Factors influencing hospital charges for tonsillectomy to treat obstructive sleep apnea in children.

PURPOSE: This study investigates the impact of patient characteristics and demographics on hospital charges for tonsillectomy as a treatment for pediatric obstructive sleep apnea (OSA). The aim is to identify potential disparities in hospital charges and contribute to efforts for equitable access to care. METHODS: Data from the 2016 Healthcare Cost and Utilization Project (HCUP) Kid Inpatient Database (KID) was analyzed. The sample included 3,304 pediatric patients undergoing tonsillectomy ± adenoidectomy for OSA. Variables such as age, race, length of stay, hospital region, residential location, payer information, and median household income were collected. The primary outcome variable was hospital charge. Statistical analyses, including t-tests, ANOVA, and multiple linear regression, were conducted. RESULTS: Among 3,304 pediatric patients undergoing tonsillectomy for OSA. The average total charges for tonsillectomy were $26,400, with a mean length of stay of 1.70 days. Significant differences in charges were observed based on patient race, hospital region, and payer information. No significant differences were found based on gender, discharge quarter, residential location, or median household income. Multiple linear regression showed race, hospital region, and residential location were significant predictors of total hospital charges. CONCLUSION: This study highlights the influence of patient demographics and regional factors on hospital charges for pediatric tonsillectomy in OSA cases. These findings underscore the importance of addressing potential disparities in healthcare access and resource allocation to ensure equitable care for children with OSA. Efforts should be made to promote fair and affordable treatment for all pediatric OSA patients, regardless of their demographic backgrounds.

AI-generated text in otolaryngology publications: a comparative analysis before and after the release of ChatGPT.

PURPOSE: This study delves into the broader implications of artificial intelligence (AI) text generation technologies, including large language models (LLMs) and chatbots, on the scientific literature of otolaryngology. By observing trends in AI-generated text within published otolaryngology studies, this investigation aims to contextualize the impact of AI-driven tools that are reshaping scientific writing and communication. METHODS: Text from 143 original articles published in JAMA Otolaryngology - Head and Neck Surgery was collected, representing periods before and after ChatGPT's release in November 2022. The text from each article's abstract, introduction, methods, results, and discussion were entered into ZeroGPT.com to estimate the percentage of AI-generated content. Statistical analyses, including T-Tests and Fligner-Killeen's tests, were conducted using R. RESULTS: A significant increase was observed in the mean percentage of AI-generated text post-ChatGPT release, especially in the abstract (from 34.36 to 46.53%, p = 0.004), introduction (from 32.43 to 45.08%, p = 0.010), and discussion sections (from 15.73 to 25.03%, p = 0.015). Publications of authors from non-English speaking countries demonstrated a higher percentage of AI-generated text. CONCLUSION: This study found that the advent of ChatGPT has significantly impacted writing practices among researchers publishing in JAMA Otolaryngology - Head and Neck Surgery, raising concerns over the accuracy of AI-created content and potential misinformation risks. This manuscript highlights the evolving dynamics between AI technologies, scientific communication, and publication integrity, emphasizing the urgent need for continued research in this dynamic field. The findings also suggest an increasing reliance on AI tools like ChatGPT, raising questions about their broader implications for scientific publishing.

Appointment Factors Contributing to Children with Speech Disorders Missing Speech and Language Pathology Appointments.

This study explores missed pediatric speech and language pathology (SLP) appointments to identify barriers for patients with speech disorders. Data from 839 referrals at Boston Medical Center, including demographics, appointment details, COVID-19 lockdown, and number of items on patient problem lists, were analyzed using chi-square tests and logistic regression. The findings revealed that lockdown status, appointment timing, appointment type (in-person vs telemedicine), referral department (ear, nose, and throat [ENT] vs non-ENT), sex, race, primary language, birthplace, and primary care provider presence had no significant impact on attendance. However, the number of patient-listed problems, prior cancelations, and missed appointments were significant predictors of patients who did not keep appointments. In conclusion, this research emphasizes the patient's problem list and past appointment behavior as critical factors in predicting missed SLP appointments for pediatric speech disorder patients. These insights can guide targeted interventions to improve attendance and enhance SLP engagement.

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.