Event-Triggered Decision Support and Automatic Control Systems for Type 1 Diabetes

“Cyber crime” has been used to describe a wide range of offences, including offences against computer data and systems (such as “Hacking”), computer related forgery and fraud (such as “phishing”), content offences (such as disseminating child pornography), and copyright offences (such as the dissemination of pirated content). The word “Cyber Crime” has been derived from the words “Cybernetic” which means the science of communication and automatic control systems in both machines and living things.

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Automatic Control Systems for Construction Machinery

10.22260/isarc1988/0085 ◽

1988 ◽

Cited By ~ 1

Author(s):

Makoto Kakuzen ◽

Hirokazu Araya ◽

Nobuo Kimura ◽

Isao Sawamura

Keyword(s):

Automatic Control ◽

Control Systems ◽

Construction Machinery ◽

Automatic Control Systems

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Clinical decision support to improve management of diabetes and dysglycemia in the hospital: a path to optimizing practice and outcomes

BMJ Open Diabetes Research & Care ◽

10.1136/bmjdrc-2020-001557 ◽

2021 ◽

Vol 9 (1) ◽

pp. e001557

Author(s):

Ariana Pichardo-Lowden ◽

Guillermo Umpierrez ◽

Erik B Lehman ◽

Matthew D Bolton ◽

Christopher J DeFlitch ◽

...

Keyword(s):

Type 2 Diabetes ◽

Type 1 Diabetes ◽

Decision Support ◽

Clinical Decision Support ◽

Clinical Decision ◽

Stress Hyperglycemia ◽

Inappropriate Use ◽

Academic Center

IntroductionInnovative 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.Research design and methodsThe 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.ResultsWhen 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.ConclusionEMR CDS was successful in reducing hyperglycemic events among hospitalized patients with dysglycemia and diabetes, and inappropriate insulin use in patients with type 1 diabetes.

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