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Copyright (c) 2024 Hissah Abdulaziz Alyahya, Hadeel Khunayfir Alrashidi, Miad Obaidallah Almutairi, Sultan Daaj Alotaibi, Mohammed Yahya Ahmed Asiri, Khaled Eid Abdul Rahman Al-Otaibi, Norah Obaid Almutairi, Faisal Tareheb Alotebe, Samer Olaythah Ahmed Alsubhi, Meshal Ayedh Alotaibi

This work is licensed under a Creative Commons Attribution 4.0 International License.
Weaving a Digital Tapestry: The Transformative Impact of Digital Health Technologies on Multidisciplinary Healthcare Delivery
Corresponding Author(s) : Hissah Abdulaziz Alyahya
Saudi Journal of Medicine and Public Health, Vol. 1 No. 2 (2024)
Abstract
Background: The escalating complexity of chronic disease and an aging population necessitate a paradigm shift from siloed care to integrated, multidisciplinary team (MDT) delivery. Concurrently, the rapid proliferation of digital health technologies (DHTs) promises to reconfigure the architecture of collaboration, yet their real-world impact on the fabric of MDT communication, workflow, and patient-centered outcomes remains heterogeneously understood.
Aim: This narrative review aims to synthesize recent evidence (2015-2025) on the impact of DHTs on multidisciplinary healthcare delivery, examining how they reshape team dynamics, clinical workflows, and patient outcomes, while critically analyzing implementation barriers.
Methods: A structured narrative review was conducted across PubMed, Scopus, and Web of Science databases, focusing on empirical studies, systematic reviews, and meta-analyses published between 2015 and 2025. Thematic analysis was used to synthesize findings into three core domains: communication and coordination, clinical decision-making, and systemic implementation challenges.
Results: DHTs, including integrated electronic health records (EHRs), telehealth platforms, and AI-driven decision support systems, act as dual-edged instruments. They can fracture traditional workflow patterns through information overload and technological tribalism, or weave cohesive, data-rich collaborative networks via unified communication and shared situational awareness. The evidence reveals a critical gap between the potential for augmented collaboration and the reality of socio-technical friction, with success hinging on implementation strategy, digital literacy, and organizational culture.
Conclusion: Digital health technologies are not a panacea but a potent catalyst that amplifies pre-existing cultural and systemic strengths or flaws within MDTs. Their effective integration demands a human-centered, socio-technical approach that co-designs digital infrastructure with clinical workflows, reframing technology as a collaborative teammate rather than a transactional tool.
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- Abdul Rehman, M., Naeem, U., Rani, A., Banatwala, U. E. S. S., Salman, A., Abdullah Khalid, M., ... & Tahir, E. (2023). How well does the virtual format of oncology multidisciplinary team meetings work? An assessment of participants’ perspectives and limitations: a scoping review. PLoS One, 18(11), e0294635.
- Alraddadi, K. M., Aljohani, A. S. D., Saadi Saad Alahmadi, K., Abuyabes, A. A., Alharbi, K. N. S., Alrashidi, M. N. F., ... & Alanazy, M. S. (2024). Evaluating How Artificial Intelligence And Electronic Health Record Systems Influence Physician–Nurse Communication, Workflow Efficiency, And Clinical Decision-Making. The Review of Diabetic Studies, 1-18.
- Alobayli, F., O’Connor, S., Holloway, A., & Cresswell, K. (2023). Electronic health record stress and burnout among clinicians in hospital settings: a systematic review. Digital Health, 9, 20552076231220241.
- Al Saiegh, F., Munoz, A., Velagapudi, L., Theofanis, T., Suryadevara, N., Patel, P., ... & Herial, N. A. (2022). Patient and procedure selection for mechanical thrombectomy: Toward personalized medicine and the role of artificial intelligence. Journal of Neuroimaging, 32(5), 798-807.
- Baxter, G., & Sommerville, I. (2011). Socio-technical systems: From design methods to systems engineering. Interacting with computers, 23(1), 4-17.
- Eberly, L. A., Kallan, M. J., Julien, H. M., Haynes, N., Khatana, S. A. M., Nathan, A. S., ... & Adusumalli, S. (2020). Patient characteristics associated with telemedicine access for primary and specialty ambulatory care during the COVID-19 pandemic. JAMA network open, 3(12), e2031640.
- Edmondson, A. C. (2018). The fearless organization: Creating psychological safety in the workplace for learning, innovation, and growth. John Wiley & Sons.
- Endsley, M. R., Cooke, N., McNeese, N., Bisantz, A., Militello, L., & Roth, E. (2022). Special issue on human-AI teaming and special issue on AI in healthcare. Journal of Cognitive Engineering and Decision Making, 16(4), 179-181.
- Fennelly, O., Cunningham, C., Grogan, L., Cronin, H., O’Shea, C., Roche, M., ... & O’Hare, N. (2020). Successfully implementing a national electronic health record: a rapid umbrella review. International Journal of Medical Informatics, 144, 104281.
- Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J., Hughes, G., Hinder, S., ... & Shaw, S. (2017). Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. Journal of medical Internet research, 19(11), e8775.
- Greenhalgh, T., Shaw, S., Wherton, J., Vijayaraghavan, S., Morris, J., Bhattacharya, S., ... & Hodkinson, I. (2018). Real-world implementation of video outpatient consultations at macro, meso, and micro levels: mixed-method study. Journal of medical Internet research, 20(4), e150.
- Greenhalgh, T., & Papoutsi, C. (2018). Studying complexity in health services research: desperately seeking an overdue paradigm shift. BMC medicine, 16(1), 95.
- Grote, T., & Berens, P. (2020). On the ethics of algorithmic decision-making in healthcare. Journal of medical ethics, 46(3), 205-211.
- Hagemann, V., Rieth, M., Suresh, A., & Kirchner, F. (2023). Human-AI teams—Challenges for a team-centered AI at work. Frontiers in artificial intelligence, 6, 1252897.
- Hertzum, M., Ellingsen, G., & Melby, L. (2021). Drivers of expectations: Why are Norwegian general practitioners skeptical of a prospective electronic health record?. Health Informatics Journal, 27(1), 1460458220987298.
- Holdsworth, M., & Zaghloul, F. (2022, August). The impact of AI in the UK healthcare industry: A socio-technical system theory perspective. In STPIS (pp. 52-63).
- Irizarry, T., DeVito Dabbs, A., & Curran, C. R. (2015). Patient portals and patient engagement: a state of the science review. Journal of medical Internet research, 17(6), e148.
- Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of management annals, 14(1), 366-410.
- Khera, R., Simon, M. A., & Ross, J. S. (2023). Automation bias and assistive AI: risk of harm from AI-driven clinical decision support. Jama, 330(23), 2255-2257.
- Lebovitz, S., Lifshitz-Assaf, H., & Levina, N. (2022). To engage or not to engage with AI for critical judgments: How professionals deal with opacity when using AI for medical diagnosis. Organization science, 33(1), 126-148.
- Leslie, M., Paradis, E., Gropper, M. A., Kitto, S., Reeves, S., & Pronovost, P. (2017). An ethnographic study of health information technology use in three intensive care units. Health Services Research, 52(4), 1330-1348.
- Lieu, T. A., Altschuler, A., Weiner, J. Z., East, J. A., Moeller, M. F., Prausnitz, S., ... & Awsare, S. (2019). Primary care physicians’ experiences with and strategies for managing electronic messages. JAMA network open, 2(12), e1918287.
- Liu, L., Chien, A. T., & Singer, S. J. (2023, July). Enabling system functionalities of primary care practices for team dynamics in transformation to team-based care: a qualitative comparative analysis (QCA). In Healthcare (Vol. 11, No. 14, p. 2018). MDPI.
- McFarland, S., Coufopolous, A., & Lycett, D. (2021). The effect of telehealth versus usual care for home-care patients with long-term conditions: a systematic review, meta-analysis and qualitative synthesis. Journal of telemedicine and telecare, 27(2), 69-87.
- Melnick, E. R., Harry, E., Sinsky, C. A., Dyrbye, L. N., Wang, H., Trockel, M. T., ... & Shanafelt, T. (2020). Perceived electronic health record usability as a predictor of task load and burnout among US physicians: mediation analysis. Journal of medical Internet research, 22(12), e23382.
- Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453.
- Parimbelli, E., Wilk, S., Kingwell, S., Andreev, P., & Michalowski, W. (2018, December). Shared decision-making ontology for a healthcare team executing a workflow, an instantiation for metastatic spinal cord compression management. In AMIA Annual Symposium Proceedings (Vol. 2018, p. 877).
- Pelland, K. D., Baier, R. R., & Gardner, R. L. (2017). ‘It is like texting at the dinner table’: a qualitative analysis of the impact of electronic health records on patient–physician interaction in hospitals. BMJ Health & Care Informatics, 24(2).
- Pine, K. H., & Mazmanian, M. (2017). Artful and contorted coordinating: The ramifications of imposing formal logics of task jurisdiction on situated practice. Academy of Management Journal, 60(2), 720-742.
- Rao-Gupta, S., Kruger, D., Leak, L. D., Tieman, L. A., & Manworren, R. C. (2018). Leveraging interactive patient care technology to improve pain management engagement. Pain Management Nursing, 19(3), 212-221.
- Reim, D., Eom, B. W., & Kim, Y. W. (2013). Experiences of multidisciplinary gastric cancer treatment at the National Cancer Center, Korea. Korean Journal of Clinical Oncology, 9(2), 71-75.
- Rodriguez, J. A., Betancourt, J. R., Sequist, T. D., & Ganguli, I. (2021). Differences in the use of telephone and video telemedicine visits during the COVID-19 pandemic. The American journal of managed care, 27(1), 21.
- Rowland, S., Brewer, L. C., & Rosas, L. G. (2024). Digital health equity–A call to action for clinical and translational scientists. Journal of clinical and translational science, 8(1), e145.
- Shaw, J., Brewer, L. C., & Veinot, T. (2021). Recommendations for health equity and virtual care arising from the COVID-19 pandemic: narrative review. JMIR Formative Research, 5(4), e23233.
- Tamborero, D., Dienstmann, R., Rachid, M. H., Boekel, J., Lopez-Fernandez, A., Jonsson, M., ... & Lehtiö, J. (2022). The Molecular Tumor Board Portal supports clinical decisions and automated reporting for precision oncology. Nature cancer, 3(2), 251-261.
- Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature medicine, 25(1), 44-56.
- Torous, J., Bucci, S., Bell, I. H., Kessing, L. V., Faurholt‐Jepsen, M., Whelan, P., ... & Firth, J. (2021). The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World psychiatry, 20(3), 318-335.
- Unver, M. B. (2023). Governing fiduciary relationships or building up a governance model for trust in AI? Review of healthcare as a socio-technical system. International Review of Law, Computers & Technology, 37(2), 198-226.
- van Kessel, R., Hrzic, R., O'Nuallain, E., Weir, E., Wong, B. L. H., Anderson, M., ... & Mossialos, E. (2022). Digital health paradox: international policy perspectives to address increased health inequalities for people living with disabilities. Journal of medical Internet research, 24(2), e33819.
- Vinade Chagas, M. E., Rodrigues Moleda Constant, H. M., Cristina Jacovas, V., Castro da Rocha, J., Galves Crivella Steimetz, C., Cotta Matte, M. C., ... & Cezar Cabral, F. (2021). The use of telemedicine in the PICU: a systematic review and meta-analysis. PLoS One, 16(5), e0252409.
- Vos, J. F., Boonstra, A., Kooistra, A., Seelen, M., & Van Offenbeek, M. (2020). The influence of electronic health record use on collaboration among medical specialties. BMC health services research, 20(1), 676.
- Won, C. W., Ha, E., Jeong, E., Kim, M., Park, J., Baek, J. E., ... & Kim, H. (2021). World health organization integrated care for older people (ICOPE) and the integrated care of older patients with frailty in primary care (ICOOP_frail) study in korea. Annals of geriatric medicine and research, 25(1), 10.
- Zhang, Z., Joy, K., Upadhyayula, P., Ozkaynak, M., Harris, R., & Adelgais, K. (2021). Data work and decision making in emergency medical services: a distributed cognition perspective. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2), 1-32.
References
Abdul Rehman, M., Naeem, U., Rani, A., Banatwala, U. E. S. S., Salman, A., Abdullah Khalid, M., ... & Tahir, E. (2023). How well does the virtual format of oncology multidisciplinary team meetings work? An assessment of participants’ perspectives and limitations: a scoping review. PLoS One, 18(11), e0294635.
Alraddadi, K. M., Aljohani, A. S. D., Saadi Saad Alahmadi, K., Abuyabes, A. A., Alharbi, K. N. S., Alrashidi, M. N. F., ... & Alanazy, M. S. (2024). Evaluating How Artificial Intelligence And Electronic Health Record Systems Influence Physician–Nurse Communication, Workflow Efficiency, And Clinical Decision-Making. The Review of Diabetic Studies, 1-18.
Alobayli, F., O’Connor, S., Holloway, A., & Cresswell, K. (2023). Electronic health record stress and burnout among clinicians in hospital settings: a systematic review. Digital Health, 9, 20552076231220241.
Al Saiegh, F., Munoz, A., Velagapudi, L., Theofanis, T., Suryadevara, N., Patel, P., ... & Herial, N. A. (2022). Patient and procedure selection for mechanical thrombectomy: Toward personalized medicine and the role of artificial intelligence. Journal of Neuroimaging, 32(5), 798-807.
Baxter, G., & Sommerville, I. (2011). Socio-technical systems: From design methods to systems engineering. Interacting with computers, 23(1), 4-17.
Eberly, L. A., Kallan, M. J., Julien, H. M., Haynes, N., Khatana, S. A. M., Nathan, A. S., ... & Adusumalli, S. (2020). Patient characteristics associated with telemedicine access for primary and specialty ambulatory care during the COVID-19 pandemic. JAMA network open, 3(12), e2031640.
Edmondson, A. C. (2018). The fearless organization: Creating psychological safety in the workplace for learning, innovation, and growth. John Wiley & Sons.
Endsley, M. R., Cooke, N., McNeese, N., Bisantz, A., Militello, L., & Roth, E. (2022). Special issue on human-AI teaming and special issue on AI in healthcare. Journal of Cognitive Engineering and Decision Making, 16(4), 179-181.
Fennelly, O., Cunningham, C., Grogan, L., Cronin, H., O’Shea, C., Roche, M., ... & O’Hare, N. (2020). Successfully implementing a national electronic health record: a rapid umbrella review. International Journal of Medical Informatics, 144, 104281.
Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J., Hughes, G., Hinder, S., ... & Shaw, S. (2017). Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. Journal of medical Internet research, 19(11), e8775.
Greenhalgh, T., Shaw, S., Wherton, J., Vijayaraghavan, S., Morris, J., Bhattacharya, S., ... & Hodkinson, I. (2018). Real-world implementation of video outpatient consultations at macro, meso, and micro levels: mixed-method study. Journal of medical Internet research, 20(4), e150.
Greenhalgh, T., & Papoutsi, C. (2018). Studying complexity in health services research: desperately seeking an overdue paradigm shift. BMC medicine, 16(1), 95.
Grote, T., & Berens, P. (2020). On the ethics of algorithmic decision-making in healthcare. Journal of medical ethics, 46(3), 205-211.
Hagemann, V., Rieth, M., Suresh, A., & Kirchner, F. (2023). Human-AI teams—Challenges for a team-centered AI at work. Frontiers in artificial intelligence, 6, 1252897.
Hertzum, M., Ellingsen, G., & Melby, L. (2021). Drivers of expectations: Why are Norwegian general practitioners skeptical of a prospective electronic health record?. Health Informatics Journal, 27(1), 1460458220987298.
Holdsworth, M., & Zaghloul, F. (2022, August). The impact of AI in the UK healthcare industry: A socio-technical system theory perspective. In STPIS (pp. 52-63).
Irizarry, T., DeVito Dabbs, A., & Curran, C. R. (2015). Patient portals and patient engagement: a state of the science review. Journal of medical Internet research, 17(6), e148.
Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of management annals, 14(1), 366-410.
Khera, R., Simon, M. A., & Ross, J. S. (2023). Automation bias and assistive AI: risk of harm from AI-driven clinical decision support. Jama, 330(23), 2255-2257.
Lebovitz, S., Lifshitz-Assaf, H., & Levina, N. (2022). To engage or not to engage with AI for critical judgments: How professionals deal with opacity when using AI for medical diagnosis. Organization science, 33(1), 126-148.
Leslie, M., Paradis, E., Gropper, M. A., Kitto, S., Reeves, S., & Pronovost, P. (2017). An ethnographic study of health information technology use in three intensive care units. Health Services Research, 52(4), 1330-1348.
Lieu, T. A., Altschuler, A., Weiner, J. Z., East, J. A., Moeller, M. F., Prausnitz, S., ... & Awsare, S. (2019). Primary care physicians’ experiences with and strategies for managing electronic messages. JAMA network open, 2(12), e1918287.
Liu, L., Chien, A. T., & Singer, S. J. (2023, July). Enabling system functionalities of primary care practices for team dynamics in transformation to team-based care: a qualitative comparative analysis (QCA). In Healthcare (Vol. 11, No. 14, p. 2018). MDPI.
McFarland, S., Coufopolous, A., & Lycett, D. (2021). The effect of telehealth versus usual care for home-care patients with long-term conditions: a systematic review, meta-analysis and qualitative synthesis. Journal of telemedicine and telecare, 27(2), 69-87.
Melnick, E. R., Harry, E., Sinsky, C. A., Dyrbye, L. N., Wang, H., Trockel, M. T., ... & Shanafelt, T. (2020). Perceived electronic health record usability as a predictor of task load and burnout among US physicians: mediation analysis. Journal of medical Internet research, 22(12), e23382.
Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453.
Parimbelli, E., Wilk, S., Kingwell, S., Andreev, P., & Michalowski, W. (2018, December). Shared decision-making ontology for a healthcare team executing a workflow, an instantiation for metastatic spinal cord compression management. In AMIA Annual Symposium Proceedings (Vol. 2018, p. 877).
Pelland, K. D., Baier, R. R., & Gardner, R. L. (2017). ‘It is like texting at the dinner table’: a qualitative analysis of the impact of electronic health records on patient–physician interaction in hospitals. BMJ Health & Care Informatics, 24(2).
Pine, K. H., & Mazmanian, M. (2017). Artful and contorted coordinating: The ramifications of imposing formal logics of task jurisdiction on situated practice. Academy of Management Journal, 60(2), 720-742.
Rao-Gupta, S., Kruger, D., Leak, L. D., Tieman, L. A., & Manworren, R. C. (2018). Leveraging interactive patient care technology to improve pain management engagement. Pain Management Nursing, 19(3), 212-221.
Reim, D., Eom, B. W., & Kim, Y. W. (2013). Experiences of multidisciplinary gastric cancer treatment at the National Cancer Center, Korea. Korean Journal of Clinical Oncology, 9(2), 71-75.
Rodriguez, J. A., Betancourt, J. R., Sequist, T. D., & Ganguli, I. (2021). Differences in the use of telephone and video telemedicine visits during the COVID-19 pandemic. The American journal of managed care, 27(1), 21.
Rowland, S., Brewer, L. C., & Rosas, L. G. (2024). Digital health equity–A call to action for clinical and translational scientists. Journal of clinical and translational science, 8(1), e145.
Shaw, J., Brewer, L. C., & Veinot, T. (2021). Recommendations for health equity and virtual care arising from the COVID-19 pandemic: narrative review. JMIR Formative Research, 5(4), e23233.
Tamborero, D., Dienstmann, R., Rachid, M. H., Boekel, J., Lopez-Fernandez, A., Jonsson, M., ... & Lehtiö, J. (2022). The Molecular Tumor Board Portal supports clinical decisions and automated reporting for precision oncology. Nature cancer, 3(2), 251-261.
Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature medicine, 25(1), 44-56.
Torous, J., Bucci, S., Bell, I. H., Kessing, L. V., Faurholt‐Jepsen, M., Whelan, P., ... & Firth, J. (2021). The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World psychiatry, 20(3), 318-335.
Unver, M. B. (2023). Governing fiduciary relationships or building up a governance model for trust in AI? Review of healthcare as a socio-technical system. International Review of Law, Computers & Technology, 37(2), 198-226.
van Kessel, R., Hrzic, R., O'Nuallain, E., Weir, E., Wong, B. L. H., Anderson, M., ... & Mossialos, E. (2022). Digital health paradox: international policy perspectives to address increased health inequalities for people living with disabilities. Journal of medical Internet research, 24(2), e33819.
Vinade Chagas, M. E., Rodrigues Moleda Constant, H. M., Cristina Jacovas, V., Castro da Rocha, J., Galves Crivella Steimetz, C., Cotta Matte, M. C., ... & Cezar Cabral, F. (2021). The use of telemedicine in the PICU: a systematic review and meta-analysis. PLoS One, 16(5), e0252409.
Vos, J. F., Boonstra, A., Kooistra, A., Seelen, M., & Van Offenbeek, M. (2020). The influence of electronic health record use on collaboration among medical specialties. BMC health services research, 20(1), 676.
Won, C. W., Ha, E., Jeong, E., Kim, M., Park, J., Baek, J. E., ... & Kim, H. (2021). World health organization integrated care for older people (ICOPE) and the integrated care of older patients with frailty in primary care (ICOOP_frail) study in korea. Annals of geriatric medicine and research, 25(1), 10.
Zhang, Z., Joy, K., Upadhyayula, P., Ozkaynak, M., Harris, R., & Adelgais, K. (2021). Data work and decision making in emergency medical services: a distributed cognition perspective. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2), 1-32.