Abstract
The success of a decision support system based on clinical practice guidelines does not only depend on the quality of the decision model used to represent and execute guideline recommendations, but also on the design of interactions of the system with the end-user interface and the electronic patient record. This paper describes technical solutions adopted to add decision support functionalities to two existing information systems for stroke patients. Despite the specific medical application, the approach is quite general, relying on two main functionalities: a real-time decision support system based on workflow technology (careflow) and an off-line tool for non-compliance detection, called "Reasoning on Medical Action" (RoMA). The integration has been developed maintaining independence between data management and knowledge management, and minimizing changes to existing user's interfaces. The paper illustrates in particular the middleware layer created to allow communication between the evidence-based system and the electronic patient record.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 141-154 |
| Number of pages | 14 |
| Volume | 5943 LNAI |
| DOIs | |
| Publication status | Published - 2010 |
| Event | Workshop on Knowledge Representation for Health-Care: Data, Processes and Guidelines, KR4HC 2009. Held in Conjunction with the 12th Conference on Artificial Intelligence in Medicine, AIME 2009 - Verona, Italy Duration: Jul 19 2009 → Jul 19 2009 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 5943 LNAI |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | Workshop on Knowledge Representation for Health-Care: Data, Processes and Guidelines, KR4HC 2009. Held in Conjunction with the 12th Conference on Artificial Intelligence in Medicine, AIME 2009 |
|---|---|
| Country | Italy |
| City | Verona |
| Period | 7/19/09 → 7/19/09 |
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Keywords
- Clinical practice guidelines
- Electronic patient record
- Middleware
- Workflow management systems
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
Technical solutions for integrating clinical practice guidelines with electronic patient records. / Panzarasa, Silvia; Quaglini, Silvana; Cavallini, Anna; Micieli, Giuseppe; Marcheselli, Simona; Stefanelli, Mario.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5943 LNAI 2010. p. 141-154 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5943 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Technical solutions for integrating clinical practice guidelines with electronic patient records
AU - Panzarasa, Silvia
AU - Quaglini, Silvana
AU - Cavallini, Anna
AU - Micieli, Giuseppe
AU - Marcheselli, Simona
AU - Stefanelli, Mario
PY - 2010
Y1 - 2010
N2 - The success of a decision support system based on clinical practice guidelines does not only depend on the quality of the decision model used to represent and execute guideline recommendations, but also on the design of interactions of the system with the end-user interface and the electronic patient record. This paper describes technical solutions adopted to add decision support functionalities to two existing information systems for stroke patients. Despite the specific medical application, the approach is quite general, relying on two main functionalities: a real-time decision support system based on workflow technology (careflow) and an off-line tool for non-compliance detection, called "Reasoning on Medical Action" (RoMA). The integration has been developed maintaining independence between data management and knowledge management, and minimizing changes to existing user's interfaces. The paper illustrates in particular the middleware layer created to allow communication between the evidence-based system and the electronic patient record.
AB - The success of a decision support system based on clinical practice guidelines does not only depend on the quality of the decision model used to represent and execute guideline recommendations, but also on the design of interactions of the system with the end-user interface and the electronic patient record. This paper describes technical solutions adopted to add decision support functionalities to two existing information systems for stroke patients. Despite the specific medical application, the approach is quite general, relying on two main functionalities: a real-time decision support system based on workflow technology (careflow) and an off-line tool for non-compliance detection, called "Reasoning on Medical Action" (RoMA). The integration has been developed maintaining independence between data management and knowledge management, and minimizing changes to existing user's interfaces. The paper illustrates in particular the middleware layer created to allow communication between the evidence-based system and the electronic patient record.
KW - Clinical practice guidelines
KW - Electronic patient record
KW - Middleware
KW - Workflow management systems
UR - http://www.scopus.com/inward/record.url?scp=77951128704&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951128704&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-11808-1_12
DO - 10.1007/978-3-642-11808-1_12
M3 - Conference contribution
AN - SCOPUS:77951128704
SN - 3642118070
SN - 9783642118074
VL - 5943 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 141
EP - 154
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -