Trust, Responsibility, and Quality in Digital Health: Qualitative Insights Into the Enhancement of Health Information Systems
DOI:
https://doi.org/10.59890/mjst.v3i1.133Abstract
Digital health technologies have revolutionised healthcare delivery by improving accessibility, efficiency, and patient outcomes. However, persistent challenges in trust, responsibility, and quality hinder the optimal development of health information systems (HIS). This study aims to provide a comprehensive qualitative understanding of these three critical dimensions and their interplay in digital health environments. Employing a qualitative literature review methodology, data were systematically collected from 80 peer-reviewed articles retrieved from various academic databases. The selected literature was analysed using thematic synthesis, focusing on both conceptual frameworks and empirical findings relevant to trust, responsibility, and quality within HIS. The analysis reveals that trust is primarily shaped by concerns about data privacy, transparency in processes, and the robustness of institutional governance, which directly impact user adoption and sustained engagement with digital platforms. Responsibility is identified as a complex and evolving issue, marked by unclear accountability in multi-stakeholder digital health ecosystems, necessitating clearer ethical guidelines and formalised accountability mechanisms. Quality is multifaceted, encompassing data accuracy, system reliability, interoperability, and usability, all crucial to ensuring clinical effectiveness and user satisfaction. The findings demonstrate that trust, responsibility, and quality are deeply interrelated, with improvements in one area positively influencing the others, suggesting the need for integrated approaches in system design and policy-making
References
Adjekum, A., Blasimme, A., & Vayena, E. (2018). Elements of trust in digital health systems: scoping review. Journal of Medical Internet Research, 20(12), e11254. https://doi.org/10.2196/11254
Adler-Milstein, J., & Jha, A. K. (2017). HITECH Act drove large gains in hospital electronic health record adoption. Health Affairs, 36(8), 1416–1422. https://doi.org/10.1377/hlthaff.2016.1651
Afework, A., Tamene, A., Tesfaye, A., Tafa, A., & Gemede, S. (2023). Status and factors affecting patient safety culture at Dilla University teaching hospital: a mixed-method cross-sectional study. Risk Management and Healthcare Policy, 1157–1169. https://doi.org/10.2147/RMHP.S419990
Atalay, H. N., & Yücel, Ş. (2024). Decoding privacy concerns: the role of perceived risk and benefits in personal health data disclosure. Archives of Public Health, 82(1), 180. https://doi.org/10.1186/s13690-024-01416-z
Belfrage, S., Helgesson, G., & Lynøe, N. (2022). Trust and digital privacy in healthcare: a cross-sectional descriptive study of trust and attitudes towards uses of electronic health data among the general public in Sweden. BMC Medical Ethics, 23(1), 19. https://doi.org/10.1186/s12910-022-00758-z
Binzer, B., Kendziorra, J., Witte, A. K., & Winkler, T. J. (2024). Trust in public and private providers of health apps and usage intentions: a sectoral privacy calculus and control perspective. Business & Information Systems Engineering, 66(3), 273–297. https://doi.org/10.1007/s12599-024-00869-4
Brotherdale, R., Berry, K., Branitsky, A., & Bucci, S. (2024). Co-producing digital mental health interventions: a systematic review. Digital Health, 10, 20552076241239172. https://doi.org/10.1177/20552076241239172
Catapan, S. D. C., Sazon, H., Zheng, S., Gallegos-Rejas, V., Mendis, R., Santiago, P. H., & Kelly, J. T. (2025). A systematic review of consumers’ and healthcare professionals’ trust in digital healthcare. NPJ Digital Medicine, 8(1), 115. https://doi.org/10.1038/s41746-025-01510-8
Cho, D. B., Lee, Y. R., Lee, W., Lee, E. S., & Lee, J. H. (2021). Analyzing health information technology and electronic medical record system-related patient safety incidents using data from the Korea Patient Safety Reporting and Learning System. Quality Improvement in Health Care, 27(2), 57–72. https://doi.org/10.14371/QIH.2021.27.2.57
Cooper, J., Edwards, A., Williams, H., Sheikh, A., Parry, G., Hibbert, P., & Carson-Stevens, A. (2017). Nature of blame in patient safety incident reports: mixed methods analysis of a national database. The Annals of Family Medicine, 15(5), 455–461. https://doi.org/10.1370/afm.2123
Costantino, A., Noviello, D., Mazza, S., Berté, R., Caprioli, F., & Vecchi, M. (2020). Trust in telemedicine from IBD outpatients during the COVID-19 pandemic. Digestive and Liver Disease, 53(3), 291. https://doi.org/10.1016/j.dld.2020.10.035
De La Torre-D’iez, I., L’opez-Coronado, M., Vaca, C., Aguado, J. S., & de Castro, C. (2015). Cost-utility and cost-effectiveness studies of telemedicine, electronic, and mobile health systems in the literature: a systematic review. Telemedicine and E-Health, 21(2), 81–85. https://doi.org/10.1089/tmj.2014.0053
Dhagarra, D., Goswami, M., & Kumar, G. (2020). Impact of trust and privacy concerns on technology acceptance in healthcare: an Indian perspective. International Journal of Medical Informatics, 141, 104164. https://doi.org/10.1016/j.ijmedinf.2020.104164
Dobrow, M. J., Bytautas, J. P., Tharmalingam, S., & Hagens, S. (2019). Interoperable electronic health records and health information exchanges: systematic review. JMIR Medical Informatics, 7(2), e12607. https://doi.org/10.2196/12607
Farzandipour, M., Nabovati, E., Tadayon, H., & Jabali, M. S. (2021). Usability evaluation of a nursing information system by applying cognitive walkthrough method. International Journal of Medical Informatics, 152, 104459. https://doi.org/10.1016/j.ijmedinf.2021.104459
Garza, M. Y., Williams, T., Ounpraseuth, S., Hu, Z., Lee, J., Snowden, J., & Zozus, M. N. (2024). Error rates of data processing methods in clinical research: a systematic review and meta-analysis of manuscripts identified through PubMed. International Journal of Medical Informatics, 105749. https://doi.org/10.1016/j.ijmedinf.2024.105749
Ghaffari Heshajin, S., Sedghi, S., Panahi, S., & Takian, A. (2024). A framework for health information governance: a scoping review. Health Research Policy and Systems, 22(1), 109. https://doi.org/10.1186/s12961-024-01193-9
Gille, F., Smith, S., & Mays, N. (2015). Why public trust in health care systems matters and deserves greater research attention. Journal of Health Services Research & Policy, 20(1), 62–64. https://doi.org/10.1177/1355819614543161
Goktas, P., & Grzybowski, A. (2025). Shaping the future of healthcare: Ethical clinical challenges and pathways to trustworthy AI. Journal of Clinical Medicine, 14(5), 1605. https://doi.org/10.3390/jcm14051605
Graber, M. L., Byrne, C., & Johnston, D. (2017). The impact of electronic health records on diagnosis. Diagnosis, 4(4), 211–223. https://doi.org/10.1515/dx-2017-0012
Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J., Hughes, G., Hinder, S., & Shaw, S. (2017). Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. Journal of Medical Internet Research, 19(11), e8775. https://doi.org/10.2196/jmir.8775
Griffin, F. (2021). Artificial intelligence and liability in health care. Health Matrix, 31, 65.
Gupta, R., Iyengar, R., Sharma, M., Cannuscio, C. C., Merchant, R. M., Asch, D. A., & Grande, D. (2023). Consumer views on privacy protections and sharing of personal digital health information. JAMA Network Open, 6(3), e231305--e231305. https://doi.org/10.1001/jamanetworkopen.2023.1305
Herrera-Poyatos, A., Del Ser, J., de Prado, M. L., Wang, F. Y., Herrera-Viedma, E., & Herrera, F. (2025). Responsible Artificial Intelligence Systems: A Roadmap to Society’s Trust through Trustworthy AI, Auditability, Accountability, and Governance. ArXiv Preprint ArXiv:2503.04739.
Hossain, M. I., Steigner, T., Hussain, M. I., & Akther, A. (2024). Enhancing data integrity and traceability in industry cyber physical systems (ICPS) through Blockchain technology: A comprehensive approach.
Islam, M. N., Karim, M. M., Inan, T. T., & Islam, A. N. (2020). Investigating usability of mobile health applications in Bangladesh. BMC Medical Informatics and Decision Making, 20, 1–13. https://doi.org/10.1186/s12911-020-1033-3
Jayathissa, P., & Hewapathirana, R. (2023). Enhancing interoperability among health information systems in low-and middle-income countries: a review of challenges and strategies. ArXiv Preprint, arXiv:2309.
Johnson, N., Moharana, S., Harrington, C., Andalibi, N., Heidari, H., & Eslami, M. (2024). The Fall of an algorithm: Characterizing the dynamics toward abandonment. Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 337–358. https://doi.org/10.1145/3593013.3594079
Kästner, L., Langer, M., Lazar, V., Schomäcker, A., Speith, T., & Sterz, S. (2021). On the relation of trust and explainability: Why to engineer for trustworthiness. 2021 IEEE 29th International Requirements Engineering Conference Workshops (REW), 169–175. https://doi.org/10.1109/REW53955.2021.00042
Keesara, S., Jonas, A., & Schulman, K. (2020). Covid-19 and health care’s digital revolution. New England Journal of Medicine, 382(23), e82. https://doi.org/10.1056/NEJMp2005835
Kerasidou, A., & Kerasidou, C. (2023). Data-driven research and healthcare: public trust, data governance and the NHS. BMC Medical Ethics, 24(1), 51. https://doi.org/10.1186/s12910-023-00922-z
Kim, M. O., Coiera, E., & Magrabi, F. (2017). Problems with health information technology and their effects on care delivery and patient outcomes: a systematic review. Journal of the American Medical Informatics Association, 24(2), 246–250. https://doi.org/10.1093/jamia/ocw154
Kuen, L., Schürmann, F., Westmattelmann, D., Hartwig, S., Tzafrir, S., & Schewe, G. (2023). Trust transfer effects and associated risks in telemedicine adoption. Electronic Markets, 33(1), 35. https://doi.org/10.1007/s12525-023-00657-0
Kuo, K.-M., Liu, C.-F., Talley, P. C., & Pan, S.-Y. (2018). Strategic improvement for quality and satisfaction of hospital information systems. Journal of Healthcare Engineering, 2018(1), 3689618. https://doi.org/10.1155/2018/3689618
Kutney-Lee, A., Carthon, J. M. B., Sloane, D. M., Bowles, K. H., McHugh, M. D., & Aiken, L. H. (2021). Electronic health record usability: associations with nurse and patient outcomes in hospitals. Medical Care, 59(7), 625–631. https://doi.org/10.1097/MLR.0000000000001536
Laurisz, N., Ćwiklicki, M., Żabiński, M., Canestrino, R., & Magliocca, P. (2023). The stakeholders’ involvement in Healthcare 4.0 services Provision: the perspective of Co-creation. International Journal of Environmental Research and Public Health, 20(3), 2416. https://doi.org/10.3390/ijerph20032416
Li, D. M., Parikh, S., & Costa, A. (2025). A critical look into artificial intelligence and healthcare disparities. Frontiers in Artificial Intelligence, 8, 1545869. https://doi.org/10.3389/frai.2025.1545869
Liu, X., Rivera, S. C., Moher, D., Calvert, M. J., Denniston, A. K., Ashrafian, H., & Yau, C. (2020). Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension. The Lancet Digital Health, 2(10), e537--e548. https://doi.org/10.1016/S2589-7500(20)30218-1
Margam, R. (2023). Ethics and data privacy: the backbone of trustworthy healthcare practices. Socio-Economic and Humanistic Aspects for Township and Industry, 1(2), 232–236.
Marzban, S., Najafi, M., Agolli, A., & Ashrafi, E. (2022). Impact of patient engagement on healthcare quality: a scoping review. Journal of Patient Experience, 9, 23743735221125440. https://doi.org/10.1177/23743735221125439
McLennan, S., Fiske, A., Tigard, D., Müller, R., Haddadin, S., & Buyx, A. (2022). Embedded ethics: a proposal for integrating ethics into the development of medical AI. BMC Medical Ethics, 23(1), 6. https://doi.org/10.1186/s12910-022-00746-3
Meier, E., Rigter, T., Schijven, M. P., van den Hoven, M., & Bak, M. A. R. (2024). The impact of digital health technologies on moral responsibility: a scoping review. Medicine, Health Care and Philosophy, 1–15. https://doi.org/10.1007/s11019-024-10238-3
Mennella, C., Maniscalco, U., De Pietro, G., & Esposito, M. (2024). Ethical and regulatory challenges of AI technologies in healthcare: A narrative review. Heliyon, 10(4). https://doi.org/10.1016/j.heliyon.2024.e26297
Mittelstadt, B. (2017). Ethics of the health-related internet of things: a narrative review. Ethics and Information Technology, 19(3), 157–175. https://doi.org/10.1007/s10676-017-9426-4
Moy, A. J., Hobensack, M., Marshall, K., Vawdrey, D. K., Kim, E. Y., Cato, K. D., & Rossetti, S. C. (2023). Understanding the perceived role of electronic health records and workflow fragmentation on clinician documentation burden in emergency departments. Journal of the American Medical Informatics Association, 30(5), 797–808. https://doi.org/10.1093/jamia/ocad038
Munn, Z., Peters, M. D., Stern, C., Tufanaru, C., McArthur, A., & Aromataris, E. (2018). Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Medical Research Methodology, 18, 1–7. https://doi.org/10.1186/s12874-018-0611-x
Neumann, V., Davidge, G., Harding, M., Cunningham, J., Davies, N., Devaney, S., & Ainsworth, J. (2023). Examining public views on decentralised health data sharing. Plos One, 18(3), e0282257. https://doi.org/10.1371/journal.pone.0282257
Ong, J., Parchment, V., & Zheng, X. (2018). Effective regulation of digital health technologies. Journal of the Royal Society of Medicine, 111(12), 439–443. https://doi.org/10.1177/0141076818812437
Parthasarathy, A., Phalnikar, A., Jauhar, A., Somayajula, D., Krishnan, G. S., & Ravindran, B. (2024). Participatory Approaches in AI Development and Governance: A Principled Approach. ArXiv Preprint ArXiv:2407.13100.
Pettersson, L., Johansson, S., Demmelmaier, I., & Gustavsson, C. (2023). Disability digital divide: survey of accessibility of eHealth services as perceived by people with and without impairment. BMC Public Health, 23(1), 181. https://doi.org/10.1186/s12889-023-15094-z
Procter, R., Tolmie, P., & Rouncefield, M. (2023). Holding AI to account: challenges for the delivery of trustworthy AI in healthcare. ACM Transactions on Computer-Human Interaction, 30(2), 1–34. https://doi.org/10.1145/3583422
Raji, I. D., Smart, A., White, R. N., Mitchell, M., Gebru, T., Hutchinson, B., & Barnes, P. (2020). Closing the AI accountability gap: Defining an end-to-end framework for internal algorithmic auditing. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 33–44. https://doi.org/10.48550/arXiv.2001.00973
Rong, Y., Castner, N., Bozkir, E., & Kasneci, E. (2022). User trust on an explainable ai-based medical diagnosis support system. ArXiv Preprint ArXiv:2204.12230.
Rowland, S. P., Fitzgerald, J. E., Lungren, M., Lee, E., Harned, Z., & McGregor, A. H. (2022). Digital health technology-specific risks for medical malpractice liability. NPJ Digital Medicine, 5(1), 157. https://doi.org/10.1038/s41746-022-00698-3
Ruotsalainen, P., & Blobel, B. (2020). Health information systems in the digital health ecosystem—problems and solutions for ethics, trust and privacy. International Journal of Environmental Research and Public Health, 17(9), 3006. https://doi.org/10.3390/ijerph17093006
Schroeder, T., Haug, M., & Gewald, H. (2022). Data privacy concerns using mHealth apps and smart speakers: comparative interview study among mature adults. JMIR Formative Research, 6(6), e28025. https://doi.org/10.2196/28025
Seroussi, B., & Zablit, I. (2024). Implementation of digital health ethics: a first step with the adoption of 16 European ethical principles for digital health. MEDINFO 2023—The Future Is Accessible, 1588–1592. https://doi.org/10.3233/SHTI230530
Shamsujjoha, M., Grundy, J., Li, L., Khalajzadeh, H., & Lu, Q. (2021). Human-centric issues in ehealth app development and usage: A preliminary assessment. 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), 506–510. https://doi.org/10.1109/SANER50967.2021.00071
Sharma, T., Dhull, A., Singh, A., & Singh, K. K. (2025). Designing transparent and accountable AI systems for healthcare. In Responsible and Explainable Artificial Intelligence in Healthcare (pp. 91–106). Academic Press. https://doi.org/10.1016/B978-0-443-24788-0.00004-2
Shaw, J., Rudzicz, F., Jamieson, T., & Goldfarb, A. (2019). Artificial intelligence and the implementation challenge. Journal of Medical Internet Research, 21(7), e13659. https://doi.org/10.2196/13659
Shin, D., & Park, Y. (2019). Role of fairness, accountability, and transparency in algorithmic affordance. Computers in Human Behavior, 98, 277–284. https://doi.org/10.1016/j.chb.2019.04.019
Shoukat, S., Usman, Z., & Fatima, M. (2024). Quality Assurance Frameworks in Higher Education: A Comparative Approach between Developed and Developing Countries. Annals of Human and Social Sciences, 5(3), 270–278. https://doi.org/10.35484/ahss.2024(5-III)25
Shull, J. G. (2019). Digital health and the state of interoperable electronic health records. JMIR Medical Informatics, 7(4), e12712. https://doi.org/10.2196/12712
Silven, A. V, van Peet, P. G., Boers, S. N., Tabak, M., de Groot, A., Hendriks, D., & Villalobos-Quesada, M. (2022). Clarifying responsibility: professional digital health in the doctor-patient relationship, recommendations for physicians based on a multi-stakeholder dialogue in the Netherlands. BMC Health Services Research, 22(1), 129. https://doi.org/10.1186/s12913-021-07316-0
Smith, H., Birchley, G., & Ives, J. (2024). Artificial intelligence in clinical decision‐making: Rethinking personal moral responsibility. Bioethics, 38(1), 78–86. https://doi.org/10.1111/bioe.13222
Stahl, B. C., Timmermans, J., & Flick, C. (2017). Ethics of emerging information and communication technologies: On the implementation of responsible research and innovation. Science and Public Policy, 44(3), 369–381. https://doi.org/10.1093/scipol/scw069
Starke, G., Gille, F., Termine, A., Aquino, Y. S. J., Chavarriaga, R., Ferrario, A., & Ienca, M. (2025). Finding consensus on trust in AI in health care: Recommendations from a panel of international experts. Journal of Medical Internet Research, 27, e56306. https://doi.org/10.2196/56306
Syed, R., Eden, R., Makasi, T., Chukwudi, I., Mamudu, A., Kamalpour, M., & Myers, T. (2023). Digital health data quality issues: systematic review. Journal of Medical Internet Research, 25, e42615. https://doi.org/10.2196/42615
Terzis, P., & Santamaria Echeverria, O. E. (2023). Interoperability and governance in the European Health Data Space regulation. Medical Law International, 23(4), 368–376. https://doi.org/10.1177/09685332231165692
Torab-Miandoab, A., Samad-Soltani, T., Jodati, A., & Rezaei-Hachesu, P. (2023). Interoperability of heterogeneous health information systems: a systematic literature review. BMC Medical Informatics and Decision Making, 23(1), 18. https://doi.org/10.1186/s12911-023-02115-5
Trocin, C., Mikalef, P., Papamitsiou, Z., & Conboy, K. (2023). Responsible AI for digital health: a synthesis and a research agenda. Information Systems Frontiers, 25(6), 2139–2157. https://doi.org/10.1007/s10796-021-10146-4
Van Velthoven, M. H., & Cordon, C. (2019). Sustainable adoption of digital health innovations: perspectives from a stakeholder workshop. Journal of Medical Internet Research, 21(3), e11922. https://doi.org/10.2196/11922
Veinot, T. C., Mitchell, H., & Ancker, J. S. (2018). Good intentions are not enough: how informatics interventions can worsen inequality. Journal of the American Medical Informatics Association, 25(8), 1080–1088. https://doi.org/10.1093/jamia/ocy052
Villegas-Galaviz, C., & Martin, K. (2024). Moral distance, AI, and the ethics of care. AI & Society, 39(4), 1695–1706. https://doi.org/10.1007/s00146-023-01642-z
Vimalachandran, P., Wang, H., Zhang, Y., Heyward, B., & Whittaker, F. (2016). Ensuring data integrity in electronic health records: A quality health care implication. 2016 International Conference on Orange Technologies (ICOT), 20–27.
Wang, Y., Coiera, E., Gallego, B., Concha, O. P., Ong, M. S., Tsafnat, G., & Magrabi, F. (2016). Measuring the effects of computer downtime on hospital pathology processes. Journal of Biomedical Informatics, 59, 308–315. https://doi.org/10.1016/j.jbi.2015.12.007
Wong, L. P., Wu, Q., Hao, Y., Chen, X., Chen, Z., Alias, H., & Han, L. (2022). The role of institutional trust in preventive practices and treatment-seeking intention during the coronavirus disease 2019 outbreak among residents in Hubei, China. International Health, 14(2), 161–169. https://doi.org/10.1093/inthealth/ihab023
Zhan, X., Abdi, N., Seymour, W., & Such, J. (2024). Healthcare voice ai assistants: factors influencing trust and intention to use. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW1), 1–37. https://doi.org/10.1145/3637339
Zhang, J., & Zhang, Z. M. (2023). Ethics and governance of trustworthy medical artificial intelligence. BMC Medical Informatics and Decision Making, 23(1), 7. https://doi.org/10.1016/j.is.2022.102090
Zhu, P., Hu, J., Zhang, Y., & Li, X. (2021). Enhancing traceability of infectious diseases: a blockchain-based approach. Information Processing & Management, 58(4), 102570. https://doi.org/10.1016/j.ipm.2021.102570








