Omnichannel AI-Enabled Healthcare Contact Centers: Enabling Seamless Patient Journey Continuity

Authors

  • Suresh Padala Independent Researcher, USA. Author

DOI:

https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I1P115

Keywords:

Omnichannel Healthcare Contact Center, AI-Enabled Patient Engagement, Healthcare Communication Integration, Patient Experience Continuity, Hipaa-Compliant Data Interoperability

Abstract

At the same time, modern health systems seek to connect with patients across voice, SMS, web chat, email, patient portals, and mobile apps. Too often, however, these patient touchpoints are a series of disconnected silos that result in an inconsistent patient experience and suboptimal business processes. The article analyzes the architecture, functionalities, and organizational outcomes of omnichannel AI-enabled healthcare contact centers, which are contact centers that unify disparate channels into smart engagement ecosystems. The article conducts a systematic review of peer-reviewed literature and identifies the technical underpinnings of multichannel integration: (1) AI-enabled contextual intelligence engines that conduct intent classification and sentiment analysis using natural language processing (NLP), (2) unified patient data solutions that achieve 360-degree views of patients by enabling interoperable systems to connect, and (3) continuous context that avoids repeated information requests. In general, the evidence for process automation's effect on such things as accuracy of processing and timeliness to resolution, as well as patient experience, is strong and correlates well with patient-reported access quality and care coordination. Omnichannel AI infrastructure is a foundational capability health systems must possess to achieve patient-centric care delivery by enabling cross-channel continuity, interdepartmental care coordination, operational efficiencies from digital deflection of routine patient engagement inquiries, and differentiation in value-based care environments. As healthcare delivery continues to transition toward data-driven and personalized care, integrated communication architectures designed for delivery systems will be a key enabler for operational excellence and improved engagement outcomes․

References

1. Calisto, F. M., & Ferreira, A. (2021). Toward a clinical decision support system for data-driven healthcare marketing. IEEE Transactions on Engineering Management, 69(6), 3324–3336. https://doi.org/10.1109/TEM.2021.3069103

2. Sawesi, S., Rashrash, M., Phalakornkule, K., Carpenter, J. S., & Jones, J. F. (2016). The impact of information technology on patient engagement and health behavior change: A systematic review of the literature. JMIR Medical Informatics, 4(1), e1. https://doi.org/10.2196/medinform.4514

3. Schiavone, F., Metallo, C., Albano, R., & Lerro, A. (2019). Determinants of a smart service ecosystem: Evidence from the healthcare sector. Service Business, 13(2), 269–291. https://doi.org/10.1007/s11628-018-0380-5

4. Ayaz, M., Pashazadeh, S., & Sharifi, A. M. (2020). A privacy-preserving and HIPAA-compliant architecture for cloud-based health data integration. International Journal of Cloud Applications and Computing (IJCAC), 10(1), 1–22. https://doi.org/10.4018/IJCAC.2020010101

5. Basyal, G. P., Rimal, B. P., & Zeng, D. (2020). A systematic review of natural language processing for knowledge management in healthcare. arXiv. https://arxiv.org/abs/2007.09134

6. Giordano, C., Brennan, M., Mohamed, B., Rashidi, P., & Modave, F. (2021). Accessing artificial intelligence for clinical decision-making. Frontiers in Digital Health, 3, 645232. https://doi.org/10.3389/fdgth.2021.645232

7. Laranjo, L., Kocaballi, A. B., Bashir, R., Rezazadegan, D., Tong, H. L., Wang, L., & Coiera, E. (2018). A service-oriented architecture for the design of a personalized health information system. International Journal of Medical Informatics, 115, 31–39. https://doi.org/10.1016/j.ijmedinf.2018.04.004

8. Shang, L., Zuo, M., Ma, D., & Yu, Q. (2019). The antecedents and consequences of health care professional–patient online interactions: Systematic review. Journal of Medical Internet Research, 21(9), e13940. https://doi.org/10.2196/13940

9. Kevin N. Griffith et al., “Call Center Performance Affects Patient Perceptions of Access and Satisfaction," National Library of Medicine, 2021. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC8177735/

10. Gotlib Conn, L., McKenzie, M., Pearsall, E. A., & McLeod, R. S. (2015). Successful implementation of an enhanced recovery after surgery program: The role of the nurse practitioner. Canadian Journal of Surgery, 58(1), 25–32.

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Published

2022-03-30

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Articles

How to Cite

1.
Padala S. Omnichannel AI-Enabled Healthcare Contact Centers: Enabling Seamless Patient Journey Continuity. IJAIBDCMS [Internet]. 2022 Mar. 30 [cited 2026 Mar. 15];3(1):133-9. Available from: https://ijaibdcms.org/index.php/ijaibdcms/article/view/454