Abstract

BackgroundClinical practice guidelines (CPGs) include recommendations describing appropriate care for the management of patients with a specific clinical condition. A number of representation languages have been developed to support executable CPGs, with associated authoring/editing tools. Even with tool assistance, authoring of CPG models is a labor-intensive task. We aim at facilitating the early stages of CPG modeling task. In this context, we propose to support the authoring of CPG models based on a set of suitable procedural patterns described in an implementation-independent notation that can be then semi-automatically transformed into one of the alternative executable CPG languages.MethodsWe have started with the workflow control patterns which have been identified in the fields of workflow systems and business process management. We have analyzed the suitability of these patterns by means of a qualitative analysis of CPG texts. Following our analysis we have implemented a selection of workflow patterns in the Asbru and PROforma CPG languages. As implementation-independent notation for the description of patterns we have chosen BPMN 2.0. Finally, we have developed XSLT transformations to convert the BPMN 2.0 version of the patterns into the Asbru and PROforma languages.ResultsWe showed that although a significant number of workflow control patterns are suitable to describe CPG procedural knowledge, not all of them are applicable in the context of CPGs due to their focus on single-patient care. Moreover, CPGs may require additional patterns not included in the set of workflow control patterns. We also showed that nearly all the CPG-suitable patterns can be conveniently implemented in the Asbru and PROforma languages. Finally, we demonstrated that individual patterns can be semi-automatically transformed from a process specification in BPMN 2.0 to executable implementations in these languages.ConclusionsWe propose a pattern and transformation-based approach for the development of CPG models. Such an approach can form the basis of a valid framework for the authoring of CPG models. The identification of adequate patterns and the implementation of transformations to convert patterns from a process specification into different executable implementations are the first necessary steps for our approach.

Highlights

  • Clinical practice guidelines (CPGs) include recommendations describing appropriate care for the management of patients with a specific clinical condition

  • The research questions that we investigate in this paper are the following: (1) are workflow control patterns suitable for the description of CPG procedural knowledge?, (2) can workflow patterns be adequately implemented in different executable CPG representation languages?, and (3) can the implementation of workflow patterns in alternative executable CPG languages be supported by means of semi-automated transformations?

  • The labels in the second column should be read as follows: “no” indicates that there are strong reasons to dismiss the applicability of the pattern in the CPG domain; “yes” indicates that examples of the pattern have been found in the sample CPGs; otherwise, “unknown” means that no examples were found in the CPGs

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Summary

Introduction

Clinical practice guidelines (CPGs) include recommendations describing appropriate care for the management of patients with a specific clinical condition. A number of representation languages have been developed to support executable CPGs, with associated authoring/editing tools. Clinical practice guidelines (CPGs) are defined as “systematically developed statements to assist practitioner and patient decisions about appropriate health care for specific circumstances” [1]. With this aim, CPGs include recommendations describing appropriate care (and, inappropriate care) for the management of patients with a specific clinical condition, such as diabetes or chronic heart failure. Even with tool assistance, authoring of CPG models remains a complex and labor-intensive task that requires both clinical and technical skills

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