Diabetes Management in Urban and Rural Areas of the U.S.
Rural communities have higher rates of type 2 diabetes (T2D) and T2D-related mortality. We hypothesize that rural residents with T2D may receive inadequate monitoring and care, compared to urban residents; thus the goal is to determine if patients with T2D are more or less likely to receive comprehensive diabetes care and monitoring. We will also examine the association between living in a rural area, receipt of comprehensive diabetes care, and T2D-related health outcomes (cardiovascular events, T2D-related hospitalization, and other T2D-related complications). Our findings could be used to inform policy discussions focused on reducing T2D-related mortality in rural communities.
Using IBM's MarketScan Commercial Claims and Encounters database, we will classify individuals having any claims in 2019 by their level of urbanization, age group, and state of residence. Individuals with T2D will be identified using two years of claims data, from 2018 to 2019. We will examine T2D monitoring by identifying how many T2D patients had a claim for HbA1c testing and how many had attention to nephrology (urine drug testing claim or diagnosed nephropathy). We will also examine HbA1c control and blood pressure control. We will license the Health Effectiveness Data and Information Set comprehensive diabetes care measure to obtain standardized definitions for T2D monitoring and control.
We will analyze data at the regional or state level as well as at the national level, collapsing across age for individuals that are 18-64 and comparing rural and urban rates of T2D prevalence, monitoring or control. Because IBM MarketScan data do not include a measure of race/ethnicity, we will add additional information about the racial diversity of rural areas within each state, to aid in interpretation of these state-level results. For the nationwide descriptive analysis, we will aggregate across state and examine four distinct age groups: 18-34, 35-44, 45-54, and 55-64.
To determine the impact of T2D monitoring and control on health outcomes, we will examine whether patients experienced any of the following health outcomes during the course of 2019: a major cardiovascular event, a T2D-related hospitalization (identified through inpatient claims including T2D as a primary diagnosis), or at least one T2D-related complication. Each of these outcomes will be modeled with a logistic regression. The list of predictors used in the regressions may include urbanization, region, sex, age, presence of HbA1c testing, HbA1c control, blood pressure control, and attention to nephropathy.