An Ontology to Bridge the Clinical Management of Patients and Public Health Responses for Strengthening Infectious Disease Surveillance: Design Science Study.

Background: Novel surveillance approaches using digital technologies, including the Internet of Things (IoT), have evolved, enhancing traditional infectious disease surveillance systems by enabling real-time detection of outbreaks and reaching a wider population. However, disparate, heterogenous infectious disease surveillance systems often operate in silos due to a lack of interoperability. As a life-changing clinical use case, the COVID-19 pandemic has manifested that a lack of interoperability can severely inhibit public health responses to emerging infectious diseases.

Personalized Assistive Technologies for Motor-Impaired Students: A Case of Learning Process Mining.

Motor disability includes the lack of sensation, movement, or coordination, and Assistive Technologies (AT) can help overcome these challenges. Motor-disabled students need different ATs and configurations depending on courses and individual needs, and some solutions can be expensive. Some affordable AT has roots in gaming but can also be used for other purposes.

DIdM-EIoTD: Distributed Identity Management for Edge Internet of Things (IoT) Devices.

The Internet of Things (IoT) paradigm aims to enhance human society and living standards with the vast deployment of smart and autonomous devices, which requires seamless collaboration. The number of connected devices increases daily, introducing identity management requirements for edge IoT devices. Due to IoT devices' heterogeneity and resource-constrained configuration, traditional identity management systems are not feasible.

dfgcompare: a library to support process variant analysis through Markov models.

Background: Data-driven process analysis is an important area that relies on software support. Process variant analysis is a sort of analysis technique in which analysts compare executed process variants, a.k.

IMSC-EIoTD: Identity Management and Secure Communication for Edge IoT Devices.

The Internet of things (IoT) will accommodate several billions of devices to the Internet to enhance human society as well as to improve the quality of living. A huge number of sensors, actuators, gateways, servers, and related end-user applications will be connected to the Internet. All these entities require identities to communicate with each other.

Evaluating a Clinical Decision Support System for Drug-Drug Interactions.

Janusmed is a clinical decision support system, developed by the Stockholm County Council that supports physicians in identifying drug-drug interactions. To determine how Janusmed is used in and affects the clinical practice, an evaluation study is currently being carried out that analyzes multiple data sources through descriptive statistics. The study focuses on how Janusmed affects the behavior of the physicians, in particular, to what extent physicians reconsider their prescription decisions based on warnings from Janusmed.

The coordination hub: Toward patient-centered and collaborative care processes.

The organization and processes of today's health and social care are becoming ever more complex as a consequence of societal trends, including an aging population and an increased reliance on care at home. One aspect of the increased complexity is that a single patient may receive care from several care providers, which easily results in situations with potentially incoherent, uncoordinated, and interfering care processes. In order to describe and analyze such situations, the article introduces the notion of a process conglomeration.

A new approach for goal-oriented analysis of healthcare processes.

The development of efficient e-services for patient-centered healthcare requires insight into concrete problems in administrative and clinical work processes as well as an understanding of the strategic goals that should guide these healthcare processes. However, considering both concrete process related problems and high-level strategic goals during process analysis and solution design can be problematic. To address this, we propose a structured approach for analyzing both high- and low-level goals in a healthcare process and relating these to identified problems.