View source for From adverse drug event detection to prevention. A novel clinical decision support framework for medication safety

==First 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 [[A Pragmatic Approach to Implementing Best Practices for Clinical Decision Support Systems in Computerized Provider Order Entry Systems|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-oriented architecture|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.  


==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 ===
The novelty of the framework lies in its design that approaches the problem holistically, i.e., starting from knowledge discovery to provide reliable numbers about ADEs per hospital or medical unit to describe their consequences and probable causes, and next employing the acquired knowledge for decision support services development and deployment. Major design features of the framework’s services are: a) their adaptation to the context of care (i.e. patient characteristics, place of care, and significance of ADEs), and b) their straightforward integration in the healthcare information technologies (IT) infrastructure thanks to the adoption of a service-oriented architecture (SOA) and relevant standards.

=== Results ===
Our results illustrate the successful interoperability of the framework with two commercially available IT products, i.e., a Computerized Physician Order Entry (CPOE) and an Electronic Health Record (EHR) system, respectively, along with a Web prototype that is independent of existing healthcare IT products. The conducted clinical validation with domain experts and test cases illustrates that the impact of the framework is expected to be major, with respect to patient safety, and towards introducing the CDSS functionality in practical use.

=== Conclusions ===
This study illustrates an important potential for the applicability of the presented framework in delivering con- textualized decision support services at the point of care and for making a substantial contribution towards ADE prevention. Nonetheless, further research is required in order to quantitatively and thoroughly assess its impact in medication safety.

=== Comments ===
A major obstacle to promote quality and safety in the US healthcare is medical errors. In particular, medication errors or ADEs predominantly harm patients and compromises the goal of meaningful use of EHRs and HIT. Therefore, integration of a framework into CDSS that can be utilized to effectively detect and prevent ADEs promotes public welfare or patient safety.

==Related Articles==
*[[Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials.]]


==References==
<references/>

[[Category: Reviews]] 
[[Category: Patient Safety]]
[[Category: EMR]]
[[Category: CPOE]]
[[Category: CDSS]]
[[Category: Adverse drug event]]
[[Category: Methodologies and Frameworks]]
[[Category: HI5313-2015-FALL]]