Department of Business Administration, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America.
Krannert School of Management, Purdue University, West Lafayette, Indiana, United States of America.
PLoS One. 2021 Apr 12;16(4):e0249084. doi: 10.1371/journal.pone.0249084. eCollection 2021.
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.
医生与 2 型糖尿病患者的接触可以激发患者进行自我管理和生活方式调整，这对糖尿病治疗至关重要。我们阐明了接触使用的社会人口学来源的变化，并探讨了接触使用对血糖控制的影响，这可以用于为不同的社会人口学层次的患者推荐接触使用，以降低 2 型糖尿病的风险。
我们分析了来自美国中西部一个多机构诊所的 2124 例 2 型糖尿病患者的数据，这些患者来自 95 个邮政编码区域。我们使用零膨胀泊松模型来估计各种邮政编码水平社会人口统计学变量对接触使用的影响。建立了一个多分类逻辑回归模型来估计身体和电话接触对患者血糖水平转变的影响。这两个模型的结果结合在边缘效应分析中。
在患者的临床状况、人口统计学和保险状况的条件下，具有不同社会人口统计学特征的邮政编码区域之间存在显著的患者接触不平等现象。在六个月内增加一次身体接触，略微增加从糖尿病状态向糖尿病前期状态转变的概率为 4.3%，从糖尿病前期状态向非糖尿病状态转变的概率为 3.2%。联合边缘效应分析表明，在所有邮政编码中，高中毕业生比例处于较低四分位的邮政编码区域，每六个月的身体接触数量平均比处于较高四分位的邮政编码区域少 1 次，这使得从糖尿病前期状态向糖尿病状态转变的概率平均增加了 5.4%。我们的研究结果表明，政策制定者可以根据患者的即时社会人口学特征，针对特定的患者群体，针对那些接触不足的患者，让他们参与到糖尿病护理中，并设计方案来增加他们的接触，以获得更好的护理结果。
