An Analysis of the Use of Outpatient Generalist and Specialist Physician Services for Persons Reporting Diabetes in the United States
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Date
2023-03-27
Type of Work
Department
University of Baltimore. College of Public Affairs
Program
University of Baltimore. Doctor of Public Administration
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This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by The University of Baltimore for non-commercial research and educational purposes.
Abstract
Abstract
There is a growing concern about the role that demographics and insurance coverage play in disparities in health access among people with diabetes in the United States. This study uses Andersen's framework to examine to what extent individual-level variables, including predisposing, needs, and provider variables, are associated with access to outpatient provider services for individuals reporting either type-1 or type-2 diabetes in the United States.
The study employed a subset sample of 2,812 adults with diabetes from the 2017 NHIS national survey. Predisposing variables such as gender, race, region, and age group may increase or decrease an individual’s propensity to access and utilize care. Enabling variables such as transportation, good communication with the provider, and availability of health insurance may facilitate access and utilization of care. Need variables such as being diagnosed with hypertension and diabetic retinopathy may increase the need for care services among people with diabetes. The dependent variables employed in this study were seeing/talking to a general physician in the past 12 months and seeing or talking to a specialist physician in the past 12 months, representing a measure of access to general or specialized outpatient services for diabetics. The independent variables examined in this research include predisposing (gender, race, region, and age group), enabling (transportation, asking for opinion and insurance), and need (hypertension and diabetic retinopathy) variables.
This study employed binary logistic analysis using weight variables to correct the oversampling of certain racial minorities. The multivariate analysis consisted of two models using the same set of independent variables, but with each having its dependent variable: (i) the first model used seeing/talking to a generalist physician, and (ii) the second model used seeing/talking to a specialist physician within the past year.
As the research dataset required that a person was told that they had diabetes, it is not surprising that none of the independent variables had a statistically significant odds ratio for seeing a generalist physician in the past year. The study did not identify a significant correlation between seeing/talking to a general physician in the past 12 months and gender, race, region, no transportation, a provider who asks opinion/belief about care, health insurance coverage, hypertension, and being diagnosed with diabetic retinopathy. The second model, using specialist care as the dependent variable, contained a pattern of access suggesting potential barriers to access according to socio-demographic characteristics.
Multivariate analysis shows that hypertension had a significant positive association with seeing or talking to a general physician. However, the odds of seeing or talking to a specialist physician were lower among African Americans and American Indians, and Natives relative to Whites.
The study’s main limitation is that the 2017 NHIS data set reports individuals diagnosed with type-1 and type-2 diabetes, leaving out many people yet to be diagnosed but with a high risk for diabetes. In addition, the NHIS 2017 dataset surveys civilian and non- institutionalized populations in the United States, leaving out those in long-term care institutions such as nursing homes, prisons, and veterans. Moreover, the data could be biased since participants' data were self-reported.
Nevertheless, the study has strengths, such as a large sample size representing the national population. Besides, the data can be used to compare demographic characteristics such as age group, gender, race, and insurance, among others. Suggestions for future studies are exploring the effect of different types of insurance coverage on access to outpatient provider services
among individuals with diabetes and diabetes education in reducing outpatient provider care services.
The study findings suggest that there might be inequities in accessing specialized diabetic care that differ by race, insurance, and region. Based on this study's evidence and guided by the values of social equity, public administrators will be well-positioned to develop programs to monitor the extent and impact of healthcare disparities among individuals diagnosed with type-1 and type-2 diabetes. Public administrators will be able to set benchmarks useful in addressing healthcare access disparities.