An Examination of Machine Learning in the Process of Data Integration |
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| © 2023 by IJCTT Journal | ||
| Volume-71 Issue-6 |
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| Year of Publication : 2023 | ||
| Authors : Shashank Agarwal | ||
| DOI : 10.14445/22312803/IJCTT-V71I6P115 | ||
How to Cite?
Shashank Agarwal, "Graph Networks: Transforming Provider Affiliations for Enhanced Healthcare Management ," International Journal of Computer Trends and Technology, vol. 71, no. 6, pp. 86-90, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I6P115
Abstract
Provider affiliations are critical in healthcare because they facilitate care coordination, resource allocation, referral management, and network optimization. Traditional methods of establishing and maintaining affiliations rely on manual procedures, human contacts, and geographical proximity, resulting in inefficiencies and limits in accurate recording and keeping full affiliation data. To overcome these challenges, a new approach utilizing graph networks has emerged as a promising solution. Graph networks provide a comprehensive and intuitive framework for modelling and analyzing complicated interactions within provider networks. They enable healthcare organizations to integrate heterogeneous data sources, improve visibility, and gain sophisticated analytics and data-driven insights. In this paper, we focus on the application of graph networks in healthcare organizations. We discuss the advantages and challenges of implementing graph networks and discuss how to manage these challenges effectively.
Keywords
Graphical Networks, Provider affiliation, Artificial intelligence, Optimization, Artificial neural network.
Reference
[1] Rachel Mosher Henke et al., “Impact of Health System Affiliation on Hospital Resource Use Intensity and Quality of Care,” Health Services Research, vol. 53, no. 1, pp. 63-86, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[2] N. Lance Downing, David W. Bates, and Christopher A. Longhurst, “Physician Burnout in the Electronic Health Record Era: Are We Ignoring the Real Cause?,” Annals of Internal Medicine, vol. 169, no. 1, pp. 50–51, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Rudolph A. Rodriguez, John R. Hotchkiss, and Ann M. O’Hare, “Geographic Information Systems and Chronic Kidney Disease: Racial Disparities, Rural Residence and Forecasting,” Journal of Nephrology, vol. 26, no. 1, pp. 3-15, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[4] T. Ramesh and V. Santhi, “Exploring Big Data Analytics in Health Care,” International Journal of Intelligent Networks, vol. 1, pp. 135– 140, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Hoangmai H. Pham et al., “Primary Care Physicians’ Links to other Physicians through Medicare Patients: The Scope of Care Coordination,” Annals of Internal Medicine, vol. 150, no. 4, pp. 236–242, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Ashley M. Kranz et al., “Health System Affiliation of Physician Organizations and Quality of Care for Medicare Beneficiaries Who Have High Needs,” Health Services Research, vol. 55, no. 53, pp. 1118-1128, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Mustafa Ozkaynak et al., “Infinicare Framework for Integrated Understanding of Health-Related Activities in Clinical and Daily-Living Contexts,” Health Systems, vol. 7, no. 1, pp. 66-78, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Christine Tvedt et al., “A Cross-Sectional Study to Identify Organisational Processes Associated with Nurse-Reported Quality and Patient Safety,” BMJ Open, vol. 2, no. 6, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Claudio Gutierrez, and Juan F. Sequeda, “Knowledge Graphs,” Communications of ACM, vol. 64, no. 3, pp. 96–104, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[10] M. F. Furukawa et al., “Landscape of Health Systems in the United States,” Medical Care Research and Review, vol. 77, no. 4, pp. 357- 366, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Ameneh Ghazal Saatchi, Francesca Pallotti, and Paul Sullivan, “Network Approaches and Interventions in Healthcare Settings: A Systematic Scoping Review,” PLoS One, vol. 18, no. 2, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Jasdeep Singh, and Divya Singhal, “Potential Antiviral Therapies for Coronavirus Disease 2019 (COVID-19),” Data Science for COVID-19, pp. 729-748, 2022.
[CrossRef] [Publisher Link]
[13] Said Ahmad Maisam Najafizada et al., “Ranked Performance of Canada’s Health System on the International Stage: A Scoping Review,” Healthcare Policy, vol. 13, no. 1, pp. 59-73, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Siddharth Sharma, “Revolutionizing HR: The Role and Potential of Chatbots in Human Capital Management,” SSRN, 2023.
[Publisher Link]
[15] Iris Reychav et al., “Graph Network Techniques to Model and Analyze Emergency Department Patient Flow,” Mathematics, vol. 10, no. 9, p. 1526, 2022.
[CrossRef] [Google Scholar] [Publisher Link]