Reasons for and consequences of missed appointments in general practice in the UK: questionnaire survey and prospective review of medical records

Exploring the appointment factors affecting pediatric patients with swallow disorders: Implications for speech and language pathology attendance

INTRODUCTION

Feeding and swallowing disorders have become increasingly prevalent among children, necessitating effective management to prevent long-term complications. Speech and language pathology (SLP) services play a crucial role in diagnosing and treating these disorders. The objective of this study was to explore the factors that influence patient attendance to SLP appointments for swallow disorders.

METHODS

This study was conducted at Boston Medical Center, involving 359 pediatric patients referred to SLP for swallow-related concerns. De-identified patient and appointment information was obtained from the electronic medical record. Various factors such as age, gender, race/ethnicity, primary language, appointment date/time, and COVID-19 lockdown status were analyzed to determine their impact on patient no-shows. Statistical analyses, including Chi-Square tests and binary logistic regression, were conducted using appropriate methodologies.

RESULTS

355 individual patient records were included in the analysis. Lockdown status and appointment time of day did not significantly affect patient no-shows. However, appointments conducted through telemedicine showed a significant difference in attendance. Patient referral department, gender, race, language, and being born at the medical center did not significantly influence patient attendance. Notably, having a primary care provider (PCP) at the medical center significantly affected patient attendance. Furthermore, previous appointment cancellations made a patient more likely to no-show.

CONCLUSION

This study provides valuable insights into the factors influencing patient attendance at SLP appointments for pediatric swallowing disorders. Having a PCP at the medical center and utilizing telemedicine appointments were associated with higher attendance rates. Addressing appointment cancellations and investigating underlying reasons behind missed appointments should be prioritized in future research. Understanding these factors will facilitate the development of interventions to optimize patient attendance and improve the delivery of SLP services in pediatric populations.

Reasons for non-attendance in youth mental health clinics: Insights from mobile messaging communications

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.

Application of a Machine Learning Algorithm to Develop and Validate a Prediction Model for Ambulatory Non-Arrivals

BACKGROUND

Non-arrivals to scheduled ambulatory visits are common and lead to a discontinuity of care, poor health outcomes, and increased subsequent healthcare utilization. Reducing non-arrivals is important given their association with poorer health outcomes and cost to health systems.

OBJECTIVE

To develop and validate a prediction model for ambulatory non-arrivals.

DESIGN

Retrospective cohort study.

PATIENTS OR SUBJECTS

Patients at an integrated health system who had an outpatient visit scheduled from January 1, 2020, to February 28, 2022.

MAIN MEASURES

Non-arrivals to scheduled appointments.

KEY RESULTS

There were over 4.3 million ambulatory appointments from 1.2 million adult patients. Patients with appointment non-arrivals were more likely to be single, racial/ethnic minorities, and not having an established primary care provider compared to those who arrived at their appointments. A prediction model using the XGBoost machine learning algorithm had the highest AUC value (0.768 [0.767-0.770]). Using SHAP values, the most impactful features in the model include rescheduled appointments, lead time (number of days from scheduled to appointment date), appointment provider, number of days since last appointment with the same department, and a patient's prior appointment status within the same department. Scheduling visits close to an appointment date is predicted to be less likely to result in a non-arrival. Overall, the prediction model calibrated well for each department, especially over the operationally relevant probability range of 0 to 40%. Departments with fewer observations and lower non-arrival rates generally had a worse calibration.

CONCLUSIONS

Using a machine learning algorithm, we developed a prediction model for non-arrivals to scheduled ambulatory appointments usable for all medical specialties. The proposed prediction model can be deployed within an electronic health system or integrated into other dashboards to reduce non-arrivals. Future work will focus on the implementation and application of the model to reduce non-arrivals.

Associations between symptoms with healthcare utilization and death in advanced cancer patients

INTRODUCTION

There is limited data about assessments that are associated with increased utilization of medical services among advanced oncology patients (AOPs). We aimed to identify factors related to healthcare utilization and death in AOP.

METHODS

AOPs at a comprehensive cancer center were enrolled in a Center for Medicare and Medicaid Innovation program. Participants completed the Edmonton Symptom Assessment Scale (ESAS) and the Functional Assessment of Cancer Therapy-General (FACT-G) scale. We examined factors associated with palliative care (PC), acute care (AC), emergency room (ER), hospital admissions (HA), and death.

RESULTS

In all, 817 AOPs were included in these analyses with a median age of 69. They were generally female (58.7%), white (61.4%), stage IV (51.6%), and represented common cancers (31.5% GI, 25.2% thoracic, 14.3% gynecologic). ESAS pain, anxiety, and total score were related to more PC visits (B=0.31, 95% CI [0.21, 0.40], p<0.001; B=0.24 [0.12, 0.36], p<0.001; and B=0.038 [0.02, 0.06], p=0.001, respectively). Total FACT-G score and physical subscale were related to total PC visits (B=-0.021 [-0.037, -0.006], p=0.008 and B=-0.181 [-0.246, -0.117], p<0.001, respectively). Lower FACT-G social subscale scores were related to more ER visits (B=-0.03 [-0.53, -0.004], p=0.024), while increased tiredness was associated with fewer AC visits (B=-0.039 [-0.073, -0.006], p=0.023). Higher total ESAS scores were related to death within 30 days (OR=0.87 [0.76, 0.98], p=0.027).

CONCLUSIONS

The ESAS and FACT-G assessments were linked to PC and AC visits and death. These assessments may be useful for identifying AOPs that would benefit from routine PC.

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.

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.

Predicting no-show appointments in a pediatric hospital in Chile using machine learning

The Chilean public health system serves 74% of the country's population, and 19% of medical appointments are missed on average because of no-shows. The national goal is 15%, which coincides with the average no-show rate reported in the private healthcare system. Our case study, Doctor Luis Calvo Mackenna Hospital, is a public high-complexity pediatric hospital and teaching center in Santiago, Chile. Historically, it has had high no-show rates, up to 29% in certain medical specialties. Using machine learning algorithms to predict no-shows of pediatric patients in terms of demographic, social, and historical variables. To propose and evaluate metrics to assess these models, accounting for the cost-effective impact of possible intervention strategies to reduce no-shows. We analyze the relationship between a no-show and demographic, social, and historical variables, between 2015 and 2018, through the following traditional machine learning algorithms: Random Forest, Logistic Regression, Support Vector Machines, AdaBoost and algorithms to alleviate the problem of class imbalance, such as RUS Boost, Balanced Random Forest, Balanced Bagging and Easy Ensemble. These class imbalances arise from the relatively low number of no-shows to the total number of appointments. Instead of the default thresholds used by each method, we computed alternative ones via the minimization of a weighted average of type I and II errors based on cost-effectiveness criteria. 20.4% of the 395,963 appointments considered presented no-shows, with ophthalmology showing the highest rate among specialties at 29.1%. Patients in the most deprived socioeconomic group according to their insurance type and commune of residence and those in their second infancy had the highest no-show rate. The history of non-attendance is strongly related to future no-shows. An 8-week experimental design measured a decrease in no-shows of 10.3 percentage points when using our reminder strategy compared to a control group. Among the variables analyzed, those related to patients' historical behavior, the reservation delay from the creation of the appointment, and variables that can be associated with the most disadvantaged socioeconomic group, are the most relevant to predict a no-show. Moreover, the introduction of new cost-effective metrics significantly impacts the validity of our prediction models. Using a prototype to call patients with the highest risk of no-shows resulted in a noticeable decrease in the overall no-show rate.

Pediatric Practices' Perceptions of Text Message Communication with Families: An American Academy of Pediatrics (AAP), Pediatric Research in Office Settings (PROS) Study

Background

Text messages can be an effective and low-cost mechanism for patient reminders; however, they are yet to be consistently integrated into pediatric primary care.

Objective

The aim of this study was to explore pediatric primary care clinician and staff perceptions of pediatric office text message communication with families.

Methods

As part of the National Institutes of Health-funded Flu2Text randomized controlled trial of second-dose influenza vaccine text message reminders, we conducted 7 focus groups and 4 individual interviews in July-August 2019 with primary care pediatric clinicians and staff (n = 39). Overall, 10 Pediatric Research in Office Settings (PROS) pediatric practices in 10 states were selected using stratified sampling. Semi-structured discussion guides included perspectives on possible uses, perceived usefulness, and ease of use of text messages; practices' current text messaging infrastructure; and perceived barriers/facilitators to future use of texting. Two investigators independently coded and analyzed transcripts based on the technology acceptance model using NVIVO 12 Plus (intercoder reliability, K = 0.86).

Results

Overall, participants were supportive of text reminders for the second-dose influenza vaccine, other vaccines, and appointments and perceived texting as a preferred method of communication for caregivers. Health information privacy and patient confidentiality were the main concerns cited. Only respondents from practices with no internal appointment text message reminder system prior to the study expressed concerns about technology implementation logistics, time, and cost.

Conclusion

Text message reminders, for various uses, appear to be well accepted among a group of geographically widespread pediatric practices after participation in a trial of influenza vaccine text message reminders. Privacy, confidentiality, and resource barriers need to be addressed to facilitate successful implementation.

Hearing healthcare for workers with hearing loss: audiologists' experiences and views

PURPOSE

This study explored audiologists' perspectives regarding their interactions with workers with hearing loss (WHL).

MATERIALS AND METHODS

Semi-structured interviews were conducted with twenty-five audiologists working in the National Health Service (NHS) and independent companies (IC) in the UK and were thematically analysed.

RESULTS

The developed themes and sub-themes (shown in parenthesis) are (1) Current practices and routines (Same approach for most patients; Variations between hearing care services; Audiologists' personal experience of hearing loss) (2) Perceived challenges (Non-routine and challenging cases; The role of hearing technology; Concerns about lack of awareness and knowledge; Communication difficulties between services, Limited funding and resources) (3) Scope for better support (Would like to be informed; Other potential service improvements).

CONCLUSIONS

This study revealed that audiologists' perceived deficiencies in the hearing rehabilitation for WHL and identified ways to improve it. Key priorities for improvement were found to include addressing audiologists' informational and training needs, facilitating WHLs' access to appointments, improving communication between services, raising awareness in the workplace, developing relevant resources and extending funding for provision of longer appointments and hearing technologies. This is the first time this information has been reported in the literature. Opportunities for conducting further research in this area are suggested.Implications for rehabilitationWorkers with hearing loss face many challenges in work life and have the option of audiologic rehabilitation to alleviate their difficulties and improve their wellbeing; however, this study suggests that workers' audiological care needs improvements.Audiologists should assess and consider patients' work needs and psychosocial concerns in consultations to provide personalised care.Audiology educational programmes, services, and the healthcare system can assist audiologists in helping workers with hearing loss by providing updated knowledge, continuous training and improved interprofessional communication and patients' access to useful resources.

Development and validation of a social vulnerabilities survey for medical inpatients

OBJECTIVES

Our objective was to validate a Social Vulnerabilities Survey that was developed to identify patient barriers in the following domains: (1) salience or priority of health; (2) social support; (3) transportation; and (4) finances.

DESIGN

Cross-sectional psychometric study.Questions for one domain (health salience) were developed de novo while questions for the other domains were derived from national surveys and/or previously validated questionnaires. We tested construct (ie, convergent and discriminative) validity for these new questions through hypothesis testing of correlations between question responses and patient characteristics. Exploratory factor analysis was conducted to determine structural validity of the survey as a whole.

SETTING

Patients admitted to the inpatient internal medicine service at a tertiary care hospital in Calgary, Canada.

PARTICIPANTS

A total of 406 patients were included in the study.

RESULTS

The mean age of respondents was 55.5 (SD 18.6) years, with the majority being men (55.4%). In feasibility testing of the first 107 patients, the Social Vulnerabilities Survey was felt to be acceptable, comprehensive and met face validity. Hypothesis testing of the health salience questions revealed that the majority of observed correlations were exactly as predicted. Exploratory factor analysis of the global survey revealed the presence of five factors (eigenvalue >1): social support, health salience, drug insurance, transportation barriers and drug costs. All but four questions loaded to these five factors.

CONCLUSIONS

The Social Vulnerabilities Survey has face, construct and structural validity. It can be used to measure modifiable social vulnerabilities, such that their effects on health outcomes can be explored and understood.

Evaluating the reasons for nonattendance to outpatient consultations: is waiting time an important factor?

Background

 Nonattendance is a common problem worldwide. Important factors for nonattendance are a queue or the waiting time until the planned service.

Aims

The aims of this study were to identify the reasons for nonattendance to planned consultations, assess the waiting time from registration to access to an outpatient specialist consultation, and identify the associations between the reasons for nonattendance and the waiting time until the planned outpatient specialist consultation.

Methods

A cross-sectional study based on a phone questionnaire was conducted among patients not attending a planned consultation at the outpatient department of the Lithuanian University of Health Sciences Kaunas Hospital in Kaunas, Lithuania. A total of 972 phone calls were made, and 389 telephone surveys were completed.

Results

The mean respondents’ waiting time until the planned outpatient consultation was 15.13 ± 10 days. The highest proportion of nonattendance was observed when the wait time was between 6 and 17 days.

More often, the patients did not attend the planned outpatient consultation due to worsened health status (24.69%), unidentified personal problems (14.91%), work-related problems (13.62%) and being unaware about the appointment (11.82%). A longer waiting time was significantly associated with the following reasons for nonattendance: work-related problems, health problems solved at another health care institution, unidentified personal problems and unknown reasons for nonattendance. The highest proportions of nonattending patients had consultations registered with neurologists (17.0%), traumatologists (11.3%) and cardiologists (10.5%).

Conclusions

Patients did not identify the long waiting time until outpatient specialist consultation among the main reasons for nonattendance. The issue of waiting time is not an important aspect of nonattendance.

Predictors of No-Show in Neurology Clinics

In this study, we aim to identify predictors of a no-show in neurology clinics at our institution. We conducted a retrospective review of neurology clinics from July 2013 through September 2018. We compared odds ratio of patients who missed appointments (no-show) to those who were present at appointments (show) in terms of age, lead-time, subspecialty, race, gender, quarter of the year, insurance type, and distance from hospital. There were 60,012 (84%) show and 11,166 (16%) no-show patients. With each day increase in lead time, odds of no-show increased by a factor of 1.0019 (p < 0.0001). Odds of no-show were higher in younger (p ≤ 0.0001, OR = 0.49) compared to older (age ≥ 60) patients and in women (p < 0.001, OR = 1.1352) compared to men. They were higher in Black/African American (p < 0.0001, OR = 1.4712) and lower in Asian (p = 0.03, OR = 0.6871) and American Indian/Alaskan Native (p = 0.055, OR = 0.6318) as compared to White/Caucasian. Patients with Medicare (p < 0.0001, OR = 1.5127) and Medicaid (p < 0.0001, OR = 1.3354) had higher odds of no-show compared to other insurance. Young age, female, Black/African American, long lead time to clinic appointments, Medicaid/Medicare insurance, and certain subspecialties (resident and stroke clinics) are associated with high odds of no show. Possible suggested interventions include better communication and flexible appointments for the high-risk groups as well as utilizing telemedicine.

Investigating the reasons for missing an outpatient appointment in Royal Hospital, Sultanate of Oman: Perspectives of patients and medical staff in a survey

Introduction

Missed appointments are a major health issue in the healthcare systems globally. They directly impact on the use of hospital resources, patient's health, and can lead to patient's dissatisfaction. This study was conducted to assess the reasons for missing a hospital appointment.

Methods

A survey was conducted with a randomly selected sample of patients who missed their outpatient appointment in Royal hospital, Sultanate of Oman, from March to April 2021 in six clinics. Patients were interviewed via telephone to answer a structured survey. In addition, a self‐administered survey was distributed to medical staff to explore their perspectives.

Results

Two hundred eighty patients and 52 medical staff participated in the study. Frequent patient‐reported reasons for missed appointment were transportation difficulties (11.4%), no longer needing (7.5%), or forgetting the appointment (6.8%); staff‐reported reasons were transportation (23.8%), no SMS received (16.9%), and forgetting the appointment (15.4%). Frequencies of reasons varied substantially between clinics. Family obligations were the main theme in obstetrics (odds ratio [OR] 9.48; 95% confidence interval [CI] 2.66‐33.78) and in diabetes clinic (OR 10.55; 95% CI 2.68‐38.58), where transportation issue was the main theme in Oncology clinic (OR 4.83; 95% CI 1.11‐21.02). The recommendations for improvement were mainly around improving the reminder system, the use of telephone reminders, and developing a flexible appointment scheduling system.

Conclusion

Knowing the reasons for missed appointment from patients and health professionals can help to develop effective interventions. The heterogeneity between clinics in reasons for missed appointment indicates for interventions tailored to clinic and frequent reasons.

Sociodemographic predictors of attendance at a Scottish pain management programme

We examined relationships between various sociodemographic factors and attendance at the Glasgow Pain Management Programme (n = 2899 from 2011 to 2019). We tested for associations between gender, age and socioeconomic deprivation of patients who were invited to attend, and uptake to a programme when invited, attendance at screening assessment, eligibility, adherence and attendance at 3- and 6-month reviews. Uptake was significantly higher for patients from more affluent areas (95% confidence interval (CI) = 0.93–0.99, p = 0.002) and for older patients (95% CI = 0.98–0.99, p = 0.006), although effect sizes were very small. Patients were significantly more likely to be assessed as suitable if they were younger (95% CI = 0.98–0.99, p = 0.013) or female (95% CI = 0.55–0.84, p < 0.001). Attendance at sessions and at 3- and 6-month reviews was higher for patients from more affluent areas (95% CI = 1–1.09, p = 0.001, and 95% CI = 1–1.1, p = 0.044 respectively). We argue that there are multiple potential explanations for these findings and that future work should attempt to determine whether these patterns replicate in other populations and to determine any modifiable causes.

Demographic and Clinical Factors Are Associated Wwith Frequent Short-Notice Cancellations in Veterans with Multiple Sclerosis on Disease Modifying Therapies

OBJECTIVES

(1) To identify the rate of short-notice canceled appointments in a large national sample of persons with multiple sclerosis (MS) and (2) examine the demographic and clinical factors associated with frequent cancellations.

DESIGN

Retrospective cross-sectional cohort using electronic health records.

SETTING

Veterans Health Administration.

PARTICIPANTS

Veterans with MS (N=3742) who were part of the Veterans Health Administraiton's MS Center of Excellence Data Repository and (1) had at least one outpatient appointment at the VA in 2013, (2) were alive in 2015, and (3) were prescribed a disease modifying therapy (DMT).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Frequent short-notice cancellations, defined as >20% of scheduled appointments canceled with less than 24-hour notification over a 24-month period. This threshold was based on the definition of ≤80% for suboptimal treatment adherence. Several demographics and clinical variables were examined as potential explanatory factors.

RESULTS

Approximately 75% (n=2827) had at least 1 short-notice cancellation, with more than 3% (n=117) categorized as frequent cancelers. The odds of frequent cancellations were greater in women (odds ratio [OR], 1.81; P=.004) and among 18- to 44-year-olds (OR, 2.77; P=.004) and 45- to 64-year-olds (OR, 2.49; P=.003) compared to those over 65. The odds were lower among persons who lived <25 miles away (OR, 0.58; P=.043) compared with persons who lived ≥75 miles away and those who had at least 1 emergency department visit (OR, 0.55; P=.012).

CONCLUSIONS

Short-notice cancellations are common in persons with MS, although few have more than 20%. These findings highlight who is at greater risk for frequent cancellation and disruptions in their care. Although additional research is needed, the results provide insights into how clinics may approach handling frequent short-notice cancellations among persons with MS.

Adherence to TB treatment remains low during continuation phase among adult patients in Northwest Ethiopia

BACKGROUND

Patients' failure to adhere to TB treatment was a major challenge that leads to poor treatment outcomes. In Ethiopia, TB treatment success was low as compared with the global threshold. Despite various studies done in TB treatment adherence, little was known specifically in continuation phase where TB treatment is mainly patient-centered. This study aimed to determine adherence to TB treatment and its determinants among adult patients during continuation phase.

METHODS

We deployed a facility-based cross-sectional study design supplemented with qualitative data to explore perspectives of focal healthcare providers. The study population was all adult (≥18 years) TB patients enrolled in the continuation phase and focal healthcare workers in TB clinics. The study included 307 TB patients from 22 health facilities and nine TB focal healthcare providers purposively selected as key-informant. A short (11 questions) version Adherence to Refill and Medication Scale (ARMS) was used for measuring adherence. Data was collected using an interviewer-administered questionnaire and in-depth interview for qualitative data. Binary logistic regression was applied to identify factors associated with patient adherence. We followed a thematic analysis for the qualitative data. The audio data was transcribed, coded and categorized into themes using OpenCode software.

RESULTS

Among 307 participants, 64.2% (95% CI (58.6-69.4%) were adherent to TB treatment during continuation phase. A multi-variable analysis shown that secondary education (AOR = 4.138, 95% CI; 1.594-10.74); good provider-patient relationship (AOR = 1.863, 95% CI; 1.014-3.423); good knowledge on TB treatment (AOR = 1.845, 95% CI; 1.012-3.362) and middle family wealth (AOR = 2.646, 95% CI; 1.360-5.148) were significantly associated with adherence to TB treatment. The majority (58%) of patients mentioned forgetfulness, and followed by 17.3% of them traveling away from home without pills as major reasons for non-adherence to TB treatment.

CONCLUSIONS

The study indicated that patients' adherence to TB treatment remains low during continuation phase. The patient's education level, knowledge, family wealth, and provider-patient relationship were found positively associated with patient adherence. Forgetfulness, traveling away, and feeling sick were major reasons for non-adherence to TB treatment. Interventional studies are needed on those factors to improve patient adherence to TB treatment during continuation phase.

Facilitators and Barriers to Access to Pediatric Medical Services in a Community Hospital

Background: Missed medical appointments decrease continuity of medical care, waste resources, and may affect health outcomes. We examined the factors associated with missed children's supervision visits in Eastern Brooklyn, NY, USA. Methods: We surveyed guardians whose children received routine medical care at four pediatric clinics. Participants filled out a questionnaire that queried: demographics, food security, recent relocation, parental support of healthy behaviors, and length of knowing provider. Preexisting disease(s) and missed visits were retrieved from medical records. Regression analyses were used to determine factors that were associated with missing medical appointments. Results: Among 213 families, 33% faced food insecurity and 16.4% reported moving within the past 12 months. Forty percent of children missed at least 1 visit. Food insecurity (adjusted odds ratio [aOR] 2.3, 95% confidence interval [CI 1.0% to 5.2%) and recent relocation (aOR 1.8, 95% CI 1.1-3.4 were associated with missed health supervision visits, whereas greater parental healthy behaviors (aOR 0.5, 95% CI 0.3-0.9) and longer length of knowing provider (aOR 0.8, 95% CI 0.7-1.0) were associated with fewer missed appointments. Conclusion: This study indicates that social inequity may contribute to poor adherence to medical appointments through multiple mechanisms, including food insecurity, lack of social stability, and parental health behaviors. Multidimensional proactive prevention, and reactive tolerance should be considered as opportunities to mitigate the impact of social inequity on health outcomes.

Predicting non-attendance in hospital outpatient appointments using deep learning approach

The hospital outpatient non-attendance imposes a substantial financial burden on hospitals and roots in multiple diverse reasons. This research aims to build an advanced predictive model for predicting non-attendance regarding the whole spectrum of probable contributing factors to non-attendance that could be collated from heterogeneous sources including electronic patients records and external non-hospital data. We proposed a new non-attendance prediction model based on deep neural networks and machine learning models. The proposed approach works upon sparse stacked denoising autoencoders (SDAEs) to learn the underlying manifold of data and thereby compacting information and providing a better representation that can be utilised afterwards by other learning models as well. The proposed approach is evaluated over real hospital data and compared with several well-known and scalable machine learning models. The evaluation results reveal the proposed approach with softmax layer and logistic regression outperforms other methods in practice.

Which patients miss appointments with general practice and the reasons why: a systematic review

Background

Missed GP appointments have considerable time and cost implications for healthcare services.

Aim

This systematic review aims to explore the rate of missed primary care appointments, what the reported reasons are for appointments being missed, and which patients are more likely to miss appointments.

Design and setting

This study reports the findings of a systematic review. The included studies report the rate or reasons of missed appointments in a primary care setting.

Method

Databases were searched using a pre-defined search strategy. Eligible studies were selected for inclusion based on detailed inclusion criteria through title, abstract, and full text screening. Quality was assessed on all included studies, and findings were synthesised to answer the research questions.

Results

A total of 26 studies met the inclusion criteria for the review. Of these, 19 reported a rate of missed appointments. The mean rate of missed appointments was 15.2%, with a median of 12.9%. Twelve studies reported a reason that appointments were missed, with work or family/childcare commitments, forgetting the appointment, and transportation difficulties most commonly reported. In all, 20 studies reported characteristics of people likely to miss appointments. Patients who were likely to miss appointments were those from minority ethnicity, low sociodemographic status, and younger patients (<21 years).

Conclusion

Findings from this review have potential implications for targeted interventions to address missed appointments in primary care. This is the first step for clinicians to be able to target interventions to reduce the rate of missed appointments.

Transdiagnostic CBT versus counselling sessions: a naturalistic trial from Saudi Arabia

In a previous feasibility trial, we found that transdiagnostic cognitive behavioural therapy (T-CBT) showed promising results in improving emotional disorders in adults from Saudi Arabia. The primary aim of this study was to replicate these findings and compare T-CBT results with results for counselling sessions. The overall sample consisted of 276 patients (175 in the T-CBT group and 101 in the counselling group). Of the overall sample, 110 patients (39.9%) completed the treatment plan, and 166 (60.1%) disengaged from treatment. The pre- and post-assessments of the clients who completed the treatment showed large effect sizes for almost all outcome measures for both the T-CBT and counselling groups. For patients who decided to disengage from therapy, T-CBT had medium effect sizes for all three measures (depression, anxiety and function), while counselling sessions had medium effect size for the anxiety measure only. This study provides additional evidence that T-CBT is suitable for patients from Saudi Arabia with emotional disorders. The study also provides information regarding when and why T-CBT or counselling was applied in a real clinical setting. Implications and recommendations are discussed.

Key learning aims

(1)

Factors associated with dropout from treatment: An exploratory study

AIM

To evaluate the factors associated with treatment dropout among patients attending the psychiatric outpatient services.

MATERIALS AND METHODS

Seventy-two patients who dropped out from treatment were contacted and they were compared with 200 regular attendees for sociodemographic and clinical variables, medication adherence, treatment satisfaction, attitude toward medication, insight, and therapeutic alliance.

RESULTS

Compared to "regular attendees," those who dropped out from treatment were significantly older, were more likely to be married, had higher age of onset, had longer duration of illness, received less supervision for medication at home, higher proportion of them continued to remain symptomatic, had more negative attitude toward medications, had poorer insight, were poorly complaint with medication, were less satisfied with the treatment provided, and had poor quality of therapeutic alliance.

CONCLUSION

This study suggests that dropout from treatment can be avoided by addressing issues of negative attitude toward medications, improving satisfaction with the treatment contact and enhancing therapeutic alliance.

Association between attendance at outpatient follow-up appointments and blood pressure control among patients with hypertension

Objective

The aim of this study was to assess the impact of regularity in treatment follow-up appointments on treatment outcomes among hypertensive patients attending different healthcare settings in Islamabad, Pakistan. Additionally, factors associated with regularity in treatment follow-up were also identified.

Methods

A cross-sectional study was undertaken in selected primary, secondary and tertiary healthcare settings between September, 2017 and December, 2018 in Islamabad, Pakistan. A structured data collection form was used to gather sociodemographic and clinical data of recruited patients. Binary logistic regression analyses were undertaken to determine association between regularity in treatment follow-up appointments and blood pressure control and to determine covariates significantly associated with regularity in treatment follow-up appointments.

Results

A total of 662 patients with hypertension participated in the study. More than half 346 (52%) of the patients were females. The mean age of participants was 54 ± 12 years. Only 274 (41%) patients regularly attended treatment follow-up appointments. Regression analysis found that regular treatment follow-up was an independent predictor of controlled blood pressure (OR 1.561 [95% CI 1.102–2.211; P = 0.024]). Gender (OR 1.720 [95% CI 1.259–2.350; P = 0.001]), age (OR 1.462 [CI 95%:1.059–2.020; P = 0.021]), higher education (OR 1.7 [95% CI 1.041–2.778; P = 0.034]), entitlement to free medical care (OR 3.166 [95% CI 2.284–4.388; P = 0.0001]), treatment duration (OR 1.788 [95% CI 1.288–2.483; P = 0.001]), number of medications (OR 1.585 [95% CI 1.259–1.996; P = 0.0001]), presence of co-morbidity (OR 3.214 [95% CI 2.248–4.593; P = 0.0001]) and medication adherence (OR 6.231 [95% CI 4.264–9.106; P = 0.0001]) were significantly associated with regularity in treatment follow-up appointments.

Conclusion

Attendance at follow-up visits was alarmingly low among patients with hypertension in Pakistan which may explain poor treatment outcomes in patients. Evidence-based targeted interventions should be developed and implemented, considering local needs, to improve attendance at treatment follow-up appointments.

"If You Call Them, They Will Come": A Telephone Call Reminder to Decrease the No-Show Rate in an Outpatient Palliative Medicine Clinic

INTRODUCTION

A high outpatient clinic no-show rate affects clinical outcomes, increases healthcare costs, and reduces both access to care and provider productivity. In an effort to reduce the no-show rate at a busy palliative medicine outpatient clinic, a quality improvement project was launched consisting of a telephone call made by clinic staff prior to appointments. The study aimed to determine the effect of this intervention on the no-show rate, and assess the financial impact of a decreased no-show rate.

METHODS AND MATERIALS

The outpatient clinic no-show rate was measured from September 1 to December 31, 2015. Data from the first 8 months of the calendar year was removed since these could not be verified. Starting January 1, 2016, patients received a telephone call reminder 24 hours prior to their scheduled outpatient appointment for confirmation. No-show rate was again measured for the calendar year 2016. Opportunity costs were calculated for unfulfilled clinic visits.

RESULTS

Of the 1224 completed visits from September 1 to December 31, 2015, 271 were no-shows with an average rate of 11.8%. After the intervention, there were 4368 completed visits and 562 no-shows. The no-show rate for 2016 averaged 6.9% (p < 0.001), down 4.9% from the last 4 months of 2015. Estimated opportunity costs were about 396 no-show visits avoided, equivalent to an annual savings of about $79,200.

CONCLUSION

A telephone call reminder to patients 24 hours prior to their appointment decreased the no-show rate in an outpatient palliative medicine clinic. Avoiding unfulfilled visits resulted in substantial opportunity costs.

It's how you say it: Systematic A/B testing of digital messaging cut hospital no-show rates

Failure to attend hospital appointments has a detrimental impact on care quality. Documented efforts to address this challenge have only modestly decreased no-show rates. Behavioral economics theory has suggested that more effective messages may lead to increased responsiveness. In complex, real-world settings, it has proven difficult to predict the optimal message composition. In this study, we aimed to systematically compare the effects of several pre-appointment message formats on no-show rates. We randomly assigned members from Clalit Health Services (CHS), the largest payer-provider healthcare organization in Israel, who had scheduled outpatient clinic appointments in 14 CHS hospitals, to one of nine groups. Each individual received a pre-appointment SMS text reminder five days before the appointment, which differed by group. No-show and advanced cancellation rates were compared between the eight alternative messages, with the previously used generic message serving as the control. There were 161,587 CHS members who received pre-appointment reminder messages who were included in this study. Five message frames significantly differed from the control group. Members who received a reminder designed to evoke emotional guilt had a no-show rates of 14.2%, compared with 21.1% in the control group (odds ratio [OR]: 0.69, 95% confidence interval [CI]: 0.67, 0.76), and an advanced cancellation rate of 26.3% compared with 17.2% in the control group (OR: 1.2, 95% CI: 1.19, 1.21). Four additional reminder formats demonstrated significantly improved impact on no-show rates, compared to the control, though not as effective as the best performing message format. Carefully selecting the narrative of pre-appointment SMS reminders can lead to a marked decrease in no-show rates. The process of a/b testing, selecting, and adopting optimal messages is a practical example of implementing the learning healthcare system paradigm, which could prevent up to one-third of the 352,000 annually unattended appointments in Israel.

A Randomized Controlled Trial of Group Well-Child Care: Improved Attendance and Vaccination Timeliness

Well-child care has suboptimal outcomes regarding adherence to appointments and recall of guidance, especially among families facing structural barriers to health. Group well-child care (GWCC) aims to improve these outcomes by enhancing anticipatory guidance discussions and peer education. We conducted a randomized controlled trial, comparing GWCC with traditional, individual well-child care (IWCC) and assessed health care utilization, immunization timeliness, recall of anticipatory guidance, and family-centered care. Ninety-seven mother-infant dyads were randomized to GWCC or IWCC. Compared with IWCC infants, GWCC infants attended more of the 6 preventive health visits (5.41 vs 4.87, P < .05) and received more timely immunization at 6 months and 1 year but did not differ in emergency or hospital admission rates. There were no differences in mothers' reports of anticipatory guidance received or family-centered care. As primary care is redesigned for value-based care and structural vulnerabilities are considered, GWCC may be a key option to consider.

Patients' missed appointments in academic family practices in Quebec

OBJECTIVE

To determine the prevalence of no-show patients in 4 family medicine teaching units (FMTUs) and to investigate the reasons given by patients for past missed appointments in order to identify factors that could be acted on to improve access to care.

DESIGN

Retrospective data collection through electronic medical records and a self-administered survey.

SETTING

Four FMTUs at the University of Montreal in Quebec.

PARTICIPANTS

Patients older than 18 years of age (or younger patients' guardians) who were able to read French and had visited the clinic at least once.

MAIN OUTCOMES MEASURES

No-show prevalence among patients scheduled to see different types of health care professionals, and patients' reasons for past missed appointments and for not notifying the clinic before missing an appointment.

RESULTS

The overall prevalence of no-show patients was 7.8% (2700 missed appointments of 34 619 scheduled appointments), ranging from 6.3% to 9.0% among the 4 FMTUs. The survey participation rate was 91.0% (1757 completed surveys of 1930 distributed surveys). A total of 19.1% of respondents acknowledged previous no-show behaviour. Resolved issues (22.9%) and work obligations (19.4%) were the most frequent personal reasons for missing an appointment, whereas inconvenient timing of the appointment (17.0%), delay before the appointment (14.6%), and lack of confirmation (13.7%) were the most frequent organizational reasons. The most frequent reason for not notifying the clinic of the absence was forgetting to call (55.2%).

CONCLUSION

The no-show phenomenon, although not very prevalent in our clinics, is present and can potentially affect access to care. Reasons for missing an appointment without notifying the clinic are varied and point toward different potential solutions to reduce no-shows. Educating patients about the importance of informing the clinic when they cannot come, offering a wider range of appointment dates and times, systematically confirming appointments, improving telephone service, and offering different methods to communicate with the clinic could all be solutions to improve access to care.

Correlation of Appointment Times and Subspecialty With the No-Show Rates in an Orthopedic Ambulatory Clinic

EXECUTIVE SUMMARY

Unexpectedly missed appointments ("no-shows") cause clinic inefficiency, lost time and revenue, wasted healthcare resources, and provider dissatisfaction. No-shows can be associated with miscommunication, transportation difficulties, employment status, age, race, and socioeconomic status. This study investigates the association between no-show rates and patient, appointment time, and provider characteristics. Data for all scheduled appointments in a single orthopedic multispecialty institution during calendar year 2016 were obtained. Data points included patient age, gender, and race; hour; month; and subspecialty. Chi-square testing was used to compare no-show and kept appointments with respect to patient and appointment characteristics. Logistic regression was used to calculate differences in no-show rates between orthopedic subspecialties. The overall no-show rate was 11.5%. Race, age, and subspecialties were all found to be associated with higher no-show rates. No significant differences were observed for gender, appointment time, or month of appointment. The authors suggest that patients at higher risk of not showing up for scheduled appointments may need extra effort from providers to accommodate the patients' schedules when making appointments, to confirm their appointments a few days before, and/or to incentivize patients to minimize no-shows.

Does phone messaging improves tuberculosis treatment success? A systematic review and meta-analysis

BACKGROUND

Compliance to anti-TB treatment is crucial in achieving cure and avoiding the emergence of drug resistance. Electronic health (eHealth) interventions are included in the strategy to end the global Tuberculosis (TB) epidemic by 2035. Evidences showed that mobile messaging systems could improve patient adherence to clinic appointment for diagnosis and treatment. This review aimed to assess the effect of mobile-phone messaging on anti-TB treatment success.

METHODS

All randomized controlled trial (RCT) and quasi-experimental studies done prior to August 26, 2019 were included in the review. Studies were retrieved from PubMed, EMBASE, Cochrane and ScienceDirect databases including, grey and non-indexed literatures from Google and Google scholar. Quality of studies were independently assessed using Cochrane Risk of Bias Assessment Tool. A qualitative synthesis and quantitative pooled estimation were used to measure the effect of phone messaging on TB treatment success rate. PRISMA flow diagrams were used to summarize article selection process.

RESULTS

A total of 1237 articles were identified, with 14 meeting the eligibility criteria for qualitative synthesis. Eight studies with a total of 5680 TB patients (2733 in intervention and 2947 in control groups) were included in meta-analysis. The pooled effect of mobile-phone messaging revealed a small increase in treatment success compared to standard of care (RR 1.04, 95% CI 1.02 to 1.06), with low heterogeneity (I2 = 7%, p < 0.0002). In the review, performance, detection and attrition biases were reported as major risk of biases.

CONCLUSIONS

Mobile-phone messaging showed a modest effect in improving anti-TB treatment success; however, the quality of evidence was low. Further controlled studies are needed to increase the evidence-base on the role of mHealth interventions to improve TB care.

PROTOCOL REGISTRATION NUMBER

CRD420170744339. http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42017074439.

A modified walk-in clinic for shoe insoles: Follow-up of non-attendants

BACKGROUND

In a previous study (n = 1286), we found that a modified walk-in system reduced waiting times for prescription of shoe insoles by 40 days compared to scheduled appointments but resulted in a non-attendance rate of 17% compared to 6% for scheduled appointments.

OBJECTIVES

To investigate the reasons for non-attendance at the modified walk-in clinic.

STUDY DESIGN

This is a cross-sectional survey.

METHODS

Unlike traditional walk-in clinics, a limited number of patients were invited each week from the waiting list to attend the modified walk-in clinic on pre-specified days during the following 5 weeks. A questionnaire was sent to 137 patients who did not attend the modified walk-in clinic, of whom 50 (36%) responded.

RESULTS

The most frequently reported reasons for not attending were the following: could not attend on the suggested days and times (30%), had already received help (18%) and illness or other medical interventions (16%). The majority of these issues could have been overcome by rescheduling to a scheduled appointment.

CONCLUSION

The main reason for not attending a modified walk-in clinic was that suggested days and times did not suit the patients. The option to reschedule the appointment needs to be clearly emphasized in the information provided to the patient.

CLINICAL RELEVANCE

With clear information about rescheduling options, a modified walk-in clinic could be used to reduce waiting times for certain groups of patients.

Who is not coming to clinic? A predictive model of excessive missed appointments in persons with multiple sclerosis

BACKGROUND

Missed appointments can have negative effects on several facets of healthcare, including disruption of services, worse patient health outcomes, and increased costs. The influence of demographic and clinical factors on missed appointments has been studied in a number of chronic conditions, but not yet in multiple sclerosis (MS). Engagement in healthcare services is a particular concern with this population, given the complexity of the condition. Furthermore, excessive missed appointments has emerged as a risk factor for suboptimal adherence to disease modifying therapies (DMTs), prompting further exploration into this issue and whether a tool could be developed to triage possible interventions for persons with MS on DMTs who are missing their appointments. As such, this study aimed to investigate the rate and factors associated with missed appointments among a large national sample of persons with MS and develop a predictive model of excessive missed appointments.

METHODS

Administrative data from 01/01/2013 to 12/31/2015 were extracted from the VA MS Center of Excellence Data Repository. Variables not related to excessive missed appointments, defined as missing more than 20% of scheduled appointments, in bivariate analyses (p > 0.20) were excluded. Remaining baseline co-occurring conditions, demographic, and healthcare utilization variables were entered into a logistic regression model, using a backward elimination criteria of p < 0.05. Calibration and discrimination of the model were assessed. An initial predictive score was generated based on the value of the variable and its β-value from the final model.

RESULTS

The number of missed appointments ranged from 0 to 84 over a two-year period. Over 59% missed at least one appointment, though only 4.28% had excessive missed appointments. Seven variables were retained in the model: adherence to DMTs, age, distance, histories of post-traumatic stress disorder, congestive heart failure, and chronic obstructive pulmonary disease, and emergency visits. Predictive scores ranged from -6.42 to 0.96 (M = -2.61, SD = 1.15). The final model had good discrimination, calibration, and fit.

CONCLUSIONS

By using this model and accompanying score, clinicians could have a good chance of predicting individuals who will miss more than 20% of their appointments and triaging interventions.

No-shows in ambulatory clinics and non-utilized appointments for elective operations in selected surgical departments at a tertiary hospital in Israel

Background

The phenomenon of a patient missing a medical appointment without notification is called a “no-show”. In contrast, “non-utilized appointments” are a broader phenomenon including all appointments that didn’t occur as registered – whether due to actions taken by providers or patients. Both no-shows and non-utilized appointments can lead to reduced quality of care, loss in productivity, financial losses and impaired patient outcomes.

Methods

The study was carried out between August 2016 and January 2017 in the ENT, Orthopedics and General Surgery Departments of the Jerusalem-based Shaare Zedek Medical Center. The study team sought to examine the reasons for non-utilized appointments in elective operations. The study team also interviewed no-show ambulatory care patients regarding the causes of the no-show and reviewed medical records of no-show patients to determine the nature of the missed appointments.

Results

The rate of non-utilization of appointments for elective operations was 6%. The leading reasons for non-utilization of these appointments were: patient health issues, patient surgery postponement and surgery schedule overload (together accounting for 52% of cases and 72% of known reasons). The no-show rate for ambulatory clinic appointments was approximately 15%. The leading reasons for ambulatory clinic no-shows were: administrative issues, illness and forgetfulness (together accounting for 58% of all reasons). The leading types of appointments missed were:post-operation follow-ups and chronic illness follow-up (together accounting for 46% of cases and 63% of known reasons).

Conclusions

In this study, the non-utilized appointment rate for elective operations was found to be lower than those noted in the medical literature, while the no-show rate for ambulatory visits was found to be similar to that found in the literature. There is room to question the necessity of certain types of postoperative follow-up appointments since they are at “high risk” for no-show. One promising way to reduce the no-show rate would involve improving the hospital’s information and computing systems in order to identify patients who are susceptible to a no-show incident.

Improved Outcomes in Patients with Retinal Detachment after Implementation of a Silicone Oil Registry and Phone Call Reminder System

PURPOSE

This retrospective study was performed to assess the clinical impact in reducing silicone oil (SO)-related complications such as keratopathy of a registry and appointment reminder system for patients with complicated retinal detachment (RD) who underwent pars plana vitrectomy (PPV) with SO tamponade.

DESIGN

Retrospective cohort study.

PARTICIPANTS

A total of 87 eyes of 87 patients who received SO tamponade were included.

METHODS

The study was carried out at Zuckerberg San Francisco General Hospital and Trauma Center (ZSFG). Patients were divided into those who received SO before (control group, n = 48) or after (treatment group, n = 39) implementation of an SO registry and patient reminder system in 2014. Patient records were reviewed to identify clinical characteristics and outcomes.

MAIN OUTCOME MEASURES

The primary outcome measure was the difference in the rate of loss to follow-up before versus after the implementation of the registry and reminder system. Secondary outcomes were the duration of SO tamponade, keratopathy rate, and intraocular pressure (IOP) at the last visit before SO removal.

RESULTS

Forty-eight patients were included in the control group, and 39 patients were included in the treatment group. The number of patients lost to follow-up was 23 (47.9%) in the control group versus 6 (15.4%) in the treatment group (P = 0.0015). The mean duration before SO removal was 79.6±91.7 weeks in the control group and 36.3±31.5 weeks in the treatment group (mean±standard deviation [SD]) (P = 0.015). Keratopathy developed in 33.3% of patients in the control group and 12.8% of patients in the treatment group (P = 0.0425). Mean IOP at the last visit before SO removal was 13.0±5.2 mmHg (mean±SD) in the control group and 13.3±7 mmHg (mean±SD) in the treatment group (P > 0.05).

CONCLUSIONS

A phone call appointment reminder system for patients with complicated RD who underwent PPV and SO tamponade reduced the rate of loss to follow-up and the duration of SO tamponade, correlating with a reduction in the rate of keratopathy.

Effect of weather on GP home visits: a cross-sectional study

BACKGROUND

GPs in the UK conduct >13 million home visits each year. The visits, which are resource intensive, are usually to the frailest patients who are least resilient to adverse weather.

AIM

To explore the relationship between meteorological variables (temperature, rainfall, sunshine) and temporal variables (day of the week, season) with GP home visits (HVs).

DESIGN AND SETTING

A cross-sectional study using data provided by Herts Urgent Care for its GP acute in-hours visiting service and UK Meteorological (Met) Office weather data for the Herts & South East region of the UK.

METHOD

The association between the number of GP HVs and weather and temporal variables was explored using univariable and multivariable negative binomial regression.

RESULTS

There was a significant 0.4% decrease in HVs per degrees Celsius increase in minimum temperature (incidence rate ratio [IRR] 0.996, 95% confidence interval [CI] = 0.993 to 0.999), and a 0.4% decrease per hour increase in sunshine (IRR 0.996, 95% CI = 0.992 to 1.000), as well as significant decreases in weekday HVs compared with Mondays (Thursday IRR 0.824, 95% CI = 0.790 to 0.859). There were 6.2% fewer HVs in summer compared with winter (IRR 0.938, 95% CI = 0.902 to 0.975). Multivariable negative binomial regression showed non-significant relationships between meteorological variables and HVs, but a significant day-of-the-week relationship.

CONCLUSION

GP HVs increased on cold days and fell on sunnier days. The effect sizes were small so it is unlikely that there is any clinically significant effect of weather on HVs in this acute GP visit setting. A tentative conclusion might also be that GPs in this system can deliver care to frail housebound patients in most weather conditions.

Self-management capability in patients with long-term conditions is associated with reduced healthcare utilisation across a whole health economy: cross-sectional analysis of electronic health records

Objective

To quantify the association between patient self-management capability measured using the Patient Activation Measure (PAM) and healthcare utilisation across a whole health economy.

Results

12 270 PAM questionnaires were returned from 9348 patients. In the adjusted analyses, compared with the least activated group, highly activated patients (level 4) had the lowest rate of contact with a general practitioner (rate ratio: 0.82, 95% CI 0.79 to 0.86), emergency department attendances (rate ratio: 0.68, 95% CI 0.60 to 0.78), emergency hospital admissions (rate ratio: 0.62, 95% CI 0.51 to 0.75) and outpatient attendances (rate ratio: 0.81, 95% CI 0.74 to 0.88). These patients also had the lowest relative rate (compared with the least activated) of ‘did not attends’ at the general practitioner (rate ratio: 0.77, 95% CI 0.68 to 0.87), ‘did not attends’ at hospital outpatient appointments (rate ratio: 0.72, 95% CI 0.61 to 0.86) and self-referred attendance at emergency departments for conditions classified as minor severity (rate ratio: 0.67, 95% CI 0.55 to 0.82), a significantly shorter average length of stay for overnight elective admissions (rate ratio 0.59, 95% CI 0.37 to 0.94), and a lower likelihood of 30- day emergency readmission (rate ratio: 0.68, 95%  CI 0.39 to 1.17), though this did not reach significance.

Conclusions

Self-management capability is associated with lower healthcare utilisation and less wasteful use across primary and secondary care.

Frequency and reasons for missed appointments of outpatient mental health care users in the uMgungundlovu District

Background

Over the years, there has been a rapid growth in the use of mobile technology which has been proven to increase treatment adherence. Short message services may improve service delivery through appointment reminders and improve communication between health care workers and patients. Missed appointments are becoming common amongst mental health care users, and this has a significant economic burden on mental health symptoms.

Objectives

The aim of the study was to determine the frequency and reasons for missed appointments of outpatient mental health care users for their follow-up care in the uMgungundlovu District.

Method

This study used a quantitative survey. A non-probability convenient sampling method was used to select 182 participants at the psychiatric clinics.

Results

Of the 182 participants, results of the study indicated that n = 84 (46.2%) respondents had missed their appointment at some stage. Of the n = 84 (46.2%) respondents who had missed appointments, n = 28 (33.3%) had missed their appointment once, and n = 45 (53.6%) had missed their appointment 2–3 times. Most common reasons for missed appointments included mental health care users forgetting (n = 58; 69%), work commitments (n = 14; 16.7%), no transportation (n = 4; 4.8%) and financial constraints (n = 5; 6%).

Conclusion

The main reasons for missed appointments that were identified included forgetfulness, work commitments, lack of transportation and financial constraints. A significant number of participants (53.6%) had missed their appointments 2–3 times.

A prospective 52-week randomized controlled trial of patient-initiated care consultations for patients with psoriasis

BACKGROUND

Treatment and care of moderate-to-severe psoriasis require lifelong consultations with a dermatologist with close monitoring of systemic treatment.

OBJECTIVES

To investigate the effect of patient-initiated care consultation (PICC) for patients with psoriasis in a dermatology outpatient clinic.

METHODS

A prospective randomized controlled trial with patients on well-controlled systemic treatment randomized to either (i) the PICC group, where they participated in one annual consultation with a dermatologist but were able to initiate consultations when needed; or (ii) routine care, where they participated in a consultation every 12-16 weeks. The primary outcome was the Dermatology Life Quality Index (DLQI). Other outcomes were safety, patient adherence and satisfaction with healthcare assessed at baseline and after 52 weeks. The study was registered with clinical trials number NCT02382081.

RESULTS

In total 150 patients were included, with 58·0% treated with biologics, 37·3% with methotrexate and 4·7% with acitretin. At week 52 no statistically significant mean difference between groups was detected in DLQI (0·28, 95% confidence interval -0·35 to 0·9) or Psoriasis Area and Severity Index (-0·24, 95% confidence interval -0·84 to 0·36). Patients in the PICC group requested 63% fewer consultations with a dermatologist: mean 2·5 ± 0·1 vs. 5·1 ± 0·6 (P = 0·001). Patient adherence and safety with treatment monitoring were equal between groups, but the PICC group was significantly better at attending consultations than the control group (P = 0·003).

CONCLUSIONS

PICC offers additional clinical benefits over routine care, making patients less dependent on clinical visits. The intervention adds no harm to monitoring systemic treatment, and patients report high quality of life and satisfaction with healthcare.

Responsibility for follow-up during the diagnostic process in primary care: a secondary analysis of International Cancer Benchmarking Partnership data

BACKGROUND

It is unclear to what extent primary care practitioners (PCPs) should retain responsibility for follow-up to ensure that patients are monitored until their symptoms or signs are explained.

AIM

To explore the extent to which PCPs retain responsibility for diagnostic follow-up actions across 11 international jurisdictions.

DESIGN AND SETTING

A secondary analysis of survey data from the International Cancer Benchmarking Partnership.

METHOD

The authors counted the proportion of 2879 PCPs who retained responsibility for each area of follow-up (appointments, test results, and non-attenders). Proportions were weighted by the sample size of each jurisdiction. Pooled estimates were obtained using a random-effects model, and UK estimates were compared with non-UK ones. Free-text responses were analysed to contextualise quantitative findings using a modified grounded theory approach.

RESULTS

PCPs varied in their retention of responsibility for follow-up from 19% to 97% across jurisdictions and area of follow-up. Test reconciliation was inadequate in most jurisdictions. Significantly fewer UK PCPs retained responsibility for test result communication (73% versus 85%, P = 0.04) and non-attender follow-up (78% versus 93%, P<0.01) compared with non-UK PCPs. PCPs have developed bespoke, inconsistent solutions to follow-up. In cases of greatest concern, 'double safety netting' is described, where both patient and PCP retain responsibility.

CONCLUSION

The degree to which PCPs retain responsibility for follow-up is dependent on their level of concern about the patient and their primary care system's properties. Integrated systems to support follow-up are at present underutilised, and research into their development, uptake, and effectiveness seems warranted.

Association between age and outpatient clinic arrival time: myth or reality?

BACKGROUND

Non-attendance and late arrivals diminish patient flow in outpatient clinics. On the other hand, patient earliness may also be undesirable. Physicians often experience that older patients are more punctual than younger patients, and often they come excessively early. The aim of this study was to determine whether an association between age and outpatient clinic arrival time could be established or not, i.e. to find out if it is a myth or a reality.

METHODS

Prospective descriptive study performed at a neurological outpatient clinic. Data were collected from all scheduled appointments during an eight-week period. Variables included were age, gender, appointment time, arrival time, no-shows, appointment type, need for assistance and if it was an early or late appointment. Outcomes were unpunctuality (early and late arrivals) and non-attendance.

RESULTS

Of 1353 appointments, non-attendance rate was 9.5 and 5.1% were late arrivals. Median age increased with increased patient earliness (p <  0.001). Younger age (p = 0.007) and new referrals (p = 0.025) were associated with non-attendance.

CONCLUSIONS

The intuition of an association between age and outpatient clinic arrival time was confirmed, thus it is a reality that older patients attend their appointments more frequently and have better punctuality than younger adults. This age effect in outpatient clinics should be considered when developing future simulation models and intervention studies.

eHealth as a facilitator of equitable access to primary healthcare: the case of caring for non-communicable diseases in rural and refugee settings in Lebanon

OBJECTIVES

Assess the effect of selected low-cost eHealth tools on diabetes/hypertension detection and referrals rates in rural settings and refugee camps in Lebanon and explore the barriers to showing-up to scheduled appointments at Primary Healthcare Centers (PHC).

METHODS

Community-based screening for diabetes and hypertension was conducted in five rural and three refugee camp PHCs using an eHealth netbook application. Remote referrals were generated based on pre-set criteria. A phone survey was subsequently conducted to assess the rate and causes of no-shows to scheduled appointments. Associations between the independent variables and the outcome of referrals were then tested.

RESULTS

Among 3481 screened individuals, diabetes, hypertension, and comorbidity were detected in 184,356 and 113 per 1000 individuals, respectively. 37.1% of referred individuals reported not showing-up to scheduled appointments, owing to feeling better/symptoms resolved (36.9%) and having another obligation (26.1%). The knowledge of referral reasons and the employment status were significantly associated with appointment show-ups.

CONCLUSIONS

Low-cost eHealth netbook application was deemed effective in identifying new cases of NCDs and establishing appropriate referrals in underserved communities.

Demographic and practice factors predicting repeated non-attendance in primary care: a national retrospective cohort analysis

BACKGROUND

Addressing the causes of low engagement in health care is a prerequisite for reducing health inequalities. People who miss multiple appointments are an under-researched group who might have substantial unmet health needs. Individual-level patterns of missed general practice appointments might thus provide a risk marker for vulnerability and poor health outcomes. We sought to ascertain the contributions of patient and practice factors to the likelihood of missing general practice appointments.

METHODS

For this national retrospective cohort analysis, we extracted UK National Health Service general practice data that were routinely collected across Scotland between Sept 5, 2013, and Sept 5, 2016. We calculated the per-patient number of missed appointments from individual appointments and investigated the risk of missing a general practice appointment using a negative binomial model offset by number of appointments made. We then analysed the effect of patient-level factors (including age, sex, and socioeconomic status) and practice-level factors (including appointment availability and geographical location) on the risk of missing appointments.

FINDINGS

The full dataset included information from 909 073 patients, of whom 550 083 were included in the analysis after processing. We observed that 104 461 (19·0%) patients missed more than two appointments in the 3 year study period. After controlling for the number of appointments made, patterns of non-attendance could be differentiated, with patients who were aged 16-30 years (relative risk ratio [RRR] 1·21, 95% CI 1·19-1·23) or older than 90 years (2·20, 2·09-2·29), and of low socioeconomic status (Scottish Index of Multiple Deprivation decile 1: RRR 2·27, 2·22-2·31) significantly more likely to miss multiple appointments. Men missed fewer appointments overall than women, but were somewhat more likely to miss appointments in the adjusted model (1·05, 1·04-1·06). Practice factors also substantially affected attendance patterns, with urban practices in affluent areas that typically have appointment waiting times of 2-3 days the most likely to have patients who serially miss appointments. The combination of both patient and practice factors to predict appointments missed gave a higher pseudo R² value (0·66) than models using either group of factors separately (patients only R²=0·54; practice only R²=0·63).

INTERPRETATION

The findings that both patient and practice characteristics contribute to non-attendance of general practice appointments raise important questions for both the management of patients who miss multiple appointments and the effectiveness of existing strategies that aim to increase attendance. Addressing these issues should lead to improvements in provision of services and public health.

FUNDING

Scottish Government Chief Scientist Office and Data Sharing and Linkage Service of the Scottish Government.

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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12875-017-0655-8) contains supplementary material, which is available to authorized users.

A dynamic approach for outpatient scheduling

AIMS

Patient no-show is a recurrent problem in medical centers and, in conjunction with cancellation of appointments, often results in loss of productivity and excessive patient time to appointment. The purpose of this study was to develop a dynamic procedure for scheduling patients within an outpatient clinic where patients are expected to have multiple appointments, such as physical therapy, occupational therapy, primary care, and dentistry.

METHODS

This retrospective study involved the year 2014 de-identified patient records from an outpatient clinic affiliated with a large university hospital. A number of patient characteristics, appointment data, and historical attendance records were examined to determine whether they significantly impacted patients who missed scheduled appointments (no-shows). Patient attendance behaviors over multiple appointments were examined to determine whether their no-show and cancellation patterns differed from one appointment to the next. Decision tree analysis was applied to those predictors that significantly correlated with patient attendance behavior to assess the likelihood of a patient no-show. A sample dynamic appointment scheduling procedure that utilized different overbooking strategies for different appointment numbers was then developed. Computer simulation was used to assess the effectiveness of the dynamic procedure versus two other methods consisting of randomly assigned and uniformly assigned appointments.

RESULTS

The dynamic scheduling procedure resulted in increased scheduling efficiency through overbooking but with less than 5% risk of appointment conflicts (i.e. two patients showing at the same time), equating to approximately 0.16 conflicts per clinician per day. It also increased clinic utilization by about 6.7%. It consistently outperformed the other two methods with respect to the percentage of appointment conflicts.

LIMITATIONS

The study is limited with respect to potential clinician cost increase resulting from possible appointment conflicts. A second limitation is that patients experiencing appointment conflicts might not wait for treatment, resulting in potential loss of revenue. A third limitation is that the model does not take into account patient satisfaction, nor the ethics of overbooking patients.

CONCLUSIONS

A dynamic appointment scheduling procedure was developed using actual patient characteristics. The procedure resulted in creation of more efficient appointment schedules thereby increasing the clinic utilization.

A Multi-way Multi-task Learning Approach for Multinomial Logistic Regression*. An Application in Joint Prediction of Appointment Miss-opportunities across Multiple Clinics

OBJECTIVES

Whether they have been engineered for it or not, most healthcare systems experience a variety of unexpected events such as appointment miss-opportunities that can have significant impact on their revenue, cost and resource utilization. In this paper, a multi-way multi-task learning model based on multinomial logistic regression is proposed to jointly predict the occurrence of different types of miss-opportunities at multiple clinics.

METHODS

An extension of L₁ / L₂ regularization is proposed to enable transfer of information among various types of miss-opportunities as well as different clinics. A proximal algorithm is developed to transform the convex but non-smooth likelihood function of the multi-way multi-task learning model into a convex and smooth optimization problem solvable using gradient descent algorithm.

RESULTS

A dataset of real attendance records of patients at four different clinics of a VA medical center is used to verify the performance of the proposed multi-task learning approach. Additionally, a simulation study, investigating more general data situations is provided to highlight the specific aspects of the proposed approach. Various individual and integrated multinomial logistic regression models with/without LASSO penalty along with a number of other common classification algorithms are fitted and compared against the proposed multi-way multi-task learning approach. Fivefold cross validation is used to estimate comparing models parameters and their predictive accuracy. The multi-way multi-task learning framework enables the proposed approach to achieve a considerable rate of parameter shrinkage and superior prediction accuracy across various types of miss-opportunities and clinics.

CONCLUSIONS

The proposed approach provides an integrated structure to effectively transfer knowledge among different miss-opportunities and clinics to reduce model size, increase estimation efficacy, and more importantly improve predictions results. The proposed framework can be effectively applied to medical centers with multiple clinics, especially those suffering from information scarcity on some type of disruptions and/or clinics.

[Analysis of economic cost of missed outpatient appointments]

AIM

To estimate the economic costs of missed Outpatient appointments by the Costa del Sol Health Agency (ASCS).

METHOD

An analysis was performed on the costs arising from missed outpatient appointments (first appointment and examinations) of each of the specialities in the Centres belonging to the ASCS. A formula was used to determine the unit cost per appointment and per centre and speciality. This involved the direct imputation of the controllable costs and the indirect imputation of the service costs, together with an estimated cost of re-appointments based on a previous case-control study.

RESULTS

The cost of missed appointments per centre in the Costa del Sol Hospital was €2,475,640, with a failure rate of 14.2% (256,377 appointments). In the Benalmádena High Resolution Hospital it was €515,936, with an absence rate of 12.2% (44,848 appointments), and in the Mijas High Resolution Centre, a cost of €395,342 with an absence rate of the 13.5% (99,536 appointments). The mean extra cost of a re-appointment was €12.95. The specialities with a higher medium cost were Digestive Diseases, Internal Medicine, and Rehabilitation.

CONCLUSIONS

The economic cost of patients not turning up for scheduled appointments in the ASCS was greater than 3 million Euros for a non-attendance rate of the 13.8%, with Mijas High Resolution Centre being the centre that showed the lowest mean unitary cost per medical appointment.

Use of Mobile Phone Technology to Improve follow-up at a Community Mental Health Clinic: A Randomized Control Trial

BACKGROUND

Mobile phone technology is being used worldwide to improve follow-ups in health care.

AIM

Aim of the study is to evaluate whether the use of mobile technology will improve or not the follow-up of Indian patients from a community mental health center.

MATERIALS AND METHODS

Patients or caregivers having mobile phones and consenting for study were enrolled, and sociodemographic and clinical details of patients were taken. Participants were randomized into two groups (short message service [SMS] vs. non-SMS group). At first intervention level, a SMS was sent to SMS group (not in non-SMS group) 1 day before their appointment. At second-level intervention (voice call level), patients from both groups who missed their first appointment were given a voice call requesting them to come for follow-up, and the reasons for first missed appointments (MA) were also elicited. The effect of these two intervention levels (first SMS for SMS group and next voice calls for both groups) on follow-up was evaluated.

RESULTS

A total of 214 patients were enrolled in the study. At first SMS intervention level of SMS group (n = 106), 62.26% of participants reached appointment-on-time (RA), while in the non-SMS/as usual group (n = 108), 45.37% of patients RA. The difference of these groups is statistically significant. At second-level intervention (voice call), 66 of 88 (another 15 were unable to contact) were came for follow-up consultation within 2 days of MA. Distance and diagnosis of alcohol dependence were significantly associated with MA. Social reasons were most common reasons for first MA.

CONCLUSION

The use of mobile phone technology in an outpatient community psychiatric clinic improved follow-up significantly.

Does pain take holidays? Non-attendance rates at a hospital-based pain clinic are elevated during the Jewish high-holidays

Background

Patient non-attendance is an expensive and persistent problem worldwide with rates between 5–39% reported in the literature. The objective of the study was to assess whether there is a higher incidence of non-attendance in a hospital-based pain clinic during the period of the Jewish High Holidays (Rosh-Hashanah to Sukkot) and whether this is further compounded by other factors, such as demographic characteristics and previous visits to the clinic.

Methods

Records were taken from the Lowenstein Rehabilitation Hospital appointment scheduling system. Data was gathered from two time-periods: High-Holidays and Control for each year, over a total of 6 years 2008–2013. Non-attendance was analyzed by period, by age, by gender and by previous visits to the clinic.

Results

In the entire population studied (666 distinct records), the non-attendance rate was higher during the High-Holidays as compared to the Control period (32 vs. 24.1%; p = 0.030). Non-attendance rates were significantly higher during the Holidays among repeating patients (28.6 vs. 14.8%; p = 0.002) and among women (34.6 vs. 20.7%; p = 0.004).

Discussion

Our data suggest that non-attendance is elevated during the High-Holidays in specific groups of patients, namely, repeating patients and women. Despite no direct inquiry into the reasons for non-attendance, we speculate that the elevated well-being and familial support during the holidays contribute to the patients’ ability to cope with persistent pain and possibly directly reduce the amount of pain, leading to patients missing their pain clinic appointments.

Conclusion

Our results, provided they can be corroborated by larger-scale studies, can assist in scheduling policy adjustments such as avoidance of appointments during the High-holidays for specific patient populations and more rigorous reminder efforts during these times of the year that may lead to reduction in overall non-attendance rates in the pain clinic. Further, our data provide an impetus for further studies of non-attendance patterns among pain clinic patients, in order to acquire a better understanding of the reasons for non-attendance and develop strategies to reduce it and thus contribute to the continuous improvement of the Israeli health systems as well as others worldwide.

Electronic supplementary material

The online version of this article (doi:10.1186/s13584-017-0132-9) contains supplementary material, which is available to authorized users.