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Related Concept Videos

Insulin Formulations: Types and Delivery01:27

Insulin Formulations: Types and Delivery

Insulin preparations are categorized by their duration of action into short-acting and long-acting types. Two strategies are used to modify insulin's absorption and pharmacokinetic profile: slowing the absorption post-subcutaneous injection, or altering human insulin's amino acid sequence or protein structure. These changes retain the insulin's ability to bind to the insulin receptor, but alter its behavior in solution or after injection.
Short-acting insulins are divided into rapid-acting...
Insulin: Dosing Regimen and Adverse Effects01:16

Insulin: Dosing Regimen and Adverse Effects

Insulin-replacement therapy usually includes both long-acting insulin (basal) and short-acting insulin (to cater to postprandial needs). In a diverse group of type 1 diabetes patients, the average daily insulin dose is typically 0.5-0.7 units/kg body weight. However, obese patients and pubertal adolescents may need more due to insulin resistance.
The basal dose constitutes about 40%-50% of the total daily dose, with the rest as premeal insulin. The mealtime insulin dose should mirror...
SBAR II: Application of SBAR01:14

SBAR II: Application of SBAR

SBAR is an effective communication tool used by healthcare professionals to communicate patient information accurately. SBAR stands for Situation, Background, Assessment, and Recommendation. For a better understanding, an example is given below.
SBAR Report from a Nurse to a Health Care Provider
S: "Hello, Dr. Smith. This is Jane, RN, from the Med Surg unit. I am calling to tell you about Ms. White in Room 210, who is experiencing increased pain and redness at her incision site. Her recent...
Dosage Regimen: Individualization01:24

Dosage Regimen: Individualization

Individualization in dosing regimens is the customization of medication doses for individual patients. Its necessity arises from the goal of maximizing therapeutic benefits while minimizing risks. This approach is pivotal because human responses to drugs can vary widely; what is effective for one person may be inadequate or excessive for another. Interpatient (intersubject) variability refers to differences in drug responses between individuals, while intrapatient (intrasubject) variability...
Guidelines and Strategies for Safe Computer Charting01:18

Guidelines and Strategies for Safe Computer Charting

The guidelines and strategies provided by the American Nurses Association (ANA) and the Canadian Nurses Association (CNA) offer essential principles for ensuring safe and secure computer charting systems in healthcare settings. Let's break down each recommendation:
Maintain Confidentiality and Security:
Insulin: Biosynthesis, Chemistry, and Preparation01:25

Insulin: Biosynthesis, Chemistry, and Preparation

The endoplasmic reticulum (ER) of pancreatic β-cells synthesizes preproinsulin, which consists of a signal peptide, A and B chains, and a C-peptide. Preproinsulin is then cleaved and folded into proinsulin, which translocates to the Golgi apparatus for sorting and packaging into secretory granules. In these granules, enzymatic clipping generates insulin and C-peptide.
Damage or functional impairment of β-cells inhibits insulin production, leading to diabetes. Diabetes treatment primarily uses...

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Related Experiment Video

Updated: Jul 5, 2026

Improving IV Insulin Administration in a Community Hospital
12:08

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

Reasons for declining computerized insulin protocol recommendations: application of a framework.

K Sward1, J Orme, D Sorenson

  • 1College of Nursing, University of Utah, 10 South 2000 East, Salt Lake City, UT 84112, USA. kathy.sward@nurs.utah.edu

Journal of Biomedical Informatics
|May 24, 2008
PubMed
Summary
This summary is machine-generated.

Analyzing reasons for declining clinical decision support (CDS) recommendations in intensive care units (ICUs) helps refine protocols and improve software usability. Understanding noncompliance is key to enhancing healthcare technology adoption.

Related Experiment Videos

Last Updated: Jul 5, 2026

Improving IV Insulin Administration in a Community Hospital
12:08

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

Area of Science:

  • Health Informatics
  • Medical Software Implementation
  • Clinical Protocol Optimization

Background:

  • Clinical decision support (CDS) systems provide treatment recommendations for intensive care unit (ICU) providers.
  • Open-loop CDS systems allow clinicians to decline protocol recommendations, offering valuable feedback for system improvement.
  • Understanding reasons for noncompliance is crucial for iterative validation and refinement of clinical protocols.

Purpose of the Study:

  • To identify and categorize reasons why ICU nurses declined recommendations from an insulin-titration protocol.
  • To apply an established IT implementation framework to analyze clinician feedback on CDS software.
  • To uncover potential protocol improvement targets and barriers to software use.

Main Methods:

  • Utilized an IT implementation framework (Kukafka et al., 2003) to categorize reasons for declining protocol recommendations.
  • Collected data through two methods: analysis of actual software use (declined recommendations) and a nurse questionnaire.
  • Applied framework to actual software use data and nurse questionnaire responses for comprehensive analysis.

Main Results:

  • Noncompliance patterns with the insulin-titration protocol provided insights into areas for improvement.
  • Analysis revealed specific barriers impeding the effective use of the CDS software.
  • The chosen framework facilitated the analysis and interpretation of clinician feedback, despite data source limitations.

Conclusions:

  • Even with overall good acceptance, analyzing noncompliance with CDS protocols is vital for identifying improvement opportunities.
  • Understanding clinician reasons for declining recommendations helps reduce barriers and enhance software adoption in critical care settings.
  • The study highlights the utility of IT implementation frameworks in evaluating and refining clinical decision support systems.