Missed Appointments For Patients Research Articles

Socioeconomic and demographic factors predictive of missed appointments in outpatient radiation oncology: an evaluation of access

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

Missed Appointments: Research Protocol for a mixed method study about the causes of patient non-attendance at medical appointments in Denmark.

Approximately one third of patient appointments in health care result in failures, leading to patient risk and sizable resource "waste". Existing interventions to alleviate the no-shows often target the patients. The underlying reason behind these interventions is a view that attendance/non-attendance is solely the patient's problem. However, these interventions often prove ineffective and can perpetuate social biases and health inequalities, leaving behind the more vulnerable or disadvantaged patients (in terms of social, economical, linguistic factors, etc.). A more holistic understanding of no-shows is needed to optimize processes, to reduce waste and support vulnerable patients. This study aims to gain a deeper and more comprehensive understanding of the causes, mechanisms and recurring patterns and elements contributing to non-attendance at Danish hospitals in the Region of Southern Denmark. It emphasizes the patient perspective and analyses the relational and organizational processes surrounding no-shows in healthcare. Additionally, the study aims to identify effective communicative strategies and organizational processes that can support development and implementation of successful interventions. The research employs mixed quantitative-qualitative methods, encompassing four analytical projects focusing on non-attendance patterns, patient knowledge and behaviour, management of hospital appointments, and in-situ communication. To address the complexity of no-shows in healthcare the study incorporates various data sources. The quantitative data sources include the electronic patient records, the Danish central registries, the Danish National Patient Registry, and the Register of Medicinal Product Statistics. Baseline characteristics of patients at different levels are compared using Chi2 and Kruskal-Wallis tests. The qualitative studies involve observational data, individual semi-structured interviews with patients and practitioners, and video recordings of patient consultations. This paper presents the protocol of the study, which was funded by the Novo Nordisk Foundation in July 2022. The study was registered with The Danish Data Protection Agency (Registry ID: 22/54791) and with The Open Patient Data Explorative Network (Registry ID: OP_1800) in January 2023. Recruitment started in February 2023. It is anticipated that the quantitative data analysis will be completed by the end of September 2023, with the qualitative investigation starting in October 2023. The first study findings are anticipated to be available by the end of 2024. The existing research on non-attendance in Danish healthcare is inadequate in addressing relational and organisational factors leading to hospital no-shows. Interventions have had limited effect, high-lighting the Danish healthcare system's failure to accommodate for vulnerable patients. Effective interventions require a qualitative approach and robust ethnographic data to supplement the description and categorization of no-shows at hospitals. Obtaining comprehensive knowledge about the causes of missed patient appointments will yield practical benefits, enhancing safety, coherence and quality of treatment in healthcare.

To confirm your appointment, please press one: Examining demographic and health system interface factors that predict missed appointments in a pediatric outpatient neuropsychology clinic

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

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

BackgroundThere 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.MethodsSchool 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.Results112,534 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).ConclusionsThis 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.

COVID-19 PANDEMIC: MISSED INITIAL AND FOLLOW UP APPOINTMENTS AT AN ACADEMIC MEDICAL INSTITUTION IN SOUTH INDIA

The global outbreak of COVID-19 has greatly influenced the health care delivery system and health seeking behavior by patients. This study aimed to explore the missed patient appointments and the factors lead to missed appointments, at an academic medical institution in South India during COVID-19 pandemic. The study used descriptive retrospective survey design to collect register based data from all departments of the hospital during the period 1st January 2020 to 30th June 2020. Among the 8390 missed patient appointments reported during this period, 4670 patients were included in the sampling frame and 130 samples were selected using systematic sampling. Socio demographic variables, clinical variables and reasons for missed appointments were collected from hospital data base and telephonic interview. Age ranged from 1 month to 85 years with the median age of 42 (± 22.9) years. Male female ratio was 1:1. Of this 69.5% (90) patients were married and 41.5% was educated up to high school. Majority of the cases (57.7%) belonged to nuclear family; highest representation was from the economic non priority subsidy. More than half of missed appointments were noted in the medicine department and the most of the appointments was review cases. Reported reasons for missed appointments were personal constraints (50.8%), financial and family constraints (5.4%) time constraints (5.4%) hospital related reasons (4.6%) and COVID-19 related reasons (2.3%). During COVID-19 pandemic there was no significant number of missed appointments in the study centre. The missed appointment group belonged to non priority economic category. The majority of cases found were review appointments. When enquiries were marked departmental-wise for the missed appointments, medical departments had more missed appointments than others. The present study highlights the need for developing strategies to ensure healthy flow of non COVID health care services during pandemic period. KEYWORDS: COVID-19, Health care services, Missed Appointments, Non-COVID Health Care, Pandemic

Automated Text Message Reminders Improve Radiation Therapy Compliance

Protraction of radiation therapy courses can lead to lower cancer control and cancer-specific survival rates. The requirement for daily, consecutive radiation treatments coupled with the complexities of multimodality cancer care and quality assurance can occasionally lead to missed patient appointments or clinical inefficiency. To determine whether an automated text messaging (short message service [SMs]) platform could improve patient compliance with scheduled radiation therapy delivery, we created an automated SMS platform to send daily reminders of radiation therapy appointments. An automated SMS text messaging program was used from July 2016 to January 2017 to deliver daily appointment time reminders to patients on an elective basis. Automated text messages were sent 2hours before treatment appointments with appointment-specific information. We analyzed for compliance with radiation therapy appointments for patients who elected to receive SMS reminders versus those who did not. Multivariate analysis of >37,000 encounters involving ∼3400 patients demonstrated that of the factors considered, nonreceipt of SMS appointment reminders had a strong association with 15- to 60-minute tardiness (odds ratio [OR], 1.25; 95% confidence interval [CI], 1.13-1.38; P < .0001), >60-minute tardiness (OR, 1.56; 95% CI, 1.34-1.82; P<.0001) and no-shows (OR, 6.77; 95% CI, 5.45-8.41; P<.0001). Other demographic factors associated with decreased compliance included being early in a radiation therapy course, having an appointment earlier in the day, younger age, and male sex. Receipt of an SMS message did not correlate with overall treatment package time. Receipt of text messages correlates with compliance for radiation therapy appointments. Prospective randomized trials would be required to determine conclusively whether SMS is an effective intervention for improving compliance in populations at risk for being late to or missing radiation therapy appointments.

Evaluation of Missed Clinic Visits at an Academic Multi-Provider Urology Clinic

IntroductionIn this study we elucidated patient characteristics and reasons for visit associated with missed appointments for patients in a multi-provider urology clinic. MethodsWe retrospectively reviewed characteristics of clinic patient data for 4 urologists at 0.5 FTE (full-time equivalent) at a single location between March 18, 2014 and March 18, 2015. Data were collected on new and established patients, including age, health insurance status, time of appointment, reason for clinic visit and gender. The reasons for clinic visit were divided into 27 groups. We used chi-square analysis to evaluate statistical significance (p <0.05) based on expected rates for age, gender, time of appointment, season of appointment, health insurance status, benign vs malignant conditions and new or returning visit. ResultsA total of 4,812 clinic visits were analyzed with 999 missed patient appointments for an overall no-show rate of 20.76%. There was no statistically significant difference in the rate of attendance based on patient gender, season of appointment, or morning or afternoon appointment. A statistically significant difference was found in no-show rate between benign and malignant conditions (23.23% vs 8.85%, p <0.01) and whether it was a new or returning patient visit (29.78% vs 16.66%, p <0.01). In addition, there was a statistically significant difference in patients based on insurance status (p <0.01). Patients without insurance had the highest no-show rate and those with private insurance had the lowest (38.53% vs 16.35%). ConclusionsThese data reveal identifiable characteristics associated with missed clinic visits.

Open access scheduling: Improving access to rural healthcare

Background and Purpose: Open access scheduling is a model that allows patients to choose appointments at their convenience in an effort to provide timely access to healthcare. Healthcare providers typically have overbooked schedules that make it difficult to provide access to primary care appointments for patients in need without long wait times. The purpose of this quality improvement project was to implement open access scheduling at a federally-qualified health center to evaluate the number of missed patient appointments and the amount of time it takes to receive an appointment. Methods: Patient appointments (N=1,333) were analyzed via the Allscripts™ electronic computer system. During project implementation, staff utilized a written protocol for open access that had been tested at a satellite office with successful results. Patients were placed in appointment slots daily as they were available. Conclusions: The highest no-show rate prior to implementation was 42%, which improved after open access to 27%. Average TNAA trended downward post-implementation from 8.9 days three-months pre-intervention to 4.3 days three-months post-implementation. This scheduling model was successful in decreasing no-show rates by allowing patients to be seen in a timely manner and can be utilized in primary care to improve access to healthcare.

Redesigning care to meet national recommendation of four or more yearly clinic visits in patients with cystic fibrosis

Cystic fibrosis (CF) is a chronic disease requiring patients to have frequent specialty healthcare visits to delay progression of lung disease, prevent and treat failure to thrive and initiate early...

Missed Appointments in Resident Continuity Clinic: Patient Characteristics and Health Care Outcomes

Frequent missed patient appointments in resident continuity clinic is a well-documented problem, but whether rates of missed appointments are disproportionate to standard academic practice, what patient factors contribute to these differences, and health care outcomes of patients who frequently miss appointments are unclear. The overall population for the study was composed of patients in an academic internal medicine continuity clinic with 5 or more office visits between January 2006 and December 2008. We randomly selected 325 patients seen by resident physicians and 325 patients cared for by faculty. Multivariate linear regression was used to examine the relationship between patient factors and missed appointments. Health outcomes were compared between patients with frequent missed appointments and the remainder of the study sample, using Cox regression analysis. Resident patients demonstrated significantly higher rates of missed appointments than faculty patients, but this difference was explained by patient factors. Factors associated with more missed appointments included use of a medical interpreter, Medicaid insurance, more frequent emergency department visits, less time impanelled in the practice, and lower proportion of office visits with the primary care provider. Patients with frequent missed appointments were less likely to be up to date with preventive health services and more likely to have poorly controlled blood pressure and diabetes. We found that the disproportionate frequency of missed appointments in resident continuity clinic is explained by patient factors and practice discontinuity, and that patients with frequent missed appointments demonstrated worse health care outcomes.