Disparities in polysomnography referral in a high-risk cardiac population.

PURPOSE: Obstructive sleep apnea (OSA) is associated with metabolic, cardiovascular, and cerebrovascular comorbidities. Appropriate diagnosis and treatment of OSA might mitigate these comorbidities. This retrospective review sought to assess the impact of sex, age, race, ethnicity, and insurance status on polysomnography (PSG) referral rates. METHODS: An institutional STOP-Bang database of 299,320 patients was filtered for patients admitted to the hospital with an acute cardiac diagnosis between 2015-2020. A cohort of 4,735 patients were risk stratified by STOP-Bang (SB) score and correlations were made between PSG referrals and demographic and clinical variables (sex, age, race, ethnicity, and insurance status). RESULTS: Of the 25.3% of the cohort with high SB scores (5-8) only 21.3% were referred for PSG. Age and female sex were negatively associated with sleep study referrals (p < 0.001). No correlation was found between sleep study referral rates and race or ethnicity. No correlation was found between sleep study referrals and insurance provider. Admitting cardiac diagnosis significantly influenced sleep study referrals with diagnoses of arrhythmias and myocardial infarction being associated with an increased rate of PSG referrals compared to heart failure patients (p < 0.002). CONCLUSIONS: Our study found no significant correlation between PSG referral rates and race, ethnicity, or insurance provider. However, we found low overall rates of PSG referral, with negative correlations between older age and female sex and a high-risk cardiac population. This represents a substantial missed opportunity to identify patients at risk for OSA, obtain a diagnosis, and provider adequate treatment.

Designing a Consumer-Friendly Radiology Report using a Patient-Centered Approach.

Patient portals have helped accelerate patient engagement in treatment. Patient understanding of radiology reports has become a necessity, and we are working to design a patient-friendly radiology report that can be easily understood. We have based the design of this new radiology report on the results of a previous study that examined patient desires and needs by exploring their questions posted on online discussion forums. The current design was tested by presenting it in two groups, a control group, and an intervention group. In our evaluation, we relied on the following five concepts: understanding (quiz), cosmetics appearance, perceived ease of use, acceptance, and preference. The results showed that the new design outperformed the current design in all five concepts with an overall of (P < .00). Based on these results, we have determined that the radiology report should include both an image and notes section, and the design can be applied to all types of radiological examinations using various imaging devices. We believe this design will be an important building block in facilitating patient understanding of radiology reports.

Social factors shaping the adoption of lead-filtering point-of-use systems: an observational study of an MTurk sample.

Some municipalities are promoting lead-filtering point-of-use (POU) systems to minimize the risk of lead exposure through drinking water, often targeting use at racial minorities and low-income households. However, links among social inequality markers and adoption of these systems are not well understood. Survey data on adoption and use of POU systems were collected from a U.S. Mechanical Turk (MTurk) sample (N = 2,867) in March 2018. We use logistic regression to assess the association of race/ethnicity, socioeconomic status (SES), and lead-filtering POU adoption. We also examined key health behaviors related to POU systems. We found that race and SES are indirectly predictive of lead-filtering POU adoption through the propensity of some respondents to report a residence with a lead service line and levels of concern and knowledge about lead exposure. In addition, individuals with similar levels of concern about lead in water have lower odds of adopting a POU system if they have lower, rather than higher, incomes. Among POU adopters, while confidence in correct use of these devices was relatively high, the frequency of filtered water use for cooking was lower than drinking frequency. Overall, these findings inform health policies aimed at mitigating risk of lead exposure through water.

A systematic approach for developing a corpus of patient reported adverse drug events: A case study for SSRI and SNRI medications.

"Psychiatric Treatment Adverse Reactions" (PsyTAR) corpus is an annotated corpus that has been developed using patients narrative data for psychiatric medications, particularly SSRIs (Selective Serotonin Reuptake Inhibitor) and SNRIs (Serotonin Norepinephrine Reuptake Inhibitor) medications. This corpus consists of three main components: sentence classification, entity identification, and entity normalization. We split the review posts into sentences and labeled them for presence of adverse drug reactions (ADRs) (2168 sentences), withdrawal symptoms (WDs) (438 sentences), sign/symptoms/illness (SSIs) (789 sentences), drug indications (517), drug effectiveness (EF) (1087 sentences), and drug infectiveness (INF) (337 sentences). In the entity identification phase, we identified and extracted ADRs (4813 mentions), WDs (590 mentions), SSIs (1219 mentions), and DIs (792). In the entity normalization phase, we mapped the identified entities to the corresponding concepts in both UMLS (918 unique concepts) and SNOMED CT (755 unique concepts). Four annotators double coded the sentences and the span of identified entities by strictly following guidelines rules developed for this study. We used the PsyTAR sentence classification component to automatically train a range of supervised machine learning classifiers to identifying text segments with the mentions of ADRs, WDs, DIs, SSIs, EF, and INF. SVMs classifiers had the highest performance with F-Score 0.90. We also measured performance of the cTAKES (clinical Text Analysis and Knowledge Extraction System) in identifying patients' expressions of ADRs and WDs with and without adding PsyTAR dictionary to the core dictionary of cTAKES. Augmenting cTAKES dictionary with PsyTAR improved the F-score cTAKES by 25%. The findings imply that PsyTAR has significant implications for text mining algorithms aimed to identify information about adverse drug events and drug effectiveness from patients' narratives data, by linking the patients' expressions of adverse drug events to medical standard vocabularies. The corpus is publicly available at Zolnoori et al. [30].

A Principal Components Analysis Approach to Quantifying Foot Clearance and Foot Clearance Variability.

Low foot clearance and high variability may be related to falls risk. Foot clearance is often defined as the local minimum in toe height during swing; however, not all strides have this local minimum. The primary purpose of this study was to identify a nondiscrete measure of foot clearance during all strides, and compare discrete and nondiscrete measures in ability to rank individuals on foot clearance and variability. Thirty-five participants (young adults [n = 10], older fallers [n = 10], older nonfallers [n = 10], and stroke survivors [n = 5]) walked overground while lower extremity 3D kinematics were recorded. Principal components analysis (PCA) of the toe height waveform yielded representation of toe height when it was closest to the ground. Spearman's rank order correlation assessed the association of foot clearance and variability between PCA and discrete variables, including the local minimum. PCA had significant (P < .05) moderate or strong associations with discrete measures of foot clearance and variability. An approximation of the discrete local minimum had a weak association with PCA and other discrete measures of foot clearance. A PCA approach to quantifying foot clearance can be used to identify the behavioral components of toe height when it is closest to the ground, even for strides without a local minimum.

Using data-driven sublanguage pattern mining to induce knowledge models: application in medical image reports knowledge representation.

BACKGROUND: The use of knowledge models facilitates information retrieval, knowledge base development, and therefore supports new knowledge discovery that ultimately enables decision support applications. Most existing works have employed machine learning techniques to construct a knowledge base. However, they often suffer from low precision in extracting entity and relationships. In this paper, we described a data-driven sublanguage pattern mining method that can be used to create a knowledge model. We combined natural language processing (NLP) and semantic network analysis in our model generation pipeline. METHODS: As a use case of our pipeline, we utilized data from an open source imaging case repository, Radiopaedia.org , to generate a knowledge model that represents the contents of medical imaging reports. We extracted entities and relationships using the Stanford part-of-speech parser and the "Subject:Relationship:Object" syntactic data schema. The identified noun phrases were tagged with the Unified Medical Language System (UMLS) semantic types. An evaluation was done on a dataset comprised of 83 image notes from four data sources. RESULTS: A semantic type network was built based on the co-occurrence of 135 UMLS semantic types in 23,410 medical image reports. By regrouping the semantic types and generalizing the semantic network, we created a knowledge model that contains 14 semantic categories. Our knowledge model was able to cover 98% of the content in the evaluation corpus and revealed 97% of the relationships. Machine annotation achieved a precision of 87%, recall of 79%, and F-score of 82%. CONCLUSION: The results indicated that our pipeline was able to produce a comprehensive content-based knowledge model that could represent context from various sources in the same domain.

Semantic-Enhanced Query Expansion System for Retrieving Medical Image Notes.

Most current image retrieval methods require constructing semantic metadata for representing image content. To manually create semantic metadata for medical images is time-consuming, yet it is a crucial component for query expansion. We proposed a new method for searching medical image notes that uses semantic metadata to improve query expansion and leverages a knowledge model developed specifically for the medical image domain to create relevant metadata. We used a syntactic parser and the Unified Medical Language System to analyze the corpus and store text information as semantic metadata in a knowledge model. Our new method has an interactive interface that allows users to provide relevance feedback and construct new queries more efficiently. Sixteen medical professionals evaluated the query expansion module, and each evaluator had prior experience searching for medical images. When using the initial query as the baseline standard, expanded queries achieved a performance boost of 22.6% in terms of the relevance score on first ten results (P-value<0.05). When using Google as another baseline, our system performed 24.6% better in terms of relevance score on the first ten results (P-value<0.05). Overall, 75% of the evaluators said the semantic-enhanced query expansion workflow is logical, easy to follow, and comfortable to use. In addition, 62% of the evaluators preferred using our system instead of Google. Evaluators who were positive about our system found the knowledge map-based visualization of candidate medical search terms helpful in refining cases from the initial search results.

SimQ: real-time retrieval of similar consumer health questions.

BACKGROUND: There has been a significant increase in the popularity of Web-based question-and-answer (Q&A) services that provide health care information for consumers. Large amounts of Q&As have been archived in these online communities, which form a valuable knowledge base for consumers who seek answers to their health care concerns. However, due to consumers' possible lack of professional knowledge, it is still very challenging for them to find Q&As that are closely relevant to their own health problems. Consumers often repeatedly ask similar questions that have already been answered previously by other users. OBJECTIVE: In this study, we aim to develop efficient informatics methods that can retrieve similar Web-based consumer health questions using syntactic and semantic analysis. METHODS: We propose the "SimQ" to achieve this objective. SimQ is an informatics framework that compares the similarity of archived health questions and retrieves answers to satisfy consumers' information needs. Statistical syntactic parsing was used to analyze each question's syntactic structure. Standardized Unified Medical Language System (UMLS) was employed to annotate semantic types and extract medical concepts. Finally, the similarity between sentences was calculated using both semantic and syntactic features. RESULTS: We used 2000 randomly selected consumer questions to evaluate the system's performance. The results show that SimQ reached the highest precision of 72.2%, recall of 78.0%, and F-score of 75.0% when using compositional feature representations. CONCLUSIONS: We demonstrated that SimQ complements the existing Q&A services of Netwellness, a not-for-profit community-based consumer health information service that consists of nearly 70,000 Q&As and serves over 3 million users each year. SimQ not only reduces response delay by instantly providing closely related questions and answers, but also helps consumers to improve the understanding of their health concerns.

RMS: a platform for managing cross-disciplinary and multi-institutional research project collaboration.

BACKGROUND: Cross-institutional cross-disciplinary collaboration has become a trend as researchers move toward building more productive and innovative teams for scientific research. Research collaboration is significantly changing the organizational structure and strategies used in the clinical and translational science domain. However, due to the obstacles of diverse administrative structures, differences in area of expertise, and communication barriers, establishing and managing a cross-institutional research project is still a challenging task. We address these challenges by creating an integrated informatics platform to reduce the barriers to biomedical research collaboration. RESULTS: The Request Management System (RMS) is an informatics infrastructure designed to transform a patchwork of expertise and resources into an integrated support network. The RMS facilitates investigators' initiation of new collaborative projects and supports the management of the collaboration process. In RMS, experts and their knowledge areas are categorized and managed structurally to provide consistent service. A role-based collaborative workflow is tightly integrated with domain experts and services to streamline and monitor the life-cycle of a research project. The RMS has so far tracked over 1,500 investigators with over 4,800 tasks. The research network based on the data collected in RMS illustrated that the investigators' collaborative projects increased close to 3 times from 2009 to 2012. Our experience with RMS indicates that the platform reduces barriers for cross-institutional collaboration of biomedical research projects. CONCLUSION: Building a new generation of infrastructure to enhance cross-disciplinary and multi-institutional collaboration has become an important yet challenging task. In this paper, we share the experience of developing and utilizing a collaborative project management system. The results of this study demonstrate that a web-based integrated informatics platform can facilitate and increase research interactions among investigators.

The Impact of Sociodemographic Factors on Rates of Tympanostomy Tube Placement for Pediatric Otitis Media.

Objective: To identify the impact of race, ethnicity, and socioeconomic status (SES) on the rate of tympanostomy tube placement. Study Design: Retrospective medical review and population-level analyses. Setting: Tertiary referral center. Methods: Demographic and population-level characteristics (age, gender, race, insurance status, and ZIP code) compared to the regional, health system, and otolaryngology clinic demographics. Results: Among 38,461 children diagnosed with otitis media (OM) 61.4% were white, 27.4% were black, 32.7% had private insurance, and 18.2% were Hispanic. Among patients seen in the pediatric ear, nose, and throat (ENT) clinics, 70.0% were white, 20.0% were black, 46.6% had private insurance, and 14.9% were Hispanic. Further disparity was noted among those receiving tympanostomy tubes: 75.6% white, 15.6% black, 61.9% private insurance, and 11.7% Hispanic. Higher rates of tube placement were noted for those of white race [odds ratio, OR: 1.96, (95% confidence interval, CI: 1.85-2.04), <.001] and non-Hispanic ethnicity [OR: 1.67, (95% CI: 1.56-1.75), <.001]. Geographically, rates of tube placement were significantly lower in areas with higher deprivation indices, areas with lower proportions of white residents, and areas with the lowest median incomes. These markers correlate strongly with black race and Hispanic ethnicity. Lower rates of tube placement were also seen in majority white locales with higher deprivation indices and lower median incomes. Conclusion: Rates of access to pediatric ENT clinics, and of tube placement, are significantly lower for those of Hispanic ethnicity and black race than for non-Hispanic white children. Higher rates of tube placement were noted among white children and those with private insurance. Lower rates of tube placement were seen in areas of lower SES regardless of racial demographics.

Evaluation of Social Determinants of Health on Dysphagia Care Pathways at a Tertiary Care Facility.

OBJECTIVES: Limited research exists evaluating the impact of social determinants of health in influencing care pathways for patients with dysphagia. A better understanding of whether these determinants correlate to altered care and resource utilization is essential as it relates to patient outcomes. STUDY DESIGN: Retrospective chart review. METHODS: All adult patients seen at a tertiary midwestern hospital were screened for ICD codes of dysphagia diagnoses from 2009 to 2019. Demographic information was collected from these patients with dysphagia including sex, race, ethnicity, and insurance status. Subgroup analysis was performed to assess referral pattern rates and types of diagnostic interventions ordered (none, videofluoroscopic swallow study, esophagram, and esophagogastroduodenoscopy). RESULTS: A total of 31,858 patients with dysphagia were seen at our institution during the study period, with a majority being female (56.36%), Caucasian (79.83%), and publicly insured (63.16%), at a median age of 60.35 years. There were no significant care delivery pattern differences based on geography/zip code analyses. African American patients were significantly more likely to have imaging or interventions performed (odds ratio [OR] 1.463, p = 0.005). Patients with public insurance also had higher rates of diagnostic study utilization (OR 1.53, p = 0.01). Only 3% of all patients with dysphagia were seen by laryngologists. CONCLUSION: No significant differences were seen in dysphagia evaluation modalities based on zip code analyses surrounding this tertiary care facility. African American patients and those with public insurance had significantly higher utilization of subsequent testing and intervention for dysphagia care. Further studies are necessary to delineate causes and outcome differences for these measurable differences in dysphagia care pathways. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:1139-1146, 2024.

Association between body-mass index, patient characteristics, and obesity-related comorbidities among COVID-19 patients: A prospective cohort study.

OBJECTIVE: Obesity is a major risk factor for adverse outcomes after COVID-19 infection. However, it is unknown if the worse outcomes are due to the confounding effect of demographic and obesity-related comorbidities. The study objective is to analyze associations between body mass index, patient characteristics, obesity-related comorbidity, and clinical outcomes in COVID-19 patients. METHODS: In this prospective cohort study, we chose patient records between March 1st, 2020, and December 1st, 2022, in a large tertiary care center in southeast Wisconsin in the United States. Patients over the age of 18 who tested positive were included in the study. Clinical outcomes included hospitalization, intensive care unit (ICU) admission, mechanical ventilation, and mortality rates. We examined the characteristics of patients who had positive clinical outcomes. We created unadjusted logistic regression models, sequentially adjusting for demographic and comorbidity variables, to assess the independent associations between BMI, patient characteristics, obesity-related comorbidities, and clinical outcomes. RESULTS: From a record of 1.67 million inpatients and outpatients at Froedtert Health Center, 55,299 (BMI: 30.5 ± 7.4 kg/m2, 62.5 % female) tested COVID-19 positive during the study period. 17,580 (31.8 %) patients were admitted to hospitals, and of hospitalized patients required ICU admission. 1038 (36.3 %) required mechanical ventilation, and 462 (44.5 %) died after a positive test for COVID-19. We found female patients show a higher hospitalization rate, while male patients have a higher rate of ICU admission, mechanical ventilation, and mortality. Obesity-related comorbidities are associated with worse outcomes compared to simple obesity without comorbidities. In logistic regression models, we found four similar V-shaped associations between BMI and four clinical outcomes. Patients with a BMI of 25 kg/m2 are at the lowest risk for clinical outcomes. Patients with a BMI lower than 18 kg/m2 or higher than 30 kg/m2 are associated with a higher risk of hospitalization, ICU, mechanical ventilation, and death. After adjusting the model for demographic factors and hypertension and diabetes as two common comorbidities, we found that demographic factors do not significantly increase the risk. Obesity alone does not significantly increase the risk of severe clinical outcomes. Obesity-related comorbidities, on the other hand, resulted in a significantly higher risk of outcomes. CONCLUSION: Obesity alone does not increase the risk of worse clinical outcomes after COVID-19 infection. It may suggest that the worse clinical outcomes of patients with obesity are mediated via hypertension and type 2 diabetes. Patients with obesity and comorbidities have a higher risk of poor outcomes. Obesity-related comorbidities, including hypertension and diabetes, are independently associated with poorer clinical outcomes among COVID-19 patients. At a BMI of more than 30 kg/m2 or less than 18 kg/m2, we found an increase in the risk of severe COVID-19 outcomes leading to hospitalization, ICU, mechanical ventilation, and death. The increased risk of severe outcomes is not attributed to patient characteristics but can be attributed to hypertension and diabetes.

The Demographics of Menière's Disease: Selection Bias or Differential Susceptibility?

OBJECTIVE: To clarify whether the reported lack of racial and ethnic diversity among Menière's disease (MD) patients is representative of selection bias or disease susceptibility. STUDY DESIGN: Retrospective medical record review and population-level analyses. SETTING: Tertiary referral center. PATIENTS: Cohort of 1091 patients diagnosed with MD by the tertiary otology service. MAIN OUTCOME MEASURE: Demographic and population-level characteristics (age, sex, race, insurance status, ZIP code, median income, education level) compared with local, regional, health system, and otolaryngology clinic demographics. RESULTS: Patients seen for MD were significantly older than those seen throughout the otolaryngology clinic (median, 65.0 versus 58.8 yr) or health system (65.0 versus 50.8 yr). A majority of patients with MD were of White race (92%), compared with 2.7% Black race and 0.5% Asian. Using population-level data, median income and having medical insurance were significantly correlated with care for MD. A disproportionate rate of care for MD was seen in ZIP codes outside urban areas as compared with other otologic and otolaryngologic conditions seen in the same clinic. CONCLUSION: Patients with MD are of older age, more likely to be of White race, and disproportionately from rural locales. The demographic profile of patients diagnosed with MD by tertiary otology is better explained by differential susceptibility to MD than by selection bias.

Factors associated with delayed referral and hearing rehabilitation for congenital sensorineural hearing loss.

OBJECTIVES: To identify the impact of social determinants of health and clinical status on referral and intervention for congenital sensorineural hearing loss. STUDY DESIGN: Retrospective chart review of children with confirmed sensorineural or mixed hearing loss between 2013 and 2021 at a single academic medical institution. METHODS: Referral rates and timing for hearing rehabilitation, rates and timing of completed evaluation, and rate and timing of amplification were recorded. Patient demographics included gestational age, race, ethnicity, sex, hearing loss severity, and CMV status. RESULTS: There were 216 children with confirmed sensorineural or mixed hearing loss, of which 77 had a unilateral hearing loss and 89 a severe or profound hearing loss. Delayed referral for hearing aid evaluation was noted in premature patients (median 375 days premature, median 147 term; p < 0.01) and publicly insured patients (median 215 days, median 123 private; p = 0.04). Delayed time to hearing aid fitting was noted for non-white patients (median 325 days, median 203 white patients; p < 0.01), publicly insured patients (median 309 days, median 212 private insurance; p < 0.02), and premature patients (median 462 days, median 224 term; p = 0.03). White patients were more likely to be referred for cochlear implant (p = 0.03).Privately insured patients and patients with a positive CMV test were more likely to be referred for cochlear implant evaluation, be seen in the cochlear implant clinic, and undergo implantation (p < 0.05). Non-white patients had a delay in cochlear implantation referral (median 928 days, median 398 days white patients; p = 0.05). Prolonged interval between evaluation in cochlear implant clinic to implantation was noted for privately insured patients (median 125 days; median 78 days publicly insured; p = 0.05). CONCLUSIONS: Sociodemographic factors were significantly associated with hearing amplification referral rates and time until amplification for children with identified congenital sensorineural hearing loss. For cochlear implantation, insurance type, CMV status were significantly associated with rate and timing of cochlear implant pathway.

Impacts of Socioeconomic Status on Dentoalveolar Trauma.

INTRODUCTION: Children sustain dentoalveolar trauma and lose teeth at the same rate regardless of socioeconomic status; however, debate surrounds these rates in adults. It is known socioeconomic status plays a major role in access and treatment in health care. This study aims to clarify the role of socioeconomic status as a risk factor for dentoalveolar trauma in adults. METHODS: A single center retrospective chart review took place from January 2011 through December 2020 for patients requiring oral maxillofacial surgery consultation in the emergency department, due to either dentoalveolar trauma (Group 1) or other dental condition (Group 2). Demographic information including age, sex, race, marital status, employment status, and type of insurance were collected. Odds ratios were calculated by chi-square analysis with significance set at P < 0.05. RESULTS: Over the course of 10 years, 247 patients (53% female) required an oral maxillofacial surgery consultation, with 65 (26%) sustaining dentoalveolar trauma. Within this group, there were significantly more subjects who were Black, single, insured with Medicaid, unemployed, and 18 - 39 years old. In the nontraumatic control group, there were significantly more subjects who were White, married, insured with Medicare, and 40 - 59 years old. CONCLUSIONS: Among those seen in the emergency department requiring an oral maxillofacial surgery consultation, those with dentoalveolar trauma have an increased likelihood of being single, Black, insured with Medicaid, unemployed, and 18 - 39 years old. Further research is needed to determine causality and the most critical/influential socioeconomic status factor in sustaining dentoalveolar trauma. Identifying these factors can assist in developing future community-based prevention and educational programs.

A Survey of Conversational Agents and Their Applications for Self-Management of Chronic Conditions.

Conversational agents have gained their ground in our daily life and various domains including healthcare. Chronic condition self-management is one of the promising healthcare areas in which conversational agents demonstrate significant potential to contribute to alleviating healthcare burdens from chronic conditions. This survey paper introduces and outlines types of conversational agents, their generic architecture and workflow, the implemented technologies, and their application to chronic condition self-management.

Telemedicine and health disparities: Association between patient characteristics and telemedicine, in-person, telephone and message-based care during the COVID-19 pandemic.

Telemedicine has been an essential form of care since the onset of the COVID-19 pandemic. However, telemedicine may exacerbate disparities for populations with limited digital literacy or access, such as older adults, racial minorities, patients of low income, rural residences, or limited English proficiency. From March 2020 to March 2022, this retrospective cohort study analyzed the use of in-person, phone/message, and telemedical care at a single tertiary care center in an oncology department. We investigated the association between economic, racial, ethnic, socioeconomic factors and forms of care, including in-person visits, telemedicine-based visits, and telephone/messages. The study results show that telemedicine utilization is lower among patients 65 and older, female patients, American Indian or Alaska Native patients, uninsured patients, and patients who require interpreters during clinical visits. As a result, it is unlikely that telemedicine will provide equal access to clinical care for all populations. On the other hand, in-person care utilization remains low in low-income and rural-living patients compared to the general population, while telephone and message use remains high in low-income and rural-living patients. We conclude that telemedicine is currently unable to close the utilization gap for populations of low socioeconomic status. Patients with low socioeconomic status use in-person care less frequently. For the disadvantaged, unusually high telephone or message utilization is unlikely to provide the same quality as in-person or telemedical care. Understanding the causes of disparity and promoting a solution to improve equal access to care for all patients is critical.

The impact of social determinants of health and clinical comorbidities on post-tympanotomy tube otorrhea.

OBJECTIVES: To measure the impact of social determinants of health and clinical comorbidities on the incidence of post-tympanotomy tube otorrhea (PTTO). METHODS: Retrospective observational cohort study. All children between the ages of 0 and 17 having tympanotomy tube placement between 2009 and 2019. Between group comparisons entailed the calculation of odds ratios (OR) with 95% confidence intervals and associated p-values. RESULTS: Among 12,757 patients who underwent myringotomy and tube placement, 2217 (17.4%) presented with PTTO within 1 year. Race and sex did not correlate with the development of PTTO. Non-Hispanic ethnicity had a negative association with PTTO (OR: 0.80 (0.70-0.91), p < .0001). Insurance status correlated with incidence of PTTO with a higher rate noted among those with public insurance (OR: 1.12 (1.02-1.23), p = .02) and a lower rate among those with private insurance (OR: 0.84 (0.77-0.92), p < .0001). Craniofacial abnormalities had the strongest positive correlation with PTTO, particularly, cleft lip and/or cleft palate (OR>2.24, p < .0001). Immunodeficiency had similar impact on PTTO (OR: 2.38 (1.46-3.91), p < .0001). Asthma and prematurity did not significantly correlate with occurrence of PTTO. CONCLUSION: Higher rates of PTTO correlated strongest with clinical factors; particularly craniofacial abnormalities and immunodeficiency. Social determinants, including private insurance and non-Hispanic ethnicity, were associated with lower rates of PTTO. Race and sex did not show significant correlations.

Proposed Questions to Assess the Extent of Knowledge in Understanding the Radiology Report Language.

Radiotherapy and diagnostic imaging play a significant role in medical care. The amount of patient participation and communication can be increased by helping patients understand radiology reports. There is insufficient information on how to measure a patient's knowledge of a written radiology report. The goal of this study is to design a tool that will measure patient literacy of radiology reports. A radiological literacy tool was created and evaluated as part of the project. There were two groups of patients: control and intervention. A sample radiological report was provided to each group for reading. After reading the report, the groups were quizzed to see how well they understood the report. The participants answered the questions and the correlation between the understanding of the radiology report and the radiology report literacy questions was calculated. The correlations between radiology report literacy questions and radiology report understanding for the intervention and control groups were 0.522, p < 0.001, and 0.536, p < 0.001, respectively. Our radiology literacy tool demonstrated a good ability to measure the awareness of radiology report understanding (area under the receiver operator curve in control group (95% CI: 0.77 (0.71-0.81)) and intervention group (95% CI: 0.79 (0.74-0.84))). We successfully designed a tool that can measure the radiology literacy of patients. This tool is one of the first to measure the level of patient knowledge in the field of radiology understanding.