Unknown

Dataset Information

0

An Electronic Health Record-Integrated Computerized Intravenous Insulin Infusion Protocol: Clinical Outcomes and in Silico Adjustment.


ABSTRACT: BACKGROUND:We aimed to describe the outcome of a computerized intravenous insulin infusion (CII) protocol integrated to the electronic health record (EHR) system and to improve the CII protocol in silico using the EHR-based predictors of the outcome. METHODS:Clinical outcomes of the patients who underwent the CII protocol between July 2016 and February 2017 and their matched controls were evaluated. In the CII protocol group (n=91), multivariable binary logistic regression analysis models were used to determine the independent associates with a delayed response (taking ≥6.0 hours for entering a glucose range of 70 to 180 mg/dL). The CII protocol was adjusted in silico according to the EHR-based parameters obtained in the first 3 hours of CII. RESULTS:Use of the CII protocol was associated with fewer subjects with hypoglycemia alert values (P=0.003), earlier (P=0.002), and more stable (P=0.017) achievement of a glucose range of 70 to 180 mg/dL. Initial glucose level (P=0.001), change in glucose during the first 2 hours (P=0.026), and change in insulin infusion rate during the first 3 hours (P=0.029) were independently associated with delayed responses. Increasing the insulin infusion rate temporarily according to these parameters in silico significantly reduced delayed responses (P<0.0001) without hypoglycemia, especially in refractory patients. CONCLUSION:Our CII protocol enabled faster and more stable glycemic control than conventional care with minimized risk of hypoglycemia. An EHR-based adjustment was simulated to reduce delayed responses without increased incidence of hypoglycemia.

SUBMITTER: Park SW 

PROVIDER: S-EPMC7043972 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications

An Electronic Health Record-Integrated Computerized Intravenous Insulin Infusion Protocol: Clinical Outcomes and <i>in Silico</i> Adjustment.

Park Sung Woon SW   Lee Seunghyun S   Cha Won Chul WC   Hur Kyu Yeon KY   Kim Jae Hyeon JH   Lee Moon Kyu MK   Park Sung Min SM   Jin Sang Man SM  

Diabetes & metabolism journal 20191021 1


<h4>Background</h4>We aimed to describe the outcome of a computerized intravenous insulin infusion (CII) protocol integrated to the electronic health record (EHR) system and to improve the CII protocol in silico using the EHR-based predictors of the outcome.<h4>Methods</h4>Clinical outcomes of the patients who underwent the CII protocol between July 2016 and February 2017 and their matched controls were evaluated. In the CII protocol group (<i>n</i>=91), multivariable binary logistic regression  ...[more]

Similar Datasets

| S-EPMC4663850 | biostudies-literature
| S-EPMC7698999 | biostudies-literature
| S-EPMC2769966 | biostudies-other
| S-EPMC6437238 | biostudies-literature
| S-EPMC9418544 | biostudies-literature
| S-EPMC11664563 | biostudies-literature
| S-EPMC7985417 | biostudies-literature
| S-EPMC9485803 | biostudies-literature
| S-EPMC10644190 | biostudies-literature
| S-EPMC3184082 | biostudies-literature