Evidence map›Paper›PMID 20082700›Full record

ArticleBMC medical informatics and decision making2010

Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines.

Femke Ongenae, Femke De Backere, Kristof Steurbaut, Kirsten Colpaert, Wannes Kerckhove, Johan Decruyenaere, Filip De Turck

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
7.3field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Pseudocode Generation from Clinical Protocol Flowchart using Large Vision-Language Models.Proceedings. IEEE International Conference on Healthcare Informatics · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Executing medical logic modules expressed in ArdenML using Drools.Journal of the American Medical Informatics Association : JAMIA
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Femke OngenaeDepartment of Information Technology (INTEC), Ghent University - IBBT, Gaston Crommenlaan 8, Bus 201, 9050 Ghent, Belgium. Femke.Ongenae@intec.ugent.be
Femke De Backere
Kristof Steurbaut
Kirsten Colpaert
Wannes Kerckhove
Johan Decruyenaere
Filip De Turck
Ghent University · BEGhent University Hospital · BEiMinds · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputerized ICUs rely on software services to convey the medical condition of their patients as well as assisting the staff in taking treatment decisions. Such services are useful for following clinical guidelines quickly and accurately. However, the development of services is often time-consuming and error-prone. Consequently, many care-related activities are still conducted based on manually constructed guidelines. These are often ambiguous, which leads to unnecessary variations in treatments and costs.The goal of this paper is to present a semi-automatic verification and translation framework capable of turning manually constructed diagrams into ready-to-use programs. This framework combines the strengths of the manual and service-oriented approaches while decreasing their disadvantages. The aim is to close the gap in communication between the IT and the medical domain. This leads to a less time-consuming and error-prone development phase and a shorter clinical evaluation phase.

methodsA framework is proposed that semi-automatically translates a clinical guideline, expressed as an XML-based flow chart, into a Drools Rule Flow by employing semantic technologies such as ontologies and SWRL. An overview of the architecture is given and all the technology choices are thoroughly motivated. Finally, it is shown how this framework can be integrated into a service-oriented architecture (SOA).

resultsThe applicability of the Drools Rule language to express clinical guidelines is evaluated by translating an example guideline, namely the sedation protocol used for the anaesthetization of patients, to a Drools Rule Flow and executing and deploying this Rule-based application as a part of a SOA. The results show that the performance of Drools is comparable to other technologies such as Web Services and increases with the number of decision nodes present in the Rule Flow. Most delays are introduced by loading the Rule Flows.

conclusionsThe framework is an effective solution for computerizing clinical guidelines as it allows for quick development, evaluation and human-readable visualization of the Rules and has a good performance. By monitoring the parameters of the patient to automatically detect exceptional situations and problems and by notifying the medical staff of tasks that need to be performed, the computerized sedation guideline improves the execution of the guideline.

Indexed as

Decision Support Systems, ClinicalIntensive Care UnitsPractice Guidelines as TopicSoftwareAlgorithmsArtificial IntelligenceHumansHypnotics and SedativesMedical ErrorsSemanticsHypnotics and Sedatives

Identifiers

PMID20082700
PMCPMC2823596
OpenAlexW1976285870

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.