An Evaluation of Patient Privacy Protection with Fuzzy Conjoint Analysis—A Case Study from Nurses’ Perspective

Author:

Gürsel Güney1,Bayer Nükhet2,Turunç Ömer3,Çalışkan Abdullah4,Akkoç İrfan5,Demirci Ayhan6,Çetin Melike7,Köroğlu Özlem4

Affiliation:

1. Software Engineering Department, Faculty of Engineering and Architecture, Konya Food and Agriculture University, Konya 42080, Turkey

2. Department of Health Sciences, Lokman Hekim University, Ankara 06530, Turkey

3. Business Administration Department, Faculty of Economic, Administrative and Social Sciences, Antalya Bilim University, Antalya 07110, Turkey

4. Health Management Department, School of Health Sciences, Toros University, Mersin 33140, Turkey

5. Rectorate, Izmir Tinaztepe University, İzmir 35400, Turkey

6. Department of International Trade and Logistics, Faculty of Economic, Administrative and Social Sciences, Toros University, Mersin 33140, Turkey

7. Department of Economics, Faculty of Economic, Administrative and Social Sciences, Antalya Bilim University, Antalya 07110, Turkey

Abstract

Background: With the rapid improvement in healthcare technologies, the security and privacy of the most sensitive data are at risk. Patient privacy has many components, even when data are in electronic format. Although patient privacy has extensively been discussed in the literature, there is no study that has presented all components of patient privacy. Methods: This study presents a complete assessment framework, develops an inventory as an assessment tool, and examines the reliability and validity of the inventory. The study was carried out in three phases: conceptual framework development, inventory development, and an evaluation case study. Fuzzy conjoint analysis was used in the evaluation to deal with subjectivity and ambiguity. As a result of the evaluation, the case study institution was given a patient privacy maturity level between 1 and 5, where 1 is the worst and 5 is the best. Results: The case study evaluated the largest hospital in Turkey, which employs 800 nurses. Half of the nurses, 400, participated in the study. According to the literature, healthcare institutions do not invest enough in protecting patients’ privacy, and the results of the study support this finding. The institution’s maturity level was 2, which is poor. Conclusions: This study measured privacy maturity with many assessment components. The result of the assessment explains to patients and the public whether their data are secure or not. With the implementation of this maturity level, patients have an idea about which institution to choose, and the public can infer the reliability of institutions in terms of patient privacy.

Funder

Scientific and Technological Research Council of Turkey

Publisher

MDPI AG

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