Standardized Electronic Health Record and its Controlled Access
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Abstract
The Electronic Health Record (EHR) is a digitalized solution to support the health care facility, irrespective of levels and sizes to improve patient care system by eliminating the paper based medical records.Standardization of EHR improves the easy sharing of health information between various levels of health care system. The availability of the patient’s data in a timely fashion can contribute to the improvement of patient’s information and performance of the Health Information System. Current health care information systems of the hospitals are usually isolated from each other as most of the hospitals and health care institutions have their own format to create EMR (Electronic Medical Records) to serve the purpose of treating the patient.Standard coding makes it simple to share health information, lowers uncertainty, enhances workflow, and makes it easier to accurately analyze data related to health care.During patient registration or hospital visit, ID proof like Aadhar Number isused as a universal patient identifier. Healthcare user authentication is archived at database level through valid user name and password.The cloud server checks the credentials against a user store of the database for validation as illustrated in Algorithm-1.The primary function of the attribute based access control (ABAC) provided by Algorithm-2 is to authorize access for healthcare users. The hospital authorities obtain the patient's agreement in the first stage, and the loop is continued by using the value YES.The role based access control (RBAC) given in Tables-II and III is one of the best method for highly complex and huge management system. All this process standerdize EHR and its controlled access safe and secure.
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References
- Afraz, A., Montazeri, M., Shahrbabaki, M. E., Ahmadian, L., and Jahani, Y. 2024. The viewpoints of parents of children with mental disorders regarding the confidentiality and security of their children’s information in the iranian national electronic health record system. International Journal of Medical Informatics 183, 105334. DOI: https://doi.org/10.1016/j.ijmedinf.2023.105334
- Almulhem, A. 2012. Threat modeling for electronic health record systems. Journal of Medical Systems 36, 2921–2926. DOI: https://doi.org/10.1007/s10916-011-9770-6
- AMSTERDAM, T. N. 2013. C. Springer Fachmedien Wiesbaden, Wiesbaden, 21–26. DOI: https://doi.org/10.1007/978-3-658-03803-8_3
- Bali, R. K., Troshani, I., Goldberg, S., and Wickramasinghe, N. 2013. Pervasive health knowledge management. DOI: https://doi.org/10.1007/978-1-4614-4514-2
- Baniulyte, G., Rogerson, N., and Bowden, J. 2023. Going paperless – qualitative monitoring of staff morale during the transition from paper to electronic health records. Heliyon 9, 10, e20645. DOI: https://doi.org/10.1016/j.heliyon.2023.e20645
- Dhaka, M., Sharma, D. P., Sharma, S. K., and Dixit, A. 2021. An analysis of electronic health record system in healthcare services in cloud: A review perspective. 2021 International Conference on Computational Performance Evaluation (ComPE), 886–892. DOI: https://doi.org/10.1109/ComPE53109.2021.9751995
- Dinote, A., Sharma, D., Tuni, A., Singh, B., and Choudhury, T. 2020. Medication processes automation using unified green computing and communication model. Journal of Green Engineering, 5763–5778.
- Dinote, A. and Sharma, D. P. 2019. Developing a unified green computing and communication system prototype for outpatient medication processes. CompSciRN: Process for the Collection. DOI: https://doi.org/10.2139/ssrn.3380322
- Doukas, C. and Maglogiannis, I. 2012. Bringing iot and cloud computing towards pervasive healthcare. In 2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing. 922–926. DOI: https://doi.org/10.1109/IMIS.2012.26
- Gergi, M., Wilkinson, K., Plante, T. B., and Zakai, N. A. 2024. Ascertaining accurate exposure to aspirin and other antithrombotic medications using a structured electronic health record data. Research and Practice in Thrombosis and Haemostasis, 102513. DOI: https://doi.org/10.1016/j.rpth.2024.102513
- Gopal, K. M. 2019. Strategies for ensuring quality health care in india: Experiences from the field. Indian Journal of Community Medicine 44, 1–3. DOI: https://doi.org/10.4103/ijcm.IJCM_65_19
- Griebel, L., Prokosch, H.-U., Kopcke, F. ¨ , Toddenroth, D., Christoph, J., Leb, I., Engel, I., and Sedlmayr, M. 2015. A scoping review of cloud computing in healthcare. BMC Medical Informatics and Decision Making 15. DOI: https://doi.org/10.1186/s12911-015-0145-7
- Huang, J., Chan, S., Fung, Y., Mak, F., Lok, V., Zhang, L., Lin, X., Lucero-Prisno III, D., Xu, W., Zheng, Z.-J., Elcarte, E., Withers, M., Wong, M., and NCD Global Health Research Group, Association of Pacific Rim Universities (APRU). 2023. Incidence, risk factors, and temporal trends of small intestinal cancer: a global DOI: https://doi.org/10.1053/j.gastro.2023.05.043
- analysis of cancer registries. Gastroenterology 165, 3 (Sept.), 600–612.
- Ibrahim, E., El-Bahnasawy, N. A., and Omara, F. A. 2016. Task scheduling algorithm in cloud computing environment based on cloud pricing models. 2016 World Symposium on Computer Applications & Research (WSCAR), 65–71. DOI: https://doi.org/10.1109/WSCAR.2016.20
- Mbonihankuye, S., Nkunzimana, A., and Ndagijimana, A. 2019. Healthcare data security technology: Hipaa compliance. Wirel. Commun. Mob. Comput. 2019, 1927495:1–1927495:7. DOI: https://doi.org/10.1155/2019/1927495
- Nahvijou, A., Esmaeeli, E., Kalaghchi, B., Sheikhtaheri, A., and Zendehdel, K. 2023. Using electronic health record system to establish a national patient’s registry : Lessons learned from the cancer registry in iran. International Journal of Medical Informatics 180, 105245. DOI: https://doi.org/10.1016/j.ijmedinf.2023.105245
- Pai, M. M. M., Ganiga, R., Pai, R. M., and Sinha, R. K. 2021. Standard electronic health record (ehr) framework for indian healthcare system. Health Services and Outcomes Research Methodology, 1–24. DOI: https://doi.org/10.1007/s10742-020-00238-0
- Rajgopal, T. 2020. Covid-19: Epidemiology and public health aspects. Indian journal of community medicine : official publication of Indian Association of Preventive amp; Social Medicine 45, 2, 111—116. DOI: https://doi.org/10.4103/ijcm.IJCM_167_20
- Rathore, J., Keswani, D. B., and Rathore, D. V. S. 2017. Analysis of various load balancing techniques in cloud computing: A review.
- Rs, D., Eb, S., and De, D. 1997. The computer-based patient record: Revised edition: An essential technology for health care.
- Sarbadhikari, S. 2018. Will health informatics gain its rightful place for ushering in digital india? Indian Journal of Community Medicine 43, 126–127. DOI: https://doi.org/10.4103/ijcm.IJCM_251_17
- Singh, S. and Kalra, M. 2014. Scheduling of independent tasks in cloud computing using modified genetic algorithm. In 2014 International Conference on Computational Intelligence and Communication Networks. 565–569. DOI: https://doi.org/10.1109/CICN.2014.128
- Srivastava, S. 2016. Adoption of electronic health records: A roadmap for india. Healthcare Informatics Research 22, 261. DOI: https://doi.org/10.4258/hir.2016.22.4.261
- Starolis, M. W., Zaydman, M. A., and Liesman, R. M. 2023. Working with the electronic health record and laboratory information system to maximize ordering and reporting of molecular microbiology results. Clinics in laboratory medicine 44 1, 95–107. DOI: https://doi.org/10.1016/j.cll.2023.10.009
- Walid, R., Joshi, K. P., and Choi, S. G. 2024. Leveraging semantic context to establish access controls for secure cloud-based electronic health records. International Journal of Information Management Data Insights 4, 1, 100211. DOI: https://doi.org/10.1016/j.jjimei.2023.100211
- Whitt, K. J., Allen, C. L., Hogg, C. W., Pericak, A., Beebe, S. L., Braungart, C., Knestrick, J., Harrod, T., and McNelis, A. M. 2024. The use of electronic health records in advanced practice nursing education: a scoping review. Journal of Professional Nursing 50, 83–94. DOI: https://doi.org/10.1016/j.profnurs.2023.11.007
- Wickremasinghe, B., Calheiros, R. N., and Buyya, R. 2010. Cloudanalyst: A cloudsimbased visual modeller for analysing cloud computing environments and applications. In 2010 24th IEEE International Conference on Advanced Information Networking and Applications. 446–452. DOI: https://doi.org/10.1109/AINA.2010.32
- Yadav, D. and Sharma, D. 2021. A study of intranet over cloud. 7, 1–6.
- Zhan, S. and Huo, H. 2012. Improved pso-based task scheduling algorithm in cloud computing. Journal of Information and Computational Science 9, 3821–3829.
- Zhang, T., Tan, T., Wang, X., Gao, Y., Han, L., Balkenende, L., D’Angelo, A., Bao, L., Horlings, H. M., Teuwen, J., Beets-Tan, R. G., and Mann, R. M. 2023. Radiologic, a healthcare model for processing electronic health records and decision-making in breast disease. Cell Reports Medicine 4, 8, 101131. DOI: https://doi.org/10.1016/j.xcrm.2023.101131
- Zhu, Q., Zhou, X., Song, Z., Tan, J., and Guo, L. 2019. Dan: deep attention neural network for news recommendation. In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence. AAAI’19/IAAI’19/EAAI’19. AAAI Press.