Related Experiment Video

Updated: Jan 20, 2026

Meta-Analysis of the Effectiveness and Safety of Shugan Jieyu Capsules for the Treatment of Insomnia
04:34

Meta-Analysis of the Effectiveness and Safety of Shugan Jieyu Capsules for the Treatment of Insomnia

Published on: February 17, 2023

1.6K

Effects of Computerized Guideline-Oriented Clinical Decision Support System on Antithrombotic Therapy in Patients

Ryota Sakurai1, Kazuhiko Ohe2

  • 1School of Medicine, International University of Health and Welfare, Chiba, Japan.

Studies in Health Technology and Informatics
|August 24, 2019
PubMed

Insights

Computerized guideline-oriented clinical decision support systems (CDSS) improve appropriate antithrombotic therapy in atrial fibrillation patients. While thromboembolic events were similar, major bleeding risk showed a trend toward reduction with CDSS use.

Area of Science:

  • Cardiology
  • Medical Informatics
  • Clinical Pharmacy

Background:

  • Atrial fibrillation necessitates appropriate antithrombotic therapy to prevent thromboembolic events.
  • Adherence to clinical guidelines for antithrombotic therapy in atrial fibrillation can be challenging.
  • Clinical decision support systems (CDSS) offer a potential solution to enhance guideline adherence.

Purpose of the Study:

  • To systematically review and meta-analyze the impact of computerized guideline-oriented CDSS on antithrombotic therapy in atrial fibrillation patients.
  • To evaluate the effectiveness of CDSS in promoting guideline-adherent antithrombotic treatment.
  • To assess the influence of CDSS on clinical outcomes, including thromboembolic events and bleeding.

Main Methods:

  • Systematic review and meta-analysis of studies identified through PubMed, Cochrane Library, and Web of Science.
  • Inclusion of four relevant studies comparing CDSS intervention with control groups.
  • Statistical analysis using risk ratios (RR) and confidence intervals (CI) to compare outcomes.

Main Results:

  • A significantly higher proportion of appropriate antithrombotic therapy was observed in the CDSS group (RR: 1.03, 95% CI: 1.01 to 1.04, P = 0.004).
  • The incidence of thromboembolic events did not differ significantly between the CDSS and control groups (RR: 1.12, 95% CI: 0.88 to 1.42, P = 0.357).
  • A trend towards a lower incidence of major bleeding was noted in the CDSS group (RR: 0.79, 95% CI: 0.61 to 1.01, P = 0.063).

Conclusions:

  • Computerized guideline-oriented CDSS demonstrate effectiveness in improving appropriate antithrombotic therapy for atrial fibrillation patients.
  • CDSS may contribute to reducing major bleeding events, although further research is warranted.
  • Implementation of CDSS holds promise for optimizing anticoagulation management in atrial fibrillation.

Keywords:
Atrial FibrillationClinicalComputersDecision Support Systems

More Related Videos

Robotic Ablation of Atrial Fibrillation11:21

Robotic Ablation of Atrial Fibrillation

Published on: May 29, 2015

20.1K
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation08:10

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Published on: July 20, 2022

2.1K

Related Concept Videos

Amyloid Fibrils03:03

Amyloid Fibrils

Amyloid fibrils are aggregates of misfolded proteins.  Under most circumstances, misfolded proteins are either refolded by chaperone proteins or degraded by the proteasome. However, in the case of a mutation or a disease, these proteins can accumulate to form large clusters and often further assemble to form elongated fibers, called fibrils. 
Amyloid deposits were observed as early as 1639 in the liver and the spleen.   In 1854, Rudolph Virchow performed iodine staining,...
11.7K
Amyloid Fibrils03:03

Amyloid Fibrils

6.3K
Review and Preview01:10

Review and Preview

In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
8.3K
Review and Preview01:13

Review and Preview

Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
10.9K
Pharmacodynamics in Geriatric Patients: Effects of Age01:27

Pharmacodynamics in Geriatric Patients: Effects of Age

Age-related pharmacokinetic changes are extensively documented, but understanding age-related pharmacodynamic alterations is relatively limited. This knowledge gap can be partly attributed to the complexity of developing appropriate measures of drug responses compared to bioanalytical methods for determining drug concentrations.Most information regarding age-related differences in human pharmacodynamics originates from cross-sectional studies. However, these studies assume that observed mean...
191
Framing Effects03:26

Framing Effects

Information is everywhere and its presentation—such as how and when items are presented—can impact our perceptions and decisions surrounding the info. This broad concept umbrellas framing effects—influences that occur due to the way information is framed in its appearance, whether it’s purely the order or the specific wording of a message. Let’s take a look at numerous ways in which two versions of something can objectively say the same thing, yet we respond in...
7.9K