Analyzing Healthcare Processes with Incremental Process Discovery: Practical Insights from a Real-World Application.

Abstract: Most process mining techniques are primarily automated, meaning that process analysts input information and receive output. As a result, process mining techniques function like black boxes with limited interaction options for analysts, such as simple sliders for filtering infrequent behavior. Recent research tries to break these black boxes by allowing process analysts to provide domain knowledge and guidance to process mining techniques, i.e., hybrid intelligence. Especially, in process discovery-a critical type of process mining-interactive approaches emerged. However, little research has investigated the practical application of such interactive approaches. This paper presents a case study focusing on using incremental and interactive process discovery techniques in the healthcare domain. Though healthcare presents unique challenges, such as high process execution variability and poor data quality, our case study demonstrates that an interactive process mining approach can effectively address these challenges.

Effective process quality control management for constipation prevention in hospitalized patients with acute coronary syndrome: An observational study.

Objective: To evaluate the effectiveness of monitoring and managing process quality control indicators in the prevention of constipation among hospitalized patients with acute coronary syndrome (ACS). Methods: A total of 512 hospitalized patients diagnosed with ACS between January and June 2022 were screened for inclusion in the study. Ultimately, 456 eligible participants were enrolled and divided into two groups based on the chronological order of admission: the control group and the observation group. Upon admission, both groups of patients received routine constipation prevention measures in the department. However, the observation group was subjected to targeted process quality control management, which included monitoring and managing five indicators related to constipation prevention: correctness of bowel movement recording; usage rate of laxatives; execution rate of physical interventions; implementation rate of constipation prevention education; completion rate of dietary structure and habit assessments. Data were analyzed using SPSS, with t tests and χ 2 tests for group comparisons. Results: In comparison to the control group, the observation group demonstrated significant advantages in terms of constipation incidence, completion rates of the five process quality control indicators, occurrence rates of adverse cardiac events during defecation, and PHQ-9 scores before discharge. These disparities demonstrated statistical significance with a p value < 0.05. Conclusion: Target-oriented process quality control management is shown to be effective in reducing constipation incidence and adverse cardiac events during constipation episodes, as well as alleviating depressive symptoms among ACS patients, thus providing a safe and effective approach to constipation prevention.

Safe Transition from Open to Total Minimally Invasive Esophagectomy for Cancer Utilizing Process Management Methodology.

Background: The global shift from open esophagectomy (OE) to minimally invasive esophagectomy (MIE) for treating esophageal cancer is well-established. Recent data indicate that transitioning from hybrid minimally invasive esophagectomy (hMIE) to total minimally invasive esophagectomy (tMIE) can be challenging due to concerns about higher leakage rates and lower lymph node counts, especially at the beginning of the learning curve. This study aimed to demonstrate that a safe transition from OE to tMIE for cancer is possible using process management methodology. Methods: A step-change approach was adopted in process management planning, with hMIE serving as an intermediate step between OE and tMIE. This single-center, case-control study included 150 patients who underwent the Ivor Lewis procedure with curative intent for esophageal cancer. Among these patients, 50 underwent OE, 50 hMIE (laparoscopic procedure followed by conventional right thoracotomy), and 50 tMIE (laparoscopic and thoracoscopic approach). A preceptored training scheme was implemented during execution, and treatment results were monitored and controlled to ensure a safe transition. Results: During the transition, the tMIE group was not worse than the hMIE and OE groups regarding operation duration (p = 0.135), overall postoperative complications (p = 0.020), anastomotic leakage rates (p = 0.773), 30-day mortality (p = 1.0), and oncological outcomes (based on R status (p = 0.628) and 2-year survival (p = 0.967)). Additionally, the tMIE group showed superior results in terms of major postoperative pulmonary complications (p = 0.004) and ICU stay duration (p < 0.001). Conclusions: Utilizing managerial methodology and practice in surgery, as a bridge between interdisciplinary and transdisciplinary approaches, demonstrated that transitioning from OE to tMIE, with hMIE as an intermediate step, is safe and feasible without compromising outcomes.

A multimedia dataset for object-centric business process mining in IT asset management.

This manuscript introduces a multimedia business process dataset provided by a German research institute. The dataset was systematically collected in a laboratory environment that reflects the workspace of IT staff managing IT Asset Management (ITAM) processes. It encompasses data from 121 process instances across six basic processes, captured using 37 video recordings from two camera perspectives, motion tracking, environmental sensors, an ITAM system trace, and event log data from user interactions. The data is made available in its raw state and processed form. The object-centric event log format (OCEL) provides discrete business process events from system activities. Event data from reality is supplied as raw video files and logs from environmental sensors. The video files were also manually labelled with identifiable business process activities and their associated entities. This multimedia dataset has been designed as a resource for developing, training, and evaluating process mining techniques based on unstructured data. Consequently, the dataset design emphasizes the traceability of activities and entities across the multimedia data sources.

The role of total quality management in enhancing customer satisfaction in Gulf Cooperation Council (GCC) countries.

This study examined the role of Total Quality Management (TQM) practices, specifically continuous improvement, customer focus, process management, and employee engagement, in advancing sustainability and enhancing customer satisfaction in the telecommunications sector, focusing on three firms in Gulf Cooperation Council (GCC) countries. Secondary quantitative data from quarterly reports (2019-2023) were analyzed using descriptive, correlation, and regression methods with STATA software.•The findings indicated an increase in net promoter score over the study period, reflecting firms' commitment to addressing changing customer needs.•Employee engagement and process management had a positive and statistically significant effect on customer satisfaction.•Integrating TQM practices to enhance customer satisfaction in telecommunications.

Reading between the Lines: Process Mining on OPC UA Network Data.

The introduction of the Industrial Internet of Things (IIoT) has led to major changes in the industry. Thanks to machine data, business process management methods and techniques could also be applied to them. However, one data source has so far remained untouched: The network data of the machines. In the business environment, process mining, for example, has already been carried out based on network data, but the IIoT, with its particular protocols such as OPC UA, has yet to be investigated. With the help of design science research and on the shoulders of CRISP-DM, we first develop a framework for process mining in the IIoT in this paper. We then apply the framework to real-world IIoT network traffic data and evaluate the outcome and performance of our approach in detail. We find tremendous potential in network traffic data but also limitations. Among other things, due to the dependence on process experts and the existence of case IDs.

The Effects of Displaying the Time Targets of the Manchester Triage System to Emergency Department Personnel: Prospective Crossover Study.

BACKGROUND: The use of triage systems such as the Manchester Triage System (MTS) is a standard procedure to determine the sequence of treatment in emergency departments (EDs). When using the MTS, time targets for treatment are determined. These are commonly displayed in the ED information system (EDIS) to ED staff. Using measurements as targets has been associated with a decline in meeting those targets. OBJECTIVE: This study investigated the impact of displaying time targets for treatment to physicians on processing times in the ED. METHODS: We analyzed the effects of displaying time targets to ED staff on waiting times in a prospective crossover study, during the introduction of a new EDIS in a large regional hospital in Germany. The old information system version used a module that showed the time target determined by the MTS, while the new system version used a priority list instead. Evaluation was based on 35,167 routinely collected electronic health records from the preintervention period and 10,655 records from the postintervention period. Electronic health records were extracted from the EDIS, and data were analyzed using descriptive statistics and generalized additive models. We evaluated the effects of the intervention on waiting times and the odds of achieving timely treatment according to the time targets set by the MTS. RESULTS: The average ED length of stay and waiting times increased when the EDIS that did not display time targets was used (average time from admission to treatment: preintervention phase=median 15, IQR 6-39 min; postintervention phase=median 11, IQR 5-23 min). However, severe cases with high acuity (as indicated by the triage score) benefited from lower waiting times (0.15 times as high as in the preintervention period for MTS1, only 0.49 as high for MTS2). Furthermore, these patients were less likely to receive delayed treatment, and we observed reduced odds of late treatment when crowding occurred. CONCLUSIONS: Our results suggest that it is beneficial to use a priority list instead of displaying time targets to ED personnel. These time targets may lead to false incentives. Our work highlights that working better is not the same as working faster.

Governance effects of pollution reduction and carbon mitigation of carbon emission trading policy in China.

China's carbon emission trading policy plays a crucial role in achieving both its "3060" dual carbon objectives and the United Nations Sustainable Development Goal 13 (SDG 13) on climate action. The policy's effectiveness in reducing pollution and mitigating carbon emissions holds significant importance. This paper investigated whether China's carbon emission trading policy affects pollution reduction (PM2.5 and SO2) and carbon mitigation (CO2) in pilot regions, using panel data from 30 provinces and municipalities in China from 2005 to 2019 and employing a multi-period difference-in-differences (DID) model. Furthermore, it analyzed the heterogeneity of carbon market mechanisms and regional variations. Finally, it examined the governance pathways for pollution reduction and carbon mitigation from a holistic perspective. The results indicate that: (1) China's carbon emission trading policy has reduced CO2 emissions by 18% and SO2 emissions by 36% in pilot areas, with an immediate impact on the "carbon mitigation" effect, while the "pollution reduction" effect exhibits a time lag. (2) Higher carbon trading prices lead to stronger "carbon mitigation" effect, and larger carbon market scales are associated with greater "pollution reduction" effects on PM2.5. Governance effects on pollution reduction and carbon mitigation vary among pilot regions: Carbon markets of Beijing, Chongqing, Shanghai, and Tianjin show significant governance effects in both "pollution reduction" and "carbon mitigation", whereas Guangdong's carbon market exhibits only a "pollution reduction" effect, and Hubei's carbon market demonstrates only a "carbon mitigation" effect. (3) Currently, China's carbon emission trading policy achieves pollution reduction and carbon mitigation through "process management" and "end-of-pipe treatment". This study could provide empirical insights and policy implications for pollution reduction and carbon mitigation, as well as for the development of China's carbon emission trading market.

Discussion paper: implications for the further development of the successfully in emergency medicine implemented AUD2IT-algorithm.

The AUD2IT-algorithm is a tool to structure the data, which is collected during an emergency treatment. The goal is on the one hand to structure the documentation of the data and on the other hand to give a standardised data structure for the report during handover of an emergency patient. AUD2IT-algorithm was developed to provide residents a documentation aid, which helps to structure the medical reports without getting lost in unimportant details or forgetting important information. The sequence of anamnesis, clinical examination, considering a differential diagnosis, technical diagnostics, interpretation and therapy is rather an academic classification than a description of the real workflow. In a real setting, most of these steps take place simultaneously. Therefore, the application of the AUD2IT-algorithm should also be carried out according to the real processes. A big advantage of the AUD2IT-algorithm is that it can be used as a structure for the entire treatment process and also is entirely usable as a handover protocol within this process to make sure, that the existing state of knowledge is ensured at each point of a team-timeout. PR-E-(AUD2IT)-algorithm makes it possible to document a treatment process that, in principle, does not have to be limited to the field of emergency medicine. Also, in the outpatient treatment the PR-E-(AUD2IT)-algorithm could be used and further developed. One example could be the preparation and allocation of needed resources at the general practitioner. The algorithm is a standardised tool that can be used by healthcare professionals of any level of training. It gives the user a sense of security in their daily work.

[Construction of the Whole Process Management Model of Hospice and Palliative Care Outpatient Clinic].

Objective To construct a scientific and practical management model of the hospice and palliative care outpatient clinic and provide a reference for the operation and development of the outpatient clinic. Methods The basic framework of the whole process management model of hospice and palliative care outpatient clinic was determined preliminarily by literature analysis,qualitative interviews and experts group meetings.Two rounds of consultation were conducted among 18 experts in hospice and palliative care and medical-nursing combined outpatient service by the Delphi method. Results The questionnaire response rates of the two rounds of expert consultation were both 100% and the authority coefficients of the two rounds of expert consultation were 0.88 and 0.91,respectively.Finally,the whole process management model of hospice and palliative care outpatient clinic was constructed,which was composed of three first-level indicators including staff composition,work structure and effect evaluation,5 second-level indicators and 62 third-level indicators. Conclusion The constructed whole process management model is scientific,innovative and continuous,which can provide a reference for the operation and development of the hospice and palliative care outpatient clinic.

A self-care process model for patients with chronic noncommunicable diseases.

Self-care of patients with chronic noncommunicable diseases is an essential component of contemporary healthcare. The purpose of this paper is to present a novel self-care process model and place it in the broader context of professional care. The extended Event-driven Process Chain approach to process modelling was used, focusing on a detailed overview of sequences of events, connections and activities and other elements/building blocks. A self-care process model was designed. The model is divided into two parts. The first part represents the self-care process when patients are able to manage their symptoms and be independent. The second part includes the process when patients are unable to perform self-care and/or need professional support. By identifying the essential elements of this process and incorporating them into the patients' care process, we can ensure that professional support for self-care creates a dynamic balance in the patients' ecosystems. Patients with chronic noncommunicable diseases need to make timely decisions about individual aspects of their health and seek professional help. In this way, an optimal level of health and well-being of patients can be achieved. Focusing on the patients' self-care process could also reduce treatment costs and improve the quality of life of patients. The novel designed model of the process of self-care, with all its essential elements, can be supported by digital technology, especially in the decision-making process and needs to become an important part of healthcare and long-term care systems.

Modelling and Predictive Monitoring of Business Processes under Uncertainty with Reinforcement Learning.

The analysis of business processes based on their observed behavior recorded in event logs can be performed with process mining. This method can discover, monitor, and improve processes in various application domains. However, the process models produced by typical process discovery methods are difficult for humans to understand due to their high complexity (the so-called "spaghetti-like" process models). Moreover, these methods cannot handle uncertainty or perform predictions because of their deterministic nature. Recently, researchers have been developing predictive approaches for running business cases of processes. This paper focuses on developing a predictive business process monitoring approach using reinforcement learning (RL), which has been successful in other contexts but not yet explored in this area. The proposed approach is evaluated in the banking sector through a use case.

[Exploration of Centralized Purchasing Management Platform for Research Reagent Supplies Based on One-stop Service].

OBJECTIVE: The national requirements for the fund management of scientific research projects are becoming more stringent, so that it is convenient to carry out scientific research work and can strengthen the regulation of scientific research reagent procurement, so this study explores the standardization of the whole process of the procurement of scientific research reagent supplies in hospitals and new modes of management. METHODS: By exploring the implementation of the centralized procurement management platform, we engage in full process supervision before, during, and after the event. RESULTS: Introduction of centralized procurement management platform for scientific research reagent supplies can normalize the procurement process, ensure the quality of procurement and improve the procurement efficiency on the basis of ensuring the quality of scientific research. CONCLUSIONS: The new model of centralized procurement of full process management based on one-stop service for scientific research reagent supplies is an important part of improving the fine scale management of public hospitals, and it is of great significance in improving the level of scientific research in China and avoiding scientific research corruption.

[Management optimization of neovascular age-related macular degeneration in Spain: Evolution towards proactive treatment models]. / Optimización del manejo de la degeneración macular asociada a la edad neovascular en España: evolución hacia modelos proactivos de tratamiento.

INTRODUCTION AND OBJECTIVE: Healthcare resources optimization is crucial to assume the growing demand of neovascular age-related macular degeneration (nAMD). This work provides guidelines and support so that each hospital can lead its change management. METHODS: The OPTIMUS project (n=10 hospitals) was based on face-to-face interviews with the key staff of the ophthalmology services, and alignment with the main responsible for each centre (nominal group) to identify potential needs for improving nAMD. The OPTIMUS nominal group was expanded to 12 centres (eVOLUTION). Through different remote work sessions, different guides and tools were defined and developed to implement proactive treatment strategies, one-step treatment administration and potential for remote visits (eConsult) in nAMD. RESULTS: The information collected from the OPTIMUS interviews and working groups (n=10 centres) defined roadmaps to promote the development of protocols and proactive treatment strategies, including healthcare workload optimization and one-stop treatment administration in nAMD. With eVOLUTION, processes and tools were developed to promote eConsult: (i) healthcare burden calculator; (ii) definition of potential patients for telematic management; (iii) definition of nAMD management archetypes; (iv) definition of processes for implementation of eConsult by archetype; and (v) key performance indicators for changing evaluation. CONCLUSIONS: Managing change is an internal task that requires an adequate diagnosis of processes and feasible implementation roadmaps. OPTIMUS and eVOLUTION provide the basic tools for an autonomous advance of hospitals in the optimization of AMD management, with the available resources.

Guiding the Lean Design of a Hospital's New Laboratory: A Case Study.

PURPOSE: To present the process used by a clinical laboratory to guide the design of their new facility, part of a major campus expansion at a pediatric hospital. OBJECTIVE: The primary objective was to generate information about arrangement and allocation of laboratory space and functional flows in the early phases of the expansion project. BACKGROUND: Seattle Children's Hospital has increased the capacity of their primary campus in response to growing demand for specialized services. The clinical laboratory was identified as one of the functional groups that would move their operations to the new building. METHODS: The clinical laboratory team agreed on a three-stage process to guide the development of their initial design specifications: formulate the concept, develop design alternatives, and evaluate those alternatives. CASE STUDY: The different tasks were executed successfully. The process defined-based on Plan, Do, Check, Act (PDCA)-provided a context for collaboration among sections of the clinical laboratory, reducing silo thinking, so common in the specialized sections within a large clinical laboratory. DISCUSSION: The process was developed to guide the lean design efforts, even when initial space and location parameters had not yet been decided and was sufficiently flexible to accommodate changes in the project constraints and emergent information generated by the concurrent design activities of other hospital functional groups to be included in the campus expansion. The three-stage process allowed the team to review each laboratory section's complexity, create multiple conceptual designs for review, and ultimately increase the likelihood of an efficient physical configuration that would satisfy a diverse group of stakeholders.

The clinical significance of complete process management for the quality control of horizontal rotational resection of a breast mass.

Objective: To explore the clinical outcomes of the complete process management of horizontal rotational resection of a breast mass. Methods: A retrospective study was conducted involving 638 patients who underwent horizontal rotational resection of breast tissue in the Department of Thyroid and Breast Surgery of the People's Hospital of China Medical University from August 2018 to August 2020 using the ultrasound Breast Imaging-Reporting and Data System (BI-RADS) classification of 4A and below. These patients were divided into the experimental group and the control group based on whether the surgery had been performed following the order of the complete process management. The time cutoff point for the two groups was June 2019. The propensity score matching method was used to implement 1:1 ratio matching according to age, mass size, location, ultrasound BI-RADS classification, and breast size (measured by basal diameter), and the patients in the two groups were compared for the duration of surgery (the time needed to performed the three-step 3D positioning), postoperative skin hematoma and ecchymosis, postoperative pathological malignancy rate, residual rate of the mass, and satisfaction rate. Results: After 278 pairs were matched, no statistically significant differences were found between the two groups in terms of demographics (P > 0.05). The duration of surgery in the experimental group was significantly shorter compared with the control group (7.90 ± 2.18 min vs. 10.20 ± 5.99 min, respectively; P < 0.05); the satisfaction score in the experimental group (8.33 ± 1.36) was higher compared with the control group (6.48 ± 1.22) (P < 0.05); the malignant and residual rates of mass in the experimental group were lower than those in the control group, i.e., 6 vs. 21 cases (P < 0.05), and 4 vs. 16 cases, respectively (P < 0.05); the incidence of skin hematoma and ecchymosis was lower in the experimental group, i.e., 3 vs. 21 cases (P < 0.05). Conclusion: Complete process management for horizontal rotational resection of a breast mass can shorten the duration of surgery, reduce the residual mass, postoperative bleeding, and postoperative malignancy rates, and improve the breast preservation rate and patient satisfaction. Accordingly, its popularization represents research value.

Current status and frontier tracking of the China HACCP system.

In today's booming society and in the age of science and technology, the diversification of food processing methods, the continuous extension of the food trade chain, and the potential hazard factors in the food production process all make people pay more and more attention to the establishment, development, and improvement of the hazard analysis and critical control points (HACCP) system. Only terminal control and post-processing supervision of food can guarantee the absolute safety of food. In the process of processing, it is particularly important to strictly identify and evaluate the food safety hazards. To better assist food production enterprises in establishing and implementing HACCP systems, to implement the primary responsibility of food safety, and to improve the theoretical level and practical application of HACCP system in China, an investigation of the current situation and development frontier of HACCP system in China was conducted. Based on the core journal database of China Knowledge Network, the Chinese Social Science Citation Index database, and the Chinese Science Citation Database as the literature search database platform, the study used the CiteSpace visual metrics software system to analyze 1,084 pieces of literature in the field of HACCP research, in order to track the dynamics and impact of research in this field by Chinese research institutions and major authors, and analyze the research hotspots in the field. It is important for further research on HACCP. The results of the study showed that (1) the number of publications in the field of HACCP in China increased steadily from 1992 to 2004 and then began to decrease; (2) the indexes of journals with more publications were more concentrated, and the journal Food Science published the most; (3) the indexes of major research institutions showed that the cultivation bases of the State Key Laboratory of Chinese Medicinal Materials in the Center of Chinese Medicine Resources of the Chinese Academy of Traditional Medicine, the Guangdong Institute of Occupational Diseases, the Nanchang University of Life Sciences, and the Guangdong Institute of Occupational Diseases were more concentrated. Prevention and Treatment Institute, School of Life Sciences of Nanchang University, China Aquatic Products Quality Certification Center, School of Food Science and Nutrition Engineering of China Agricultural University, and other research structures have the most publications and strong scientific research strength; (4) from the main author indicators, the research in the field of HACCP has formed a total of four more active research teams, involving Chinese herbal medicine, ecological planting, ecological agriculture, occupational disease prevention and treatment, light industry handicrafts, computer software and computer application, agricultural economy, and other research directions. The cooperation between the authors of each team is closer. It is suggested that in terms of food safety requirements, China should not only integrate the traditional supervision measures for food terminals and after the event but also reflect the role of food hazard analysis and assessment in the production process and comprehensively integrate the pre-production, production, and post-production management of food so that food can really be safe.

Effect of a computerized decision support system on the treatment approach of stage III or IV pressure injury in patients with spinal cord injury: a feasibility study.

BACKGROUND: Stage III and IV pressure injuries (PIs) in patients with spinal cord injury (SCI) require complex interdisciplinary and interprofessional treatment approaches that are difficult to implement. Practical aspects, such as information exchange and coordination, remain challenging. We investigated whether a computerized decision support system (CDSS) could increase treatment adherence and improve clinical outcomes and interprofessional collaboration. METHOD: In this feasibility study, a core team developed the initial treatment process and adapted it based on several discussions with clinical experts and information technologists. The CDSS followed the Basel Decubitus Approach and was used in a clinic specializing in SCI. Thirty patients with SCI admitted for stage III/IV PI between July 2016 and May 2017 were randomly allocated to standard or CDSS-supported care. Between-group differences in treatment adherence, complication rates, length of stay, and costs were analyzed using descriptive statistics. The use of the CDSS and potential barriers and facilitators were evaluated through interprofessional focus groups, transcribed verbatim, and thematically analyzed (30 participants). RESULTS: No differences in SCI characteristics, comorbidities, or PI characteristics (localization: ischium [number (n) = 19 PI, 63%], sacrum [n = 10 PI, 33%], recurrent PI [n = 21, 70%]) were found between the two groups. Furthermore, no statistically significant differences were observed in treatment adherence, frequency of major (20% vs. 13% between CDSS and control group) and minor (33% vs 27%) complications, and length of stay (98 [±28] vs 81 [±23] days). Healthcare professionals found the CDSS to be helpful for visualizing the treatment process. However, the high workload and difficulties in the information technology processes, such as missing reminders, slow computer performance and data processing, and poor accessibility, hindered the effective implementation of the CDSS. CONCLUSION: The implementation of the CDSS to support the treatment of stage III/IV PI in patients with SCI was feasible and included definitions of milestones, interventions, and outcomes. However, to assess the impact of the CDSS, a longer observation period is required. Further, the technical difficulties must be addressed, and solid integration of the CDSS into the clinical information system is necessary. TRIAL REGISTRATION: This quality improvement project received a declaration of no objection from the Ethics Committee of Northwest and Central Switzerland (EKNZ UBE-16/003), and ethical approval was received for the focus groups (EKNZ Req-2017-00860).

Assessment of Patient Treatment and Rehabilitation Processes Using Electromyography Signals and Selected Industry 4.0 Solutions.

Funding treatment and rehabilitation processes for patients with musculoskeletal conditions is an important part of public health insurance in European Union countries. By 2030, these processes will be planned in national health strategies (sequential process activities will be identified, care packages will be defined, service standards will be described, roles in the implementation of activities will be distinguished). Today, in many countries of the world (including the EU countries), these processes tend not to be very effective and to be expensive for both patients and insurance companies. This article aims to raise awareness of the need for process re-engineering and describes possible tools for assessing patient treatment and rehabilitation processes (using electromyographic signals-EMG and selected Industry 4.0 solutions). This article presents the research methodology prepared for the purpose of process evaluation. The use of this methodology will confirm the hypothesis that the use of EMG signals and selected Industry 4.0 solutions will improve the effectiveness and efficiency of treatment and rehabilitation processes for patients with musculoskeletal injuries.

The effect of machine learning tools for evidence synthesis on resource use and time-to-completion: protocol for a retrospective pilot study.

BACKGROUND: Machine learning (ML) tools exist that can reduce or replace human activities in repetitive or complex tasks. Yet, ML is underutilized within evidence synthesis, despite the steadily growing rate of primary study publication and the need to periodically update reviews to reflect new evidence. Underutilization may be partially explained by a paucity of evidence on how ML tools can reduce resource use and time-to-completion of reviews. METHODS: This protocol describes how we will answer two research questions using a retrospective study design: Is there a difference in resources used to produce reviews using recommended ML versus not using ML, and is there a difference in time-to-completion? We will also compare recommended ML use to non-recommended ML use that merely adds ML use to existing procedures. We will retrospectively include all reviews conducted at our institute from 1 August 2020, corresponding to the commission of the first review in our institute that used ML. CONCLUSION: The results of this study will allow us to quantitatively estimate the effect of ML adoption on resource use and time-to-completion, providing our organization and others with better information to make high-level organizational decisions about ML.