J Am Pharm Assoc (2003). 2023 May-Jun;63(3):769-777. doi: 10.1016/j.japh.2022.12.028. Epub 2022 Dec 31.
Type 2 diabetes mellitus (T2DM) and comorbid conditions require patients to take complex medication regimens. Greater regimen complexity has been associated with poorer T2DM management; however, the relationship between overall regimen complexity and glycemic control is unclear.
Our objectives were: (1) to examine associations between regimen complexity (with the Medication Regimen Complexity Index [MRCI]) and glycemic control (A1C), and (2) to compare overall MRCI with other measures of regimen complexity (overall and diabetes-specific medication count) and diabetes-specific MRCI.
This was a secondary data analysis of cross-sectional data from a parent trial. Participants were patients with T2DM taking at least 3 chronic medications followed in safety net clinics in the Chicago area. The MRCI measures complexity based on dosing frequency, route of administration, and special instructions for prescribed medications. MRCI scores were created for overall regimens and diabetes-specific medications. Sociodemographics and outpatient visit utilization were included in models as covariates. Linear regression was used to examine the associations between variables of interest and hemoglobin A1C.
Participants (N = 432) had a mean age of 56.9 years, most were female (66.0%), and Hispanic or Latino (73.3%). Regimen complexity was high based on overall medications (mean = 6.6 medications, SD: 3.09) and MRCI (mean = 21.4, SD: 11.3). Higher diabetes-specific MRCI was associated with higher A1C in bivariate and multivariable models. In multivariable models, overall MRCI greater than 14, fewer outpatient health care visits, male gender, and absence of health insurance were independently associated with higher A1C. The variance in A1C explained by MRCI was higher compared to medication count for overall and diabetes-specific regimen complexity.
More complex regimens are associated with worse A1C and measuring complexity with MRCI may have advantages. Deprescribing, increasing insurance coverage, and promoting engagement in health care may improve A1C among underserved populations with complex regimens.
2 型糖尿病（T2DM）和合并症需要患者服用复杂的药物治疗方案。治疗方案的复杂性越大，T2DM 的管理就越差；然而，总体治疗方案的复杂性与血糖控制之间的关系尚不清楚。
我们的目的是：（1）检查治疗方案的复杂性（使用药物治疗方案复杂性指数[MRCI]）与血糖控制（A1C）之间的关联，以及（2）将总体 MRCI 与其他治疗方案复杂性指标（总体和糖尿病特定药物计数）和糖尿病特定 MRCI 进行比较。
这是对来自父母试验的横断面数据的二次数据分析。参与者是在芝加哥地区的安全网诊所接受至少 3 种慢性药物治疗的 T2DM 患者。MRCI 根据药物的给药频率、给药途径和特殊用药说明来衡量复杂性。为总体治疗方案和糖尿病特定药物制定了 MRCI 评分。社会人口统计学和门诊就诊利用率作为协变量纳入模型。线性回归用于检查感兴趣变量与血红蛋白 A1C 之间的关联。
参与者（N=432）的平均年龄为 56.9 岁，大多数为女性（66.0%），西班牙裔或拉丁裔（73.3%）。根据总体药物（平均=6.6 种药物，SD：3.09）和 MRCI（平均=21.4，SD：11.3），治疗方案的复杂性很高。在单变量和多变量模型中，糖尿病特定的 MRCI 越高，A1C 越高。在多变量模型中，MRCI 大于 14、门诊就诊次数较少、男性和没有医疗保险与 A1C 升高独立相关。与总体和糖尿病特定治疗方案复杂性的药物计数相比，MRCI 解释的 A1C 方差更高。
更复杂的治疗方案与更差的 A1C 相关，使用 MRCI 衡量复杂性可能具有优势。减少用药、增加保险覆盖范围和促进参与医疗保健可能会改善复杂治疗方案的服务不足人群的 A1C。
