Department of Medicine, Penn State Health Milton S Hershey Medical Center, Hershey, Pennsylvania, USA
Department of Medicine, Emory University, Atlanta, Georgia, USA.
BMJ Open Diabetes Res Care. 2021 Jan;9(1). doi: 10.1136/bmjdrc-2020-001557.
Innovative approaches are needed to design robust clinical decision support (CDS) to optimize hospital glycemic management. We piloted an electronic medical record (EMR), evidence-based algorithmic CDS tool in an academic center to alert clinicians in real time about gaps in care related to inpatient glucose control and insulin utilization, and to provide management recommendations.
The tool was designed to identify clinical situations in need for action: (1) severe or recurrent hyperglycemia in patients with diabetes: blood glucose (BG) ≥13.88 mmol/L (250 mg/dL) at least once or BG ≥10.0 mmol/L (180 mg/dL) at least twice, respectively; (2) recurrent hyperglycemia in patients with stress hyperglycemia: BG ≥10.0 mmol/L (180 mg/dL) at least twice; (3) impending or established hypoglycemia: BG 3.9-4.4 mmol/L (70-80 mg/dL) or ≤3.9 mmol/L (70 mg/dL); and (4) inappropriate sliding scale insulin (SSI) monotherapy in recurrent hyperglycemia, or anytime in patients with type 1 diabetes. The EMR CDS was active (ON) for 6 months for all adult hospital patients and inactive (OFF) for 6 months. We prospectively identified and compared gaps in care between ON and OFF periods.
When active, the hospital CDS tool significantly reduced events of recurrent hyperglycemia in patients with type 1 and type 2 diabetes (3342 vs 3701, OR=0.88, p=0.050) and in patients with stress hyperglycemia (288 vs 506, OR=0.60, p<0.001). Hypoglycemia or impending hypoglycemia (1548 vs 1349, OR=1.15, p=0.050) were unrelated to the CDS tool on subsequent analysis. Inappropriate use of SSI monotherapy in type 1 diabetes (10 vs 22, OR=0.36, p=0.073), inappropriate use of SSI monotherapy in type 2 diabetes (2519 vs 2748, OR=0.97, p=0.632), and in stress hyperglycemia subjects (1617 vs 1488, OR=1.30, p<0.001) were recognized.
EMR CDS was successful in reducing hyperglycemic events among hospitalized patients with dysglycemia and diabetes, and inappropriate insulin use in patients with type 1 diabetes.
需要创新方法来设计稳健的临床决策支持(CDS),以优化医院血糖管理。我们在一个学术中心试用了一种电子病历(EMR),基于证据的算法 CDS 工具,实时提醒临床医生有关住院患者血糖控制和胰岛素使用方面的护理差距,并提供管理建议。
该工具旨在识别需要采取行动的临床情况:(1)糖尿病患者严重或反复高血糖:血糖(BG)≥13.88mmol/L(250mg/dL)至少一次或 BG≥10.0mmol/L(180mg/dL)至少两次;(2)应激性高血糖患者反复高血糖:BG≥10.0mmol/L(180mg/dL)至少两次;(3)即将发生或已发生低血糖:BG 3.9-4.4mmol/L(70-80mg/dL)或≤3.9mmol/L(70mg/dL);(4)反复高血糖时不合理的胰岛素滑动量表(SSI)单药治疗,或 1 型糖尿病患者的任何时候。EMR CDS 在 6 个月内对所有成年住院患者均处于活动状态(ON),6 个月内处于非活动状态(OFF)。我们前瞻性地识别并比较了 ON 和 OFF 期间护理差距。
当处于活动状态时,医院 CDS 工具可显著减少 1 型和 2 型糖尿病患者(3342 与 3701,OR=0.88,p=0.050)和应激性高血糖患者(288 与 506,OR=0.60,p<0.001)的反复高血糖事件。低血糖或即将发生的低血糖(1548 与 1349,OR=1.15,p=0.050)与随后的分析无关。1 型糖尿病患者中不合理使用 SSI 单药治疗(10 与 22,OR=0.36,p=0.073)、2 型糖尿病患者中不合理使用 SSI 单药治疗(2519 与 2748,OR=0.97,p=0.632)和应激性高血糖患者中不合理使用 SSI 单药治疗(1617 与 1488,OR=1.30,p<0.001)。
EMR CDS 成功减少了血糖异常和糖尿病住院患者的高血糖事件,以及 1 型糖尿病患者中不合理的胰岛素使用。