Enrollment, claims, and spatial data are used to demonstrate the importance of outreach strategies for families in rural areas who have children with diabetes. Spatial barriers, alone, do not fully elucidate racial/ethnic disparities in pediatric diabetes for street-level location. (For Tables and the Figure, please access the PDF on the last page.)
Enrollment files, eligibility files, and claims/encounter data were used to identify 7233 children with diabetes in Florida’s public insurance programs to examine driving times they encounter to reach in-network endocrinologists who serve publicly insured children with diabetes in Florida; the children are categorized by sociodemographic characteristics. Average driving times to pediatric endocrinologists were ≤30 minutes for children in urban areas but ≥70 minutes for children in rural communities. White children faced the longest driving times; only 56% were ≤30 minutes from a pediatric endocrinologist. These data reinforce the importance of outreach strategies for families in rural areas and demonstrate that spatial barriers, alone, do not fully elucidate racial/ethnic disparities in pediatric diabetes.for street-level location.
Youth with type 1 and type 2 diabetes (T1D and T2D) from low socioeconomic status (SES) households are at a greater risk than others for many negative health outcomes related to glycemic control, including higher hospitalization rates for very serious complications like diabetic ketoacidosis and elevated risk for diabetes-related morbidity and mortality.1-14 Moreover, race and ethnic minority status further compounds disparate outcomes in diabetes for non-Hispanic blacks and Hispanics.6-15 Despite the need for interventions to improve
health outcomes for economically vulnerable pediatric populations with T1D and T2D,16,17 there is a paucity of research that explicates barriers that may be unique to these children and their families.
In addition to basic primary care needs shared by all pediatric populations, a critical feature to achieving optimal health for children and adolescents living with diabetes is having regular access to pediatric endocrinologists. The American Diabetes Association recommends that children and adolescents with T1D and T2D visit a specialist at least four times a year.18 Children who do not meet these recommended guidelines for routine care with pediatric endocrinologists often have less-than-optimal glycemic control and higher rates of associated health risks.18,19 Moreover, though studies are limited in this area, public health insurance status has been identified as a risk factor for irregular pediatric endocrinology clinic attendance19,20 and for underuse of specialists in general, especially for non-Hispanic blacks.21
A rising scarcity of pediatric endocrinologists and a growing demand for their services22-24 compound difficulties that economically vulnerable families face in utilizing healthcare specialists who may be located considerable distances from their residences. Despite Family and Medical Leave Act protections, service sector jobs that are common among working-poor families rarely allow for adequate paid leave time; subsequently, a significant loss of income results when time away from work is taken to accommodate routine medical visits.25-27 Rural families are disproportionately poorer than urban families, and they are also at a greater disadvantage in important ways that could negatively affect their health.28,29
Adequate access to healthcare is significantly correlated with distance, an inability to obtain a driver’s license, and the lack of access to reliable transportation. All these factors negatively affect attendance of regular check-ups.30,31 Thus, the recommended standard of care of four visits to pediatric endocrinology a year presents a potential obstacle for low-SES families living with diabetes.
To better understand barriers of geographic access to pediatric endocrinologists, our study examined proximity to in-network providers of publicly insured children as a measure for access to endocrinology care among adolescents living with T1D and T2D in the state of Florida. This analysis also examined how socio-contextual factors such as urban versus rural location, race, and ethnic minority status shape geographic access as a key determinant in the complex construct of access to care. To our knowledge, there has not been a systematic attempt to document the distance that publicly insured children with diabetes in the state of Florida need to travel for access to potential endocrinologists.
Florida is one of the four largest states in the United States with significant racial and ethnic diversity, and it ranks among the top three states for the number of low-income children (those from households earning less than 200% of the Federal Poverty Level).32 Moreover, Florida has been identified as one of the top four states with persistent pronounced disparities in access to healthcare.33
This study relied on a cohort of publicly insured children from Florida’s Title XIX and XXI programs, which include Medicaid, MediKids, Children’s Medical Services Managed Care Plan (CMS), and the Florida Healthy Kids Program (FHKP or Florida’s Children’s Health Insurance Program, Title XXI), along with the 2015 provider directories for endocrinology of each program. All protocols in this study were approved by the Institutional Review Board-01 at the University of Florida and by the agencies represented in the research, including the Florida Agency for Health Care Administration and the FHKP. This study qualified as a retrospective review of existing data and operated under a waiver of informed consent. Enrollment files and eligibility files, along with claims/encounter data for each program, were used to identify children with diabetes using the following inclusion criteria: Children were defined as individuals aged 19 years or less who had any claims with International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis (primary or secondary)
code of T1D or T2D during the year. SAS 9.4 (SAS Institute, Inc; Cary, North Carolina) was used for analysis. Information about eligibility for each insurance program is provided in Table 1.
To our knowledge, a critical review of the provider directories available to publicly insured families has not been performed, nor are there studies in which directories have been carefully examined and verified prior to mapping. A systematic examination of the endocrinology provider directories available from health plans for each public health insurance
program was conducted to verify that the specialists listed were, indeed, endocrinologists, and to further confirm their credentialing. Each provider’s license and specialization were verified using both the Florida Department of Health (FL-DOH) practitioner profile search and the National Provider Identifier (NPI) registry. Providers were categorized as PE (pediatric endocrinology), GE (general/adult endocrinology), OE (other endocrinology; eg, reproductive endocrinology), or not applicable (providers whose licenses were not clear and active, who practiced in medical specialties other than endocrinology, or whose specialty could not be conclusively determined by the search[es]).
Provider addresses were entered into an online search for verification using a combination of the FL-DOH profile search and Google Maps. When registry searches yielded ambiguous results regarding addresses or specialty categorization, the U.S. News and World Report Find a Doctor34 search tool was used to make a final determination. Each provider entry was verified by a second coder who consulted both FL-DOH and NPI registries. In the few instances in which a discrepancy arose between coders, an arbiter was used to make a final call. For a point of general comparison, the total number of pediatric endocrinology providers listed as in-network for each program was compared with the number of pediatric endocrinologists practicing in each county, as determined by use of the FL-DOH directory.
Using data on race and ethnic minority status as reported by members’ families and addresses of the identified cohort available through the enrollment and eligibility files, members were geocoded using the industry-leading Navteq 2015 ESRI StreetMap Premium location software (Environmental Systems Research Institute, Inc. Redlands, CA). Geocoding is the process of determining the spatial location (latitude and longitude) of a residence from the written address.35 Of all the members in the cohort, 95% were able to be geocoded to
their street address number. Of the remaining 5%,which were able to be located only generally (at the centroid of their ZIP code), 77% of these addresses were post office boxes, and therefore not eligible for street-level location. Provider addresses were also geocoded using the verified provider directories, and all providers’ locations were successfully found geocoding.
ArcMap ESRI Network Analyst and StreetMap Premium data were used to measure the driving time from each member residence to both the closest in-network endocrinologist and to the closest in-network pediatric endocrinologist. Average drive times to a participating endocrinologist for members of each public health insurance program. Rural counties were identified as having less than 100 persons per square mile, based on the 2010 US Census, as defined by 2015 Florida Statute 381.0406 2015.37 Adequate proximity was considered to be no more than 30 minutes driving time to a provider; the 30-minute limit has been used to identify areas with poor healthcare coverage in other studies.36
A total of 7233 children in the identified cohort were mapped to available endocrinology providers:
• 4395 for Medicaid and MediKids
• 1562 for CMS
• 1276 for the FHKP
Demographic characteristics of the cohort are presented in Table 1. In brief, the cohort included the following children:
• 54% with T1D
• 46% with T2D
• Mean age of 12.2 years (±4.62)
• 47% male
• 24% white
• 31% Hispanic
• 21% black
• 3% other race/ethnicity
• 21% of unknown race/ethnicity.
The relatively high percentage of Hispanics is reflective of the overall population characteristics of the state of Florida, where approximately 29% of all children are Hispanic/Latino and the Hispanic population is the third-highest in the United States.32
Members of each program were mapped to available providers (Figures 1a-d). The distances to available providers were examined for each program, according to provider type (PE versus GE/OE, and then “any” representing the driving distance to any type of endocrinologist). The findings from the provider directory analysis were thus used to create a typology for geocoding output and to calculate proximity to a location with at least one provider. Key to this analysis was examining possible variations in driving distances depending on whether a member lived in a rural or urban location, and to see how this relationship between distance and location type varied by race and ethnic minority status (Table 2 and Table 3). As expected, rural populations represented a smaller proportion of the overall cohort and were more commonly non-Hispanic white. Ninety-five percent of non-Hispanic
black members resided in urban counties, and the members in densely urban, southeast Florida were 60% Hispanic.
In all, members in urban areas for all programs tended to have similar driving times to pediatric endocrinologists or to any endocrinologist. For urban members in the FHKP, driving time to any endocrinologist was an average of 12 minutes (13 to a pediatric endocrinologist); for CMS members, driving time was 29 minutes (30 to a pediatric endocrinologist);
and for Medicaid members, driving time was 13 minutes (18 to a pediatric endocrinologist). However, for rural families, driving times were significantly longer. Average driving times
for rural families were as follows: For members in the FHKP, driving time to any endocrinologist was 59 minutes (70 to a pediatric endocrinologist); for CMS members, driving time was 75 minutes (75 to a pediatric endocrinologist); and for Medicaid members, driving time was 60 minutes (72 to a pediatric endocrinologist).
When driving times were examined according to race and ethnic minority status, non-Hispanic white families faced the longest driving times overall (34 minutes to a pediatric endocrinologist compared with 18 for Hispanics and 20 for non-Hispanic blacks). Further, only 56% of the non-Hispanic white families were less than 30 minutes from a pediatric endocrinologist, compared with 84% of Hispanics and 80% of non-Hispanic blacks.
Systematic categorization of the providers listed in the Medicaid provider directories, which include both adult and pediatric endocrinologists due to Medicaid Managed Medical Assistance plans serving both populations, indicated that rural areas suffer from a dearth of practicing endocrinologists. Medicaid providers in the state served 36 of 67 counties,
and among those, only six counties were classified as rural. To ascertain whether rural counties had other pediatric endocrinologists that simply were not available to publicly insured children in the state of Florida (eg, providers who do not accept these types of insurance programs), a county-level search was conducted through the FL-DOH registry to enumerate
the total number of active licensed practitioners with a specialty in pediatric endocrinology in the state of Florida.
Overall, rural counties that were lacking providers for publicly insured children tended not to have any practicing pediatric endocrinologists at all. Findings from the FL-DOH registry demonstrate that the primary practice locations of the 107 providers listed as active, licensed pediatric endocrinologists in Florida at the time of analysis represented only 20 out
of 67 counties statewide. Among those 20 counties, only one county was classified as rural. The instances where pediatric endocrinologists existed but were not available to publicly insured members were in urban hubs (eg, Miami) where families had more options for providers who did accept public forms of health insurance. Therefore, the issue of limited availability of endocrinology providers in rural areas of the state is not unique to public insurance status, but representative of a systemic lack of providers overall.
For publicly insured children with T1D and T2D living in urban areas, average driving time to an endocrinologist was 30 minutes or less. Conversely, publicly insured rural children faced driving times of one hour or more when traveling to see available endocrinologists. Notably, non-Hispanic white families had the longest driving times compared with Hispanics or non-Hispanic blacks, which may be best explained by the geographic distribution of these ethnicities among the publicly insured population. Based on US Census data,
we expected Hispanic and non-Hispanic black children to have the shortest driving times due to demographic patterns of urban hubs like Miami, Orlando, Jacksonville, and Tampa. Results from this geospatial analysis provide new insight into the specific disparity in driving distances faced by rural, publicly insured families who need pediatric diabetes care, and how these times vary according to race and ethnic minority status.
The implications of these findings are important. Our analysis demonstrates that rural families utilizing public health insurance in the state of Florida face disproportionate barriers in access to pediatric endocrinologists. The costs associated with traveling an hour or more, 4 times a year, to see a specialist for routine care are likely to be considerable for low-income families. These findings reinforce calls for efforts to reach families affected by diabetes and living in rural communities through telemedicine and other novel outreach
modalities.38,39 Additionally, our findings clarify that lack of access to specialists in rural areas is not a problem specific to the publicly insured; rather, this is an overall problem facing any child living with diabetes in rural counties of Florida. While this distance constitutes a barrier for all children living in rural areas who require an endocrinologist’s care, the economic vulnerability of publicly insured children presents multiple unique hardships that may augment the difficulty of seeking endocrinology care. The presence of a specialist in a rural area is associated with better health outcomes,40 but there simply are not enough endocrinologists in rural pockets of the state to accommodate the ever-growing need.
Finally, disparities in health outcomes associated with race and ethnic minority status in pediatric diabetes cannot be solely attributed to issues of geographic access, as the vast majority of nonwhite urban families who are at risk for negative diabetes-related outcomes live within minutes of in-network endocrinologists.
This research offers the first detailed account of actual driving times faced by families in Florida’s public health insurance programs when in need of an endocrinologist. The methodological approach to this analysis is comprehensive: Most existing studies on geographic distance focus on adult and general populations, Euclidian distance (straight
line), and primary care settings (rather than specialists).This study uses a state-of-the-art software to estimate driving times and breaks down analyses to program-specific, in-network specialists.
There are several limitations to this work. Future studies on underserved populations would benefit from including complete information about the race/ethnicity of members. Given that families are not required to provide this information on applications for public health insurance, 21% of the study population’s race/ethnicity was unknown. Also, this study cannot speak to member-level experiences with driving time and the degree to which it is perceived as a barrier. Rural residents may perceive distance as less of a barrier if the provider is within close proximity of routes they regularly travel.30 Finally, though existing research indicates that publicly insured children and non-Hispanic black children are most at risk for underutilizing routine endocrinology care19-21 these findings cannot speak to actual utilization rates as they are beyond the scope of this study.
Reducing disparate health outcomes in diabetes will require multi-level interventions, but basic access to care is paramount. More research is needed to better explicate barriers for nonwhite families living in close proximity to available providers, and to test other mechanisms through which rural children at great distance from providers can receive care.
We posit that entities working to improve health outcomes for children with T1D and T2D intentionally partner with state agencies that administer public health insurance programs when developing new interventions, as their enrollment files provide a robust way of identifying and reaching economically vulnerable children within a state. The pioneering
efforts of this study will undoubtedly contribute to future studies that examine actual utilization rates and outcomes data alongside geographic access and contributing barriers.Acknowledgments
This study was funded by a seed money grant from the Pediatric Workgroups, a collaboration among the University of Florida’s Department of Pediatrics, Department of Health Outcomes and Policy, Institute for Child Health Policy, and Family Data Center. Part of this research was presented at the 2017 American Diabetes Association Scientific Sessions in San Diego, California.
The authors have no conflicts of interest to disclose.
We extend our sincere gratitude to the State of Florida for supporting this research. In particular, we thank Beth Kidder and Jason Ottinger from Florida’s Agency for Healthcare Administration, and Fred Knapp and Rebecca Matthews from the Florida Healthy Kids Corporation. We extend our thanks to Yijun Sun, PhD, and Bin Zang, PhD, for their outstanding
work in programming. Excellent research assistance was provided by Kimberly Baker, MLIS; Alexandra M. Lee; Ilyssa Schatz; Claudia Anez-Zabala; Jamie Hensley; Donny Weinbrenner; and Debbie Berrier, all at the University of Florida’s Institute for Child Health Policy.
Ashby F. Walker, PhD, is affiliated with the University of Florida Diabetes Institute and the Department of Health Services Research, Management and Policy, Gainesville, Florida. Michael J. Haller, MD, Henry J. Rohrs, MD, and Desmond A. Schatz, MD, are affiliated with the University of Florida Diabetes Institute and the Department of Pediatrics, Gainesville, Florida. Jaclyn M. Hall, PhD, Matthew J. Gurka, PhD, and Heather L. Morris, PhD, are affiliated with the Institute for Child Health Policy and the Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville. Elizabeth A. Shenkman, PhD, is affiliated with the Department of Health Outcomes and Biomedical Informatics, The Institute for Child Health Policy, and the Department of Pediatrics at the University of Florida, Gainesville. Kelsey R. Salazar, MPH, is affiliated with the Health Care Improvement Foundation in
Ashby F. Walker, PhD, University of Florida Diabetes Institute, PO Box 100309, Gainesville, FL 32610. Email: email@example.com.
AFW served as principal investigator (PI) for the study, designed the study, secured IRB-01 approval for the study, provided oversight for data delivery and management, secured the Data Use Agreement with Florida’s Agency for Health Care Administration, coordinated all communications related to this project, and wrote the article. DAS contributed to the study design, served as co-PI for the Pediatric working group with AFW reviewed findings, and reviewed and edited the article. BAS serves as PI on the External Quality of Review
contracts with Florida and thus provided access needed for the research, contributed to the study design, and reviewed and edited the article. JMH served as the spatial geographer for the study, conducted all mapping and related output, wrote the methodology for the mapping, and reviewed and edited the article. HLM provided oversight of the provider directory work for CMS, provided input on the study design, helped create all demographic tables, and reviewed and edited the article. MJG served as the biostatistician for the research, reviewed data, and reviewed and edited the article. MJH and HJR provided oversight for the study design, provided continual expertise about the provider directory analysis, reviewed data, and reviewed and edited the article. KRS contributed to the literature review, had all oversight of research coordinators working on the provider directory analysis, wrote the methodology for the provider directory analysis, and reviewed and edited the article.
AFW is the guarantor of this work, and as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of data analysis.References
1. Secrest AM, Costacou T, Gutelius B, Miller RG, Thomas SJ, Trevor OJ. Association of socioeconomic status with mortality in type 1 diabetes: the Pittsburgh Epidemiology of Diabetes Complications Study. Ann Epidemiol. 2011;21(5):367-373. doi: 10.1016/j.annepidem. 2011.02.011.
2. Secrest AM, Costacou T, Gutelius B, Miller RG, Thomas SJ, Trevor OJ. Associations between socioeconomic status and major complications in type 1 diabetes: the Pittsburgh Epidemiology of Diabetes Complication (EDC) Study. Ann Epidemiol. 2011;21(5):374-381. doi: 10.1016/j. annepidem.2011.02.007.
3. Berhan YT, Eliasson M, Möllsten A, Waernbaum I, Dahlquist G. Impact of parental socioeconomic status on excess mortality in a population-based cohort of subjects with childhood-onset type 1 diabetes. Diabetes Care. 2015;38(5):827-832. doi: 10.2337/dc14-1522.
4. Cutfield SW, Derraik JGB, Reed PW, Hofman PL, Jefferies C, Cutfield WS. Early markers of glycaemic control in children with type 1 diabetes mellitus. PLoS ONE. 2011;6(9):e25251. doi: 10.1371/journal. pone.0025251.
5. Keenan HT, Foster HT, Bratton SL. Social factors associated with prolonged hospitalization among diabetic children. Pediatrics. 2002;109(1):40-44.
6. Willi SM, Miller KM, DiMeglio LA, et al. Racial-ethnic disparities in management and outcomes among children with type 1 diabetes. Pediatrics. 2015;135(3):424-434. doi: 10.1542/peds.2014-1774.
7. Kamps JL, Hempe JM, Chalew SA. Racial disparity in A1C independent of mean blood glucose in children with type 1 diabetes. Diabetes Care. 2010;33(5):1025-1027. doi: 10.2337/dc09-1440.
8. Valenzuela J, La Greca A, Hsin O, Taylor C, Delamater A. Prescribed regimen intensity in diverse youth with type 1 diabetes: role of family and provider perceptions. Pediatr Diabetes. 2011;12(8):696-703. doi: 10.1111/j.1399-5448.2011.00766.x.
9. Gallegos-Macias AR, Macias SR, Kaufman E, Skipper B, Kalishman N. Relationship between glycemic control, ethnicity and socioeconomic status in Hispanic and non-Hispanic youths with type 1 diabetes mellitus. Pediatr Diabetes. 2003;4(1):19-23.
10. Mayer-Davis EJ, Beyer J, Bell RA, et al; SEARCH for Diabetes in Youth Study Group. Diabetes in African American youth: prevalence, incidence, and clinical characteristics: the SEARCH for Diabetes in Youth Study. Diabetes Care. 2009;32(suppl 2):S112-S122. doi: 10.2337/dc09-S203.
11. Petitti DB, Klingensmith GJ, Bell RA, et al; SEARCH for Diabetes in Youth Study Group. Glycemic control in youth with diabetes: the SEARCH for Diabetes in Youth Study. J Pediatr. 2009;155(5):668-672. e1-e3. doi: 10.1016/j.jpeds.2009.05.025.
12. Imperatore G, Stevens M, Beckles G, Williams DE, Gregg EW. Socio-economic status and type 2 diabetes risk factors among US children and young adults: the National Health and Nutrition Examination Survey, 1999-2004. Diabetes. 2007;56(suppl 1):A488-A489.
13. Dowell M, Rozell B, Roth D, Delugach H, Chaloux P, Dowell J. Economic and clinical disparities in hospitalized patients with type 2 diabetes. J Nurs Scholarsh. 2004;36(1):66-72. doi: 10.1111/j.1547-5069.2004.04015.x.
14. Dabelea D, Mayer-Davis EJ, Saydah S, et al. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA. 2014;311(17):1778-1786. doi: 10.1001/jama.2014.3201.
15. Saydah S, Imperatore G, Cheng Y, Geiss LS, Albright A. Disparities in diabetes death among children and adolescents — United States, 2000-2014. MMWR Morb Mortal Wkly Rep. 2017;66(19):502-505. doi:10.15585/mmwr.mm6619a4.
16. Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications Research Group. Effect of intensive therapy on the microvascular complications of type 1 diabetes mellitus. JAMA. 2002;287(19):2563-2569.
17. Wagmiller RL, Adelman RM. Childhood and intergenerational poverty: the long-term consequences of growing up poor. National Center for Children in Poverty website. nccp.org/publications/pdf/text_909.pdf. Published November 2009. Accessed June 7, 2017.
18. American Diabetes Association. Standards of Medical Care in Diabetes—2016. children and adolescents. Diabetes Care. 2016;39(suppl
1):S86-S93. doi: 10.2337/dc16-S014.
19. Jacobson AM, Hauser ST, Willett J, Wolfsdorf JI, Herman L. Consequences of irregular versus continuous medical follow-up in children and adolescents with insulin-dependent diabetes mellitus. J Pediatr. 1997;131(5):727-733.
20. Kaufman FR, Halvorson M, Carpenter S. Association between diabetes control and visits to a multidisciplinary pediatric diabetes clinic. Pediatrics. 1999;103(5 Pt 1):948-951.
21. Shenkman E, Tian L, Nackashi J, Schatz D. Managed care organizational characteristics and outpatient specialty use among children with chronic illness. Pediatrics. 2005;115(6):1547-1554. 22. Rizza RA, Vigersky RA, Rodbard HW, et al. A model to determine workforce needs for endocrinologists in the United States until
2020. J Clin Endocrinol Metab. 2003;88(5):1979-1987.
23. Vigersky RA, Fish L, Hogan P, et al. The clinical endocrinology workforce:current status and future projections of supply and demand. J Clin Endocrinol Metab. 2014;99(9):3112-3121. doi: 10.1210/jc.2014-2257.
24. Lee JM, Davis MM, Menon RK, Freed GL. Geographic distribution of childhood diabetes and obesity relative to the supply of pediatric endocrinologists in the United States [published correction appears in J Pediatr. 2008;152(6):893]. J Pediatr. 2008;152(3):331-336. doi:10.1016/j.jpeds.2007.08.037.
25. Chaudry A, Pedroza J, Sandstrom H. How employment constraints affect low-income working parents’ child care decisions. The Urban Institute website. urban.org/research/publication/how-employmentconstraints-affect-low-income-working-parents-child-care-decisions. Published February 22, 2012. Accessed June 7, 2017.
26. Sandstrom H, Chaudry A. “You have to choose your childcare to fit your work”: childcare decision-making among low-income working families. J Child Poverty. 2012;18(2):89-119. doi:10.1080/10796126.2012.710480.
27. Ehrenreich B. Nickel and Dimed: On (Not) Getting By in America.10th anniversary ed. New York, NY: Picador; 2011.
28. Duncan CM. Rural Poverty in America. Westport, CT: Auburn House; 1992.
29. Kusmin LD, Parker TS. Rural employment at a glance. US Department of Agriculture website. ers.usda.gov/webdocs/publications/44135/29853_eib21_002.pdf?v=41305. Published December 2006. Accessed June 7, 2017.
30. Arcury TA, Gesler WM, Preisser JS, Sherman J, Spencer J, Perin J. The effects of geography and spatial behavior on healthcare utilization among the residents of a rural region. Health Serv Res. 2005;40(1):135-156. doi: 10.1111/j.1475-6773.2005.00346.x.
31. Nemet GF, Bailey AJ. Distance and healthcare utilization among the rural elderly. Soc Sci Med. 2000;50(9):1197-1208.
32. American Community Survey 1-Year estimates. US Census Bureau website. factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_14_1YR_B03003&prodType=table. Published 2014. Accessed March 3, 2016.
33. Rasmussen PW, Collins SR, Doty MM, Beutel S. Healthcare coverage and access in the nation’s four largest states. The Commonwealth Fund website. commonwealthfund.org/publications/issue-briefs/2015/apr/coverage-and-access. Published April 10, 2015. Accessed June 7, 2017.
34. Find a doctor. U.S. News and World Report website. health.usnews.com/doctors. Accessed February 13, 2018.
35. Higgs G. The role of GIS for health utilization studies: literature review. Health Serv Outcomes Res Methodol. 2009;9(2):84-99. doi:10.1007/s10742-009-0046-2.
36. Chan L, Hart LG, Goodman DC. Geographic access to healthcare for rural Medicare beneficiaries. J Rural Health. 2006;22(2):140-146. doi: 10.1111/j.1748-0361.2006.00022.x.
37. Fla Stat Title XXIX, ch 381, §406. Public Health General Provisions, Rural Health Networks, 2015. flsenate.gov/Laws/Statutes/2015/381.0406. Accessed June 7, 2017.
38. Wood C, Clements S, McFann K, Slover R, Thomas J, Wadwa R. Use of telemedicine to improve adherence to American Diabetes Association standards in pediatric type 1 diabetes. Diabetes Technol Ther. 2016;18(1):7-14. doi: 10.1089/dia.2015.0123.
39. Simm PJ, Wong N, Fraser L, et al. Geography does not limit optimal diabetes care: use of a tertiary centre model of care in an outreach service for type 1 diabetes mellitus. J Paediatr Child Health. 2014;50(6):471-475. doi: 10.1111/jpc.12499.
40. Odisho AY, Cooperberg MR, Fradet V, Ahmad AE, Carroll PR. Urologist density and county-level urologic cancer mortality. J Clin Oncol.
2010;28(15):2499-2504. doi: 10.1200/JCO.2009.26.9597.