Difference between revisions of "From adverse drug event detection to prevention. A novel clinical decision support framework for medication safety"

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=== Objectives===
 
=== Objectives===
To establish a clinical decision support framework that can be utilized for detecting and preventing [[Adverse drug event |adverse drug events (ADEs)]] <ref name=" Koutkias 2015"> Koutkias, V. G., McNair, P., Kilintzis, V., Skovhus Andersen, K., Niès, J., Sarfati, J.-C., … Maglaveras, N. (2015). From adverse drug event detection to prevention. A novel clinical decision support framework for medication safety. Methods of Information in Medicine, 53(6), 482–492. http://doi.org/10.3414/ME14-01-0027.</ref>.  
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Although significant research has been conducted in the field, still medication safety is a crucial issue, while few research outcomes are mature enough to be considered for use in actual clinical settings. In this paper, we present a clinical decision support framework targeting medication safety with major focus on adverse drug event (ADE) prevention.
  
 
=== Methods ===
 
=== Methods ===

Revision as of 00:06, 5 November 2015

First Review

Background

This article intends to explore how a newly designed clinical decision support system (CDSS) framework could improve patient safety and the quality of care through preventing medical errors (adverse drug events (ADEs)) at the point of care.

Objectives

To establish a clinical decision support framework that can be utilized for detecting and preventing adverse drug events (ADEs) [1].

Methods

According to the authors, the novelty of framework is that they established or created approaches and methods to access and track historical problems related to ADEs. For example[1]:

  • Beginning with medical knowledge discovery and further accumulating reliable numbers of ADEs for each hospital or medical unit.
  • Describing their medical outcomes and possible causes.
  • Utilizing the data, information, and knowledge acquired from above to develop and implement clinical decision support system.

Features of the framework

  • The environment of implementation is so called the context of care.
  • Intuitive and straightforward integration in the health information technology (HIT) infrastructure, based on a “service-orientated architecture (SOA) and related standards” [1].


Results

The authors claimed the success of their project and framework due to: *Compatibility and interoperability of their framework with certain types of electronic health record (EHR) and computerized physician order entry (CPOE) systems. *Created an independent web prototype that can be used for clinical decision support. *Clinical validation by domain experts in the relevant field proved its usability and potential impact on the ADE prevention and quality improvement.


Conclusions

This article provides a proof-of-concept study that involved in a framework related to “delivering contextualized decision support services”, which can be utilized to monitor and prevent ADEs [1].

Comments

Medical errors are the major obstacles for promoting quality and safety of healthcare in the US. Of which medication errors or ADEs are the dominant portion that harms patients and compromises our goal for the meaningful use of EHRs and HIT. Therefore, development and deployment of framework, which can be integrated into CDSSs and utilized for effective detection and prevention of ADEs, represent significant interest of public welfare.


Second Review

Background

Errors related to medication seriously affect patient safety and the quality of healthcare. It has been widely argued that various types of such errors may be prevented by introducing Clinical Decision Support Systems (CDSSs) at the point of care.

Objectives

Although significant research has been conducted in the field, still medication safety is a crucial issue, while few research outcomes are mature enough to be considered for use in actual clinical settings. In this paper, we present a clinical decision support framework targeting medication safety with major focus on adverse drug event (ADE) prevention.

Methods

According to the authors, the novelty of framework is that they established or created approaches and methods to access and track historical problems related to ADEs. For example[1]:

  • Beginning with medical knowledge discovery and further accumulating reliable numbers of ADEs for each hospital or medical unit.
  • Describing their medical outcomes and possible causes.
  • Utilizing the data, information, and knowledge acquired from above to develop and implement clinical decision support system.

Features of the framework

  • The environment of implementation is so called the context of care.
  • Intuitive and straightforward integration in the health information technology (HIT) infrastructure, based on a “service-orientated architecture (SOA) and related standards” [1].


Results

The authors claimed the success of their project and framework due to: *Compatibility and interoperability of their framework with certain types of electronic health record (EHR) and computerized physician order entry (CPOE) systems. *Created an independent web prototype that can be used for clinical decision support. *Clinical validation by domain experts in the relevant field proved its usability and potential impact on the ADE prevention and quality improvement.


Conclusions

This article provides a proof-of-concept study that involved in a framework related to “delivering contextualized decision support services”, which can be utilized to monitor and prevent ADEs [1].

Comments

Medical errors are the major obstacles for promoting quality and safety of healthcare in the US. Of which medication errors or ADEs are the dominant portion that harms patients and compromises our goal for the meaningful use of EHRs and HIT. Therefore, development and deployment of framework, which can be integrated into CDSSs and utilized for effective detection and prevention of ADEs, represent significant interest of public welfare.


References

  1. 1.0 1.1 1.2 1.3 1.4 1.5 1.6 Koutkias, V. G., McNair, P., Kilintzis, V., Skovhus Andersen, K., Niès, J., Sarfati, J.-C., … Maglaveras, N. (2015). From adverse drug event detection to prevention. A novel clinical decision support framework for medication safety. Methods of Information in Medicine, 53(6), 482–492. http://doi.org/10.3414/ME14-01-0027.