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

2020 ◽  
Vol 44 (1) ◽  
pp. 56 ◽  
Author(s):  
Sung Woon Park ◽  
Seunghyun Lee ◽  
Won Chul Cha ◽  
Kyu Yeon Hur ◽  
Jae Hyeon Kim ◽  
...  
Informatics ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 25
Author(s):  
Terrence C. Lee ◽  
Neil U. Shah ◽  
Alyssa Haack ◽  
Sally L. Baxter

Predictive analytics using electronic health record (EHR) data have rapidly advanced over the last decade. While model performance metrics have improved considerably, best practices for implementing predictive models into clinical settings for point-of-care risk stratification are still evolving. Here, we conducted a systematic review of articles describing predictive models integrated into EHR systems and implemented in clinical practice. We conducted an exhaustive database search and extracted data encompassing multiple facets of implementation. We assessed study quality and level of evidence. We obtained an initial 3393 articles for screening, from which a final set of 44 articles was included for data extraction and analysis. The most common clinical domains of implemented predictive models were related to thrombotic disorders/anticoagulation (25%) and sepsis (16%). The majority of studies were conducted in inpatient academic settings. Implementation challenges included alert fatigue, lack of training, and increased work burden on the care team. Of 32 studies that reported effects on clinical outcomes, 22 (69%) demonstrated improvement after model implementation. Overall, EHR-based predictive models offer promising results for improving clinical outcomes, although several gaps in the literature remain, and most study designs were observational. Future studies using randomized controlled trials may help improve the generalizability of findings.


2020 ◽  
pp. 193229682096661
Author(s):  
Kristen Kulasa ◽  
Brittany Serences ◽  
Michael Nies ◽  
Robert El-Kareh ◽  
Kirk Kurashige ◽  
...  

Background: Computerized insulin infusion protocols have demonstrated higher staff satisfaction, better compliance with protocols, and increased time with glucose in range compared to paper protocols. At University of California San Diego Health (UCSDH), we implemented an insulin infusion computer calculator (IICC) and transitioned it from a web-based platform directly into the electronic medication administration record (eMAR) of our primary electronic health record (EHR). Methods: This is a retrospective analysis of 6306 adult patients at UCSDH receiving intravenous (IV) insulin infusion from March 7, 2013 to May 30, 2019. We created three periods of the study—(1) the pre-eMAR integration period; (2) the eMAR integration period; and (3) the post-eMAR integration period—and looked at the percentage of readings within goal range (90-150 mg/dL for intensive care unit [ICU], 90-180 mg/dL for non-ICU) in patients with and without hyperglycemic emergencies. As our safety endpoints, we elected to look at incidence of blood glucose (BG) readings <70 mg/dL, <54 mg/dL, and <40 mg/dL. Results: Pre-eMAR 69.8% of readings were in the 90-150 mg/dL range compared to 70.2% post-eMAR ( P = .03) and 82.7% of readings were in the 90-180 mg/dL range pre-eMAR versus 82.9% ( P = .09) post-eMAR in patients without hyperglycemic emergencies. Rates of hypoglycemia with BG <70 mg/dL were 0.43%, <54 mg/dL were 0.07%, and <40 mg/dL were 0.01% of readings pre- and post-eMAR. Conclusions: At UCSDH, our IICC has shown to be safe and effective in a wide variety of clinical situations and we were able to successfully transition it from a web-based platform directly into the eMAR of our primary EHR.


2021 ◽  
Vol 39 ◽  
pp. 101075
Author(s):  
Ami R. Buikema ◽  
Paul Buzinec ◽  
Misti L. Paudel ◽  
Katherine Andrade ◽  
Jonathan C. Johnson ◽  
...  

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