Rural Otolaryngology Care Disparities: A Scoping Review

Modeling the importance of physician training in practice location for Ohio otolaryngologists

CONTEXT

Underserved communities in southeastern Ohio and Appalachia face significant healthcare accessibility challenges, with the Midwest offering a lower density of healthcare providers compared to coastal regions. Specifically, underserved communities in southeastern Ohio and Appalachia are disadvantaged in otolaryngology care.

OBJECTIVES

This analysis aims to identify factors that lead otolaryngologists to a respective practice location, and if any of that influence comes from where otolaryngologists completed their medical education.

METHODS

The proportion of otolaryngologists who performed medical school, residency, and/or fellowship in Ohio was analyzed utilizing a three-sample test for equality. Multivariate logistic regression and Pearson prediction models were produced to analyze the impact of performing medical training (medical school, residency, and fellowship) in Ohio.

RESULTS

Going to medical school in Ohio significantly increases the odds of going to an otolaryngology residency in the state (p<0.001). Moreover, between medical school and residency, medical school was a significantly better predictor of otolaryngologists practicing in Appalachia (Δ Bayesian Information Criterion [BIC]>2) and southeast Ohio (ΔBIC>10). Medical school in state was also a better predictor of percent rural and median household income than residency (ΔBIC>10). The multivariate model of medical school and residency was significantly better than either predictor alone for the population (ΔBIC>2). All models predicting percent rural were significantly improved with the addition of a Doctor of Osteopathy (DO) degree (ΔBIC>10).

CONCLUSIONS

Where physicians complete their medical training (medical school, residency, and fellowship) in state has a significant impact on predicting their future place of practice. This study found that the location of such training has a positive predictive nature as to whether that physician will practice in a rural and underserved area in the future. Notably, the addition of being licensed as a DO also increased the probability of that physician practicing in a rural area.

Comparison of ChatGPT-4, Copilot, Bard and Gemini Ultra on an Otolaryngology Question Bank

OBJECTIVE

To compare the performance of Google Bard, Microsoft Copilot, GPT-4 with vision (GPT-4) and Gemini Ultra on the OTO Chautauqua, a student-created, faculty-reviewed otolaryngology question bank.

STUDY DESIGN

Comparative performance evaluation of different LLMs.

SETTING

N/A.

PARTICIPANTS

N/A.

METHODS

Large language models (LLMs) are being extensively tested in medical education. However, their accuracy and effectiveness remain understudied, particularly in otolaryngology. This study involved inputting 350 single-best-answer multiple choice questions, including 18 image-based questions, into four LLMS. Questions were sourced from six independent question banks related to (a) rhinology, (b) head and neck oncology, (c) endocrinology, (d) general otolaryngology, (e) paediatrics, (f) otology, (g) facial plastics, reconstruction and (h) trauma. LLMs were instructed to provide an output reasoning for their answers, the length of which was recorded.

RESULTS

Aggregate and subgroup analysis revealed that Gemini (79.8%) outperformed the other LLMs, followed by GPT-4 (71.1%), Copilot (68.0%), and Bard (65.1%) in accuracy. The LLMs had significantly different average response lengths, with Bard (x̄ = 1685.24) being the longest and no difference between GPT-4 (x̄ = 827.34) and Copilot (x̄ = 904.12). Gemini's longer responses (x̄ =1291.68) included explanatory images and links. Gemini and GPT-4 correctly answered image-based questions (n = 18), unlike Copilot and Bard, highlighting their adaptability and multimodal capabilities.

CONCLUSION

Gemini outperformed the other LLMs in terms of accuracy, followed by GPT-4, Copilot and Bard. GPT-4, although it has the second-highest accuracy, provides concise and relevant explanations. Despite the promising performance of LLMs, medical learners should cautiously assess accuracy and decision-making reliability.

An Analysis of the Otolaryngology Workforce in Pennsylvania

Objective

This study aims to analyze the distribution of otolaryngologists between urban and rural counties in Pennsylvania.

Study Design

Retrospective database.

Setting

American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) database and Centers for Medicare and Medicaid Services (CMS) Database.

Methods

The AAO-HNS database (Entnet.org) and the CMS Database were used to identify otolaryngologists, their primary location, and their state of training. The 2023 Rural-Urban Continuum Codes were used to classify metropolitan (codes 1-3) and nonmetropolitan counties (codes 4-9) and determine county populations.

Results

A total of 388 otolaryngologists were identified across 67 Pennsylvania counties (33 metropolitan, 34 nonmetropolitan), 80% of which were male. There were 354 otolaryngologists in metropolitan counties serving 11.2 million people, with an average of 2.4 otolaryngologists per 100,000 people (/100 k). The majority of otolaryngologists (n = 235, 60.6%) are located in counties designated by code 1. There were 34 otolaryngologists in nonmetropolitan counties serving 1.8 million people, with an average of 2.4 otolaryngologists/100 k. Montour County (code 6) is home to a large academic center and accounts for 14/34 otolaryngologists in the nonmetropolitan counties. With the exception of Montour County, the remaining nonmetropolitan counties averaged 1.0 otolaryngologist/100 k. Only 3 metropolitan counties did not have otolaryngologists compared to 19 nonmetropolitan counties without otolaryngologists. Most otolaryngologists received their residency training in Pennsylvania (n = 177). New York (n = 35) and Maryland (n = 24) were the second most common states for training.

Conclusion

There is a lack of otolaryngologists in rural counties of Pennsylvania, except in counties home to large academic centers.

Insurance Status and Access to Otolaryngology Care: National Mystery Caller Study in the United States

OBJECTIVE

To investigate potential differences in new patient appointment wait times for otolaryngology care based on insurance types and explore factors influencing these wait times.

STUDY DESIGN

A cross-sectional audit study, using a "mystery caller" approach, analyzed with a linear mixed Poisson model to adjust for confounding factors.

SETTING

A total of 612 physicians across 49 states and the District of Columbia, representing 6 otolaryngology subspecialties, were included.

METHODS

Otolaryngology physicians were contacted by mystery callers via telephone with scripted clinical vignettes as patients with either Medicaid or Blue Cross/Blue Shield (BCBS) insurance. Callers requested next available appointment. Wait times for new patient appointments were recorded and analyzed in R using a generalized linear mixed Poisson model.

RESULTS

A total of 1183 of 1224 calls reached a representative. Medicaid patients waited 5.73% longer (P < .001) compared to BCBS patients (IRR: 1.06; confidence interval [CI]: 1.03-1.09; P < .001), with respective mean wait times of 36.8 days (SE ± 1.6) and 32.4 days (SE ± 1.6). Longer waiting times were also associated with physicians affiliated with universities (P = .001) and certain subspecialties, such as pediatric otolaryngology (P < .001) and neurotology (P = .008). Regional differences were also observed, with specific AAO-HNS regions showing shorter wait times. The model achieved a conditional R-squared value of 0.947.

CONCLUSION

This study reveals disparities in wait times for otolaryngology care based on insurance type, with extended wait times for Medicaid beneficiaries. The findings highlight a potential access to care disparity, which begets the need for strategies that ensure equitable access to otolaryngology care and further research to understand the underlying reasons for these potential disparities.

Geospatial evaluation of access to otolaryngology care in the United States

Objectives

This county-level epidemiological study evaluated the travel distance to the nearest otolaryngologist for continental US communities and identified socioeconomic differences between low- and high-access regions.

Methods

Geospatial analysis of publicly available 2015-2022 NPI records was combined with US census data to identify geospatial gaps in otolaryngologist distribution. Moran's index geospatial clustering in distance to the nearest county with an otolaryngologist was used as the core metric for differential access determination. Univariate logistic analysis was conducted between low- and high-access counties for 20 socioeconomic and demographic variables.

Results

Nationally, the average person was 22 miles from an otolaryngologist. 444 counties were identified as geospatially "low access" with increased travel distance in the Midwest, Great Planes, and Nevada with a median of 47 miles. 1231 counties in the Eastern United States and Western Coast were identified as "high access" with a 3-mile median travel distance. Areas of low access to otolaryngological care had smaller median populations (12,963 vs. 558,306), had smaller percent Black and Asian populations (2% vs. 11%, 1% vs. 5%, respectively), had a greater percent American Indian population (2% vs. 1%), were less densely populated (8 vs. 907 people per square mile), had fewer percent college graduates (20% vs. 34%), and fewer otolaryngologists per county (median: 0.01-20).

Conclusion

These findings highlight disparity in otolaryngology care in the United States and the need for otolaryngology funding initiatives in the Midwest and Great Plains regions.

Level of Evidence

Level 3.

Evaluating Geographic Access to Interdisciplinary Laryngology and Speech-Language Pathology Clinic Models in the Southeast Region of the United States

OBJECTIVE

An interdisciplinary model of care for the evaluation and treatment of voice, swallowing, and upper airway disorders with laryngologists and specialized speech-language pathologists is known to increase revenue, attendance to visits, patient adherence, and most importantly, improve patient outcomes. Individuals who live outside of areas with high population density often have reduced geographic access to this specialized care. The primary aim of this study is to identify the percentage of the population that has an "extended drive time" to access an interdisciplinary clinic in the Southeast region of the United States.

STUDY DESIGN

NA.

METHODS

Interdisciplinary laryngology and speech-language pathology clinics were identified via publicly accessible information including an internet search and state department of public health databases. Included clinics had at least one full-time fellowship-trained laryngologist and at least one full-time speech-language pathologist on staff. Descriptive statistics and visual representation of the results were achieved with the use of Smappen, a location intelligence online platform, to identify the percent of the population with a drive time greater than 1 hour.

RESULTS

47.24% of the Southeast population of the United States must drive over 1 hour to access an interdisciplinary clinic. Visual representations of these data are included and generated by Smappen.

CONCLUSIONS

While close geographic proximity does not ensure access to care, it can increase the likelihood that healthcare services will be used. This study identified the population in the Southeast region of the United States with extended drive time to interdisciplinary voice and swallowing centers due to their geographic distance from these centers. The results from this study support the need for increased geographic access to specialty care clinics, specifically voice, swallowing, and upper airway care, and provide insight into potential sites for interdisciplinary centers based on population density in areas that are underserved.

The Global Otolaryngology-Head and Neck Surgery Workforce

Importance

A core component of delivering care of head and neck diseases is an adequate workforce. The World Health Organization report, Multi-Country Assessment of National Capacity to Provide Hearing Care, captured primary workforce estimates from 68 member states in 2012, noting that response rates were a limitation and that updated more comprehensive data are needed.

Objective

To establish comprehensive workforce metrics for global otolaryngology-head and neck surgery (OHNS) with updated data from more countries/territories.

Design, Setting, and Participants

A cross-sectional electronic survey characterizing the OHNS workforce was disseminated from February 10 to June 22, 2022, to professional society leaders, medical licensing boards, public health officials, and practicing OHNS clinicians.

Main Outcome

The OHNS workforce per capita, stratified by income and region.

Results

Responses were collected from 121 of 195 countries/territories (62%). Survey responses specifically reported on OHNS workforce from 114 countries/territories representing 84% of the world's population. The global OHNS clinician density was 2.19 (range, 0-61.7) OHNS clinicians per 100 000 population. The OHNS clinician density varied by World Bank income group with higher-income countries associated with a higher density of clinicians. Regionally, Europe had the highest clinician density (5.70 clinicians per 100 000 population) whereas Africa (0.18 clinicians per 100 000 population) and Southeast Asia (1.12 clinicians per 100 000 population) had the lowest. The OHNS clinicians deliver most of the surgical management of ear diseases and hearing care, rhinologic and sinus diseases, laryngeal disorders, and upper aerodigestive mucosal cancer globally.

Conclusion and Relevance

This cross-sectional survey study provides a comprehensive assessment of the global OHNS workforce. These results can guide focused investment in training and policy development to address disparities in the availability of OHNS clinicians.

Urban and Rural Surgical Practice Patterns for Papillary Thyroid Carcinoma

Background: The 2015 American Thyroid Association (ATA) guidelines shifted recommendations toward less aggressive management of papillary thyroid cancer (PTC). Subsequently, several studies demonstrated a trend in performing thyroid lobectomy (TL) over total thyroidectomy (TT). However, regional variation has persisted without a clear indication of what factors may be influencing practice variation. We aimed to evaluate the surgical management of PTC in patients in rural and urban settings to assess trends of TL compared with TT following the implementation of the 2015 ATA guidelines. Methods: A retrospective cohort analysis was performed using the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2019 of patients with localized PTC <4 cm who underwent TT or TL. Patients were classified as living in urban or rural counties based on the 2013 Rural-Urban Continuum Codes. Procedures performed from 2004 to 2015 were categorized as preguidelines, while those performed from 2016 to 2019 were categorized as postguidelines. Chi-square, Student's t-test, logistic regression, and Cochran-Mantel-Haenszel test were used. Results: A total of 89,294 cases were included in the study. Eighty thousand one hundred and fifty (89.8%) were from urban settings and 9144 (9.2%) were from rural settings. Patients from rural settings were older (52 vs. 50 years, p < 0.001) and had smaller nodules (p < 0.001). On adjusted analysis, patients in rural areas were less likely to undergo TT (adjusted odds ratio 0.81, confidence interval [CI] 0.76-0.87). Before the 2015 guidelines, patients in urban settings had a 24% higher odds of undergoing TT compared with those in rural settings (odds ratio 1.24, CI 1.16-1.32, p < 0.001). There was no difference in the proportions of TT and TL based on setting following guideline implementation (p = 0.185). Conclusions: The 2015 ATA guidelines led to a change in overall practice in surgical management of PTC toward increasing TL. While urban and rural practice variation existed before 2015, both settings had an increase in TL following the guideline change, emphasizing the importance of clinical practice guidelines to ensure best practice in both rural and urban settings.

Medicare Utilization and Reimbursement Variation Between Rural and Urban Otolaryngologists

OBJECTIVE

To compare billing practices, reimbursement rates, and patient populations of otolaryngology (ORL) physicians practicing in rural and urban settings.

STUDY DESIGN

Retrospective cross-sectional study.

SETTING

Medicare Provider Utilization and Payment Data: Physician and Other Supplier Data.

METHODS

Medicare-allowed payments, number of services, and number of patients were gathered along with patient population comorbidity statistics, including average hierarchical condition category risk scores.

RESULTS

In 2019, 92% of the overall total 8959 ORL physicians practiced in an urban setting. These 8243 urban ORL physicians, on average, billed for 51 (interquartile range [IQR], 31-67) unique Healthcare Common Procedure Coding System (HCPCS) codes, cared for 393 (IQR, 172-535) Medicare patients, performed 1761 (IQR, 502-2070) services, and collected $139,957 (IQR, $55,527-$178,479) per provider. In contrast, the 704 rural ORL physicians, on average, billed for a greater number of unique HCPCS codes (59; IQR, 37-77; P < .001), treated more Medicare patients (445; IQR, 242-614; P < .001), and performed more services (2330; IQR, 694-2748; P < .001) but collected about the same per provider ($141,035; IQR, $56,555-$172,864; P = .426). Older age was associated with rural practice (P = .027). Among both urban and rural ORL physicians, the variety and complexity of procedures and patient comorbidity profiles were comparable.

CONCLUSION

Most ORL physicians practice in large urban settings, a finding potentially related to financial sustainability and career opportunity. With an already small workforce, the aging rural ORL physician population is an identifiable weak point in the otolaryngology specialty that must be addressed with geo-specific recruitment campaigns, rural work incentivization, and the development of career advancement opportunities in rural areas.