AI-Driven Transformation of Home Health Care: Advancing Patient Outcomes, Operational Excellence, and Sustainable Care
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V6I4P112Keywords:
Artificial Intelligence in Healthcare, Home Health Technology, Remote Patient Monitoring, Predictive Health Analytics, AI-Driven Care Optimization, Personalized Home Care, Digital Health TransformationAbstract
AI in Home Health Care is changing the method in which patient-centered care is provided at home by combining the precision of Clinical Care with the caring aspects of In-Home Support. With the world's aging population growing and the amount of people suffering from Chronic Illnesses increasing, Healthcare Systems have many challenges ahead of them in terms of Quality, Accessibility and Efficiency. This study examines how AI technologies are transforming Home Health Care in the areas of Anticipatory Patient Monitoring, Customized Care Planning, Operational Efficiency and Compliance as well as how AI improves Patient Safety, Staff Productivity and Regulatory Compliance. Additionally, the study highlights how AI will provide caregivers with data-driven decision making capabilities, reduce the caregiver burden and create a sustainable home care delivery model that meets the needs of an evolving healthcare system. Finally, this study emphasizes the need for Ethical and Transparent AI systems to be developed so that Technology does not replace but enhance the Personal Touch. Overall, this study shows that the use of AI in Home Health Care has the potential to create an Ecosystem that is not only more Effective and Predictive, but also more Compassionate, Sustainable and Patient-Centered
References
1. Wachter, R.M.; Brynjolfsson, E. Will generative artificial intelligence deliver on its promise in health care? JAMA 2024, 331, 65–69.
2. Zhang, P.; Boulos, M.N.K. Generative AI in medicine and healthcare: Promises, opportunities and challenges. Future Internet 2023, 15, 286.
3. Taherdoost H, Ghofrani A. AI's role in revolutionizing personalized medicine by reshaping pharmacogenomics and drug therapy. Intelligent Pharmacy. 2024;2(5):643-650. https://doi.org/10.1016/j.ipha.2024.08.005
4. Alum EU, Ugwu OPC. Artificial intelligence in personalized medicine: transforming diagnosis and treatment. Discover Applied Sciences.2025;7(193). https://doi.org/10.1007/s42452-025-06625-x
5. Chen YM, Hsiao TH, Lin CH, Fann YC. Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence. Journal of Biomedical Science.2025;32(16). https://doi.org/10.1186/s12929-024-01110-w
6. van Dam PMEL, van Doorn WPTM, van Gils F, Sevenich L, Lambriks L, Meex SJR, Cals JWL, Stassen PM. Machine learning for risk stratification in the emergency department (MARS-ED) study protocol for a randomized controlled pilot trial on the implementation of a prediction model based on machine learning technology predicting 31-day mortality in the emergency department. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine. 2024;32(5). https://doi.org/10.1186/s13049-024-01177-2.
7. Mishra R, Shridevi S. Knowledge graph driven medicine recommendation system using graph neural netwoks on longitudinal medical records. Scientific Reports. 2024;14(25449). https://doi.org/10.1038/s41598-024-75784-5
8. MGH Institute of Health Professions. Big data in healthcare: opportunities and challenges. MGH IHP. 2025 Jan 10
9. van Kessel R, Ranganathan S, Anderson M, McMillan B, Mossialos E. Exploring potential drivers of patient engagement with their health data through digital platforms: A scoping review. International Journal of Medical Informatics. 2024;189:105513. https://doi.org/10.1016/j.ijmedinf.2024.105513
10. Nori LP, Lohitha M, Vadapalli RR, Bonthagarala B, Nagineni SR, Kalidindi VR. Revolutionizing healthcare: The impact of AI on precision medicine. International Journal of Pharmaceutical Investigation. 2025 Feb 12;15(2). https://jpionline.org/10.5530/ijpi.20250100
11. Singhal A, Neveditsin N, Tanveer H, Mago V. Toward fairness, accountability, transparency, and ethics in AI for social media and health care: Scoping review. JMIR Medical Informatics. 2024;12:e50048. https://doi.org/10.2196/50048
12. You JG, Hernandez-Boussard T, Pfeffer MA, Landman A, Mishuris RG. Clinical trials informed framework for real world clinical implementation and deployment of artificial intelligence applications. npj Digital Medicine. 2025 Feb 17;8(107). https://doi.org/10.1038/s41746-025-01506-4
13. Lekadir K, Frangi AF, Porras AR, Glocker B, Cintas C, Langlotz CP, et al. FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare. BMJ. 2025 Feb 5;388:e081554. https://doi.org/10.1136/bmj-2024-081554.
14. Zocco A, Pérez-Sánchez H, Geer J, Koppen V, Ciola V. Navigating the AI revolution: a roadmap for pharma's future. Drug Target Review. 2025 Mar 13. https://www.drugtargetreview.com/article/157270/navigating-the-ai-revolution-a-roadmap-for-pharmas-future/
15. Roche. AI and machine learning: revolutionising drug discovery and transforming patient care. 2025 Jan 30. https://www.roche.com/stories/ai-revolutionising-drug-Discovery-and-transforming-patient-care
16. Mount Sinai. Mount Sinai launches AI small molecule drug discovery center. 2025 Apr 2. https://www.mountsinai.org/about/newsroom/2025/mount-sinai-launches-ai-Small-molecule-drug-discovery-center
17. Applied Clinical Trials. Addressing clinical trial challenges through AI and scalable solutions. 2025 Mar 27. https://www.appliedclinicaltrialsonline.com/view/addressing-Clinical-trial-challenges-ai-scalable-solutions
18. Health Affairs. Artificial intelligence in health and health care: priorities for action. 2025 Jan 22. https://www.healthaffairs.org/doi/10.1377/hlthaff.2024.01003
19. Nirali P Shah, Navigating challenges in new product development: Strategies for reducing failure rates in the medical device industry, World Journal of Advanced Research and Reviews, 2024, 22(03), 786–795.
20. Clinical Leader. How did clinical researchers actually use AI in 2024. 2024 Dec 5. https://www.clinicalleader.com/doc/how-did-clinical-researchers-actually-use-ai-in-0001
21. Arunkumar Paramasivan. (2019). Cognitive AI Systems in Financial Transactions: Enhancing Accuracy and Efficiency. INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY, 5(5), 1–10. https://doi.org/10.5281/zenodo.14551626
