The adoption of blockchain shows a variety of benefits owing to an incorruptible digital ledger and a decentralized database. This has eliminated the need for a gatekeeper to oversee all associated transactions. Blockchain, the underlying technology behind Bitcoin and other crypto-currencies, has found use in many industries besides finance, such as healthcare, where it is used for verifying medical licensing and credentialing, for tracking medical equipment (or consumables) from production to usage, and in cases associated with high levels of privacy and security. Patient data is collected using a plethora of patient-generated data devices, such as Internet of Things (IoT)-enabled wearables, health trackers, and home use medical devices. As a result, the data is siloed amongst several applications and/or vendors’ proprietary solutions. Of all this data, only some of it is transmitted to Electronic Medical Records. This produces the risk that not all data collected will be reviewed at the point of care due to the abundance of data collected. This article explains the areas within healthcare where blockchain could address data usability challenges and analyzes new ways in which patient health data can be collected to address the increasing number of challenges associated with the amount of data being generated over time. It also describes the drivers behind this data collection trend, the associated challenges and the subsequent ramifications. It concludes with a review of previous studies on data usability challenges and the means by which blockchain can be used to overcome these challenges.

The use of ergonomic evaluation tools can help in identifying the potential for musculoskeletal disorders (MSDs) arising from the design of work tasks. Rapid upper limb assessment (RULA) and rapid entire body assessment (REBA) are ergonomic assessment tools developed to evaluate the risks associated with these disorders. Both tools primarily evaluate these risks by examining body joint angle inputs, specifically by estimating a single joint angle, but in realistic situations, a full range of angles experienced is required to produce reliable evaluation. Furthermore, users of these tools may be uncertain of his/her estimation, especially if only a single joint angle is considered. A new approach based on Monte-Carlo simulation (MCS) in which joint angles are represented in distributions instead of single values is proposed to handle such issues. An empirical example is presented to compare traditional RULA and REBA to Monte-Carlo-RULA/Monte-Carlo-REBA approaches. The proposed approach exhibited a higher degree of sensitivity with respect to joint angles associated with variability and uncertainty.

Global supply chain shocks and interruptions underscore the importance of supply chain nervousness (SCN). A clear understanding of nervousness in the event of a crisis allows an organization to make a good plan to deal with interruptions and future shocks. This study aims to develop a model for assessing nervousness parameters in the supply chains (SCs) by incorporating the fuzzy-FMEA theory and gray correlation approach to rank the SCN factors. The integrated model used in this study can improve the accuracy of outcomes when uncertainty exists in the SCN data. The results show that the most important nervousness factors are SC planning, visibility, stability, decision support systems, and SC flexibility. The developed SCN approach allows understanding and prioritizing SCN factors with more realistic and effective assessment. Findings offer beneficial insights for SCN prevention, and suggestions are made to identify nervousness mitigations. The outcomes of this research can be used by researchers and SC specialists to develop decision support systems.

Patient satisfaction is an important and frequently used outcome measure for the quality of healthcare services. Any increase in patient satisfaction scores translates directly into an improved reputation, customer loyalty, profitability, and growth. This study investigates the effect of a well-designed work environment on medical laboratory employee satisfaction and in turn on patient satisfaction. The Quality Function Deployment methodology is used to translate the voice of patients into a set of critical to quality ergonomic aspects that are converted to prioritized and actionable ergonomic processes. By understanding the importance of ergonomic process elements of medical laboratory employee satisfaction and their effect on patient satisfaction level, it is possible to make informed decisions about the workplace elements that need to be considered for improvement. The results of this study highlight the role and responsibilities of healthcare execution managers in creating ergonomics-based organizational policies and strategies, leading to improved healthcare quality performance and financial results.