Open Access
ITM Web Conf.
Volume 62, 2024
International Conference on Exploring Service Science (IESS 2.4)
Article Number 02003
Number of page(s) 13
Section Smart Healthcare & Pharmacy
Published online 01 February 2024
  1. J. M. Corrigan, Crossing the quality chasm. Building a better delivery system, 89. (2005) [Google Scholar]
  2. C. Pires, M. J. Sousa, The Role of Community Pharmacies in Smart Cities: A Brief Systematic Review and a Conceptual Framework. In Proceedings of International Conference on Information Technology and Applications (pp. 629–641). Springer, Singapore (2023) [Google Scholar]
  3. M. M. E. Khatib, G. Ahmed, Robotic pharmacies potential and limitations of artificial intelligence: A case study. IJBIR, 23 (3), 298–312 (2020) [CrossRef] [Google Scholar]
  4. M. I. Pramanik, R. Y. Lau, H. Demirkan, M. A. K. Azad, Smart health: Big data enabled health paradigm within smart cities. Expert Systems with Applications, 87, 370–383 (2017) [CrossRef] [Google Scholar]
  5. S. L. Vargo, R. F. Lusch, Service-dominant logic 2025. Int. J. Res. Mark., 34 (1), 46–67 (2017) [CrossRef] [Google Scholar]
  6. J. C. Spohrer, H. Demirkan, V. Krishna, Service and science. The Science of Service Systems, 325–358 (2011) [CrossRef] [Google Scholar]
  7. K. A. Joiner, R. F. Lusch, Evolving to a new service-dominant logic for health care. Innovation and Entrepreneurship in Health, 25–33 (2016) [CrossRef] [Google Scholar]
  8. F. Polese, S. Barile, F. Caputo, L. Carrubbo, L. Waletzky, Determinants for value cocreation and collaborative paths in complex service systems: A focus on (smart) cities. Service Science, 10 (4), 397–407 (2018) [CrossRef] [Google Scholar]
  9. L. Xiao, Y. Zhang, AI-driven smart pharmacology. Intelligent Pharmacy (2023) [Google Scholar]
  10. A. Bohr, K. Memarzadeh, The rise of artificial intelligence in healthcare applications. In Artificial Intelligence in healthcare (pp. 25–60). Academic Press (2020) [CrossRef] [Google Scholar]
  11. A. M. Preininger, B. South, J. Heiland, A. Buchold, M. Baca, S. Wang, G. P. Jackson, Artificial intelligence-based conversational agent to support medication prescribing. JAMIA open, 3 (2), 225–232 (2020) [CrossRef] [Google Scholar]
  12. A. Bohlmann, J. Mostafa, M. Kumar, Machine learning and medication adherence: scoping review. JMIRx Med, 2(4), e26993 (2021) [CrossRef] [Google Scholar]
  13. R. Li, K. Curtis, S. T. Zaidi, C. Van, R. Castelino, A new paradigm in adverse drug reaction reporting: consolidating the evidence for an intervention to improve reporting. Expert Opinion on Drug Safety, 21 (9), 1193–1204 (2022) [CrossRef] [Google Scholar]
  14. N. Singh, U. Varshney, IT-based reminders for medication adherence: systematic review, taxonomy, framework and research directions. Eur. J. Inf. Syst., 29 (1), 84–108 (2020) [CrossRef] [Google Scholar]
  15. N. G. Badr, Learning Healthcare Ecosystems for Equity in Health Service Provisioning and Delivery: Smart Cities and the Quintuple Aim. In Proceedings of the International Conference on Smart City Applications (pp. 237–251). Cham: Springer International Publishing (2022, October) [Google Scholar]
  16. A. C. Lin, J. Lee, M. K. Gabriel, R. N. Arbet, Y. Ghawaa, A. M. Ferguson, The Pharmacy 5.0 framework: A new paradigm to accelerate innovation for large-scale personalized pharmacy care. AJHP, zxad212 (2023) [Google Scholar]
  17. S. Selvaganapathy, Smart Pharmacy Kanban System in Post Covid Era. In Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, Dec. 7-8 2021, Chennai, India (2021) [Google Scholar]
  18. P. Bhinder, M. S. Oberoi, “Smart Pharmacy” Master Blends Integrated Supply Chains with Patient Care to Uphold Regulatory Compliances. In Annual International Conference of the EMBS. (pp. 1707–1709) (2009, January) [Google Scholar]
  19. N. B. Al-Jehani, Z. A. Hawsawi, N. E. Radwan, M. Farouk, Development of artificial intelligence techniques in Saudi Arabia: the impact on COVID-19 pandemic. Literature review. JESTEC, 16 (6), 4530–4547 (2021) [Google Scholar]
  20. L. Almansoori, F. Almusabi, M. Alharbi, A. Shuhaiber, M. Tubishat, ‘Robpha’: A Robotic-Based Pharmacy for a Smart Hospital. In 2023 International Conference on Smart Applications, Communications and Networking (1–6), IEEE (2023, July) [Google Scholar]
  21. H. Wu, Y. Wang, H. Ma, B. Li, Y. Jin, Vision Based Real-time High-accuracy Automatic Counting with Applications for Smart Pharmacy. In 2021 40th Chinese Control Conference (CCC) (pp. 6429–6435). IEEE. (2021, July). [Google Scholar]
  22. A. Al Harweel, S. P. Angeline Kirubha, M. A. Ghannam, Internet of things based smart pharmacy. In AIP Conference Proceedings (Vol. 2603, No. 1), AIP Publishing (2023, April) [Google Scholar]
  23. A. H. Issa, S. A. Gitaffa, Y. S. Al-Saffar, Developing the HealthCare System for Smart Drugstore Based on the IoT and the Embedded System. IJOIR, 9 (1), 12–30 (2022) [CrossRef] [Google Scholar]
  24. A. M. Goedken, C. M. Butler, R. P. McDonough, M. J. Deninger, W. R. Doucette, Continuous Medication Monitoring (CoMM): A foundational model to support the clinical work of community pharmacists. RSAP, 14 (1), 106–111 (2018) [Google Scholar]
  25. Z. J. Krauss, M. Abraham, J. Coby, Clinical pharmacy services enhanced by electronic health record (EHR) access: An innovation narrative. Pharmacy, 10 (6), 170 (2022) [CrossRef] [Google Scholar]
  26. A. Tapuria, T. Porat, D. Kalra, G. Dsouza, G. S. Xiaohui, V. Curcin, Impact of patient access to their electronic health record: systematic review. Inform Health Soc Care, 46 (2), 194–206 (2021) [CrossRef] [Google Scholar]
  27. S. Rahaman, S. Mohammed, T. Manchanda, R. Mahadik, E-Pharm assist: The future approach for dispensing medicines in smart cities. In 2019 International Conference on Digitization (ICD) (pp. 263–267), IEEE (2019, November) [CrossRef] [Google Scholar]
  28. S. Baldoni, F. Amenta, G. Ricci, Telepharmacy services: present status and future perspectives: a review. Medicina, 55 (7), 327 (2019) [CrossRef] [Google Scholar]
  29. A. Z. Al Meslamani, Applications of AI in pharmacy practice: a look at hospital and community settings. J. Med. Econ., 26 (1), 1081–1084 (2023) [CrossRef] [Google Scholar]
  30. A. Wright, D. S. McEvoy, S. Aaron, A. B. McCoy, M. G. Amato, H. Kim, …, D. F. Sittig, Structured override reasons for drug-drug interaction alerts in electronic health records. JAMIA, 26(10), 934–942 (2019) [Google Scholar]
  31. L. C. Maclagan, N. P. Visanji, Y. Cheng, M. Tadrous, A. M. Lacoste, L. V. Kalia, …, C. Marras, Identifying drugs with disease-modifying potential in Parkinson’s disease using artificial intelligence and pharmacoepidemiology. Pharmacoepidemiol Drug Saf, 29 (8), 864–872 (2020) [CrossRef] [Google Scholar]
  32. C.A. Lester, A. B. Coe, M. P. Dorsch, K. B. Farris, A. J. Flynn, A learning pharmacy practice enabled by the pharmacists’ patient care process. JAPhA, 60(6) (2020) [Google Scholar]
  33. N. G. Badr, L. Carrubbo, M. Ruberto, Responding to COVID-19: Potential Hospital-at- Home Solutions to Re-configure the Healthcare Service Ecosystem. In HEALTHINF (pp. 344–351) (2021) [Google Scholar]
  34. M. Drăgoicea, N. G. Badr, L. M. Manea, Emerging information common goods for the development of complex services in public safety. In 2019 23rd International Conference on System Theory (ICSTCC) (pp. 407-412). IEEE (2019, October) [Google Scholar]
  35. B. Jimmy, J. Jose, Patient medication adherence: measures in daily practice. Oman Med. J., 26 (3), 155 (2011) [CrossRef] [Google Scholar]
  36. A. Zimmermann, R. Schmidt, K. Sandkuhl, D. Jugel, C. Schweda, M. Möhring, B. Keller, Conceptualizing artificial intelligence-based service ecosystems. In International Conference on Applied Human Factors and Ergonomics (pp. 377-384) (2021) [Google Scholar]
  37. S. Reddy, S. Allan, S. Coghlan, P. Cooper, A governance model for the application of AI in health care. JAMIA, 27 (3), 491–497 (2020) [Google Scholar]
  38. V. Bhatt, S. Chakraborty, Improving service engagement in healthcare through internet of things based healthcare systems. JSTPM, 14 (1), 53–73 (2023) [CrossRef] [Google Scholar]
  39. S. F. Blalock, A. J. Beard, S. B. Dusetzina, Individual and interpersonal models of health and illness behavior. Social and Behavioral Aspects of Pharmaceutical Care, 37–60 (2010) [Google Scholar]
  40. D.C. Gonçalves-Bradley, A. R. J. Maria, I. Ricci-Cabello, G. Villanueva, M. S. Fønhus, C. Glenton, S. Shepperd, Mobile technologies to support healthcare provider to healthcare provider communication and management of care. Cochrane Database of Systematic Reviews, (8) (2020). [Google Scholar]
  41. N. G. Badr, M. Sorrentino, M. De Marco, M. Fugini, Improving interaction in integrated chronic care management. In 2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (pp. 265–270) (2019, June) [Google Scholar]
  42. N. Badr, L. Walletzký, L. Carrubbo, M. Dragoicea, A. M. Toli, Modelling for ethical concerns for traceability in time of pandemic “do no harm” or “better safe than sorry!” In 54th Annual Hawaii International Conference on System Sciences, HICSS 2021 (pp. 1779–1788) (2021) [Google Scholar]
  43. N. G. Badr, Learning Healthcare Ecosystems for Equity in Health Service Provisioning and Delivery: Smart Cities and the Quintuple Aim. In: Ben Ahmed, M., Boudhir, A.A., Santos, D., Dionisio, R., Benaya, N. (eds) Innovations in Smart Cities Applications Volume 6. SCA 2022. Lecture Notes in Networks and Systems, vol 629. Springer, Cham (2023) [Google Scholar]
  44. E. Jaakkola, Designing conceptual articles: four approaches. AMS review, 10 (1-2), 18–26 (2020) [CrossRef] [Google Scholar]
  45. S. D. Reese. Writing the conceptual article: A practical guide. Digital Journalism, 11(7), 1195–1210. (2023) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.