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Title: | New Approach to Privacy-Preserving Clinical Decision Support Systems for HIV Treatment | Authors: | Spini, Gabriele MANCINI, Emiliano Attema, Thomas Abspoel, Mark de Gier, Jan Fehr, Serge Veugen, Thijs van Heesch, Maran Worm, Daniel De Luca, Andrea Cramer, Ronald Sloot, Peter M. A. |
Issue Date: | 2022 | Publisher: | SPRINGER | Source: | JOURNAL OF MEDICAL SYSTEMS, 46 (12) (Art N° 84) | Abstract: | Background HIV treatment prescription is a complex process. Clinical decision support systems (CDSS) are a category of health information technologies that can assist clinicians to choose optimal treatments based on clinical trials and expert knowledge. The usability of some CDSSs for HIV treatment would be significantly improved by using the knowledge obtained by treating other patients. This knowledge, however, is mainly contained in patient records, whose usage is restricted due to privacy and confidentiality constraints. Methods A treatment effectiveness measure, containing valuable information for HIV treatment prescription, was defined and a method to extract this measure from patient records was developed. This method uses an advanced cryptographic technology, known as secure Multiparty Computation (henceforth referred to as MPC), to preserve the privacy of the patient records and the confidentiality of the clinicians' decisions. Findings Our solution enables to compute an effectiveness measure of an HIV treatment, the average time-to-treatment-failure, while preserving privacy. Experimental results show that our solution, although at proof-of-concept stage, has good efficiency and provides a result to a query within 24 min for a dataset of realistic size. Interpretation This paper presents a novel and efficient approach HIV clinical decision support systems, that harnesses the potential and insights acquired from treatment data, while preserving the privacy of patient records and the confidentiality of clinician decisions. | Notes: | Spini, G (corresponding author), TNO, Appl Cryptog & Quantum Algorithms, NL-2509 JE The Hague, Netherlands. gabriele.spini@tno.nl |
Keywords: | Clinical decision support systems;Anti-HIV agents;Secure multiparty computation;Privacy;Confidentiality | Document URI: | http://hdl.handle.net/1942/38865 | ISSN: | 0148-5598 | e-ISSN: | 1573-689X | DOI: | 10.1007/s10916-022-01851-x | ISI #: | 000870256900001 | Rights: | The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons. org/licenses/by/4.0/. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2023 |
Appears in Collections: | Research publications |
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