CONFlexFlow: Integrating Flexible clinical pathways into clinical decision support systems using context and rules

Abstract

We propose CONFlexFlow (Clinical cONtext based Flexible workFlow) as a novel approach for integrating clinical pathways into Clinical Decision Support Systems (CDSS). It recognizes that clinical pathways involve frequent deviations and require considerable flexibility. Thus, integration of flexible pathways is critical for the success of CDSS. Further, it is based on a better understanding of clinical context through ontologies, and bringing them to bear in deciding the right rules for a certain activity. We also describe an approach for dynamically realizing context dependent medical activities in a clinical pathway based on the needs of a specific case. To illustrate the feasibility of our approach, we propose an implementation framework and present a proof of concept prototype using multiple open source tools. The role of semantic web technologies in realizing flexible clinical pathways and integrating them into CDSS is highlighted. Preliminary results from our initial implementation are discussed.

Introduction

Workflows play an important role in clinical environments by delineating the steps through which the treatment of a patient progresses. The temporal order and correct coordination of the various steps are clearly important. The workflows in these environments are called clinical pathways. These pathways generally follow well-established standards or clinical guidelines. However, they differ from other workflows found in business and production environments because clinical processes involve frequent deviations, and hence there is a need for considerable flexibility. Typically, a medical facility develops clinical pathways from clinical guidelines on the basis of its local resources and settings. Moreover, the pathway is further customized into a treatment scheme to suit an individual patient's needs [3].

Clinical workflows are highly dynamic, context sensitive, event driven, and knowledge intensive. In this respect, they are quite unique. In general, a patient interacts with a Primary Care Physician's (PCP) office, a pharmacy, labs, and one or more specialists, etc. In this setting, it is important to maintain coordination and flow of information among these various entities to ensure an optimal outcome. The need for new modeling techniques for designing such flexible workflows is motivated by several considerations. First, although many research efforts are geared towards establishing international healthcare standards (e.g., HL7 [22]) and a representation for sharable guidelines (e.g., GLIF [36]) for clinical practice, formal models of executable and flexible clinical workflows are very few (e.g., [13], [55]). The execution of a clinical workflow is highly dependent on the existing body of medical knowledge, available resources, and specific case data. For example, doctors with different skill levels and fields of expertise may offer differing treatments to the same patient. A sudden rise in a patient's blood pressure may require an additional test and alter her treatment in the subsequent pathway. Thus, different pathways can arise based on case specifics and the proclivities of attending doctors, and it is important to formally model these scenarios. Second, since medical staff handles a lot of cases each day, they are prone to making mistakes in prescribing medications, performing procedures, and even making diagnoses [8], [29], [51]. Hence, Clinical Decision Support Systems (CDSS) and Computer Interpretable Guidelines (CIGs) [49] can assist care professionals in reducing the likelihood of errors and improving care quality.

Our goal is to show how flexible clinical pathways can be designed taking into account medical knowledge in the form of rules, and also detailed contextual information, for a medical workflow involving multiple participants to improve care quality. We propose a methodology for designing formal workflow models that capture medical knowledge and context in a common framework, and yet allow flexibility. Since a clinical workflow should naturally be aligned with clinical guidelines, it is necessary to ensure that it is formal and correct so that integrating decision support into this workflow can be helpful. The methodology is based on a formal rule and context taxonomy using ontologies. The rule taxonomy organizes the rules into a hierarchy while context encompasses aspects of patients, providers, resources, and environment. We will focus on how context is captured, described and summarized, and how rules are developed. A proof of concept prototype is built and preliminary results are given to show the feasibility of our approach. In this paper, the terms pathway and workflow are used interchangeably.

The organization of this paper is as follows. Section 2 provides background and related work. Then we introduce a meta-model for our CONFlexFlow system and present the architecture for system implementation in Section 3. Next, Section 4 presents an ontology-based context model and discusses rule-based medical reasoning. Based on this knowledge framework, we present our approach for designing flexible clinical workflows using BPMN 2.0 ad hoc subprocesses and describe a preliminary implementation in Section 5. Later, Section 6 gives a brief discussion and plans for future work, followed by a conclusion in Section 7.