Understanding the causes of missingness in primary care: a realist review.

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.

Associations between Missed Colonoscopy Appointments and Multiple Prior Adherence Behaviors in an Integrated Healthcare System: An Observational Study.

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.

Childcare needs as a barrier to healthcare among women in a safety-net health system.

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.

Cross-sectional analysis of primary care clinics' policies, practices, and availability of patient support services during the COVID-19 pandemic.

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.

Decision analysis framework for predicting no-shows to appointments using machine learning algorithms.

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.

Investigating How the Use of Technology Can Reduce Missed Appointments: Quantitative Case Study at a General Practitioner Surgery.

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.

Reducing No-Show Appointments in Preanesthesia Screening.

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.

Behaviourally informed, patient-led interventions to reduce missed appointments in general practice: a 12-month implementation study.

BACKGROUND: Scalable, positive, behaviourally informed interventions may help people remember to attend their primary care appointment or cancel in good time, but have not yet been implemented long term. AIM: To examine effects of social norms and making active commitments on missed and cancelled appointments in primary care over 12 months and explore implementation factors. DESIGN AND SETTING: A mixed-methods design evaluation and implementation study led by a Patient Participation Group (PPG) member in a large GP practice in the West Midlands. METHODS: Following a 6-month baseline, waiting room notices were redesigned to emphasise positive social norms for desired behaviours. When booking appointments, receptionists were trained to invite patients to (i) verbally actively commit to cancelling if needed; (ii) write down their own appointment details. Monthly missed appointments (MAs) and cancellations were statistically compared with baseline averages and seasonally equivalent months. To explore implementation, reception staff completed a knowledge, attitude, and behaviour questionnaire at 9 months, analysed descriptively. Study team field notes were thematically analysed. RESULTS: Across 12 intervention months there was a mean of 37.67 fewer MAs per month (20% reduction) and 102.66 more cancellations (21.07% increase) compared with 6-month baseline means [MAs t(11) = -6.15, P < 0.001; cancellations t(11) = 3.637, P = 0.004] with statistically significant differences in seasonally equivalent months [MAs t(5) = -4.65, P = 0.006; cancellations t(5) = 3.263, P = 0.022]. Receptionists (n = 12) reported implementing the strategies except when facing pressures; knowledge and attitudes varied. CONCLUSIONS: Behaviourally informed interventions reduced primary care MAs longer term; PPGs and practice teams can work together on quality improvement projects with support from leaders to prioritise and embed new practices.

The impact of the COVID-19 pandemic on rates and predictors of missed hospital appointments in multiple outpatient clinics of The Royal Hospital, Sultanate of Oman: a retrospective study.

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.

Factors associated with appointment 'no-shows' at two tertiary level outpatient oculoplastic clinics.

PURPOSE: Appointment no-shows in clinics can adversely impact patients and physicians alike. This study aimed to determine the rate and potential causes of missed appointments in oculoplastic clinics and compare a private practice and hospital-based academic setting. METHODS: A retrospective review of patients who booked appointments for oculoplastic consultation, between August 2019 and January 2020 at two oculoplastic clinics was performed. Demographic and patient-specific characteristics of patients who failed to attend their appointment were identified. Data were analysed to determine and compare the no-show rates in both clinics and logistic regression was performed to determine factors associated with them. RESULTS: The rate of missed appointments was 3% and 17% at the oculoplastic clinics of Lions Eye Institute (LEI, private practice) and Albany Medical Center (AMC, academic hospital-based office), respectively. Patients at the AMC clinic were more likely to be male, younger, have a lower household income, not carry private insurance, and suffer from trauma. Logistic regression analysis showed lower patient age to significantly increase the likelihood of no-shows in both clinics (p = .01 for LEI, p = .003 for AMC), and lead appointment time greater than 90 days to be a significant risk factor for no-shows at LEI (p = .01). CONCLUSIONS: The no-show rate for oculoplastic appointments is 3% and 17% at LEI and AMC clinics, respectively. Our analysis shows that younger patients are more likely to miss appointments at both clinics, and an appointment lead time greater than 90 days is a significant risk factor for no-shows at LEI.

Closing the Gap: The Role of Discharge Nurses in an Emergency Department.

INTRODUCTION: Patients discharged from the emergency department may require a follow-up appointment with an outpatient specialty clinic. Referral processes vary by clinic, some requiring faxed referrals, some providing appointments immediately, and others contacting the patients directly. The frequency with which patients are successfully connected with outpatient follow-up services is largely unknown. METHODS: The ED discharge nurse role was developed to facilitate the navigation of patient follow-up and confirm that patients successfully connect with specialty outpatient clinics. Eight emergency nurses were recruited into this position to study the problem using a quality improvement approach. The ED discharge nurses reviewed referrals, contacted clinics and patients discharged from the emergency department, and intervened when barriers to transition occurred. RESULTS: The ED discharge nurses were able to determine specific causes and themes of missed appointments experienced by patients. Systemic problems identified include lost faxes, illegible contact information, incomplete referrals, and referral refusals by the clinics without patient notification. Considering the variability of clinic processes outside the emergency department's control, the ED discharge nurse role became crucial in minimizing the risk of lost/unsuccessful follow-up for patients discharged from the emergency department. DISCUSSION: Implementing the ED discharge nurse role created a contact for outpatient clinic referrals, patient inquiry, and a process to track errors and data to better understand the frequency of missed follow-up. In this quality improvement initiative, the role of the ED discharge nurse addressed the risk of patients falling through the cracks of a complex system.

Missed initial appointments at Israeli child development centres: Rate, reasons, and associated characteristics.

INTRODUCTION: Missed appointments (MAs) at child development centres (ChDCs) cause multiple problems: they preclude timely diagnosis and treatment of both the invited child and children whose appointment was delayed due to overbooking, as well as disrupting efficient organisational management. The aim of this study was to assess the rate and describe the reasons for missed appointments at Israeli ChDCs, and to evaluate the association of socio-demographic, clinical, and administrative variables with MA rates. METHODS: This nested case-control study included all children scheduled for initial appointments (N = 1143) at three centres during 1 year. Parents of children who missed their appointment and a sample of those who attended were interviewed by telephone. RESULTS: The rate of missed appointments was 26.6%, and the most frequent reasons were unexpected events (26.0%) and lack of insurance coverage (23.4%). Variables associated with lower MA rates were: having had ≥3 types of rehabilitative interventions (odds ratios (OR) = 0.26; 95% confidence interval [CI] 0.16-0.44), detailed referral letter (OR = 0.48; 95%CI 0.30-0.75), telephone reminder (OR = 0.37; 95%CI 0.24-0.57) and health maintenance organisations or private insurance coverage (OR = 0.12; 95%CI 0.06-0.17 and OR = 0.56; 95% CI 0.38-0.89, respectively). CONCLUSION: Encouraging physician's referral letters and personal-contact reminders can reduce missed appointments. Understanding the family's and the child's personal characteristics, and the organisational/administrative aspects of missed appointments may guide efforts to ensure timely care for every child.

Educational associations with missed GP appointments for patients under 35 years old: administrative data linkage study.

BACKGROUND: There is an evidence gap about whether levels of engagement with public services such as schools and health care affect people across the lifespan. Data on missed patient appointments from a nationally representative sample of Scottish general practices (GP) (2013-2016) were probabilistically linked to secondary school pupil data. We tested whether school attendance, exclusions (2007-2011) or lower educational attainment (2007-2016) was associated with an increased risk of missing general practice appointments. METHODS: School attendance data were classified into quartiles of possible days attended for years we had data. School exclusions were derived as a categorical variable of 'ever excluded'. Attainment data were categorised via the Scottish Credit and Qualifications Framework (SCQF) level 3 or 6; a cumulative measure of attainment on leaving school. The associations between school attendance, exclusions and attainment and risk of missing medical appointments were investigated using negative binomial models, offset by number of GP appointments made and controlling for potential confounders. RESULTS: 112,534 patients (all aged under 35) had GP appointment and retrospective school attendance and exclusion data, and a subset of 66,967 also had attainment data available. Patients who had lower attendance, had been excluded from school or had lower educational attainment had an increased risk of missing GP appointments (all rate ratios > 1.40). CONCLUSIONS: This study provides the first evidence from a population-representative sample in a high-income country that increased numbers of missed appointments in health care are associated with reduced school attendance, higher levels of school exclusion and lower educational attainment. Insights into the epidemiology of missingness across public services can support future research, policy and practice that aim to improve healthcare, health outcomes and engagement in services.

Enhancing Usability of Appointment Reminders: Qualitative Interviews of Patients Receiving Care in the Veterans Health Administration.

BACKGROUND: No-shows are a persistent and costly problem in all healthcare systems. Because forgetting is a common cause of no-shows, appointment reminders are widely used. However, qualitative research examining appointment reminders and how to improve them is lacking. OBJECTIVE: To understand how patients experience appointment reminders as part of intervention development for a pragmatic trial of enhanced appointment reminders. DESIGN: Qualitative content analysis PARTICIPANTS: Twenty-seven patients at a single Department of Veterans Affairs hospital and its satellite clinics APPROACH: We conducted five waves of interviews using rapid qualitative analysis, in each wave continuing to ask veterans about their experience of reminders. We double-coded all interviews, used deductive and inductive content analysis to identify themes, and selected quotations that exemplified three themes (limitations, strategies, recommendations). KEY RESULTS: Interviews showed four limitations on the usability of current appointment reminders which may contribute to no-shows: (1) excessive information within reminders; (2) frustrating telephone systems when calling in response to an appointment reminder; (3) missing or cryptic information about clinic logistics; and (4) reminder fatigue. Patients who were successful at keeping appointments often used specific strategies to optimize the usability of reminders, including (1) using a calendar; (2) heightening visibility; (3) piggybacking; and (4) combining strategies. Our recommendations to enhance reminders are as follows: (1) mix up their content and format; (2) keep them short and simple; (3) add a personal touch; (4) include specifics on clinic location and contact information; (5) time reminders based on the mode of delivery; and (6) hand over control of reminders to patients. CONCLUSIONS: Appointment reminders are vital to prevent no-shows, but their usability is not optimized for patients. There is potential for healthcare systems to modify several aspects of the content, timing, and delivery of appointment reminders to be more effective and patient-centered.

Reduced No-Show Rates and Sustained Patient Satisfaction of Telehealth During the COVID-19 Pandemic.

Introduction: The unprecedented COVID-19 pandemic has thrust telehealth into the center stage of health care, leading to a dramatic increase in utilization of telehealth services. The impact of telehealth on patient satisfaction during the current pandemic is yet to be fully understood. Objective: This study aimed to identify patient perspectives and behaviors toward virtual primary care appointments at a telehealth-naïve institution during the COVID-19 pandemic and establish the rate of missed appointments to help guide future implementation of telehealth services. Methods: Patients at a primary and specialty care clinic, seen between March and May 2020, completed a survey analyzing nine commonly used satisfaction metrics. The rate of missed appointments was recorded and compared with analogous cohorts of in-person office visits. Results: The no-show rate of telehealth visits during the COVID-19 pandemic was 7.5% (14/186), lower than both the no-show rate of 36.1% for in-office visits (56/155) (p < 0.0001) and a pre-pandemic in-office no-show rate of 29.8% (129/433) (p < 0.0001). Surveyed patients who experienced telehealth visits (n = 65) had similar satisfaction compared with those surveyed who attended in-office visits (n = 36) in seven of nine metrics. No statistically significant differences were identified in the satisfaction metrics with telehealth visits performed on video (n = 26) versus the phone-only format (n = 38). Patients aged 65 years or over were less likely to have a video component to their virtual visit (1/12, 8.3%) than those under age 65 (25/44, 56.8%) (p = 0.0031). Discussion/Conclusions: Telehealth offers significant benefits for both patients and providers, strongly supporting its widespread utilization both during and following the COVID-19 pandemic.

Morbidity, mortality and missed appointments in healthcare: a national retrospective data linkage study.

BACKGROUND: Recently, studies have examined the underlying patient and practice factors for missed appointments, but less is known about the impact on patient health. People with one or more long-term conditions who fail to attend appointments may be at risk of premature death. This is the first study to examine the effect of missed primary healthcare appointments on all-cause mortality in those with long-term mental and physical health conditions. METHODS: We used a large, nationwide retrospective cohort (n = 824,374) extracted from routinely collected general practice data across Scotland over a 3-year period from September 2013 until September 2016. This data encompasses appointment history for approximately 15% of the Scottish population, and was linked to Scottish deaths records for patients who had died within a 16-month follow-up period. We generated appointment attendance history, number of long-term conditions and prescriptions data for patients. These factors were used in negative binomial and Cox's proportional hazards modelling to examine the risk of missing appointments and all-cause mortality. RESULTS: Patients with a greater number of long-term conditions had an increased risk of missing general practice appointments despite controlling for number of appointments made, particularly among patients with mental health conditions. These patients were at significantly greater risk of all-cause mortality, and showed a dose-based response with increasing number of missed appointments. Patients with long-term mental health conditions who missed more than two appointments per year had a greater than 8-fold increase in risk of all-cause mortality compared with those who missed no appointments. These patients died prematurely, commonly from non-natural external factors such as suicide. CONCLUSIONS: Missed appointments represent a significant risk marker for all-cause mortality, particularly in patients with mental health conditions. For these patients, existing primary healthcare appointment systems are ineffective. Future interventions should be developed with a particular focus on increasing attendance by these patients.

The impact of personalized reminders in addition to an automated patient reminder system on pediatric dermatology no-show rates: A pilot study.

We investigated the impact of a personalized telephone call reminder for patients that had not confirmed their clinic appointment, in addition to automated reminders, on monthly no-show rates. Our data revealed a reduction in the monthly no-show rate from 16.0% (SD = 3.91%) before the intervention to 13.1% (SD = 0.27%, P = 0.0997) after the intervention, which was not statistically significant. The standard deviation of the no-show rate with the intervention was reduced, leading to a predictable monthly no-show rate (range 12.93%-13.51%). Thus, the number of patients attending clinic was more predictable. This study highlights the need for additional investigation of factors associated with appointment nonadherence in pediatric dermatology.

Sociodemographic Predictors of Missed Appointments Among Patients With Cleft Lip and Palate.

OBJECTIVE: To identify disparities in compliance of and care for patients with cleft lip and/or palate (CL/P) by determining the impact of sociodemographic variables on the rate of missed appointments and Child Protective Services (CPS) involvement. DESIGN: A retrospective, noninterventional quality assessment and quality improvement study were designed. SETTING: This institutional study was performed at the University of Michigan in Ann Arbor, Michigan. PATIENTS: All patients born between January 1, 2011, and December 31, 2014, who underwent surgical CL/P repair, excluding those with fewer than 5 appointments (n = 178). MAIN OUTCOME MEASURE: The rate of missed appointments, calculated as the total number of no-show appointments divided by the total number of scheduled appointments. All appointments from CL/P diagnosis to data collection were considered, including those outside of plastic surgery. RESULTS: The average patient was 4.5 years of age and had 49 total scheduled appointments. The overall rate of missed appointments was 9.6%, with 66.8% of patients missing at least 1 scheduled visit. Patients who were black ( P = .04), not affiliated with a religion ( P = .01), Medicaid users ( P = .01), from an unstable social background ( P = .01), or received need-based financial assistance ( P = .00) were significantly more likely to miss appointments. Child Protective Services was involved with 3.9% of patients. CONCLUSIONS: Disparities exist in attendance rates among patients with CL/P, and at-risk patient populations have been identified. The allocation of cleft care resources must be efficiently planned in order to enhance the quality of care for at-risk individuals.

A missed primary care appointment correlates with a subsequent emergency department visit among children with asthma.

OBJECTIVE: Since the Affordable Care Act's implementation, emergency department (ED) visits have increased. Poor asthma control increases the risk of acute exacerbations and preventable ED visits. The Centers for Medicare and Medicaid Services support the reduction of preventable ED visits to reduce healthcare spending. Implementation of interventions to avoid preventable ED visits has become a priority for many healthcare systems yet little data exist examining children's missed asthma management primary care (PC) appointments and subsequent ED visits. METHODS: Longitudinal, retrospective review at a children's hospital was conducted for children with diagnosed asthma (ICD-9 493.xx), ages 2-18 years, scheduled for a PC visit between January 1, 2010, and June 30, 2012 (N = 3895). Records were cross-referenced with all asthma-related ED visits from January 1, 2010 to December 31, 2012. Logistic regression with maximum likelihood estimation was conducted. RESULTS: None of the children who completed a PC appointment experienced an ED visit in the subsequent 6 months whereas 2.7% of those with missed PC appointments had an ED visit (χ2 = 64.28, p <.0001). Males were significantly more likely to have an ED visit following a missed PC appointment than females (χ2 = 34.37, p <.0001). There was a statistically significant interaction of sex × age. Younger children (<12 years) made more visits than older children. CONCLUSIONS: The importance of adherence to PC appointments for children with asthma as one mechanism for preventing ED visits was demonstrated. Interventions targeting missed visits could decrease asthma-related morbidity, preventable ED visits, and healthcare costs.

Reasons for missed appointments linked to a public-sector intervention targeting patients with stable chronic conditions in South Africa: results from in-depth interviews and a retrospective review of medical records.

BACKGROUND: Missed appointments serve as a key indicator for adherence to therapy and as such, identifying patient reasons for this inconsistency could assist in developing programmes to improve health outcomes. In this article, we explore the reasons for missed appointments linked to a centralised dispensing system in South Africa. This system dispenses pre-packed, patient-specific medication parcels for clinically stable patients to health facilities. However, at least 8%-12% of about 300,000 parcels are not collected each month. This article aims to establish whether missed appointments for collection of medicine parcels are indicative of loss-to-follow-up and also to characterise the patient and health system factors linked to missed appointments. METHODS: We applied an exploratory mixed-methods design in two overlapping research phases. This involved in-depth interviews to yield healthcare practitioners' and patients' experiences and medical record reviews. Data collection was conducted during the period 2014-2015. Qualitative data were analysed through a hybrid process of inductive and deductive thematic analysis which integrated data-driven and theory-driven codes. Data from medical records (N = 89) were analysed in MS excel using both descriptive statistics and textual descriptions. RESULTS: Review of medical records suggests that the majority of patients (67%) who missed original appointments later presented voluntarily to obtain medicines. This could indicate a temporal effect of some barriers. The remaining 33% revealed a range of CDU implementation issues resulting from, among others, erroneous classification of patients as defaulters. Interviews with patients revealed the following reasons for missed appointments: temporary migration, forgetting appointments, work commitments and temporary switch to private care. Most healthcare practitioners confirmed these barriers to collection but perceived that some were beyond the scope of health services. In addition, healthcare practitioners also identified a lack of patient responsibility, under-utilisation of medicines and use of plural healthcare sources (e.g. traditional healers) as contributing to missed appointments. CONCLUSION: We suggest developing a patient care model reflecting the  local context, attention to improving CDU's implementation processes and strengthening information systems in order to improve patient monitoring. This model presents lessons for other low-and-middle income countries with increasing need for dispensing of medicines for chronic illnesses.