Poster for Artificial Intelligence in Medicine Conference 2009 - Verona

1. Implementing a Clinical Decision Support System for
Glucose Control for the Intensive Cardiac Care
R.J. Barendse, J.A. Lipton, M.J.B. van Ettinger, S.P. Nelwan, N.H.J.J. van der Putten
Erasmus MC, Department of Cardiology, Rotterdam, Netherlands
Background Glucose Screen
•High glucose levels in cardiac patients are associated with Eight-bed display with five
adverse outcome admitted patients shown.
•Glucose regulation in patients admitted to the Intensive Empty beds are grey.
Cardiac Care Unit (ICCU) is difficult to achieve
•Implementation of a Clinical Decision Support System
Pop-up displays new glucose
(CDSS) can improve compliance with protocols value and protocol advice.
Study Aim
Bars represent preceding
values; touching one displays
To develop a CDSS to improve the glucose regulation of the information.
patients admitted to the ICCU. To evaluate shortcomings in
the glucose protocol with the CDSS.
Insulin dose is displayed by the
black marks.
Methods
Ajax-driven screen that uses a web service to update
•Retrospective analysis of 918 patients with 15360 glucose automatically. It displays the last lab values received from the
measurements during 18 months HIS and the pump standings from the replicated PDMS
•Development and implementation of a web 2.0-based CDSS database. Advice is generated by the web service for each
screen for glucose management new value.
•Evaluation of prospectively collected data from 187 patients
with 3418 glucose measurements during 4 months Discussion
•Patients needed to have at least 2 glucose measurements to •Implementation of CDSS led to improved protocol compliance
be included •Protocol deviations occurred due to feeding, time of day, rate
Patient Data Management
System (PDMS) Web Interface Monthly Report of change
(Innovian Dräger)
•Further improvement of protocol is needed
•Enable protocol modifications by physicians
Glucose Screen
PDMS
Database
Replicated
Database
Nurse
Future work
SQL
CDSS •Expand our work with an updated protocol for glucose
•Rule engine
•Caching
management taking into account the investigation on protocol
Lab Database
•Web service (.NET) deviations
•Implement a 3rd party rule engine (Gaston) to enable
HL7 physicians to modify protocols
Hospital Information
•Expand our work to support other protocols
System (HIS) •Integrate with other systems such as the electronic patient
Dataflow of the CDSS. Web service collects the lab, pump record and PDMS
settings and patient information from the different data •Expand the CDSS to portable devices
sources. This data and generated rules are cached for •Expand to other departments in our hospital
performance.
Results Conclusion
Compliance with protocol regarding timing of glucose
•Implementation of a dedicated web based CDSS screen
measurements:
led to improved protocol compliance regarding two
•Increased from 41% to 55% on time, an increase of 13.2%
variables (time and dosage)
(95%CI 11.4% to 15.1% P<0.001)
•Future work is needed to expand the current program
Compliance with protocol regarding insulin dosage: with an enhanced protocol and a 3rd party protocol
•Increased from 48% to 58%, an increase of 9.8% (95% CI editor
7.9% to 11.6% P<0.001)