. RESULTS: This paper presents the protocol of the study, which was funded by the Novo Nordisk Foundation in July 2022. Recruitment started in February 2023. It is anticipated that the quantitative data analysis will be completed by the end of September 2023, with the qualitative investigation starting in October 2023. The first study findings are anticipated to be available by the end of 2024. CONCLUSIONS: The existing studies of nonattendance in Danish health care are inadequate in addressing relational and organizational factors leading to hospital no-shows. Interventions have had limited effect, highlighting the Danish health care system's failure to accommodate patients who are vulnerable. Effective interventions require a qualitative approach and robust ethnographic data to supplement the description and categorization of no-shows at hospitals. Obtaining comprehensive knowledge about the causes of missed patient appointments will yield practical benefits, enhancing the safety, coherence, and quality of treatment in health care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/46227.

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Background The purpose of this study was to determine the pattern of dental appointment adherence in the College of Dentistry (COD), King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS).  Methodology The electronic dental record SALUD (Two-Ten Health, Dublin, Ireland; n = 15,193) was used in this cross-sectional study. The primary outcome measure was adherence to dental appointments, categorized as attended, canceled by the patient, canceled by the school, or missed. Other variables of interest were demographic and appointment-related factors. Descriptive statistics were used to describe patterns of dental appointments. In addition, the proportion of check-in time for dental appointments among those who attended was calculated. For requested dental appointments among dental specialties, we calculated the percentage of booked, canceled, and rejected appointment requests for each specialty and compared the proportions across specialties. Results The proportion of attended dental appointments was 70.92% (10,775), with 9.14% (1,388) of appointments being missed and 16.70% (2,537) being canceled. Approximately 54% (5,765) of dental appointments were checked in on time. Approximately 77% (10,115) of dental appointment requests were scheduled. Pedodontics and orthodontics had the most scheduled appointments, while restorative dentistry had the most appointment requests. Conclusions The utilization of data from electronic dental records revealed a low rate of missed dental appointments. Identifying those who were late or skipped appointments was critical to determining the possible causes.

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BACKGROUND: Antenatal care is vital for pregnant women and fetuses. However, the coronavirus disease 2019 (COVID-19) pandemic has hindered access to care worldwide, resulting in missed appointments. Therefore, assessing the quality of antenatal care during the pandemic is crucial. This study evaluated the care provided at King Abdulaziz University Hospital in Saudi Arabia and suggested areas for improvement. METHODS: This retrospective medical records review involved 400 pregnant patients who received antenatal care at King Abdulaziz University Hospital in the past two years. A checklist was used to collect patient data, including demographics, antenatal care visits, ultrasounds, gestational age at first visit and ultrasound, prior cesarean section and preterm delivery, and virtual clinic attendance during the COVID-19 pandemic. Statistical analyses were performed using SPSS version 25 (Armonk, NY: IBM Corp.). RESULTS: The sample had a mean age of 30±6 years, and most participants (87.8%) were Saudi women. Over half of the participants did not attend any antenatal follow-up visits, and the majority had only one ultrasound. Only a small proportion of mothers attended virtual clinics during the pandemic. Having a prior cesarean section and a parity of 1-3 were positively associated with ultrasound attendance, while prior preterm delivery was positively associated with antenatal visits and virtual clinic attendance. CONCLUSION: This study highlighted the importance of improving antenatal care quality at King Abdulaziz University Hospital, especially during COVID-19. To achieve this, strategies such as increasing visits, ultrasound attendance, and virtual clinic access should be considered. By implementing these recommendations, the hospital can enhance care and promote maternal and fetal health.

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AIM: Non-attendance at appointments in youth mental health services is a common problem which contributes to reduced service effectiveness and unmet needs. Reasons cited by young people for non-attendance are poorly understood. Information derived from short-message-service (SMS) conversations about appointments between patients and clinicians can uncover new insights about the circumstances leading to 'did not attend' events. METHODS: Text messages between young people and clinicians were examined in a retrospective audit of medical records in two youth mental health services in Perth, Australia. Frequently non-attending young people aged 16-24 (n = 40) engaged in 302 SMS message chains about appointments. Mixed methods included quantitative data and qualitative thematic analysis of textual data. RESULTS: Medical reasons (32/190, 16.8%) and forgetfulness (20/190, 10.5%) were the most frequent reasons for non-attendance. Major issues included non-avoidable events while others were potentially preventable and could be addressed by the service. CONCLUSIONS: The analysis of mobile communications in clinical practice can be used for service evaluation and to reveal barriers that impede attendance to ongoing care.

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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.

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