Enhanced Information Systems Success Model for Patient Information Assurance

Authors

  • Lilian Adhiambo Agunga School of informatics & innovative systems, Jaramogi Oginga Odinga University of Science & Technology, Bondo, Kenya
  • Joshua Agola School of informatics & innovative systems, Jaramogi Oginga Odinga University of Science & Technology, Bondo, Kenya
  • Paul Abuonji School of informatics & innovative systems, Jaramogi Oginga Odinga University of Science & Technology, Bondo, Kenya

DOI:

https://doi.org/10.30564/jcsr.v3i4.3734

Abstract

The current health information systems have many challenges such as lack of standard user interfaces, data security and privacy issues, inability to uniquely identify patients across multiple hospital information systems, probable misuse of patient data, high technological costs, resistance to technology deployments in hospital management, lack of data gathering, processing and analysis standardization. All these challenges, among others hamper either the acceptance of the health information systems, operational efficiency or expose patient information to cyber attacks. In this paper, an enhanced information systems success model for patient information assurance is developed using an amalgamation of Technology Acceptance Model (TAM) and Information Systems Success Model (ISS). This involved the usage of Linear Structured Relationship (LISREL) software to model a combination of ISS and Intention to Use (ITU), TAM and ITU, ISS and user satisfaction (US), and finally TAM and US. The sample size of 110 respondents was obtained based on the total population of 221 using the Conhrans formula. Thereafter, simple random sampling was employed to select members within each category of employees to take part in the study. The questionnaire as a research tool was checked for reliability via Cronbach’s Alpha. The results obtained showed that for ISS and ITU modeling, only perceived ease of use, system features, response time, flexibility, timeliness, accuracy, responsiveness and user training positively influenced the intention to use. However, for the TAM and ITU modeling, only TAM’s measures such as timely information, efficiency, increased transparency, and proper patient identification had a positive effect on intension to use. The ISS and US modeling revealed that perceived ease of use had the greatest impact on user satisfaction while response time had the least effect on user satisfaction. On its part, the TAM and US modeling showed that timely information, effectiveness, consistency, enhanced communication, and proper patients identification had a positive influence on user satisfaction.

Keywords:

Information assurance, ISS, Modeling, Privacy, Security, TAM, User satisfaction

References

[1] M. Evans, L.A. Maglaras, Y. He, and H. Janicke, “Human behaviour as an aspect of cybersecurity assurance,” Security and Communication Networks, 9(17), 4667-4679, 2016.

[2] W.J. George, and S.M. Shawon, “Exploring Challenges And Opportunities In Cybersecurity Risk And Threat Communications Related To The Medical Internet Of Things (MIOT),” International Journal of Network Security & Its Applications (IJNSA), 11(4), pp. 75-86, 2019.

[3] S. Murphy, “Is cyber security possible in healthcare?,” National Cyber-security Institute Journal, 1(3) 49-63, 2015.

[4] Loukaka, Alain and Rahman, Shawon, “Discovering New Cyber Protection Approaches From a Security Professional Prospective,” International Journal of Computer Networks & Communications (IJCNC), 9(4), 2017.

[5] D.A. Handel DA, “Implementing electronic health records in the emergency department,” J Emerg Med, 38: 257-263, 2010.

[6] E. Zahra, T. Hamed, D. Kolsoum, M. Sayyed, and T. Mahmood, “Determining the Hospital Information System (HIS) Success Rate: Development of a New Instrument and Case Study,” Macedonian Journal of Medical Sciences, 7(9):1407-1414, 2019.

[7] Y.H. Al-Mamary, A. Shamsuddin, and N. Aziati, “The relationship between system quality, information quality, and organizational performance,” International Journal of Knowledge and Research in Management & E-Commerce, 4(3), 7-10, 2014.

[8] A. Asad, Z. Aisha, Z. Muhammad, A. Kainat, K. Aiman, and S. Georgia, “Applications of Blockchain Technology in Medicine and Healthcare: Challenges and Future Perspectives,” MDPI, 3, pp. 1-16, 2019.

[9] J. Zhang, N. Xue, and X. Huang, “A Secure System for Pervasive Social Network Based Healthcare,” IEEE Access, 4, 9239–9250, 2016.

[10] T.T. Kuo, H. Kim, and L. Ohno-Machado, “Blockchain distributed ledger technologies for biomedical and health care applications,” J. Am. Med. Inform. Assoc. 24, 1211–1220, 2017.

[11] S. Angraal, H.M. Krumholz, and W.L. Schulz, “Blockchain technology: applications in health care,” Circulation: Cardiovascular quality and outcomes, 10(9), e003800, 2017.

[12] S. Acharya, B. Coats, A. Saluja, and D. Fuller, “Secure electronic health record exchange: achieving the meaningful use objectives,” in 2013 46th Hawaii International Conference on System Sciences, IEEE, pp. 2555-2564, 2013.

[13] G. Comandé, L. Nocco, and V. Peigné, “An empirical study of healthcare providers and patients׳ perceptions of electronic health records,” Computers in Biology and Medicine, 59, 194-201, 2015.

[14] D.I. Rosenthal, “Instant replay,” in Healthcare, Elsevier, vol. 1, No. 1-2, pp. 52-54, 2013.

[15] C.A. Caligtan, and P.C. Dykes, “Electronic health records and personal health records,” in Seminars in oncology nursing, WB Saunders, 27(3), pp. 218-228, 2011.

[16] B.S. Buckley, A.W. Murphy, and A.E. MacFarlane, “Public attitudes to the use in research of personal health information from general practitioners’ records: a survey of the Irish general public,” Journal of Medical Ethics, 37(1), 50-55, 2011.

[17] A. Otokiti, “Using informatics to improve healthcare quality,” International journal of health care quality assurance, 32(2), pp. 425-430, 2019.

[18] N. Perlroth, and D.E. Sanger, “Hackers hit dozens of countries exploiting stolen NSA tool,” New York Times, 12, 2017.

[19] J.C. Hsieh, A.H. Li, and C.C. Yang, “Mobile, cloud, and big data computing: contributions, challenges, and new directions in tele-cardiology,” International journal of environmental research and public health, 10(11), 6131-6153, 2013.

[20] C. Camara, P. Peris-Lopez, and J.E. Tapiador, “Security and privacy issues in implantable medical devices: A comprehensive survey,” Journal of Biomedical Informatics, 55, 272–289, 2015.

[21] E.C. Cheng, Y. Le, J. Zhou, and Y. Lu, “Healthcare services across China–on implementing an extensible universally unique patient identifier system,” International Journal of Healthcare Management, 11(3), 210-216, 2018.

[22] N.A. Mohamadali, and N.F. Ab Aziz, “The technology factors as barriers for sustainable health information systems (his)–a review,” Procedia Computer Science, 124, 370-378, 2017.

[23] K. Garrety, I. McLoughlin, R. Wilson, G. Zelle, and M. Martin, “National electronic health records and the digital disruption of moral orders,” Social Science & Medicine, 101, 70-77, 2014.

[24] M. Smith, “Electronic health records and healthcare identifiers: legislation discussion paper,” Population Health and Research Network, 2015.

[25] K.N. Griggs, O. Ossipova, C.P. Kohlios, A.N. Baccarini, E.A. Howson, and T. Hayajneh, “Healthcare blockchain system using smart contracts for secure automated remote patient monitoring,” Journal of medical systems, 42(7), 1-7, 2018.

[26] D. Ivan, “Moving toward a blockchain-based method for the secure storage of patient records,” in ONC/ NIST Use of Blockchain for Healthcare and Research Workshop. Gaithersburg, Maryland, United States: ONC/NIST, pp. 1-11, 2016.

[27] Y. Chen, S. Ding, Z. Xu, H. Zheng, and S. Yang, “Blockchain-based medical records secure storage and medical service framework,” Journal of medical systems, 43(1), 1-9, 2019.

[28] S. Wang, J. Wang, X. Wang, T. Qiu, Y. Yuan, L. Ouyang, and F.Y. Wang, “Blockchain-powered parallel healthcare systems based on the ACP approach,” IEEE Transactions on Computational Social Systems, 5(4), 942-950, 2018.

[29] S. Jiang, J. Cao, H. Wu, Y. Yang, M. Ma, and J. He, “Blochie: a blockchain-based platform for healthcare information exchange,” in 2018 IEEE international conference on smart computing (smartcomp), IEEE, 49-56, 2018.

[30] M.A. Cyran, “Blockchain as a foundation for sharing healthcare data. Blockchain in Healthcare Today, pp.1-6, 2018.

[31] S. Shubbar, “Ultrasound Medical Imaging Systems Using Telemedicine and Blockchain for Remote Monitoring of Responses to Neoadjuvant Chemotherapy in Women’s Breast Cancer: Concept and Implementation,” Master’s Thesis, Kent State University, Kent, OH, USA, 2017.

[32] T. Guimaraes, C.P. Armstrong, and B.M. Jones, “A new approach to measuring information systems quality,” Quality Management Journal, 16(1), 42-51, 2009.

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How to Cite

Agunga, L. A., Agola, J., & Abuonji, P. (2021). Enhanced Information Systems Success Model for Patient Information Assurance. Journal of Computer Science Research, 3(4), 31–42. https://doi.org/10.30564/jcsr.v3i4.3734

Issue

Vol. 3 , Iss. 4 (October 2021)

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