Business Process Management for optimizing clinical processes: A systematic literature review

Use of Real-World FHIR Data Combined with Context-Sensitive Decision Modeling to Guide Sentinel Biopsy in Melanoma

Background: To support clinical decision-making at the point of care, the "best next step" based on Standard Operating Procedures (SOPs) and actual accurate patient data must be provided. To do this, textual SOPs have to be transformed into operable clinical algorithms and linked to the data of the patient being treated. For this linkage, we need to know exactly which data are needed by clinicians at a certain decision point and whether these data are available. These data might be identical to the data used within the SOP or might integrate a broader view. To address these concerns, we examined if the data used by the SOP is also complete from the point of view of physicians for contextual decision-making. Methods: We selected a cohort of 67 patients with stage III melanoma who had undergone adjuvant treatment and mainly had an indication for a sentinel biopsy. First, we performed a step-by-step simulation of the patient treatment along our clinical algorithm, which is based on a hospital-specific SOP, to validate the algorithm with the given Fast Healthcare Interoperability Resources (FHIR)-based data of our cohort. Second, we presented three different decision situations within our algorithm to 10 dermatooncologists, focusing on the concrete patient data used at this decision point. The results were conducted, analyzed, and compared with those of the pure algorithmic simulation. Results: The treatment paths of patients with melanoma could be retrospectively simulated along the clinical algorithm using data from the patients' electronic health records. The subsequent evaluation by dermatooncologists showed that the data used at the three decision points had a completeness between 84.6% and 100.0% compared with the data used by the SOP. At one decision point, data on "patient age (at primary diagnosis)" and "date of first diagnosis" were missing. Conclusions: The data needed for our decision points are available in the FHIR-based dataset. Furthermore, the data used at decision points by the SOP and hence the clinical algorithm are nearly complete compared with the data required by physicians in clinical practice. This is an important precondition for further research focusing on presenting decision points within a treatment process integrated with the patient data needed.

Addressing unforeseen public health risks via the use of sustainable system and process management

During the coronavirus disease 2019 (COVID-19) pandemic, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was designated by the World Health Organization in January 2020 as a newly emerging coronavirus in 2019, and its variants have placed unbearable strain on the healthcare systems of various countries, with serious implications for sustainable development worldwide. Researchers have proposed several solutions, such as the use of digital technologies to improve prevention systems. However, the challenges of epidemic prevention and control failures have not been addressed fundamentally, as the key causes of epidemic failures (i.e., outbreaks) and strategies for process management have been neglected. The purpose of the current study is to address these issues by exploring the causes of epidemic prevention and control failure and targeting improvement strategies that combine system structure of epidemic prevention and process management. Specifically, following an exploration of the main reasons for COVID-19 prevention and control failures through a case study of two tertiary hospitals, this paper outlines a targeted prevention and control system based on triangular validation and a loosely coupled process management framework and verifies the expected results using simulation methods together with statistical data on the spread of SARS-CoV-2 in Wuhan, China. The findings not only advance the development of epidemic risk prevention and control theory, especially the complementary nature of IT applications and process management in the field of epidemic risk prevention and control, but also provide guidance on the innovation and implementation of epidemic prevention and control systems and process management and recommendations for countries to promote sustainable development from a health-focused perspective.

Improving the mental health care process in response to Covid-19 pandemic: The case of a penitentiary mental health division

Covid-19 outbreak led all organizations to reorganize their processes to prevent infection and contagion risk. All healthcare facilities, included penitentiary mental health services, had to redesign their processes to safely deliver care services. In this paper, the case of a Penitentiary Mental Health Division located in southern Italy is presented. Soft System Methodology and Business process management principles and techniques are adopted to analyse and redesign the detainees' mental health care process. The process, characterized by direct, close and prolonged contact with patients, exposes detainees and healthcare staff to a high Covid-19 infection risk. Through document analysis, interviews with the actors involved in the process and direct observation, the process's inefficiencies and criticalities are identified. The process is redesigned to make it compliant with Covid-19 prevention provisions and national penitentiary regulations and address the other criticalities. The proposed methodological approach-which innovatively combines Soft System Methodology and Business Process Management-constitutes a human-centered process-based redesign approach that can be used both in healthcare and other organizational settings.

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.

ProDeM: A Process-Oriented Delphi Method for systematic asynchronous and consensual surgical process modelling

Surgical process models support improving healthcare provision by facilitating communication and reasoning about processes in the medical domain. Modelling surgical processes is challenging as it requires integrating information that might be fragmented, scattered, and not process-oriented. These challenges can be faced by involving healthcare domain experts during process modelling. This paper presents ProDeM: a novel Process-Oriented Delphi Method for the systematic, asynchronous, and consensual modelling of surgical processes. ProDeM is an adaptable and flexible method that acknowledges that: (i) domain experts have busy calendars and might be geographically dispersed, and (ii) various elements of the process model need to be assessed to ensure model quality. The contribution of the paper is twofold as it outlines ProDeM, but also demonstrates its operationalisation in the context of a well-known surgical process. Besides showing the method's feasibility in practice, we also present an evaluation of the method by the experts involved in the demonstration.

Business Process Model and Notation and openEHR Task Planning for Clinical Pathway Standards in Infections: Critical Analysis

Background

Clinical pathways (CPs) are usually expressed by means of workflow formalisms, providing health care personnel with an easy-to-understand, high-level conceptual model of medical steps in specific patient conditions, thereby improving overall health care process quality in clinical practice. From a standardized perspective, the business process model and notation (BPMN), a widely spread general-purpose process formalism, has been used for conceptual modeling in clinical domains, mainly because of its easy-to-use graphical notation, facilitating the common understanding and communication of the parties involved in health care. However, BPMN is not particularly oriented toward the peculiarities of complex clinical processes such as infection diagnosis and treatment, in which time plays a critical role, which is why much of the BPMN clinical-oriented research has revolved around how to extend the standard to address these special needs. The shift from an agnostic, general-purpose BPMN notation to a natively clinical-oriented notation such as openEHR Task Planning (TP) could constitute a major step toward clinical process improvement, enhancing the representation of CPs for infection treatment and other complex scenarios.

Objective

Our work aimed to analyze the suitability of a clinical-oriented formalism (TP) to successfully represent typical process patterns in infection treatment, identifying domain-specific improvements to the standard that could help enhance its modeling capabilities, thereby promoting the widespread adoption of CPs to improve medical practice and overall health care quality.

Methods

Our methodology consisted of 4 major steps: identification of key features of infection CPs through literature review, clinical guideline analysis, and BPMN extensions; analysis of the presence of key features in TP; modeling of relevant process patterns of catheter-related bloodstream infection as a case study; and analysis and proposal of extensions in view of the results.

Results

We were able to easily represent the same logic applied in the extended BPMN-based process models in our case study using out-of-the-box standard TP primitives. However, we identified possible improvements to the current version of TP to allow for simpler conceptual models of infection CPs and possibly of other complex clinical scenarios.

Conclusions

Our study showed that the clinical-oriented TP specification is able to successfully represent the most complex catheter-related bloodstream infection process patterns depicted in our case study and identified possible extensions that can help increase its adequacy for modeling infection CPs and possibly other complex clinical conditions.

Implementation of online video consultations in a regional health network: a management feasibility analysis from an orthopedic perspective

Introduction

Regional health care networks with interfaces between clinics, general practitioners and patients can act faster when utilizing digital measures. This manuscript describes the establishment of an online video consultation service in a clinic and its broad health care region to exemplify challenges and solutions for potential future approaches from a management perspective.

Method

The underlying pilot project was planned and implemented for follow-up monitoring and consultative presentation of orthopedic and trauma patients within the Bundeswehr Medical Service from 2018 to 2020. With predominantly positive evaluation results regarding quality and acceptance among users, this research investigated organizational and processual aspects including total quality management, strategic control and change management approaches.

Results

The affected main and subprocesses of patient treatment could be streamlined by the project, as physician recommendations and arrangements could be accelerated and patient travel could be significantly reduced. A SWOT and portfolio analysis showed a high potential for improving existing patient treatment processes for health care enterprises via the use of digital technology. The involved staff should be strategically included at an early stage and continuously involved. By means of a PDCA cycle, the processes of the given project could be exemplarily illustrated with an outlook in the future.

Discussion

It has proven successful to consciously use management approaches to establish telemedical integrated care structures in a health region. Recommendations for the strategic introduction of an online video consultation for regional network strengthening and care development for a patient-oriented increase in efficiency could be compiled.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08352-0.

Identifying the Current State and Improvement Opportunities in the Information Flows Necessary to Manage Professional Athletes: A Case Study in Rugby Union

In sporting environments, the knowledge necessary to manage athletes is built on information flows associated with player management processes. In current literature, there are limited case studies available to illustrate how such information flows are optimized. Hence, as the first step of an optimization project, this study aimed to evaluate the current state and the improvement opportunities in the player management information flow executed within the High-Performance Unit (HPU) at a professional rugby union club in England. Guided by a Business Process Management framework, elicitation of the current process architecture illustrated the existence of 18 process units and two core process value chains relating to player management. From the identified processes, the HPU management team prioritized 7 processes for optimization. In-depth details on the current state (As-Is) of the selected processes were extracted from semi-structured, interview-based process discovery and were modeled using Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN) standards. Results were presented for current issues in the information flow of the daily training load management process, identified through a thematic analysis conducted on the data obtained mainly from focus group discussions with the main stakeholders (physiotherapists, strength and conditioning coaches, and HPU management team) of the process. Specifically, the current state player management information flow in the HPU had issues relating to knowledge creation and process flexibility. Therefore, the results illustrate that requirements for information flow optimization within the considered environment exist in the transition from data to knowledge during the execution of player management decision-making processes.

Digitally Optimizing the Information Flows Necessary to Manage Professional Athletes: A Case Study in Rugby Union

Practical case studies elaborating end-to-end attempts to improve the quality of information flows associated with athlete management processes are scarce in the current sport literature. Therefore, guided by a Business Process Management (BPM) approach, the current study presents the outcomes from a case study to optimize the quality of strength and conditioning (S&C) information flow in the performance department of a professional rugby union club. Initially, the S&C information flow was redesigned using integral technology, activity elimination and activity automation redesign heuristics. Utilizing the Lean Startup framework, the redesigned information flow was digitally transformed by designing data collection, management and visualization systems. Statistical tests used to assess the usability of the data collection systems against industry benchmarks using the System Usability Scale (SUS) administered to 55 players highlighted that its usability (mean SUS score of 87.6 ± 10.76) was well above average industry benchmarks of similar systems (Grade A from SUS scale). In the data visualization system, 14 minor usability problems were identified from 9 cognitive walkthroughs conducted with the High-Performance Unit (HPU) staff. Pre-post optimization information quality was subjectively assessed by administering a standardized questionnaire to the HPU members. The results indicated positive improvements in all of the information quality dimensions (with major improvements to the accessibility) relating to the S&C information flow. Additionally, the methods utilized in the study would be especially beneficial for sporting environments requiring cost effective and easily adoptable information flow digitization initiatives which need to be implemented by its internal staff members.

Benefits and limitations of business process model notation in modelling patient healthcare trajectory: a scoping review protocol

INTRODUCTION

The adoption of business process model notation (BPMN) in modelling healthcare trajectory can enhance the efficiency and efficacy of healthcare organisations, improve patient outcomes while restraining costs. Existing systematic reviews have been inconclusive regarding the effectiveness of BPMN in modelling healthcare trajectory. The aims of this scoping review are to map and aggregate existing evidence on the benefits and limitations associated with BPMN in healthcare trajectory, highlighting areas of improvement on BPMN and its extensions in healthcare. We will assess BPMN's ability to model key dimensions or concepts of the healthcare process and to meet the needs of stakeholders. The review will highlight the advantages of this approach to support clinical activities and decision-making processes associated with the healthcare trajectory, proposing a conceptual framework for improving the use of BPMN in healthcare.

METHODS AND ANALYSIS

This study will be performed in accordance with the methodological framework suggested by Arksey and O'Malley. A wide range of electronic databases and grey literature sources will be systematically searched using predefined keywords. The review will include any study design focusing on the application of the BPMN approach for optimising healthcare trajectories, published in either English or French from 1 January 2004 to 9 December 2021. Two reviewers will independently screen titles, abstracts and full-text articles and select articles meeting the inclusion criteria. A customised data extraction form will be used to extract data. The results will be presented using descriptive statistics and thematic analysis on qualitative data.

ETHICS AND DISSEMINATION

Research ethics approval is not required. Review findings will be used to advance understanding about BPMN, its extensions and application in healthcare trajectory optimisation. The review will develop recommendations on tailoring BPMN strategies for optimising care pathways and decision-making processes. Findings will be disseminated in peer-reviewed journals, conferences and discussions with relevant organisations and stakeholders.

Artificial Intelligence-Based Methods for Business Processes: A Systematic Literature Review

Companies are usually overloaded with data that they may not know how to take advantage of. On the other hand, artificial intelligence (AI) techniques are known to “keep learning” as the data increase. In this context, our research question emerges: what AI-based methods, in the literature, could be used to automatize business processes and support the decision-making processes of companies? To fill this gap, in this paper, we performed a review of the literature to identify these techniques. We ensured the usage of methods since they allowed reproducibility and extensions. We applied our search string in the Scopus and Web of Science databases and discovered 21 relevant papers pertaining to our question. In these papers, we identified methods that automated tasks and helped analysts make assertive decisions when designing, extending, or reengineering business processes. The authors applied diverse AI techniques, such as K-means, Bayesian networks, and swarm intelligence. Our analysis provides statistics about the techniques and problems being tackled and point to possible future directions.

BPM Support for Patient-Centred Clinical Pathways in Chronic Diseases

Epidemiological trends over the past decade show a significant worldwide increase in the burden of chronic diseases. At the same time, the human resources of health care are becoming increasingly scarce and expensive. One of the management concepts that can help in solving this problem is business process management (BPM). The results of research conducted in the healthcare sector thus far prove that BPM is an effective tool for optimizing clinical processes, as it allows for the ongoing automatic tracking of key health parameters of an individual patient without the need to involve medical personnel. The aim of this article is to present and evaluate the redesign of diagnostic and therapeutic processes enabling the patient-centric organization of therapy thanks to the use of new telemedicine techniques and elements of hyperautomation. By using an illustrative case study of one of the most common chronic diseases, Chronic Obstructive Pulmonary Disease (COPD), we discuss the use of clinical pathways (CPs) prepared on the basis of the current version of the Global Initiative for Chronic Obstructive Lung Disease (GOLD) as a communication tool between healthcare professionals, the patient and his or her caregivers, as well as the method of identifying and verifying new knowledge generated on an ongoing basis in diagnostic and therapeutic processes. We also show how conducting comprehensive, patient-focused primary health care relieves the health care system, and at the same time, thanks to the use of patient engagement and elements of artificial intelligence (predictive analyses), reduces the significant clinical risk of therapy.

Identifying Opportunities for Workflow Automation in Health Care: Lessons Learned from Other Industries

Background  Workflow automation, which involves identifying sequences of tasks that can be streamlined by using technology and modern computing, offers opportunities to address the United States health care system's challenges with quality, safety, and efficiency. Other industries have successfully implemented workflow automation to address these concerns, and lessons learned from those experiences may inform its application in health care.

Objective  Our aim was to identify and synthesize (1) current approaches in workflow automation across industries, (2) opportunities for applying workflow automation in health care, and (3) considerations for designing and implementing workflow automation that may be relevant to health care.

Methods  We conducted a targeted review of peer-reviewed and gray literature on automation approaches. We identified relevant databases and terms to conduct the searches across sources and reviewed abstracts to identify 123 relevant articles across 11 disciplines.

Results  Workflow automation is used across industries such as finance, manufacturing, and travel to increase efficiency, productivity, and quality. We found automation ranged from low to full automation, and this variation was associated with task and technology characteristics. The level of automation is linked to how well a task is defined, whether a task is repetitive, the degree of human intervention and decision-making required, and the sophistication of available technology. We found that identifying automation goals and assessing whether those goals were reached was critical, and ongoing monitoring and improvement would help to ensure successful automation.

Conclusion  Use of workflow automation in other industries can inform automating health care workflows by considering the critical role of people, process, and technology in design, testing, implementation, use, and ongoing monitoring of automated workflows. Insights gained from other industries will inform an interdisciplinary effort by the Office of the National Coordinator for Health Information Technology to outline priorities for advancing health care workflow automation.

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.

Specialization of Business Process Model and Notation Applications in Medicine—A Review

Process analysis and process modeling are a current topic that extends to many areas. This trend of using optimization and modeling techniques in various specific areas has led to the question of how widespread these approaches are overall in medical specializations. We compiled a list of 272 medical disciplines that we used as a search string with the Business Process Model and Notation (BPMN) for a Web of Science database search. Thus, we found a total of 485 documents that we subjected to the exclusion criteria. We analyzed the remaining 108 articles using bibliometric and content analyses to find answers to three research questions. This systematic review was carried out using the procedure proposed by Kitchenham and following the Preferred Items of the Systematic Review and Meta-Analysis Report (PRISMA). Due to the broad scope of the medical field, it was no surprise that for almost 85% of the sought-after medical specializations, we could not identify any publications in the given database when applying the BPMN. We analyzed the impact of upgrades to the BPMN on publishing. The keyword analysis showed a diametrical difference between the authors’ keywords and the so-called “Keywords Plus”, and we categorized the publications according to the purpose of applying the BPMN. However, the growing interest in combining BPMN with other approaches brings new challenges in practice.