Declarative and Procedural Approaches for Modelling Clinical Guidelines: Addressing Flexibility Issues

Mulyar, Nataliya; Pesic, M.; Aalst, Wil M. P. van der; Peleg, Mor

doi:10.1007/978-3-540-78238-4_35

Cited by 39 publications

(27 citation statements)

References 9 publications

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“…(Mulyar, Pesic, van der Aalst, & Peleg, 2007) has also shown that this language enables the representation of typical clinical guidelines, which are part of many loosely framed KiPs in healthcare. Declare is based on Linear…”

Section: Declare As a Foundationmentioning

confidence: 99%

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Mertens

Gailly

Poels

2017

Expert Systems with Applications

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Abstract. Modeling loosely framed and knowledge-intensive business processes with the currently available process modeling languages is very challenging. Some lack the flexibility to model this type of processes, while others are missing one or more perspectives needed to add the necessary level of detail to the models. In this paper we have composed a list of requirements that a modeling language should fulfil in order to adequately support the modeling of this type of processes. Based on these requirements, a metamodel for a new modeling language was developed that satisfies them all. The new language, called DeciClare, incorporates parts of several existing modeling languages, integrating them with new solutions to requirements thathad not yet been met. Deciclare is a declarative modeling language at its core, and therefore, can inherently deal with the flexibility required to model loosely framed processes. The complementary resource and data perspectives add the capability to reason about, respectively, resources and data values. The latter makes it possible to encapsulate the knowledge that governs the process flow by offering support for decision modeling. The abstract syntax of DeciClare has been implemented in the form of an Ecore model. Based on this implementation, the language-domain appropriateness of the language was validated by domain experts using the arm fracture case as application scenario.

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Section: Declare As a Foundationmentioning

confidence: 99%

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Mertens

Gailly

Poels

2017

Expert Systems with Applications

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“…We are not aware of any other approach for generating enactment plans from declarative specifications, however, there exist some further proposals which could be extended in such direction [21,20]. Similar to our work, [21] presents a declarative language based on ConDec (i.e., CIGDec) for the modelling and enactment of CIGs. From CIGDec specifications an automaton representing all feasible traces can be generated.…”

Section: Related Workmentioning

confidence: 76%

“…Traditional languages for modelling clinical computerinterpretable guidelines (CIGs) are of imperative nature [23,30], which usually results in complex process models for which all possible treatment scenarios need to be prespecified. Moreover, imperative languages usually present limited capabilities to provide flexibility for modelling and executing clinical guidelines [22,21,26]. This constitutes a barrier for applying process management to healthcare since the state of patients usually cannot be predicted, and hence the exactly required treatment (or sequence of diagnostic and therapeutic procedures) is not known a-priori.…”

Section: Application Examplementioning

confidence: 99%

“…This constitutes a barrier for applying process management to healthcare since the state of patients usually cannot be predicted, and hence the exactly required treatment (or sequence of diagnostic and therapeutic procedures) is not known a-priori. To increase flexibility and to reduce complexity of clinical process models, declarative CIG models [22,21] have been increasingly used to better fit with the nature of process-aware clinical IS and the requirements of the involved stakeholders [20].…”

Section: Application Examplementioning

confidence: 99%

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Optimized Time Management for Declarative Workflows

Barba

Lanz

Weber

et al. 2012

Enterprise, Business-Process and Information Systems Modeling

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Abstract. Declarative process models are increasingly used since they fit better with the nature of flexible process-aware information systems and the requirements of the stakeholders involved. When managing business processes, in addition, support for representing time and reasoning about it becomes crucial. Given a declarative process model, users may choose among different ways to execute it, i.e., there exist numerous possible enactment plans, each one presenting specific values for the given objective functions (e.g., overall completion time). This paper suggests a method for generating optimized enactment plans (e.g., plans minimizing overall completion time) from declarative process models with explicit temporal constraints. The latter covers a number of well-known workflow time patterns. The generated plans can be used for different purposes like providing personal schedules to users, facilitating early detection of critical situations, or predicting execution times for process activities. The proposed approach is applied to a range of test models of varying complexity. Although the optimization of process execution is a highly constrained problem, results indicate that our approach produces a satisfactory number of suitable solutions, i.e., solutions optimal in many cases.

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“…In fact, the current investigation focuses only on before/after temporal relations among tasks, but our final objective is the extraction of complex CIG fragments encompassing also gateways and more elaborated constraints on the process control-flow. Since the nature of the extracted constraints is declarative, we will not only focus on "procedural" specification languages (such as Asbru, Glare, BPMN), but we will also consider, at least as an intermediate format, constraint-based languages such as CigDec [15].…”

Section: Conclusion and Further Workmentioning

confidence: 99%

Process Fragment Recognition in Clinical Documents

Thorne

Cardillo

Eccher

et al. 2013

AI*IA 2013: Advances in Artificial Intelligence

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Abstract. We describe a first experiment on automated activity and relation identification, and more in general, on the automated identification and extraction of computer-interpretable guideline fragments from clinical documents. We rely on clinical entity and relation (activities, actors, artifacts and their relations) recognition techniques and use MetaMap and the UMLS Metathesaurus to provide lexical information. In particular, we study the impact of clinical document syntax and semantics on the precision of activity and temporal relation recognition.

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Declarative and Procedural Approaches for Modelling Clinical Guidelines: Addressing Flexibility Issues

Cited by 39 publications

References 9 publications

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Optimized Time Management for Declarative Workflows

Process Fragment Recognition in Clinical Documents

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