Assessing the Role of Medical Information Science in Digital Therapeutics and Virtual Healthcare
DOI:
https://doi.org/10.56294/mw2024518Keywords:
Medical Information Science, Digital Therapeutics, Virtual Healthcare, Artificial Intelligence in Medicine, Telemedicine, Healthcare Data AnalyticsAbstract
Medical Information Science is very important for improving digital therapies and virtual healthcare because it lets people make decisions based on data, improves patient management, and makes treatment more personalised. Using artificial intelligence (AI), big data analytics, and blockchain together in medical computing has changed how patients are involved, how they are monitored remotely, and how evidence-based treatments are used. Digital medicines, which use software-based treatments, are being used more and more to help people with mental health problems, control chronic diseases, and get better. Telemedicine, digital health tracking, and mobile apps are all examples of virtual healthcare solutions that depend on fast data processing, compatibility, and privacy to make sure that patients get safe and smooth care. This research looks at how Medical Information Science helps make healthcare better by making hospital processes more efficient, making sure diagnoses are correct, and supporting predictive analytics. It also looks at the problems that digital health tools cause when it comes to data protection, sharing, and following the rules. The study also talks about how electronic health records (EHRs) can be connected to AI-powered decision support systems to give doctors real-time information and help them make personalised treatment plans. As virtual healthcare and digital treatments continue to develop, strong medical informatics systems are needed to make sure that everyone can get the care they need and that patients have the same chances of having a good result. This essay stresses how important it is to focus on the patient in digital medicines and supports standard data control practices. The results show that Medical Information Science has the power to change the future of digital healthcare environments.
References
Crisafulli, S.; Santoro, E.; Recchia, G.; Trifirò, G. Digital Therapeutics in Perspective: From Regulatory Challenges to Post-Marketing Surveillance. Front. Drug Saf. Regul. 2022, 2, 900946.
Renton, T.; Tang, H.; Ennis, N.; Cusimano, M.D.; Bhalerao, S.; Schweizer, T.A.; Topolovec-Vranic, J. Web-based intervention programs for depression: A scoping review and evaluation. J. Med. Internet Res. 2014, 16, e209.
Darcy, A.; Beaudette, A.; Chiauzzi, E.; Daniels, J.; Goodwin, K.; Mariano, T.Y.; Wicks, P.; Robinson, A. Anatomy of a Woebot® (WB001): Agent guided CBT for women with postpartum depression. Expert Rev. Med. Devices 2022, 19, 287–301.
Maher, C.A.; Davis, C.R.; Curtis, R.G.; Short, C.E.; Murphy, K.J. A Physical Activity and Diet Program Delivered by Artificially Intelligent Virtual Health Coach: Proof-of-Concept Study. JMIR mHealth uHealth 2020, 8, e17558.
Denecke, K. Framework for Guiding the Development of High-Quality Conversational Agents in Healthcare. Healthcare 2023, 11, 1061.
Yang, H.; Li, D. Understanding the dark side of gamification health management: A stress perspective. Inf. Process. Manag. 2021, 58, 102649.
Aronson, J.K.; Heneghan, C.; Ferner, R.E. Medical Devices: Definition, Classification, and Regulatory Implications. Drug Saf. 2020, 43, 83–93
Prochaska, J.J.; Vogel, E.A.; Chieng, A.; Kendra, M.; Baiocchi, M.; Pajarito, S.; Robinson, A. A Therapeutic Relational Agent for Reducing Problematic Substance Use (Woebot): Development and Usability Study. J. Med. Internet Res. 2021, 23, e24850.
May, R.; Security, K.D.; Care, I.H.S. Security, privacy, and healthcare-related conversational agents: A scoping review. Inform. Health Soc. Care 2021, 47, 194–210.
Godovykh, M.; Pizam, A. Measuring patient experience in healthcare. Int. J. Hosp. Manag. 2023, 112, 103405.
Majeed, S.; Kim, W.G. Toward understanding healthcare hospitality and the antecedents and outcomes of patient-guest hospital-hotel choice decisions: A scoping review. Int. J. Hosp. Manag. 2022, 112, 103383.
Chavriya, S.; Sharma, G.D.; Mahendru, M. Financial inclusion as a tool for sustainable macroeconomic growth: An integrative analysis. Ann. Public Coop. Econ. 2023, 95, 527–551.
Snyder, H. Literature review as a research methodology: An overview and guidelines. J. Bus. Res. 2019, 104, 333–339.
Spreadbury, J.; Young, A.; Kipps, C.A. Comprehensive Literature Search of Digital Health Technology Use in Neurological Conditions: Review of Digital Tools to Promote Self-management and Support. J. Med. Internet Res. 2022, 24, e31929.
Nebeker, C.; Gholami, M.; Kareem, D.; Kim, E. Applying a Digital Health Checklist and Readability Tools to Improve Informed Consent for Digital Health Research. Front. Digit. Health 2021, 3, 690901.
Botti, A.; Monda, A. Sustainable Value Co-Creation and Digital Health: The Case of Trentino eHealth Ecosystem. Sustainability 2020, 12, 5263.
Stoumpos, A.I.; Kitsios, F.; Talias, M.A. Digital Transformation in Healthcare: Technology Acceptance and Its Applications. Int. J. Environ. Res. Public Health 2023, 20, 3407.
Published
Issue
Section
License
Copyright (c) 2024 Swarna Swetha Kolaventi, Debasmita Tripathy, Madireddy Sirisha, Manish Nagpal, Prakriti Kapoor, Neha Rana, Malathi.H (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
