Interoperability Is a Process - The Data Sharing Framework

Common syntax and data semantics are core components of healthcare interoperability standards. However, interoperable data exchange processes are also needed to enable the integration of existing systems between organizations. While solutions for healthcare delivery processes are available and have been widely adopted, support for processes targeting bio-medical research is limited. Our Data Sharing Framework creates a platform to implement research processes like cohort size estimation, reviews and approvals of research proposals, consent checks, record linkage, pseudonymization and data sharing across organizations. The described framework implements a distributed business process engine for executing BPMN 2.0 processes with synchronization and data exchange using FHIR R4 resources. Our reference implementation has been rolled out to 38 organizations across three research consortia in Germany and is available as open source under the Apache 2.0 license.

Toward an interoperable, intraoperative situation recognition system via process modeling, execution, and control using the standards BPMN and CMMN

PURPOSE

For the modeling, execution, and control of complex, non-standardized intraoperative processes, a modeling language is needed that reflects the variability of interventions. As the established Business Process Model and Notation (BPMN) reaches its limits in terms of flexibility, the Case Management Model and Notation (CMMN) was considered as it addresses weakly structured processes.

METHODS

To analyze the suitability of the modeling languages, BPMN and CMMN models of a Robot-Assisted Minimally Invasive Esophagectomy and Cochlea Implantation were derived and integrated into a situation recognition workflow. Test cases were used to contrast the differences and compare the advantages and disadvantages of the models concerning modeling, execution, and control. Furthermore, the impact on transferability was investigated.

RESULTS

Compared to BPMN, CMMN allows flexibility for modeling intraoperative processes while remaining understandable. Although more effort and process knowledge are needed for execution and control within a situation recognition system, CMMN enables better transferability of the models and therefore the system. Concluding, CMMN should be chosen as a supplement to BPMN for flexible process parts that can only be covered insufficiently by BPMN, or otherwise as a replacement for the entire process.

CONCLUSION

CMMN offers the flexibility for variable, weakly structured process parts, and is thus suitable for surgical interventions. A combination of both notations could allow optimal use of their advantages and support the transferability of the situation recognition system.

No Transfer Without Validation: A Data Sharing Framework Use Case

Availability and accessibility are important preconditions for using real-world patient data across organizations. To facilitate and enable the analysis of data collected at a large number of independent healthcare providers, syntactic- and semantic uniformity need to be achieved and verified. With this paper, we present a data transfer process implemented using the Data Sharing Framework to ensure only valid and pseudonymized data is transferred to a central research repository and feedback on success or failure is provided. Our implementation is used within the CODEX project of the German Network University Medicine to validate COVID-19 datasets at patient enrolling organizations and securely transfer them as FHIR resources to a central repository.

A model-driven transformation approach for the modelling of processes in clinical practice guidelines

Clinical Practice Guidelines (CPGs) include recommendations aimed at optimising patient care, informed by a review of the available clinical evidence. To achieve their potential benefits, CPG should be readily available at the point of care. This can be done by translating CPG recommendations into one of the languages for Computer-Interpretable Guidelines (CIGs). This is a difficult task for which the collaboration of clinical and technical staff is crucial. However, in general CIG languages are not accessible to non-technical staff. We propose to support the modelling of CPG processes (and hence the authoring of CIGs) based on a transformation, from a preliminary specification in a more accessible language into an implementation in a CIG language. In this paper, we approach this transformation following the Model-Driven Development (MDD) paradigm, in which models and transformations are key elements for software development. To demonstrate the approach, we implemented and tested an algorithm for the transformation from the BPMN language for business processes to the PROforma CIG language. This implementation uses transformations defined in the ATLAS Transformation Language. Additionally, we conducted a small experiment to assess the hypothesis that a language such as BPMN can facilitate the modelling of CPG processes by clinical and technical staff.

Policy-Based Holistic Application Management with BPMN and TOSCA

With the wide adoption of cloud computing across technology industries and research institutions, an ever-growing interest in cloud orchestration frameworks has emerged over the past few years. These orchestration frameworks enable the automated provisioning and decommissioning of cloud applications in a timely and efficient manner, but they offer limited or no support for application management. While management functionalities, such as configuring, monitoring and scaling single components, can be directly covered by cloud providers and configuration management tools, holistic management features, such as backing up, testing and updating multiple components, cannot be automated using these approaches. In this paper, we propose a concept to automatically generate executable holistic management workflows based on the TOSCA standard. The practical feasibility of the approach is validated through a prototype implementation and a case study.

Don't overthink it: The paradoxical nature of expertise for the detection of errors in conceptual business process models

Business process models are widely used artifacts in design activities to facilitate communication about business domains and processes. Despite being an extensively researched topic, some aspects of conceptual business modeling are yet to be fully explored and understood by academicians and practitioners alike. We study the attentional characteristics specific to experts and novices in a semantic and syntactic error detection task across 75 Business Process Model and Notation (BPMN) models. We find several intriguing results. Experts correctly identify more error-free models than novices, but also tend to find more false positive defects. Syntactic errors are diagnosed faster than semantic errors by both groups. Both groups spend more time on error-free models. Our findings regarding the ambiguous differences between experts and novices highlight the paradoxical nature of expertise and the need to further study how best to train business analysts to design and evaluate conceptual models.

Secure Multi-Party Computation Based Distributed Feasibility Queries - A HiGHmed Use Case

The integration of routine medical care data into research endeavors promises great value. However, access to this extra-domain data is constrained by numerous technical and legal requirements. The German Medical Informatics Initiative (MII) - initiated by the Federal Ministry of Research and Education (BMBF) - is making progress in setting up Medical Data Integration Centers to consolidate data stored in clinical primary information systems. Unfortunately, for many research questions cross-organizational data sources are required, as one organization's data is insufficient, especially in rare disease research. A first step, for research projects exploring possible multi-centric study designs, is to perform a feasibility query, i.e., a cohort size calculation transcending organizational boundaries. Existing solutions for this problem, like the previously introduced feasibility process for the MII's HiGHmed consortium, perform well for most use cases. However, there exist use cases where neither centralized data repositories, nor Trusted Third Parties are acceptable for data aggregation. Based on open standards, such as BPMN 2.0 and HL7 FHIR R4, as well as the cryptographic techniques of secure Multi-Party Computation, we introduce a fully automated, decentral feasibility query process without any central component or Trusted Third Party. The open source implementation of the proposed solution is intended as a plugin process to the HiGHmed Data Sharing Framework. The process's concept and underlying algorithms can also be used independently.

Guideline-Based Context-Sensitive Decision Modeling for Melanoma Patients

INTRODUCTION

The provision of knowledge through clinical practice guidelines and hospital-specific standard operating procedures (SOPs) is ubiquitous in the medical context and in the treatment of melanoma patients. However, these knowledge sources are only available in unstructured text form and without any contextual link to real patient data. The aim of our project is to give a modeled decision support for the next treatment step based on the actual data and position of a patient.

METHODS

First, we identified passages for qualified decision-making necessary at the point of care from the SOP for melanoma. Thereby, the patient-specific contextual reference data at decision points was considered in parallel and represented by FHIR (Fast Healthcare Interoperability Resource) resources. The decision algorithm was then formalized using BPMN modeling with FHIR annotations. Validation was provided by medical experts, dermatooncologists from University Hospital Essen.

RESULTS

The resulting BPMN model is presented here with the diagnostic procedure of sentinel lymph node excision as the example snippet from the whole algorithm. Each decision point is edited with FHIR resources covering the patient data and preparing the context sensitivity of the model.

CONCLUSION

Modeling guideline-based information into a decision algorithm that can be presented at the point of care with contextual reference, may have the potential to support patient-specific clinical decision-making. For patients from a certain status like in the metastatic setting modeling becomes highly tailored to specific patient cases, alternative and individualized treatment options.

Towards circular economy in the textiles and clothing value chain through blockchain technology and IoT: A review

The textile and clothing industry sector has today a big environmental impact, not only due to the consumption of water and the use of toxic chemicals but also due to the increasing levels of textile waste. One way to reduce the problem is to circularise the, currently linear, textile and clothing value chain, by using discarded clothes as raw material for the production of new clothes, transforming it into a model of circular economy. This way, while reducing the need to produce new raw materials (e.g. cotton), the problem of textile waste produced is also reduced, thus contributing to a more sustainable industry. In this article, we review the current approaches for traceability in the textile and clothing value chain, and study a set of technologies we deem essential for promoting the circular economy in this value chain - namely, the blockchain technology - for registering activities on traceable items through the value chain, and the Internet of Things (IoT) technology, for easily identifying the traceable items' digital twins.

A novel approach to educate hospitalized cardiovascular disease patients about lifestyle and behavior modifications

Background

Cardiovascular diseases (CVDs) are always considered by healthcare specialists for different reasons, including extensive prevalence, increased costs, chronicity, and high risk of death. The control of CVDs is highly influenced by behavior and lifestyle and it seems necessary to train special abilities about lifestyle and behavior modification to improve self-care skills for patients, and their caregivers. As a result, the development of effective training systems should be considered by healthcare specialists.

Methods

Hence, in this study, a framework for improving cardiovascular patients’ education processes is presented. Initially, an existing training system for cardiovascular patients is reviewed. Using field observations and targeted interviews with hospital experts, all components of its educating processes are identified, and their process maps are drawn up. After that, challenges in the training system are extracted with the aid of in-depth semi-structured interviews with experts. Due to the importance and different influence of the identified challenges, they are prioritized using a Multiple Criteria Decision-making (MCDM) method, and then their root causes were investigated. Finally, a novel framework is proposed and evaluated with hospital experts' help to improve the main challenges.

Results

The most important challenges included high nursing workload and shortage of time, lack of understanding of training concepts by patients, lack of attention to training, disruption of the training processes by the patients’ caregivers, and patient's weakness in understanding the standard language. In identifying the root causes, learner, educator, and educational tools are the most effective in the training process; therefore, the improvement scenarios were designed accordingly in the proposed framework.

Conclusions

Our study indicated that presenting a framework with applying different quantitative and qualitative methods has great potential to improve the processes of patient education for chronic diseases such as cardiovascular disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-021-01680-x.

Data Sharing in Distributed Architectures - Concept and Implementation in HiGHmed

Medical routine data has the potential to benefit research. However, transferring this data into a research context is difficult. For this reason Medical Data Integration Centers are being established in German university hospitals to consolidate data from primary information systems in a single location. But, small data-sets from one organization can be insufficient to answer a research question adequately. In order to obtain larger data-sets, attempts to merge and provide data-sets across institutional boundaries are made. Therefore, this paper proposes a possible process that can extract, merge, pseudonymize and provide distributed data-sets from several organizations conforming to privacy regulations. This process is executed according to the open standard BPMN 2.0, the underlying process data model is based on HL7 FHIR R4. The proposed solution is currently being deployed at eight university hospitals and one Trusted Third Party in the HiGHmed consortium.

Feasibility Queries in Distributed Architectures - Concept and Implementation in HiGHmed

Medical routine data promises to add value for research. However, the transfer of this data into a research context is difficult. Therefore, Medical Data Integration Centers are being set up to merge data from primary information systems in a central repository. But, data from one organization is rarely sufficient to answer a research question. The data must be merged beyond institutional boundaries. In order to use this data in a specific research project, a researcher must have the possibility to query available cohort sizes across institutions. A possible solution for this requirement is presented in this paper, using a process for fully automated and distributed feasibility queries (i.e. cohort size estimations). This process is executed according to the open standard BPMN 2.0, the underlying process data model is based on HL7 FHIR R4 resources. The proposed solution is currently being deployed at eight university hospitals and one trusted third party across Germany.

Executing Distributed Healthcare and Research Processes - The HiGHmed Data Sharing Framework

Several standards and frameworks have been described in existing literature and technical manuals that contribute to solving the interoperability problem. Their data models usually focus on clinical data and only support healthcare delivery processes. Research processes including cross organizational cohort size estimation, approvals and reviews of research proposals, consent checks, record linkage and pseudonymization need to be supported within the HiGHmed medical informatics consortium. The open source HiGHmed Data Sharing Framework implements a distributed business process engine for executing arbitrary biomedical research and healthcare processes modeled and executed using BPMN 2.0 while exchanging information using FHIR R4 resources. The proposed reference implementation is currently being rolled out to eight university hospitals in Germany as well as a trusted third party and available open source under the Apache 2.0 license.

Mobile Instant Messaging (M.I.M.) in Improving S.M.E. in Manufacturing: Case Study

It is reported in the literature that there are widespread adoption and use of Mobile Instant Messaging (M.I.M.) among businesses. However, there is a lack of academic publication in this area that demonstrates by means of a case study that the M.I.M. implementation for S.M.E.'s can improve operational processes. In this case study, the company recently moved much of its Product Ordering (P.O.) processes to a freely accessible M.I.M. app. The paper uses a combination of qualitative and quantitative analysis to evaluate the impact of the change. Quantitative and qualitative analysis confirms that the introduction has enhanced the P.O. process. The analysis shows that the timeline for the full P.O. process is significantly shortened. The speed of communication allowed faster processing, approval and delivery. The paper presents the first case study that looks at how M.I.M. processes can enhance an S.M.E.'s operations.

Approaches combining methods of Operational Research with Business Process Model and Notation: A systematic review

BACKGROUND

Business process modelling is increasingly used not only by the companies' management but also by scientists dealing with process models. Process modeling is seldom done without decision-making nodes, which is why operational research methods are increasingly included in the process analyses.

OBJECTIVE

This systematic literature review aimed to provide a detailed and comprehensive description of the relevant aspects of used operational research techniques in Business Process Model and Notation (BPMN) model.

METHODS

The Web Of Science of Clarivate Analytics was searched for 128 studies of that used operation research techniques and business process model and notation, published in English between 1 January 2004 and 18 May 2020. The inclusion criteria were as follows: Use of Operational Research methods in conjunction with the BPMN, and is available in full-text format. Articles were not excluded based on methodological quality. The background information of the included studies, as well as specific information on the used approaches, were extracted.

RESULTS

In this research, thirty-six studies were included and considered. A total of 11 specific methods falling into the field of Operations Research have been identified, and their use in connection with the process model was described.

CONCLUSION

Operational research methods are a useful complement to BPMN process analysis. It serves not only to analyze the probability of the process, its economic and personnel demands but also for process reengineering.

IT-Assisted Process Management in Healthcare

Clinical processes need to be well understood before a new health IT tool can be introduced. Observations, interviews, surveys, or documentation analysis are carried out to systematically collect information to better understand a clinical process. To aggregate and visualize the collected information about a clinical process, use case diagrams can build a basis. Formal process models such as process chain diagrams or BPMN diagrams are well suited to model the process in detail. The objective of this chapter is to discuss these methods for analyzing and modeling clinical processes, as this is an important precondition for systematic process management in health care.

A BPMN Based Notation for the Representation of Workflows in Hospital Protocols

Flowcharts used for hospital protocols have a series of ambiguities and limitations in order to express some types of information. In this article, a notation proposal for flowcharts that partially avoids these problems is presented. This new notation is an adaptation of BPMNE2, an extension of the Business Process Model and Notation (BPMN), which allows direct modelling of procedures that follow the Hazard Analysis and Critical Control Points (HACCP) model. The new notation has been validated in the hospital context, specifically in the field of hazardous drugs (HDs). To measure usability from the perspective of the health staff and auditors, the System Usability Scale (SUS) was used. A total of 47 experts took part in the assessment, resulting in a SUS score of 71, that corresponds to an acceptable level of usability. The feedback provided by these participants allows us to discover benefits and drawbacks of the proposal. Also, it is noteworthy that 76.6% of professionals prefer to migrate to the new notation from the ISO 5807:1985 notation, the most commonly used model. In addition to the direct benefits of this notation from the human point of view, its machine-understandable nature provides the required support for its integration into software tools for intelligent monitoring and auditing.

A template-based approach for responsibility management in executable business processes

Process-oriented organisations need to manage the different types of responsibilities their employees may have w.r.t. the activities involved in their business processes. Despite several approaches provide support for responsibility modelling, in current Business Process Management Systems (BPMS) the only responsibility considered at runtime is the one related to performing the work required for activity completion. Others like accountability or consultation must be implemented by manually adding activities in the executable process model, which is time-consuming and error-prone. In this paper, we address this limitation by enabling current BPMS to execute processes in which people with different responsibilities interact to complete the activities. We introduce a metamodel based on Responsibility Assignment Matrices (RAM) to model the responsibility assignment for each activity, and a flexible template-based mechanism that automatically transforms such information into BPMN elements, which can be interpreted and executed by a BPMS. Thus, our approach does not enforce any specific behaviour for the different responsibilities but new templates can be modelled to specify the interaction that best suits the activity requirements. Furthermore, libraries of templates can be created and reused in different processes. We provide a reference implementation and build a library of templates for a well-known set of responsibilities.

A meta-model for computer executable dynamic clinical safety checklists

BACKGROUND

Safety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. This is due to the lack of a formal representation format that is both understandable by clinical experts and executable by computer programs.

METHODS

We developed a dynamic checklist meta-model with a three-step approach. Dynamic checklist modeling requirements were extracted by performing a domain analysis. Then, existing modeling approaches and tools were investigated with the purpose of reusing these languages. Finally, the meta-model was developed by eliciting domain concepts and their hierarchies. The feasibility of using the meta-model was validated by two case studies. The meta-model was mapped to specific modeling languages according to the requirements of hospitals.

RESULTS

Using the proposed meta-model, a comprehensive coronary artery bypass graft peri-operative checklist set and a percutaneous coronary intervention peri-operative checklist set have been developed in a Dutch hospital and a Chinese hospital, respectively. The result shows that it is feasible to use the meta-model to facilitate the modeling and execution of dynamic checklists.

CONCLUSIONS

We proposed a novel meta-model for the dynamic checklist with the purpose of facilitating creating dynamic checklists. The meta-model is a framework of reusing existing modeling languages and tools to model dynamic checklists. The feasibility of using the meta-model is validated by implementing a use case in the system.

Challenges and Approaches to Make Multidisciplinary Team Meetings Interoperable - The KIMBo Project

BACKGROUND

Multidisciplinary team meetings (MDTMs) are already in use for certain areas in healthcare (e.g. treatment of cancer). Due to the lack of common standards and accessibility for the applied IT systems, their potential is not yet completely exploited.

OBJECTIVES

Common requirements for MDTMs shall be identified and aggregated into a process definition to be automated by an application architecture utilizing modern standards in electronic healthcare, e.g. HL7 FHIR.

METHODS

To identify requirements, an extensive literature review as well as semi-structured expert interviews were conducted.

RESULTS

Results showed, that interoperability and flexibility in terms of the process are key requirements to be addressed. An architecture blueprint as well as an aggregated process definition were derived from the insights gained. To evaluate the feasibility of identified requirements, methods of explorative prototyping in software engineering were used.

CONCLUSION

MDTMs will become an important part of modern and future healthcare but the need for standardization in terms of interoperability is imminent.

Improved compliance by BPM-driven workflow automation

Using methods and technologies of business process management (BPM) for the laboratory automation has important benefits (i.e., the agility of high-level automation processes, rapid interdisciplinary prototyping and implementation of laboratory tasks and procedures, and efficient real-time process documentation). A principal goal of the model-driven development is the improved transparency of processes and the alignment of process diagrams and technical code. First experiences of using the business process model and notation (BPMN) show that easy-to-read graphical process models can achieve and provide standardization of laboratory workflows. The model-based development allows one to change processes quickly and an easy adaption to changing requirements. The process models are able to host work procedures and their scheduling in compliance with predefined guidelines and policies. Finally, the process-controlled documentation of complex workflow results addresses modern laboratory needs of quality assurance. BPMN 2.0 as an automation language to control every kind of activity or subprocess is directed to complete workflows in end-to-end relationships. BPMN is applicable as a system-independent and cross-disciplinary graphical language to document all methods in laboratories (i.e., screening procedures or analytical processes). That means, with the BPM standard, a communication method of sharing process knowledge of laboratories is also available.