Abstract
Physician encounters with patients with type 2 diabetes act as motivation for self-management and lifestyle adjustments that are indispensable for diabetes treatment. We elucidate the sociodemographic sources of variation in encounter usage and the impact of encounter usage on glucose control, which can be used to recommend encounter usage for different sociodemographic strata of patients to reduce risks from Type 2 diabetes. We analyzed data from a multi-facility clinic in the Midwestern United States on 2124 patients with type 2 diabetes, from 95 ZIP codes. A zero-inflated Poisson model was used to estimate the effects of various ZIP-code level sociodemographic variables on the encounter usage. A multinomial logistic regression model was built to estimate the effects of physical and telephonic encounters on patients' glucose level transitions. Results from the two models were combined in marginal effect analyses. Conditional on patients' clinical status, demographics, and insurance status, significant inequality in patient encounters exists across ZIP codes with varying sociodemographic characteristics. One additional physical encounter in a six-month period marginally increases the probability of transition from a diabetic state to a pre-diabetic state by 4.3% and from pre-diabetic to the non-diabetic state by 3.2%. Combined marginal effect analyses illustrate that a ZIP code in the lower quartile of high school graduate percentage among all ZIP codes has 1 fewer physical encounter per six months marginally compared to a ZIP code at the upper quartile, which gives 5.4% average increase in the probability of transitioning from pre-diabetic to diabetic. Our results suggest that policymakers can target particular patient groups who may have inadequate encounters to engage in diabetes care, based on their immediate environmental sociodemographic characteristics, and design programs to increase their encounters to achieve better care outcomes.
Highlights
In the United States, it is estimated that 30.3 million people (9.4% of the U.S population) had diabetes in 2015 [1]
Conditional on patients’ clinical status, demographics, and insurance status, significant inequality in patient encounters exists across ZIP codes with varying sociodemographic characteristics
We demonstrate that the two encounter types act differently on patient subpopulations with different sociodemographic status
Summary
In the United States, it is estimated that 30.3 million people (9.4% of the U.S population) had diabetes in 2015 [1]. The estimated total cost, including direct medical cost and indirect cost caused by loss of productivity, due to diabetes in 2017 was $327 billion [2]. Managing type 2 diabetes requires patients to stay informed from doctors about their medical conditions and treatment practice changes, and get educated about how to control glucose levels and deal with potential complications. The Chronic Care Model proposed by the Institute for Healthcare Improvement, an independent nonprofit organization, identifies productive encounters between prepared healthcare practice teams and informed and activated patients as the central tenet in managing chronic diabetes and reducing the population-level economic and healthcare burden from diabetes [5]
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