Pa. De Clercq et al., GASTON: an architecture for the acquisition and execution of clinical guideline-application tasks, MED INF IN, 25(4), 2000, pp. 247-263
Recently, studies have shown the benefits of using clinical guidelines in t
he practice of medicine. There have been numerous efforts to develop clinic
al decision support systems that support guideline-based care in an automat
ed fashion, covering a wide range of clinical settings and tasks. Despite t
hese efforts, only a few systems progressed beyond the prototype stage and
the research laboratory. For guideline-based clinical decision support syst
ems to be successful, a balance must be made between intuitive bur imprecis
e representations usually encountered by most of today's systems and repres
entations that support a strong underlying clinical performance model. The
project described in this paper tries to achieve such a balance. It present
s the GASTON architecture that contains a set of reusable software componen
ts for the application of guidelines, including design-time components to f
acilitate the guideline authoring process based on guideline representation
models along with execution-time components for building decision support
systems that incorporate these guidelines. This architecture was used to de
velop several guideline representation models such as a rule-based represen
tation to model rule-based guidelines and guideline representation models t
hat address more complex tasks. Also, decision support systems that incorpo
rate these models were developed with the architecture. For the representat
ion and application of various classes of guidelines, rules were also viewe
d as instances of more complex tasks. By identifying similar characteristic
s of sets of rules, we developed several tasks such as a drug interaction a
nd drug contraindication task. Based on these models, we have developed and
validated guidelines and decision support systems for use in several appli
cation domains such as intensive care, family physicians and psychiatry. In
order to be able to represent more complex time-oriented plans, new guidel
ine representation models are being developed.