From the Department of Medicine, Massachusetts General Hospital, Boston, MA (SB); Perelman School of Medicine, University of Pennsylvania Philadelphia, PA (DJA); Department of Medical Ethics and Health Policy, University of Pennsylvania (SB); Pritzker School of Medicine, University of Chicago, Chicago, IL (IJLH); Department of Medicine, Section of General Internal Medicine, University of Chicago (ELT); Chicago Center for Diabetes Translation Research, University of Chicago (ELT); Department of Family Medicine and Community Health, University of Pennsylvania (PFC); Center for Public Health Initiatives, University of Pennsylvania (PFC); Leonard Davis Institute of Health Economics, University of Pennsylvania (PFC).
J Am Board Fam Med. 2021 Sep-Oct;34(5):891-897. doi: 10.3122/jabfm.2021.05.200639.
Evidence suggests that clinicians may view or label patients as nonadherent in a biased manner. Therefore, we performed a retrospective cohort analysis exploring associations between patient demographics and zip code-level income with the (ICD-10) diagnoses for nonadherence among type 2 diabetes mellitus (T2DM) patients, comparing primary and specialty care settings. Providers in the primary care group included internal medicine and family medicine physicians. In the specialty care group, providers included endocrinologists and diabetologists only.
Participants were identified from 5 primary care and 4 endocrinology sites in the University of Pennsylvania Health System between January 1, 2015, and January 1, 2019. Demographics, hemoglobin A1c (HbA1c), and ICD-10 codes for T2DM and nonadherence were extracted from the electronic health record and analyzed in October 2019. Log-binomial regression models were used to estimate patients' risk of nonadherence labeling by race, insurance, and zip code-level median household income, controlling for patient characteristics and HbA1c as a proxy for diabetes self-management. Results were compared between primary and specialty care sites.
A total of 6072 patients aged 18-70 years were included in this study. Black race, Medicare, and Medicaid were associated with increased nonadherence labeling while controlling for patient characteristics ([ARR = 2.48, 95% CI: 2.01, 3.04], [ARR = 1.82, 95% CI: 1.50, 2.18], [ARR = 1.61, 95% CI: 1.32, 1.93], respectively). The results remained significant on adjustment with zip code-level income and showed no differences between primary and specialty sites. Lower-income zip codes showed a significant association with increased rates of nonadherence labeling.
Black race, non-private insurance, and lower-income zip codes were associated with disproportionately high rates of nonadherence labeling in both primary and specialty management of T2DM, possibly suggestive of racial or class bias.
有证据表明,临床医生可能会以有偏见的方式看待或标记患者为不依从者。因此,我们进行了一项回顾性队列分析,探讨了 2 型糖尿病(T2DM)患者的患者人口统计学和邮政编码收入与(ICD-10)不依从诊断之间的关联,比较了初级保健和专科护理环境。初级保健组的提供者包括内科医生和家庭医生。在专科护理组中,提供者仅包括内分泌学家和糖尿病专家。
参与者是从宾夕法尼亚大学卫生系统的 5 个初级保健和 4 个内分泌学站点于 2015 年 1 月 1 日至 2019 年 1 月 1 日期间确定的。从电子健康记录中提取人口统计学、糖化血红蛋白(HbA1c)和 T2DM 及不依从性的 ICD-10 代码,并于 2019 年 10 月进行分析。使用对数二项式回归模型来估计患者的非依从性标签风险种族、保险和邮政编码级中位数家庭收入,同时控制患者特征和 HbA1c 作为糖尿病自我管理的替代指标。结果在初级保健和专科护理站点之间进行了比较。
本研究共纳入 6072 名 18-70 岁的患者。控制患者特征后,黑种人、医疗保险和医疗补助与增加的不依从标签相关联 ([ARR = 2.48, 95%CI: 2.01, 3.04],[ARR = 1.82, 95%CI: 1.50, 2.18],[ARR = 1.61, 95%CI: 1.32, 1.93],分别)。在调整邮政编码收入后,结果仍然显著,且初级保健和专科护理站点之间无差异。低收入邮政编码与不依从标签率升高显著相关。
黑种人、非私人保险和低收入邮政编码与 T2DM 的初级保健和专科管理中不成比例的高不依从标签率相关联,可能提示存在种族或阶级偏见。