Health information is central to changes in healthcare: A clinician’s view

2017 ◽  
Vol 48 (1) ◽  
pp. 48-51 ◽  
Author(s):  
Philip Hoyle

Changes in healthcare, such as integrated care, the use of big data, electronic health records (EHRs), telemedicine, decision support systems and consumer empowerment, are impacting on the management of health information. Integrated care requires linked data; activity-based funding requires valid coding; EHRs require standards for documentation, retrieval and analysis; and decision support systems require standardised nomenclatures. The ethical oversight of how health-related information is used, as opposed to governance of its content, storage and communication, remains ill-defined. More fundamentally, the conceptual foundations of health information in terms of “diagnostic” constructs are creating limitations: Why should a medical diagnosis be privileged as the key descriptor of care, over disability or other aspects of the human experience? Who gets to say what matters, and how and by whom is that translated into meaningful information? These are important questions on which the health information management profession is well placed to lead. In this changing environment, threats and opportunities for the profession are presented and discussed. Highlighted is the need for leadership from the profession on the ethical use of health information.

2014 ◽  
Vol 6 (1) ◽  
pp. 60-80 ◽  
Author(s):  
Pietro Baroni ◽  
Daniela Fogli ◽  
Massimiliano Giacomin ◽  
Giovanni Guida ◽  
Loredana Parasiliti Provenza ◽  
...  

This article presents a participatory design approach to Decision Support Systems, which is specifically built to face the socio-technical gap that often impedes DSS acceptability by end-users in real work environments. The approach has been experimented in two case studies in the field of health-related emergencies, namely earthquake and pandemic flu. The application of the approach and the results obtained are described with specific focus on the phases of requirement analysis and system evaluation.


Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1060
Author(s):  
Daniele Spoladore ◽  
Elena Pessot

New models and technological advances are driving the digital transformation of healthcare systems. Ontologies and Semantic Web have been recognized among the most valuable solutions to manage the massive, various, and complex healthcare data deriving from different sources, thus acting as backbones for ontology-based Decision Support Systems (DSSs). Several contributions in the literature propose Ontology engineering methodologies (OEMs) to assist the formalization and development of ontologies, by providing guidelines on tasks, activities, and stakeholders’ participation. Nevertheless, existing OEMs differ widely according to their approach, and often lack of sufficient details to support ontology engineers. This paper performs a meta-review of the main criteria adopted for assessing OEMs, and major issues and shortcomings identified in existing methodologies. The key issues requiring specific attention (i.e., the delivery of a feasibility study, the introduction of project management processes, the support for reuse, and the involvement of stakeholders) are then explored into three use cases of semantic-based DSS in health-related fields. Results contribute to the literature on OEMs by providing insights on specific tools and approaches to be used when tackling these issues in the development of collaborative OEMs supporting DSS.


Sign in / Sign up

Export Citation Format

Share Document