Difference between revisions of "From adverse drug event detection to prevention. A novel clinical decision support framework for medication safety"
Line 31: | Line 31: | ||
==Second Review== | ==Second Review== | ||
+ | === Background === | ||
+ | This article intends to explore how a newly designed [[Clinical decision support systems | clinical decision support system (CDSS)]] framework could improve patient safety and the quality of care through preventing medical errors ([[Adverse drug event |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 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>. | ||
+ | |||
+ | === 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<ref name=" Koutkias 2015"></ref>: | ||
+ | *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 | health information technology (HIT)]] infrastructure, based on a “service-orientated architecture (SOA) and related standards” <ref name=" Koutkias 2015"></ref>. | ||
+ | |||
+ | |||
+ | === Results === | ||
+ | The authors claimed the success of their project and framework due to: | ||
+ | *Compatibility and interoperability of their framework with certain types of [[EMR | electronic health record (EHR)]] and [[Computerized physician order entry | 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 <ref name=" Koutkias 2015"></ref>. | ||
+ | === 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=== | ===References=== |
Revision as of 00:04, 5 November 2015
Contents
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
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.
References
- ↑ 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 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.