Factors Contributing to Missed Appointments in a Pediatric Otolaryngology Clinic

Agarwal, Pratima; Nathan, Ajay S.; Jaleel, Zaroug; Levi, Jessica R.

doi:10.1002/lary.29841

Cited by 8 publications

(8 citation statements)

References 26 publications

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“…This includes the continuous availability of in-person and telemedicine interpreters, which in other subspecialty MCV investigations has been associated with decreased MCV rates, perhaps due to more effective communication among clinics, providers, and patients. 6,11 We also note that Arabic-preferring patients in our study had lower MCV rates and lower odds for MCV than other specific language groups. Many of these patients do not permanently reside in the greater Boston area but have been sent by their home countries to receive subspecialty care.…”

Section: Discussionsupporting

confidence: 49%

“…Factors that may have partially ameliorated the increased MCV odds observed for other language groups in our study represent potential interventions. This includes the continuous availability of in‐person and telemedicine interpreters, which in other subspecialty MCV investigations has been associated with decreased MCV rates, perhaps due to more effective communication among clinics, providers, and patients 6,11 . We also note that Arabic‐preferring patients in our study had lower MCV rates and lower odds for MCV than other specific language groups.…”

Section: Discussionmentioning

confidence: 56%

“…Among sociodemographic predictors of MCVs, the relationship between patient‐preferred language and clinic visit attendance remains relatively underexplored in the pediatric literature, with previous studies producing conflicting findings. Cross‐study comparisons have been limited by using interpreter requests as a proxy for language fluency, limited language comparison (often limited to English vs. Spanish), or grouping languages other than English to achieve statistical significance 1,4–7,9,11–15 . Similarly, fewer studies have assessed the associations between patient‐preferred languages and MCV occurrence for pediatric patients utilizing telemedicine 7,9,14,15 .…”

Section: Introductionmentioning

confidence: 99%

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Analysis of missed clinic visits, preferred languages, and telemedicine in a pediatric gastroenterology practice

Crume,

Suufi,

Nabbosa

et al. 2024

J. pediatr. gastroenterol. nutr.

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ObjectivesPrevious studies have demonstrated a relationship between socioeconomic disparities and missed clinic visits (MCV). However, the relationship between patient‐preferred language and MCVs, particularly with respect to telemedicine, remains relatively underexplored. We sought to characterize the associations between MCV and patient‐level predictors, including preferred language, in a large single‐center pediatric gastroenterology, hepatology, and nutrition practice.MethodsThis retrospective longitudinal cohort study included all missed or completed outpatient visits in the Gastroenterology, Hepatology, and Nutrition Programs at Boston Children's Hospital from January 1, 2016 to May 20, 2022. Univariate and multivariate hierarchical generalized linear mixed models were employed to identify associations between visit‐ and patient‐level predictors and an MCV outcome.ResultsA total of 300,201 visits from 70,710 patients residing in Massachusetts were included. Univariate analyses revealed higher MCV odds for Hispanic patients and those from areas with the highest Social Vulnerability Index (SVI), and these odds increased with telemedicine (Hispanic in‐person odds ratio [OR] 5.21 [(95% confidence interval) 4.93–5.52] vs. telemedicine OR 8.79 [7.85–9.83]; highest SVI in‐person OR 5.28 [4.95–5.64] vs. telemedicine OR 7.82 [6.84–8.96]). Controlled multivariate analyses revealed that among six language groups, only Spanish language preference was associated with higher MCV odds, which increased with telemedicine (Spanish in‐person adjusted OR [aOR] 1.35 [1.24–1.48] vs. telemedicine aOR 2.1 [1.83–2.44]).ConclusionsPatients preferring Spanish experience unique barriers to care beyond those faced by other language preference groups, and telemedicine may exacerbate these barriers.

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Section: Discussionsupporting

confidence: 49%

Section: Discussionmentioning

confidence: 56%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of missed clinic visits, preferred languages, and telemedicine in a pediatric gastroenterology practice

Crume,

Suufi,

Nabbosa

et al. 2024

J. pediatr. gastroenterol. nutr.

View full text Add to dashboard Cite

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“…The medical facilities can use Short Message Service (SMS), an automated phone calls reminders 2-3 days before the medical appointment, mainly if the lead time is so long (more than four months). Furthermore, changing the lead days to be no more than 2-3 months [31][32].…”

Section: Resultsmentioning

confidence: 99%

The Prediction of Pediatric Outpatient No-Show Visits by Employing Machine Learning Framework

Alshammari¹,

Alaboodi²,

Alshammari³

2022

IJACSA

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Patient no-show for a booked medical appointment is a significant problem that negatively impacts healthcare resource utilization, cost, efficiency, quality, and patient outcomes. This paper developed a machine learning framework to predict pediatric patients' no-shows to medical appointments accurately. Thirty months of outpatient visits data were extracted from data warehouse from January 2017 to July 2019 of the Ministry of National Guard Health Affairs (MNGHA), Saudi Arabia. The researchers retrieved the data from all healthcare facilities in the central region, and more than 100 attributes were generated. The data includes over 100,000 pediatric patients and more than 3.7 million visits. Five machine learning algorithms were deployed, where Gradient Boosting (GB) algorithm outperformed the other four machine learning algorithms: decision tree, random forest, logistic regression, and neural network. The study evaluated and compared the performance of the five models based on five evaluations criteria. GB achieved a Receiver Operating Characteristic (ROC) score of 97.1%. Furthermore, this research paper identified the factors that have massive potential for effecting patients' adherence to scheduled appointments.

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“…As for the afternoon slot (13:00-13:30), patients are at their lunch break, and that is probably why more patients arrive late than in other time slots. Therefore, under the principle of giving priority to patients with an appointment, punctuality and special circumstances, a certain punishment mechanism for late arrivals may be adopted in the waiting areas of the outpatient clinic, such as arranging delayed visits, etc., in order to guide the change of patients' visit habits [22] .…”

Section: Discussionmentioning

confidence: 99%

Analysis on the Characteristics of Patients Late for Appointment Slots in a Thoracic Surgery Clinic

Guo

Zhang

et al. 2022

Preprint

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Background: With the development of internet-assisted medical services, in the outpatient time slot-based online appointment system, patients’ late arrival has a negative impact on the output of medical services. Identifying the characteristics of late-arriving outpatients helps identify intervention strategies and management mechanisms against late arrival.Methods: In this study, the demographic information and appointment-based visit information of 29,337 patients in the Thoracic Surgery Clinic in 2019 were retrieved from the hospital information system of a Class A tertiary hospital in China, covering nine fields. After excluding those with missing information, valid data from 9,378 patients were obtained. The patients who were on time for visits constituted the control group. The SPSS 24.0 software was used to conduct statistical tests and regression analysis of patients with late arrival (P <0.05). Results: Univariate test showed that there were seven characteristics that affected patients’ late arrival, including gender, place of origin, visit type, weekday of visit, booking method, the level of specialist and visit time slot. Multivariate analysis showed a total of six combined characteristics: gender, age, visit type, weekday of visit, booking method and level of specialist. Patients had the highest rate of late arrival on Mondays, reaching 34.6%. Among the morning slots of the day, the rate of late arrivals during 08:30-09:00 was the highest, reaching 78.1%; and among the afternoon slots, the rate of late arrivals during 13:00-13:30 was the highest, reaching 65.7%. The group of late-arriving patients on Mondays were characterised by the time slot of visit, visit type and payment type, while the group of late-arriving patients in the two peak slots were characterised by booking method, payment type, weekday of visit and level of specialist.Conclusion: Patients who arrived later than the booked time slots are characterized by some features, such as being female, showing ‘morning-market’ feature and residing in a short distance. This study discussed the possible interventions for late arrival and the recommended strategies for making appointments based on the above characteristics.

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Factors Contributing to Missed Appointments in a Pediatric Otolaryngology Clinic

Cited by 8 publications

References 26 publications

Analysis of missed clinic visits, preferred languages, and telemedicine in a pediatric gastroenterology practice

Analysis of missed clinic visits, preferred languages, and telemedicine in a pediatric gastroenterology practice

The Prediction of Pediatric Outpatient No-Show Visits by Employing Machine Learning Framework

Analysis on the Characteristics of Patients Late for Appointment Slots in a Thoracic Surgery Clinic

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