View source for Understanding keys to successful implementation of electronic decision support in rural hospitals: analysis of a pilot study for antimicrobial prescribing



== Background ==
[[CDS|Clinical Decision Support]] (CDS) provides clinicians the opportunity to have [[evidence-based medicine]] information at the right moment to enhance medical decision making. Despite its potential in reducing medical errors, improve clinical outcomes and increase healthcare quality, CDSS are still not widely used by clinicians. Factors such as complexity, lack of adequate training and support as well as increase cost, are constantly cited by clinicians as barriers preventing CDSS implementation.

== Introduction ==
Antimicrobial agents constitute a major portion of hospital pharmacy expenditures, accounting for 20% to 50% of the total budget. Rural hospitals are specially in great disadvantage regarding CDSS implementations because of factors such as insufficient resources, limited clinical information systems as well as limited access to infectious disease physicians providing advice or assistance. Therefore, internet-based decision support tools offer to clinicians an option to provide adequate antimicrobial prescribing advice to those individuals in rural communities lacking access to other complex decision support systems.<ref name="Stevenson et al">Understanding Keys to Successful Implementation of Electronic Decision Support in Rural Hospitals: Analysis of a Pilot Study for Antimicrobial Prescribing  http://ca3cx5qj7w.search.serialssolutions.com/OpenURL_local?sid=Entrez:PubMed&id=pmid:16280394</ref>

== Study design ==
Pretest/Post-test

== Methods ==
A therapeutic clinical decision support system for the management of infectious diseases called "Antibiotic Assistant" was used during this study. Antibiotic assistant provides patient-specific antimicrobial recommendations based on factors such as co-morbid conditions, recommendations based on demographics characteristics, vitals signs and results of microbiology studies. Five rural hospitals from southwest Idaho were selected; selection was based on various factors such as involvement in a local rural health network as well as geographic proximity to the research team. Participants accessed an internet based platform during the study; this platform was developed and supported by the Centers for Medicare & Medicaid Services. Each prescribing clinician at the different hospitals was asked to introduce patients' data into the Internet-based decision support tool (antibiotic assistant) and to implement the recommendations when making therapeutic and dosing decisions. An antimicrobial management team (AMT) consisting of a nurse, pharmacist and infection control staff was formed in each hospital to prevent the under-utilization the decision support tool as well as to ensure that a clinician was aware of the CDSS recommendations during the first 24 hours of a patient's hospital admission.

== Results ==
First, physicians were reluctant to use the internet-based decision support tool because of perceived length of time required for log in and overall system run time. It was also reported that computers were not constantly located in patient care areas. Despite the formation of the Antimicrobial management teams to obtain CDSS recommendations in a timely fashion and provide that information to clinicians, transfer of information failed to occur in 3 of the participating hospitals. In another participating hospital, clinicians decided not to follow the CDSS recommendations most of the times; this was attributed to the mechanism of information communication. In the first hospital (A), clinicians were notified of recommendations in 32% of the cases in which the prescribed drugs differed from those recommended; it was noticed that antimicrobial orders were modified in 50% of those cases. In contrast, physicians in the second hospital (B) were notified of the recommendations by the AMT in 71% of the cases; However, they followed the recommendations in only 24%. It was noticed that the local hospital environment and community discouraged that member of the AMT (Non-physicians) questioned clinicians' decisions. 

== Conclusion ==
Cultural factors represented a barrier for the implementation of electronic decision support tools. Although cultural factors have recently surged as possible barriers for the uptake of electronic decision support tools, this is not the first study to show that we may be overlooking cultural factors when developing and implementing ITS. 

== References ==
<references/> 

[[Category:  Reviews]]
[[Category: Technologies]]
[[Category: CDSS]]
[[Category: HI5313-2015-FALL]]
[[Category: Evidence Based Medicine (EBM)]]