Visual Modeling Languages in Patient Pathways: Scoping Review

BACKGROUND

Patient pathways (PPs) are presented as a panacea solution to enhance health system functions. It is a complex concept that needs to be described and communicated well. Modeling plays a crucial role in promoting communication, fostering a shared understanding, and streamlining processes. Only a few existing systematic reviews have focused on modeling methods and standardized modeling languages. There remains a gap in consolidated knowledge regarding the use of diverse visual modeling languages.

OBJECTIVE

This scoping review aimed to compile visual modeling languages used to represent PPs, including the justifications and the context in which a modeling language was adopted, adapted, combined, or developed.

METHODS

After initial experimentation with the keywords used to describe the concepts of PPs and visual modeling languages, we developed a search strategy that was further refined and customized to the major databases identified as topically relevant. In addition, we consulted gray literature and conducted hand searches of the referenced articles. Two reviewers independently screened the articles in 2 stages using preset inclusion criteria, and a third reviewer voted on the discordance. Data charting was done using an iteratively developed form in the Covidence software. Descriptive and thematic summaries were presented following rounds of discussion to produce the final report.

RESULTS

Of 1838 articles retrieved after deduplication, 22 satisfied our inclusion criteria. Clinical pathway is the most used phrase to represent the PP concept, and most papers discussed the concept without providing their operational definition. We categorized the visual modeling languages into five categories: (1) general purpose-modeling language (GPML) adopted without major extension or modification, (2) GPML used with formal extension recommendations, (3) combination of 2 or more modeling languages, (4) a developed domain-specific modeling language (DSML), and (5) ontological modeling languages. The justifications for adopting, adapting, combining, and developing visual modeling languages varied accordingly and ranged from versatility, expressiveness, tool support, and extensibility of a language to domain needs, integration, and simplification.

CONCLUSIONS

Various visual modeling languages were used in PP modeling, each with varying levels of abstraction and granularity. The categorization we made could aid in a better understanding of the complex combination of PP and modeling languages. Standardized GPMLs were used with or without any modifications. The rationale to propose any modification to GPMLs evolved as more evidence was presented following requirement analyses to support domain constructs. DSMLs are infrequently used due to their resource-intensive development, often initiated at a project level. The justifications provided and the context where DSMLs were created are paramount. Future studies should assess the merits and demerits of using a visual modeling language to facilitate PP communications among stakeholders and use evaluation frameworks to identify, modify, or develop them, depending on the scope and goal of the modeling need.

Developing a Data-Driven Approach in Order to Improve the Safety and Quality of Patient Care

Objective: To improve the safety and quality of patient care in hospitals by shaping clinical pathways throughout the patient journey.

Study Setting: A risk model designed for healthcare organizations in the context of the challenges arising from comorbidity and other treatment-related complexities.

Study Design: The core of the model is the patient and his intra-hospital journey, which is analyzed using a data-driven approach. The structure of a predictive model to support organizational and clinical decision-making activities is explained. Data relating to each step of the intra-hospital journey (from hospital admission to discharge) are extracted from clinical records.

Principal Findings: The proposed approach is feasible and can be used effectively to improve safety and quality. It enables the evaluation of clinical risks at each step of the patient journey.

Conclusion: Based on data from real cases, the model can record and calculate, over time, variables and behaviors that affect the safety and quality of healthcare organizations. This provides a greater understanding of healthcare processes and their complexity which can, in turn, advance research relating to clinical pathways and improve strategies adopted by organizations.

Are emergency department clinical pathway interventions adequately described, and are they delivered as intended? A systematic review

Introduction

The accurate reproduction of clinical interventions and the evaluation of provider adherence in research publications improve the evaluation and implementation of research findings into clinical practice. We sought to examine the proportion of clinical pathway publications in an emergency department setting that adequately reported the following: (1) the exact reproduction of the clinical pathway that was implemented in the study, (2) the adherence to and correct execution of the clinical pathway intervention, and (3) the presence of a pre-implementation education phase.

Methods

We performed a descriptive systematic review of the literature from 2006 to 2015 using MEDLINE, EMBASE, CENTRAL, and CINAHL. All types of prospective trial designs were eligible. Validated clinical pathway criteria were used to identify relevant publications. Two reviewers independently collected data using a piloted data abstraction tool. Risk of bias was assessed using the Cochrane Effective Practice and Organization of Care Group Risk of Bias Tool and the Newcastle-Ottawa Scale.

Results

We identified 5947 publications, 44 of which met our inclusion criteria. The formal clinical pathway was fully reproduced in 27 (61%) publications, partially reproduced in 9 (21%), and not reproduced in 8 (18%). Only 14 (32%) studies reported whether at least one decision step was executed correctly. The presence of a pre-implementation education phase was reported in 33 (75%) studies.

Conclusion

The underreporting of intervention elements may present a barrier to both the evaluation and accurate replication of clinical pathway interventions. These finding may be useful for the elaboration of complex intervention reporting guidelines, improved reporting in future clinical pathway publications, and improved knowledge translation and exchange of clinical pathway interventions.