The Impact of COVID-19 and Socioeconomic Determinants on Appointment Non-Attendance in an Urban Otolaryngology Clinic: A Retrospective Analysis From a Safety Net Hospital.

OBJECTIVE: The objective of this study is to investigate various demographic, socioeconomic, COVID-related, and clinical factors associated with missed otolaryngology appointments in the outpatient setting at Boston Medical Center (BMC), an urban safety net hospital. METHODS: A retrospective chart review was conducted on adults (≥18 years old) with scheduled appointments in the otolaryngology department at BMC from May 1, 2015, to May 1, 2022. Data were extracted from the electronic medical record and included appointment-related factors (eg, status and type), demographic variables (eg, age, sex, race, and ethnicity), and socioeconomic factors (eg, employment and insurance). Statistical analyses utilized a binary mixed-effects model to identify predictors of appointment non-attendance, with pre-COVID, during COVID, and post-COVID periods defined for comparative analysis. RESULTS: Out of 14 050 patients, 5725 (40.8%) were classified as no-show. Older age decreased the likelihood of missing appointments (OR = 0.989, 95% CI = [0.986, 0.992]). Males (OR = 1.090, 95% CI = [1.022, 1.161]), Black/African American (OR = 2.047, 95% CI = [1.878, 2.231]), and Hispanic or Latino individuals (OR = 1.369, 95% CI = [1.232, 1.521]) were more likely to not show up. Retired participants (OR = 0.859, 95% CI = [0.753, 0.981]) and those with private insurance (OR = 0.698, 95% CI = [0.643, 0.758]) were less likely to miss appointments. During the COVID-19 pandemic, appointment attendance improved (OR = 0.865, 95% CI = [0.767, 0.976]). In-person appointments had a significantly higher non-attendance rate compared to telemedicine appointments (OR = 6.133, 95% CI = [5.248, 7.167]). CONCLUSIONS: Appointment non-attendance in otolaryngology is influenced by various demographic and socioeconomic factors, with significant disparities observed among racial and ethnic groups. The COVID-19 pandemic altered attendance patterns, highlighting the potential benefits of telemedicine. These findings underscore the need for targeted interventions to address healthcare disparities and improve appointment adherence, particularly among minority and socioeconomically disadvantaged populations. Future research should incorporate patient perspectives to better understand barriers to appointment attendance.

Genomic structural equation modeling reveals latent phenotypes in the human cortex with distinct genetic architecture.

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs, although sensitivity analyses indicated that other structures were plausible. The multivariate GWASs of the GIBNs identified 74 genome-wide significant (GWS) loci (p < 5 × 10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed between attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD). CT GIBNs displayed a negative genetic correlation with alcohol dependence. Even though we observed model instability in our application of genomic SEM to high-dimensional data, jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across neuroimaging phenotypes offers new insights into the genetics of cortical structure and relationships to psychopathology.

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.

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.

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.

Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic.

Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2's propensity for asymptomatic transmission, raise the question "how reliable was contact tracing for COVID-19 in the United States"? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62-1.68%) of transmission events with PCR testing and 1.00% (95% uncertainty interval 0.98-1.02%) with rapid antigen testing. When considering a more robust contact tracing scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6-62.8%). We did not assume presence of asymptomatic transmission or superspreading, making our estimates upper bounds on the actual percentages traced. These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens.

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.

Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic.

Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests (with a high false negative rate) due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2's propensity for asymptomatic transmission, raise the question "how reliable was contact tracing for COVID-19 in the United States"? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62%-1.68%) of transmission events with PCR testing and 0.88% (95% uncertainty interval 0.86%-0.89%) with rapid antigen testing. When considering an optimal scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6%-62.8%). These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens.

Accuracy of Inferences About the Reproductive Number and Superspreading Potential of SARS-CoV-2 with Incomplete Contact Tracing Data.

The basic reproductive number (R0) and superspreading potential (k) are key epidemiological parameters that inform our understanding of a disease's transmission. Often these values are estimated using the data obtained from contact tracing studies. Here we performed a simulation study to understand how incomplete data due to preferential contact tracing impacted the accuracy and inferences about the transmission of SARS-CoV-2. Our results indicate that as the number of positive contacts traced decreases, our estimates of R0 tend to decrease and our estimates of ktend to increase. Notably, when there are large amounts of positive contacts missed in the tracing process, we can conclude that there is no indication of superspreading even if we know there is. The results of this study highlight the need for a unified public health response to transmissible diseases.