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JAMA Ophthalmology
JAMA Ophthalmol. 2023 Mar; 141(3): 242–249.
Published online 2023 Jan 26. doi:10.1001/jamaophthalmol.2022.6010
PMCID: PMC9880864
PMID: 36701149
Hannah L. Walsh, BS,1 Abraham Parrish, MA, MILS,2 Lauren Hucko, BA,1 Jayanth Sridhar, MD,3 and Kara M. Cavuoto, MD3
Author information Article notes Copyright and License information PMC Disclaimer
See commentary "Where Have All the Pediatric Ophthalmologists Gone?-Pediatric Eye Care Scarcity and the Challenge of Creating Equitable Health Care Access." in JAMA Ophthalmol, 36701142.
Associated Data
- Supplementary Materials
This cross-sectional study analyzes the geographic distribution of pediatric ophthalmologists in 2022 and compares the distribution to population demographic characteristics in the US.
Key Points
Question
What is the current geographic distribution of pediatric ophthalmologists and how does this correspond to regional patient demographic characteristics?
Findings
In this cross-sectional study of 1056 pediatric ophthalmologists, disparities in geographical access to pediatric ophthalmologists persisted in 2022, and the range of practitioner to million persons has increased since 2007. Disparities in practitioner distribution were associated with lower socioeconomic status.
Meaning
Findings of this study suggest that disparities in access to pediatric ophthalmological care are associated with socioeconomic status; evidence-based measures and accurate publicly available information on locations of pediatric ophthalmologists are warranted to increase access to care.
Abstract
Importance
The geographic distribution of pediatric ophthalmological care has not been reported on since 2007; understanding this distribution could shed light on potential avenues to increase access, which is a necessary first step in addressing the pediatric ophthalmological needs of underserved areas.
Objective
To analyze the number and location (ie, geographic distribution) of pediatric ophthalmologists in relation to US population demographic characteristics.
Design, Setting, and Participants
In this cross-sectional study, public databases from the American Academy of Ophthalmology and American Association for Pediatric Ophthalmology and Strabismus were used to identify pediatric ophthalmologists in the US as of March 2022.
Main Outcomes and Measures
Geographic distribution of pediatric ophthalmologists listed in public databases and any association between pediatric ophthalmologist distribution and US population demographic characteristics. Addresses were geocoded using ArcGIS Pro (Esri).
Results
A total of 1056 pediatric ophthalmologists (611 men [57.9%]) were identified. States with the most pediatric ophthalmologists were California (n = 116 [11.0%]), New York (n = 97 [9.2%]), Florida (n = 69 [6.5%]), and Texas (n = 62 [5.9%]), the 4 most populous states. A total of 2828 of 3142 counties (90.0%) and 4 of 50 states (8.0%) had 0 pediatric ophthalmologists. In 314 counties (10.0%) with 1 or more pediatric ophthalmologists, the mean (range) pediatric ophthalmologists per million persons was 7.7 (0.4-185.5). The range of practitioner to million persons has increased since 2007. Counties with 1 or more pediatric ophthalmologists had a higher median (SD) household income compared with counties with 0 pediatric ophthalmologists ($70 230.59 [$18 945.05] vs $53 263.62 [$12 786.07]; difference, −$16 966.97; 95% CI, −$18 544.57 to −$14 389.37; P < .001). Additionally, the proportion of families in each county without internet service (8.0% vs 4.7%; difference, 3.4%; 95% CI, 3.0%-3.7%; P < .001), the proportion of persons younger than 19 years without health insurance (5.7% vs 4.1%; difference, 1.6%; 95% CI, 1.1%-2.2%; P < .001), and the proportion of households without vehicle access (2.1% vs 1.8%; difference, 0.3%; 95% CI, 0.6%-5.2%; P = .001) were greater in counties with 0 compared with counties with 1 or more pediatric ophthalmologists.
Conclusion and Relevance
This cross-sectional study found that disparities in access to pediatric ophthalmological care have increased over the past 15 years and are associated with lower socioeconomic status. As patients may rely on online sources to identify the nearest pediatric ophthalmologist, accurate publicly available databases are important.
Introduction
The national shortage of pediatric ophthalmologists in relation to the expanding population of the US has become increasingly apparent over the past few years. This shortage is compounded by an overall lack of trainee interest in pediatric ophthalmology, as nearly half of pediatric ophthalmology and strabismus fellowship positions go unfilled each year.1 Reasons for this shortage are multifactorial and include lower reimbursem*nt rates, the difficulty of performing eye examinations in children, and lack of mentorship.2 Furthermore, the pediatric ophthalmologist shortage is complicated by a lack of geographic distribution among the existing practitioners.2 Prior investigations by the American Association for Pediatric Ophthalmology and Strabismus (AAPOS) workforce reported on nationwide pediatric ophthalmologist service coverage analysis with the introduction of an interactive map display; however, service coverage was last reported in 2007.3 In the past 15 years, the demographic landscape of the US has changed considerably, especially in regard to increased population diversity and geographic distribution.4 These differences need to be evaluated appropriately to address how the needs of important services, such as health care, have changed. Moreover, to our knowledge, no previous reports have addressed demographic and socioeconomic differences between areas served by pediatric ophthalmologists and those without access to pediatric ophthalmologists. The goal of this study was to assess the number and location (ie, geographic distribution) of pediatric ophthalmologists in the US in relation to US population demographic characteristics.
Methods
In this cross-sectional study, pediatric ophthalmologists were identified in March 2022 using 2 online public databases: the “Find an Ophthalmologist” tool on the American Academy of Ophthalmology (AAO) website and the “Find a Doctor” tool on the AAPOS website. We used all addresses listed on these websites to ascertain location. Office address, state, zip code, sex, degree, and specialty listed online were all collected for each pediatric ophthalmologist. The University of Miami Institutional Review Board deemed the study exempt from review and waived the requirement for informed consent because all data were publicly available. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
Addresses were geocoded using ArcGIS Pro, version 2.9 (Esri). For the 14 addresses that showed a post office box address instead of an office address, the address was found using a Google search (Alphabet Inc).
Statistical Analysis
We selected US counties to serve as the population unit. Counties were split into 2 groups for statistical analysis: 1 group consisted of counties with at least 1 practicing pediatric ophthalmologist and the other consisted of counties with 0 practicing pediatric ophthalmologists. Independent-sample t tests were performed using SPSS, version 28.0.0.0 (IBM Corp). P values were 2-tailed and were not adjusted for multiple analyses; P < .05 was considered statistically significant.
Population demographic data were collected using the ArcGIS Pro Business Analyst tool, version 10.1 (Esri). The overall county population, county population aged 0 to less than 19 years, median family income for 2021, population aged 25 years or older with a bachelor’s degree in 2021, mean consumer spending (including and excluding Blue Cross Blue Shield) for vision care insurance for 2021, and mean spending for eyeglasses and contact lenses for 2021 were sourced from the Esri software and US Bureau of Labor Statistics. Data on race, ethnicity, and age were obtained from the US Census Bureau (2020) using the ArcGIS Pro Business Analyst tool. The population of households without internet access per county, the population of households with members younger than 19 years without health insurance, the population of households with no members younger than 18, and the language spoken at home for members aged 18 to 64 years were sourced from the American Community Survey (5-year estimate 2014-2019).
Results
A total of 1056 pediatric ophthalmologists (611 [57.9%] men and 445 [42.1%] women) in the US were identified. Of these, 981 physicians (92.9%) were identified using the AAO “Find an Ophthalmologist” tool, and 75 physicians (7.1%) were identified using the AAPOS “Find a Doctor” tool. A total of 968 (91.7%) held a doctor of medicine degree, 63 (6.0%) held a doctor of medicine dual degree, 21 (2.0%) held a doctor of osteopathic medicine degree, and 4 (0.4%) held a bachelor of medicine, bachelor of surgery degree. Men outnumbered women in each degree category except for the doctor of osteopathic medicine category, in which there were 10 men (0.9%) and 11 women (1.0%).
The geographic distribution of pediatric ophthalmologists by county in the US is illustrated in the Figure. The distribution of pediatric ophthalmologists by state, state population, and pediatric ophthalmologists per person are summarized in Table 1. The states with the most pediatric ophthalmologists were California (n = 116 [11.0%]), New York (n = 97 [9.2%]), Florida (n = 69 [6.5%]), and Texas (n = 62 [5.9%]), the 4 most populous states according to the 2020 US Census.5 There were 314 of 3142 counties (10.0%) with 1 or more pediatric ophthalmologists, and 140 of 314 counties (44.6%) had only 1 pediatric ophthalmologist. Counties with the most pediatric ophthalmologists were Los Angeles County, California (n = 38 [3.6%]), New York County, New York (n = 26 [2.5%]), Cook County, Illinois (n = 20 [1.9%]), Suffolk County, Massachusetts (n = 19 [1.8%]), and Harris County, Texas (n = 17 [1.6%]). Four states (New Mexico, North Dakota, South Dakota, and Vermont; 8.0%) and 2828 counties (90.0%) had 0 pediatric ophthalmologists. Totals for the 30 most populous US counties stratified by the number of pediatric ophthalmologists, by total population, and by total population younger than 19 years are shown in Table 2. Nineteen of the 30 counties (63.3%) with the greatest number of pediatric ophthalmologists are also among the 30 most populated counties. Additionally, 19 of the 30 counties (63.3%) with the most pediatric ophthalmologist coverage were among the top 30 counties by population younger than 19 years. The 20 most populous Metropolitan Statistical Areas from 2007 are listed in Table 3 as a comparison over time.
Figure.
Geographic Distribution of Pediatric Ophthalmologists
The figure displays the geographic distribution of US pediatric ophthalmologists (PO) per population younger than 19 years. This image was created using ArcGIS Pro (Esri) with data from Garmin, Food and Agriculture Organization of the United Nations, National Oceanic and Atmospheric Administration, United States Geological Survey, Geographic Information Systems User Community, and OpenStreetMap.
Table 1.
Summary of Highest and Lowest Representation of Pediatric Ophthalmologists by Statea
State | Pediatric ophthalmologists per state, No. (%) (N = 1056) | State population, No. | Pediatric ophthalmologists per person | Pediatric ophthalmologists per persons aged <19 y |
---|---|---|---|---|
California | 116 (11.0) | 39 538 223 | 1:340 846 | 1:81 803 |
New York | 97 (9.2) | 20 538 187 | 1:211 733 | 1:48 867 |
Florida | 69 (6.5) | 21 538 187 | 1:312 147 | 1:69 413 |
Texas | 62 (5.9) | 29 145 505 | 1:470 088 | 1:118 932 |
Illinois | 49 (4.6) | 12 812 508 | 1:261 479 | 1:57 787 |
New Mexico | 0 | 2 117 552 | NA | NA |
North Dakota | 0 | 779 094 | NA | NA |
South Dakota | 0 | 886 667 | NA | NA |
Vermont | 0 | 643 077 | NA | NA |
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Abbreviation: NA, not applicable.
aPopulation demographic characteristics were extracted from the 2020 US Census.
Table 2.
Top 30 Counties by Number of Pediatric Ophthalmologists, by Total Population, and by Total Population Younger Than 19 Years
County | Population, No. |
---|---|
Total pediatric ophthalmologists, No. (%) (N = 1056) | |
Los Angeles, CA | 38 (3.6%) |
New York, NY | 26 (2.5%) |
Cook, IL | 20 (1.9%) |
Suffolk, MA | 19 (1.8%) |
Harris, TX | 17 (1.6%) |
Montgomery, MD | 15 (1.4%) |
Hennepin, MN | 13 (1.2%) |
Orange, CA | 12 (1.1%) |
San Bernardino, CA | 12 (1.1%) |
Middlesex, MA | 12 (1.1%) |
Miami-Dade, FL | 11 (1.0%) |
Bexar, TX | 11 (1.0%) |
King, WA | 11 (1.0%) |
Maricopa, AZ | 10 (0.9%) |
San Diego, CA | 10 (0.9%) |
Nassau, NY | 10 (0.9%) |
Philadelphia, PA | 10 (0.9%) |
Dane, WI | 10 (0.9%) |
District of Columbia, DC | 9 (0.9%) |
Baltimore City, MD | 9 (0.9%) |
Oakland, MI | 9 (0.9%) |
Suffolk, NY | 9 (0.9%) |
Franklin, OH | 9 (0.9%) |
Davidson, TN | 9 (0.9%) |
Santa Clara, CA | 8 (0.8%) |
Orange, FL | 8 (0.8%) |
Cuyahoga, OH | 8 (0.8%) |
Westchester, NY | 8 (0.8%) |
Hamilton, OH | 8 (0.8%) |
Johnson, IA | 8 (0.8%) |
Total population | |
Los Angeles, CA | 10 150 833 |
Cook, IL | 5 100 882 |
Harris, TX | 4 739 199 |
Maricopa, AZ | 4 503 688 |
San Diego, CA | 3 265 139 |
Orange, CA | 3 111 504 |
Dallas, TX | 2 716 831 |
Miami-Dade, FL | 2 551 257 |
Kings, NY | 2 347 653 |
Clark, NV | 2 315 861 |
King, WA | 2 235 841 |
San Bernardino, CA | 2 170 053 |
Queens, NY | 2 164 939 |
Tarrant, TX | 2 133 304 |
Bexar, TX | 2 040 819 |
Santa Clara, CA | 1 916 247 |
Broward, FL | 1 817 199 |
Wayne, MI | 1 778 411 |
Alameda, CA | 1 623 644 |
New York, NY | 1 614 981 |
Middlesex, MA | 1 607 569 |
Philadelphia, PA | 1 587 162 |
Sacramento, CA | 1 523 280 |
Hillsborough, FL | 1 476 123 |
Suffolk, NY | 1 456 420 |
Orange, FL | 1 431 976 |
Travis, TX | 1 371 899 |
Nassau, NY | 1 306 191 |
Franklin, OH | 1 302 738 |
Hennepin, MN | 1 290 766 |
Population aged <19 y | |
Los Angeles, CA | 2 509 469 |
Harris, TX | 1 343 626 |
Cook, IL | 1 243 380 |
Maricopa, AZ | 1 195 301 |
San Diego, CA | 792 155 |
Orange, CA | 768 634 |
Dallas, TX | 749 542 |
San Bernardino, CA | 615 347 |
Tarrant, TX | 598 985 |
Kings, NY | 591 584 |
Miami-Dade, FL | 588 093 |
Clark, NV | 583 230 |
Bexar, TX | 561 456 |
King, WA | 502 797 |
Santa Clara, CA | 488 545 |
Queens, NY | 471 177 |
Wayne, MI | 442 427 |
Broward, FL | 404 981 |
Alameda, CA | 392 538 |
Sacramento, CA | 389 921 |
Philadelphia, PA | 382 909 |
Salt Lake, UT | 370 085 |
Middlesex, MA | 363 614 |
Hillsborough, FL | 360 682 |
Travis, TX | 357 448 |
Orange, FL | 349 153 |
Suffolk, NY | 344 990 |
Franklin, OH | 325 474 |
Bronx, NY | 316 014 |
Hidalgo, TX | 309 340 |
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Table 3.
Practitioner to Million Persons in Top 20 Metropolitan Statistical Areas in 2007 vs Large US Counties in 2022a
Metropolitan statistical area (2007) | Total population | AAPOS member count | AAPOS member per million | US county (2022) | Total population | Pediatric ophthalmologist count | Pediatric ophthalmologist per million |
---|---|---|---|---|---|---|---|
New York-Northern New Jersey-Long Island, NY-NJ-CT-PA | 21 199 865 | 85 | 4.0 | Los Angeles, CA | 10 150 833 | 38 | 3.7 |
Los Angeles-Riverside-Orange County, CA | 16 373 645 | 41 | 2.9 | Cook, IL | 5 100 882 | 20 | 3.9 |
Chicago-Gary-Kenosha, IL-IN-WI | 9 157 540 | 31 | 3.4 | Harris, TX | 4 739 199 | 17 | 3.6 |
Washington-Baltimore, DC-MD-VA-WV | 7 608 070 | 38 | 5.0 | Maricopa, AZ | 4 503 688 | 10 | 2.2 |
San Francisco-Oakland-San Jose, CA | 7 039 362 | 21 | 3.0 | San Diego, CA | 3 265 139 | 10 | 3.1 |
Philadelphia-Wilmington-Atlantic City, PA-NJ-DE-MD | 6 188 463 | 32 | 5.2 | Orange, CA | 3 111 504 | 12 | 3.9 |
Boston-Worcester-Lawrence, MA-NH-ME-CT | 5 819 100 | 24 | 4.1 | Dallas, TX | 2 716 831 | 5 | 1.8 |
Detroit-Ann Arbor-Flint, MI | 5 456 428 | 15 | 2.7 | Miami-Dade, FL | 2 551 257 | 11 | 4.3 |
Dallas-Fort Worth, TX | 5 221 801 | 16 | 3.1 | Kings, NY | 2 347 653 | 1 | 0.4 |
Houston-Galveston-Brazoria, TX | 4 669 571 | 15 | 3.2 | Clark, NV | 2 315 861 | 7 | 3.0 |
Atlanta, GA | 4 112 198 | 12 | 2.9 | King, WA | 2 235 841 | 11 | 4.9 |
Miami-Fort Lauderdale, FL | 3 876 380 | 13 | 3.4 | San Bernardino, CA | 2 170 053 | 12 | 5.5 |
Seattle-Tacoma-Bremerton, WA | 3 554 760 | 10 | 2.8 | Queens, NY | 2 164 939 | 4 | 1.8 |
Phoenix-Mesa, AZ | 3 251 876 | 10 | 3.1 | Tarrant, TX | 2 133 304 | 6 | 2.8 |
Minneapolis-St. Paul, MN-WI | 2 968 806 | 9 | 3.0 | Bexar, TX | 2 040 819 | 11 | 5.4 |
Cleveland-Akron, OH | 2 945 831 | 13 | 4.4 | Santa Clara, CA | 1 916 247 | 8 | 4.2 |
San Diego, CA | 2 813 833 | 7 | 2.5 | Broward, FL | 1 817 199 | 6 | 3.3 |
St Louis, MO-IL | 2 603 607 | 7 | 2.7 | Wayne, MI | 1 778 411 | 6 | 3.4 |
Denver-Boulder-Greeley, CO | 2 581 506 | 7 | 2.7 | Alameda, CA | 1 623 644 | 1 | 0.6 |
Tampa-St. Petersburg-Clearwater, FL | 2 395 997 | 8 | 3.3 | New York, NY | 1 614 981 | 26 | 16.1 |
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Abbreviation: AAPOS, American Association for Pediatric Ophthalmology and Strabismus.
aData for 2007 Metropolitan Statistical Areas were reported by Estes et al.3
The 2020 US Census estimated 331 893 745 persons living in the US by July 1, 2021, with 83 267 556 of those persons younger than 19 years.5 Overall, there were 3.2 pediatric ophthalmologists per million persons in the US. For the younger US population, there were 12.7 pediatric ophthalmologists per million persons younger than 19 years. In counties with 1 or more pediatric ophthalmologists, there was a mean (range) of 7.7 (0.4-185.5) pediatric ophthalmologists per million persons and a mean (range) of 32.2 (1.6-217.5) pediatric ophthalmologists per million persons younger than 19 years. The 20 most populous US counties are listed in Table 3.
There was a greater percentage of households with no persons younger than 18 years in the 314 counties with 1 or more pediatric ophthalmologists compared with the 2828 counties with 0 pediatric ophthalmologists (71.2% vs 69.3%; difference, −1.9%; 95% CI, −2.8% to −0.1%; P < .001) (Table 4). In the counties with 1 or more pediatric ophthalmologists, there was a mean (range) of 1 pediatric ophthalmologist per 57 707 (1 per 1339 to 1 per 59 158) people younger than 19 years. There were higher densities of pediatric ophthalmologists in coastal metropolitan areas, such as Los Angeles, California; Miami, Florida; and New York, New York, and lower densities of pediatric ophthalmologists in central northern states, such as the Dakotas, Montana, and Nebraska. While there was no difference in mean (SD) family size (3.0 [0.2] vs 3.1 [0.2]; difference, 0.1; 95% CI, −1.4 to −0.1; P = .34), counties with 0 pediatric ophthalmologists had a higher median (SD) age than counties with 1 or more pediatric ophthalmologists (39.5 [5.1] years vs 37.2 [3.9] years; difference, 2.2; 95% CI, 1.7-2.9 years; P < .001).
Table 4.
Demographic Characteristics of Counties With 1 or More Pediatric Ophthalmologists vs Counties With 0 Pediatric Ophthalmologists
Characteristic | Counties with 1 or more pediatric ophthalmologists (n = 314) | Counties with 0 pediatric ophthalmologists (n = 2828) | P value |
---|---|---|---|
Family size, mean (SD) | 3.1 (0.2) | 3.0 (0.2) | .34 |
Median (SD) age, y | 37.2 (3.9) | 39.5 (5.1) | <.001 |
Households with no members aged <18 y, % | 71.2 | 69.3 | <.001 |
Households with members aged <19 y without health insurance, % | 4.1 | 5.7 | <.001 |
Population with no internet access, % | 4.7 | 8.0 | <.001 |
Median (SD) family income, $ | 70 230.59 (18 945.05) | 53 263.62 (12 786.07) | <.001 |
Population whose language at home is not English, % | 0.6 | 0.3 | .001 |
Population with no vehicle access, % | 1.8 | 2.1 | .001 |
Population aged ≥25 y with bachelor’s degree, % | 25.2 | 15.3 | <.001 |
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Socioeconomic data also differed between the 2 groups, as described in Table 4. The 2021 median (SD) family income was greater in counties with 1 or more pediatric ophthalmologists compared with counties with 0 pediatric ophthalmologists ($70 230.59 [$18 945.05] vs $53 263.62 [$12 786.07]; difference, −$16 966.97; 95% CI, −$18 544.57 to −$14 389.37; P < .001). The proportion of families in each county without internet service (8.0% vs 4.7%; difference, 3.4%; 95% CI, 3.0%-3.7%; P < .001) and the proportion of persons younger than 19 years without health insurance (5.7% vs 4.1%; difference, 1.6%; 95% CI, 1.1%-2.2%; P < .001) were greater in counties with 0 pediatric ophthalmologists compared with counties with 1 or more pediatric ophthalmologists. There was a greater proportion of persons aged 25 or older who held bachelor’s degrees in counties with 1 or more pediatric ophthalmologists compared with counties with 0 pediatric ophthalmologists (25.2% vs 15.3%; difference, −9.9%; 95% CI, −10.1% to −9.2%; P < .001). Finally, more households in counties with 0 pediatric ophthalmologists reported not having access to vehicles at home compared with counties with 1 or more pediatric ophthalmologists (2.1% vs 1.8%; difference, 0.3%; 95% CI, 0.6%-5.2%; P = .001).
Consumer spending habits for vision care also differed between the 2 groups and are displayed in the eTable in Supplement 1. On average, households in counties with 1 or more pediatric ophthalmologists spent more on Blue Cross Blue Shield vision care insurance (mean [SD], $3.41 [$0.83] vs $2.46 [$0.78]; difference, $0.95; 95% CI, $1.04-$0.86; P < .001), more on vision care insurance excluding Blue Cross Blue Shield (mean [SD], $38.82 [$10.32] vs $31.07 [$8.33]; difference, $7.74; 95% CI, $6.75-$8.74; P < .001), and more on eyeglasses and contact lenses (mean [SD], $106.54 [$28.89] vs $89.41 [$23.64]; difference, $17.13; 95% CI, $14.31-$19.96; P < .001) per month compared with households in counties with 0 pediatric ophthalmologists.
Discussion
In this cross-sectional study, we identified geographic and socioeconomic disparities in pediatric ophthalmological care. The Association of American Medical Colleges has vocalized concern for physician shortages in the US.6 These shortages are prevalent across many specialties, which suggests that a large proportion of the US population is unable to access health care in a timely, convenient manner.7 To complicate this issue further, some studies have reported that the rural-urban gap in the distribution of physicians has not only persisted but has increased in recent years.8 The extent to which this applies to all ophthalmology subspecialties is unknown, but physician shortages in rural areas have been well documented as a concern in oculofacial plastic surgery,9 cataract surgery,10 and pediatric glaucoma.11,12 Of the 1056 pediatric ophthalmologists who were identified through public databases, most had practices located in metropolitan areas in coastal states and around academic institutions. Considering the metropolitan location preference of practicing pediatric ophthalmologists in conjunction with shortages of pediatric ophthalmologists overall, we can conclude that rural populations disproportionately lack access to such care, which can impact the time to diagnosis, treatment, and management of complications of serious ophthalmological diagnoses in children.
About one-third (11 of 30) of the top 30 counties by the total number of pediatric ophthalmologists were not accounted for in the top 30 counties by total population or in the top 30 counties by population younger than 19 years, suggesting a difference between pediatric ophthalmologist practice location and counties with large pediatric populations. While these populated counties may be adjacent to a county with pediatric ophthalmologist access, driving time is widely acknowledged to decrease the use of health care services and lead to worse health outcomes.13 By cross-referencing publicly available demographic data with pediatric ophthalmologist addresses, we found that lower median family income, lower household educational level, increased uninsured status, decreased access to vehicles, and decreased home internet service were all more prevalent in counties served by 0 pediatric ophthalmologists than those in counties with 1 or more pediatric ophthalmologists. The aforementioned factors all can have marked implications for patients’ ability to seek and consistently access both virtual and in-person pediatric ophthalmological care, which may be exacerbated by the lack of available local practitioners evidenced in this study.
Using the 2020 US Census population estimates, there was 1 pediatric ophthalmologist per 3.2 million persons in the US. However, 90.0% of counties were not served by any pediatric ophthalmologists. Even in the 314 counties with at least 1 pediatric ophthalmologist, there was a median of 1 pediatric ophthalmologist per 7.7 million persons, with a range of 1 pediatric ophthalmologist per 0.4 million persons to 185.5 million persons. In the 314 counties with access to a practitioner, there was a median of 1 pediatric ophthalmologist per 32.8 million persons younger than 19 years, with a range of 1 pediatric ophthalmologist per 1.6 million persons younger than 19 years to 217.5 million persons younger than 19 years. In the 2007 AAPOS workforce distribution project that analyzed service coverage of pediatric ophthalmologists on a national level,3 the member-to-million-persons ratio varied from 1.3 to 27 (for 2.8 million persons; average unknown). While the total number of practicing pediatric ophthalmologists with publicly available addresses has increased by more than 300 over the past 15 years, so has the range of practitioner to million persons, suggesting a divergent gap in access to care. Although the different geographic units (metropolitan statistical area vs US counties) used in each report preclude a direct comparison, an adjustment to practitioner to million persons aims to account for this discrepancy and provides insight into generic patterns in pediatric ophthalmologist density over time. These results support the need to improve incentive structures to redistribute pediatric ophthalmologist resources to match the unequal health burden in underserved counties. Additionally, these results support the need to incentivize ophthalmology trainees to pursue careers in pediatric ophthalmology. Studies have reported that students exposed to niche specialties early on are more invested in the long term.14 While current efforts focus on recruiting ophthalmology residents to pursue pediatric ophthalmology, it may be more effective to introduce the field to interested individuals before they enter an ophthalmology residency or even before they choose a career in medicine (eg, high school and college students).
We found that counties served by pediatric ophthalmologists had higher rates of health insurance, higher median family incomes, more internet and vehicle access, higher rates of advanced educational attainment, and higher mean household spending on vision care items and vision care insurance, all of which can facilitate improved and sustainable access to pediatric ophthalmological care. Such populations were found in the counties with increased proportions of pediatric ophthalmologists, which suggests that the geographic distribution of pediatric ophthalmologists in the US may exacerbate existing socioeconomic inequities in pediatric ophthalmological care. Furthermore, the present analysis found that there are more households on average with children younger than 19 years in underserved counties, suggesting a large need for pediatric ophthalmologists in these areas. It is important that disadvantaged regions be targeted for recruitment of pediatric ophthalmologists, especially areas with high pediatric populations with low socioeconomic status, fewer health care resources, and less access to care. This finding on underserved counties highlights the potential need for more granular research describing the needs of counties meeting these criteria, which could then be used for creative initiatives incentivizing pediatric ophthalmologists to reach these areas.
Providing accurate, up-to-date contact information for pediatric ophthalmologists in each region may be an important first step in reaching underserved areas. As online resources and telemedicine potentially improve access to health care, pediatric ophthalmologists may be able to extend the reach of their care by providing updated contact information on websites, such as AAPOS.org and AAO.org.15,16 While our updated service coverage analysis may aid in identifying optimal locations for new pediatric ophthalmologist services, our demographic analysis identified differences in internet access as a substantial and compounding barrier that underserved counties face. Efforts to expand access to pediatric ophthalmological care should consider this factor by implementing alternate strategies, including collaboration with local pediatricians and schools alongside updated online sources to augment awareness of pediatric ophthalmologist services and locations. Furthermore, the lower rates of health insurance in counties without pediatric ophthalmologist coverage may prevent communities in need from accessing telemedicine resources. These and other social determinants of health should prompt evidence-based approaches to increase access to pediatric ophthalmologists in underserved communities. The extent to which these factors alter the use of ophthalmologic services and ultimately impact patient outcomes are pertinent future directions for research.
Limitations
This study has limitations. The AAO and AAPOS websites may list pediatric ophthalmologists who are no longer in practice or list incorrect or outdated practice addresses, which may overrepresent the populations served in those areas. In contrast, these websites also may have excluded recent graduates, pediatric ophthalmologists who recently opened a practice, or those who denied permission to publish their practice location, which could possibly underrepresent the practitioner density in those areas. Additionally, select demographic data were collected using the American Community Survey 5-year estimate.6 Although the data provide the advantage of increasing statistical reliability for data in less populated areas and with small population subgroups, they are estimates rather than exact counts and thus may overestimate or underestimate the actual demographic patterns.4 Finally, this study relies on data from the US Census and excludes large groups of individuals, such as undocumented immigrants or international patients, who did not participate in the US Census. Such populations often face barriers to health care due to insurance, immigration, and financial status; therefore, this analysis may have underidentified disparities in access to pediatric ophthalmological care in areas with a high density of nonrespondents to the US Census.17
Conclusions
Findings of this cross-sectional study suggest that disparities in access to pediatric ophthalmologists are not only persistent but have increased over time. Key demographic and socioeconomic differences exist between populations in areas with vs without access to pediatric ophthalmological care, with disparities in access to such care associated with lower socioeconomic status. Further studies are needed to examine whether these differences affect the use of pediatric ophthalmological services and ultimately patient outcomes.
Notes
Supplement 1.
eTable. Comparison of Consumer Spending Habits Between Counties With ≥1 Pediatric Ophthalmologist (PO) and Counties With 0 PO
Click here for additional data file.(163K, pdf)
Supplement 2.
Data Sharing Statement
Click here for additional data file.(14K, pdf)
References
1. O’Brien C, Marsh R. Pediatric ophthalmology: analysis of fellowships and the job market. Invest Ophthalmol Vis Sci. 2015;56(7):145. [Google Scholar]
2. Bernstein BK, Nelson LB. Workforce issues in pediatric ophthalmology. J Pediatr Ophthalmol Strabismus. 2020;57(1):9-11. doi: 10.3928/01913913-20191101-01 [PubMed] [CrossRef] [Google Scholar]
3. Estes R, Estes D, West C, Zobal-Ratner J, Droster P, Simon J. The American Association for Pediatric Ophthalmology and Strabismus workforce distribution project. J AAPOS. 2007;11(4):325-329. doi: 10.1016/j.jaapos.2006.08.014 [PubMed] [CrossRef] [Google Scholar]
4. US Census Bureau. 2020 Census statistics highlight local population changes and nation’s racial and ethnic diversity. News release. August 12, 2021. Accessed December 15, 2022. https://www.census.gov/newsroom/press-releases/2021/population-changes-nations-diversity.html
5. US Census Bureau. QuickFacts: United States. Accessed August 31, 2022. https://www.census.gov/quickfacts/fact/table/US/PST045221
6. Association of American Medical Colleges. The complexities of physician supply and demand: projections from 2018 to 2033. June 2020. Accessed August 31, 2022. https://www.aamc.org/media/45976/download
7. Streeter RA, Snyder JE, Kepley H, Stahl AL, Li T, Washko MM. The geographic alignment of primary care Health Professional Shortage Areas with markers for social determinants of health. PLoS One. 2020;15(4):e0231443. doi: 10.1371/journal.pone.0231443 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
8. Machado SR, Jayawardana S, Mossialos E, Vaduganathan M. Physician density by specialty type in urban and rural counties in the US, 2010 to 2017. JAMA Netw Open. 2021;4(1):e2033994. doi: 10.1001/jamanetworkopen.2020.33994 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
9. Hussey VM, Tao JP. Oculofacial plastic surgeon distribution by county in the United States, 2021. Orbit. 2022;41(6):687-690. doi: 10.1080/01676830.2021.1989468 [PubMed] [CrossRef] [Google Scholar]
10. Lee CS, Su GL, Baughman DM, Wu Y, Lee AY. Disparities in delivery of ophthalmic care; an exploration of public Medicare data. PLoS One. 2017;12(8):e0182598. doi: 10.1371/journal.pone.0182598 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
11. Vu DM, Stoler J, Rothman AL, Chang TC. A service coverage analysis of primary congenital glaucoma care across the United States. Am J Ophthalmol. 2021;224:112-119. doi: 10.1016/j.ajo.2020.12.009 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
12. Lee PP, Relles DA, Jackson CA. Subspecialty distributions of ophthalmologists in the workforce. Arch Ophthalmol. 1998;116(7):917-920. doi: 10.1001/archopht.116.7.917 [PubMed] [CrossRef] [Google Scholar]
13. Kelly C, Hulme C, Farragher T, Clarke G. Are differences in travel time or distance to healthcare for adults in global north countries associated with an impact on health outcomes? a systematic review. BMJ Open. 2016;6(11):e013059. doi: 10.1136/bmjopen-2016-013059 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
14. Branstetter BF IV, Faix LE, Humphrey AL, Schumann JB. Preclinical medical student training in radiology: the effect of early exposure. AJR Am J Roentgenol. 2007;188(1):W9-14. doi: 10.2214/AJR.05.2139 [PubMed] [CrossRef] [Google Scholar]
15. Chia MATA, Turner AW. Benefits of integrating telemedicine and artificial intelligence into outreach eye care: stepwise approach and future directions. Front Med (Lausanne). 2022;9(9):835804. doi: 10.3389/fmed.2022.835804 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
16. Begley BA, Martin J, Tufty GT, Suh DW. Evaluation of a remote telemedicine screening system for severe retinopathy of prematurity. J Pediatr Ophthalmol Strabismus. 2019;56(3):157-161. doi: 10.3928/01913913-20190215-01 [PubMed] [CrossRef] [Google Scholar]
17. Hacker K, Anies M, Folb BL, Zallman L. Barriers to health care for undocumented immigrants: a literature review. Risk Manag Healthc Policy. 2015;8:175-183. doi: 10.2147/RMHP.S70173 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
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