Modeling stroke rehabilitation processes using the Unified Modeling Language (UML)

APLUS: A Python library for usefulness simulations of machine learning models in healthcare

Despite the creation of thousands of machine learning (ML) models, the promise of improving patient care with ML remains largely unrealized. Adoption into clinical practice is lagging, in large part due to disconnects between how ML practitioners evaluate models and what is required for their successful integration into care delivery. Models are just one component of care delivery workflows whose constraints determine clinicians' abilities to act on models' outputs. However, methods to evaluate the usefulness of models in the context of their corresponding workflows are currently limited. To bridge this gap we developed APLUS, a reusable framework for quantitatively assessing via simulation the utility gained from integrating a model into a clinical workflow. We describe the APLUS simulation engine and workflow specification language, and apply it to evaluate a novel ML-based screening pathway for detecting peripheral artery disease at Stanford Health Care.

Using Unified Modeling Language to Analyze Business Processes in the Delivery of Child Health Services

Business Process Management (BPM) has been increasingly used in recent years in the healthcare domain to analyze, optimize, harmonize and compare clinical and healthcare processes. The main aim of this methodology is to model the interactions between medical and organizational activities needed to deliver health services, measure their complexity, variability and deviations to improve the quality of care and its efficiency. Among the different tools, languages and notations developed in the decades, UML (Unified Modeling Language) represents a widely adopted technique to model, analyze and compare business processes in healthcare. We adopted its diagrams in the MOCHA project to compare the different ways of organizing, coordinating and delivering child care across 30 EU/EEA countries both from an organization and control-flow perspectives. This paper provides an overview of the main components used to represent the business process using UML diagrams, also highlighting how we customized them to capture the specificity of the healthcare domain taking into account that processes are reconstructed on the basis of country experts' responses to questionnaires. The benefits of the application of this methodology are demonstrated by providing examples of comparing different aspects of child care.

Standardized languages and notations for graphical modelling of patient care processes: a systematic review

Purpose

The importance of working toward quality improvement in healthcare implies an increasing interest in analysing, understanding and optimizing process logic and sequences of activities embedded in healthcare processes. Their graphical representation promotes faster learning, higher retention and better compliance. The study identifies standardized graphical languages and notations applied to patient care processes and investigates their usefulness in the healthcare setting.

Data sources

Peer-reviewed literature up to 19 May 2016. Information complemented by a questionnaire sent to the authors of selected studies.

Study selection

Systematic review conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.

Data extraction

Five authors extracted results of selected studies.

Results of data synthesis

Ten articles met the inclusion criteria. One notation and language for healthcare process modelling were identified with an application to patient care processes: Business Process Model and Notation and Unified Modeling Language™. One of the authors of every selected study completed the questionnaire. Users' comprehensibility and facilitation of inter-professional analysis of processes have been recognized, in the filled in questionnaires, as major strengths for process modelling in healthcare.

Conclusion

Both the notation and the language could increase the clarity of presentation thanks to their visual properties, the capacity of easily managing macro and micro scenarios, the possibility of clearly and precisely representing the process logic. Both could increase guidelines/pathways applicability by representing complex scenarios through charts and algorithms hence contributing to reduce unjustified practice variations which negatively impact on quality of care and patient safety.

Construction of mammographic examination process ontology using bottom-up hierarchical task analysis

Describing complex mammography examination processes is important for improving the quality of mammograms. It is often difficult for experienced radiologic technologists to explain the process because their techniques depend on their experience and intuition. In our previous study, we analyzed the process using a new bottom-up hierarchical task analysis and identified key components of the process. Leveraging the results of the previous study, the purpose of this study was to construct a mammographic examination process ontology to formally describe the relationships between the process and image evaluation criteria to improve the quality of mammograms. First, we identified and created root classes: task, plan, and clinical image evaluation (CIE). Second, we described an "is-a" relation referring to the result of the previous study and the structure of the CIE. Third, the procedural steps in the ontology were described using the new properties: "isPerformedBefore," "isPerformedAfter," and "isPerformedAfterIfNecessary." Finally, the relationships between tasks and CIEs were described using the "isAffectedBy" property to represent the influence of the process on image quality. In total, there were 219 classes in the ontology. By introducing new properties related to the process flow, a sophisticated mammography examination process could be visualized. In relationships between tasks and CIEs, it became clear that the tasks affecting the evaluation criteria related to positioning were greater in number than those for image quality. We developed a mammographic examination process ontology that makes knowledge explicit for a comprehensive mammography process. Our research will support education and help promote knowledge sharing about mammography examination expertise.

A Design Methodology for Medical Processes

BACKGROUND

Healthcare processes, especially those belonging to the clinical domain, are acknowledged as complex and characterized by the dynamic nature of the diagnosis, the variability of the decisions made by experts driven by their experiences, the local constraints, the patient's needs, the uncertainty of the patient's response, and the indeterminacy of patient's compliance to treatment. Also, the multiple actors involved in patient's care need clear and transparent communication to ensure care coordination.

OBJECTIVES

In this paper, we propose a methodology to model healthcare processes in order to break out complexity and provide transparency.

METHODS

The model is grounded on a set of requirements that make the healthcare domain unique with respect to other knowledge domains. The modeling methodology is based on three main phases: the study of the environmental context, the conceptual modeling, and the logical modeling.

RESULTS

The proposed methodology was validated by applying it to the case study of the rehabilitation process of stroke patients in the specific setting of a specialized rehabilitation center. The resulting model was used to define the specifications of a software artifact for the digital administration and collection of assessment tests that was also implemented.

CONCLUSIONS

Despite being only an example, our case study showed the ability of process modeling to answer the actual needs in healthcare practices. Independently from the medical domain in which the modeling effort is done, the proposed methodology is useful to create high-quality models, and to detect and take into account relevant and tricky situations that can occur during process execution.

The Latin American laws of correct nutrition: Review, unified interpretation, model and tools

BACKGROUND

The "Laws of Correct Nutrition": the Law of Quantity, the Law of Quality, the Law of Harmony and the Law of Adequacy, provide the basis of a proper diet, i.e. one that provides the body with the energy required and nutrients it needs for daily activities and maintenance of vital functions. For several decades, these Laws have been the basis of nourishing menus designed in Latin America; however, they are stated in a colloquial language, which leads to differences in interpretation and ambiguities for non-experts and even experts in the field.

METHODS

We present a review of the different interpretations of the Laws and describe a consensus. We represent concepts related to nourishing menu design employing the Unified Modeling Language (UML). We formalize the Laws using the Object Constraint Language (OCL). We design a nourishing menu for a particular user through enforcement of the Laws.

RESULTS

We designed a domain model with the essential elements to plan a nourishing menu and we expressed the necessary constraints to make the model׳s behavior conform to the four Laws. We made a formal verification and validation of the model via USE (UML-based Specification Environment) and we developed a software prototype for menu design under the Laws.

CONCLUSION

Diet planning is considered as an art but consideration should be given to the need for a set of strict rules to design adequate menus. Thus, we model the "Laws of Nutrition" as a formal basis and standard framework for this task.