An ethical assessment model for digital disease detection technologies
Bibliographic Data
| ID | 8248684 |
|---|---|
| Authors | Kerstin Denecke (0000-0001-6691-396X, Bern University of Applied Sciences, corresponding author) |
| Year | 2017 |
| Volume | 13 |
| Issue | 1 |
| Pages | 16-16 |
| Publication date | 2017-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Life Sciences Society and Policy (JOURNAL) |
| Journal identifiers | ISSN: 2195-7819 • E-ISSN: 2195-7819 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1186/s40504-017-0062-x |
| PMID | 28929347 |
| OpenAlex | W2752065644 |
| Language | EN |
| Citations received | 1 |
| References cited | 16 |
Digital epidemiology, also referred to as digital disease detection (DDD), successfully provided methods and strategies for using information technology to support infectious disease monitoring and surveillance or understand attitudes and concerns about infectious diseases. However, Internet-based research and social media usage in epidemiology and healthcare pose new technical, functional and formal challenges. The focus of this paper is on the ethical issues to be considered when integrating digital epidemiology with existing practices. Taking existing ethical guidelines and the results from the EU project M-Eco and SORMAS as starting point, we develop an ethical assessment model aiming at providing support in identifying relevant ethical concerns in future DDD projects. The assessment model has four dimensions: user, application area, data source and methodology. The model supports in becoming aware, identifying and describing the ethical dimensions of DDD technology or use case and in identifying the ethical issues on the technology use from different perspectives. It can be applied in an interdisciplinary meeting to collect different viewpoints on a DDD system even before the implementation starts and aims at triggering discussions and finding solutions for risks that might not be acceptable even in the development phase. From the answers, ethical issues concerning confidence, privacy, data and patient security or justice may be judged and weighted
Data science · Digital health · Economic Justice · Engineering ethics · Ethical issues · Health care · Knowledge management · Management science · Political science · The Internet · Viewpoints · World Wide Web · Computer Science · COVID-19 Digital Contact Tracing · Data-Driven Disease Surveillance · Engineering · Focus Groups and Qualitative Methods
| Citations per year | 0.25 |
|---|---|
| Citation span | 2022 - 2022 (1) |
| Highly cited | No |