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Clinical Decision-Support System with Electronic Health Record: Digitization of Research in Pharma

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Innovation in Medicine and Healthcare Systems, and Multimedia

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 145))

Abstract

Clinical Decision-Support (CDS) systems are architected to resolve knowledge-intensive tasks for supporting decision-making processes in the medical fields and the healthcare industry. Furthermore, CDS systems are expected to promote and contribute to the drug discovery process in pharmaceutical companies, while the CDS system can be connected and collaborated with electronic health record (EHR). However, current solutions for CDS are not well-established across different organizations and institutions in information societies because of high implementation costs and various, complex decision-making problems by medical staffs. In this paper, we suggest that the reference architecture and framework for the CDS system with EHR will be proposed and verified by the case in a hospital. In addition, the challenge and future activities for this area are expressed.

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References

  1. Berner, E.S.: Clinical Decision Support Systems: State of the Art. AHRQ Publication (2009)

    Google Scholar 

  2. Shortliffe, E.H., et al.: Biomedical informatics: defining the science and its role in health professional education. In: Hutchison D., Kanade T., Kittler J., Kleinberg J.M., Mattern F., Mitchell J.C. (eds.) Information Quality in e-Health. Lecture Notes in Computer Science. Springer, Berlin, pp. 711–714 (2011)

    Google Scholar 

  3. Zavala, A.M., Day, G.E., Plummer, D., Bamford-Wade, A.: Decision-making under pressure: medical errors in uncertain and dynamic environments. Aust. Health Rev. (2017). http://dx.doi.org/10.1071/AH16088. PubMed PMID: 28578757

  4. Walker, J.M., Tingley, S.T.: Clinical decision support. In: Walker J.M.M.D., Walker J.M., Bieber E.J. (eds.) Implementing an Electronic Health Record System. Health Informatics. Springer, New York, pp. 67–76 (2005)

    Google Scholar 

  5. Kawamoto, K., Houlihan, C.A., Balas, E.A., Lobach, D.F.: Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ 330, 765 (2005). https://doi.org/10.1136/bmj.38398.500764.8f

    Article  Google Scholar 

  6. Garg, A.X., Adhikari, N.K.J., McDonald, H., Rosas-Arellano, M.P., Devereaux, P.J., Beyene, J., et al.: Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 293, 1223–1238 (2005)

    Article  Google Scholar 

  7. Bates, D.W., Kuperman, G.J., Wang, S., Gandhi, T., Kittler, A., Volk, L., et al.: Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. J. Am. Med. Inf. Assoc. 10, 523–530 (2003). https://doi.org/10.1197/jamia.M1370

    Article  Google Scholar 

  8. S. Boardman, E. Harrington. Open Group Snapshot - Open Platform 3.0â„¢. The Open Group, 2015

    Google Scholar 

  9. Alwadain, A., Fielt, E., Korthaus, A., Rosemann, M.: A comparative analysis of the integration of SOA elements in widely-used enterprise architecture frameworks. Int. J. Intell. Inf. Technol. 9(2), 54–70 (2014)

    Article  Google Scholar 

  10. Buckl, S., Matthes, F., Schulz, C., Schweda, C.M.: Exemplifying a framework for interrelating enterprise architecture concerns. In: Sicilia, M.A., Kop, C., Sartori, F. (eds.) Ontology, Conceptualization and Epistemology for Information Systems, Software Engineering and Service Science, vol. 62, pp. 33–46. Springer, Berlin (2010)

    Chapter  Google Scholar 

  11. Masuda, Y., Shirasaka, S., Yamamoto, S., Hardjono, T. 2017 7 1: Int. J. Enterp. Inf. Syst.- IJEIS. IGI Glob. 13, 3, pp. 1–22. https://doi.org/10.4018/ijeis.2017070101

    Article  Google Scholar 

  12. Masuda, Y., Shirasaka, S., Yamamoto, S., Hardjono, T.: Architecture board practices in adaptive enterprise architecture with digital platform: a case of global healthcare enterprise. Int. J. Enterp. Inf. Syst. IGI Glob. 14, 1 (2018)

    Article  Google Scholar 

  13. Lowe, D.: 7 Steps to Drug Discovery. ACS Webinars, American Chemical Society (2014). [online]

    Google Scholar 

  14. Turk, M.: Electronic health records: how to suture the gap between privacy and efficient delivery of healthcare. Brooklyn Law Rev. 80, 565–597 (2015). Accessed https://www.brooklaw.edu

  15. Murphy-Abdouch, K., Biedermann, S.: The electronic health record. In: Fenton, S.H., Biedermann, S. (eds.) Introduction to healthcare informatics, pp. 25–70. AHIMA Press, Chicago (2014)

    Google Scholar 

  16. International Organization for Standardization (ISO). Health Informatics-electronic Health Record Definition, Scope and Context, ISO/TR 20514 (2005)

    Google Scholar 

  17. World Health Organization Management of patient information. http://apps.who.int/iris/bitstream/10665/76794/1/9789241504645_eng.pdf [310]. ISSN 2220–5462. Nov 2012

  18. Eastaugh, S.R.: The total cost of EHR ownership. Healthc. Financ. Manag. 67(2), 66–70 (2013). Accessed https://www.hfma.org/hfm

  19. Silverman, R.D.: EHRs, EMRs, and health information technology: to meaningful use and beyond. J. Leg. Med. 34(1), 1–6 (2013). https://doi.org/10.1080/01947648.2013.768134

    Article  Google Scholar 

  20. Greenes R.A. (ed.): Clinical Decision Support: The Road to Broad Adoption, 2nd edn. Elsevier Science, Burlington (2014)

    Google Scholar 

  21. Wulff, A., Haarbrandt, B., et al.: An interoperable clinical decision-support system for early detection of SIRS in pediatric intensive care using openEHR. Artif. Intell. Medi. (2018). Elsevier

    Google Scholar 

  22. Aceto, Giuseppe, Persico, Valerio, Pescapéa, Antonio: The role of information and communication technologies in healthcare: taxonomies, perspectives, and challenges. J. Netw. Comput. Appl. 107(2018), 125–154 (2018)

    Article  Google Scholar 

  23. Calabrese, B., Cannataro, M., Cloud computing in healthcare and biomedicine. Scalable Comput. Pract. Exp. 16(1), 1–18 (2015)

    Google Scholar 

  24. Chawla, N.V., Davis, D.A.: Bringing big data to personalized healthcare: a patient-centered framework. J. Gen. Intern. Med. 28(3), 660–665 (2013)

    Article  Google Scholar 

  25. Archenaa, J., Anita, E.M.: A survey of big data analytics in healthcare and government. Proc. Comput. Sci. 50, 408–413 (2015)

    Article  Google Scholar 

  26. Chang, H., Choi, M.: Big data and healthcare: building an augmented world. Health. Inf. Res. 22(3), 153–155 (2016)

    Article  Google Scholar 

  27. Jee, K., Kim, G.-H.: Potentiality of big data in the medical sector: focus on how to reshape the healthcare system. Healthcare Inf. Res. 19(2), 79–85 (2013)

    Article  MathSciNet  Google Scholar 

  28. Garnier, J. -L., Bérubé, J., Hilliard, R.: Architecture Guidance Study Report 140430, ISO/IEC JTC 1/SC 7 Software and systems engineering (2014)

    Google Scholar 

  29. Tamm, T., Seddon, P.B., Shanks, G., Reynolds, P.: How does enterprise architecture add value to organizations? Commun. Assoc. Inf. Syst. 28, 10 (2011)

    Google Scholar 

  30. Chen, H.M., Kazman, R., Perry, O.: From software architecture analysis to service engineering: an empirical study of methodology development for enterprise SOA implementation. IEEE Trans. Serv. Comput. 3(2), 145–160 (2014). https://doi.org/10.1109/TSC.2010.21

    Article  Google Scholar 

  31. Richards, M.: Microservices vs. Service-Oriented Architecture, 1st edn. O’ Reilly Media (2015)

    Google Scholar 

  32. MacKenzie, C.M., Laskey, K., McCabe, F., Brown, P.F., and Metz, R.: Reference model for SOA 1.0. (Technical report), Advancing Open Standards for the Information Society (2006)

    Google Scholar 

  33. Newman, S.: Building Microservices. O’Reilly (2015)

    Google Scholar 

  34. Familiar, B.: Microservices, IoT, and Azure: Leveraging DevOps and Microservice Architecture to Deliver SaaS Solutions. Apress Media, LLC (2015)

    Google Scholar 

  35. Muhammad, K., Khan, M.N.A.: Augmenting mobile cloud computing through enterprise architecture: survey paper. Int. J. Grid Distrib. Comput. 8(3), 323–336 (2015)

    Article  MathSciNet  Google Scholar 

  36. Gill, A.Q., Smith, S., Beydoun, G., Sugumaran, V.: Agile enterprise architecture: a case of a cloud technology-enabled government enterprise transformation. In: Proceedings of the 19th Pacific Asia Conference on Information Systems (PACIS 2014), pp. 1–11 (2014)

    Google Scholar 

  37. Masuda, Y., Shirasaka, S., Yamamoto, S.: Integrating mobile IT/Cloud into enterprise architecture: a comparative analysis. In: Proceedings of the 21th Pacific Asia Conference on Information Systems (PACIS 2016), Paper 4 (2016)

    Google Scholar 

  38. Aleksovska-Stojkovska, L., Loskovska, S.: Clinical decision support systems: medical knowledge acquisition and representation methods. In: IEEE International Conference on Electro/Information Technology (EIT), p. 1 (2010)

    Google Scholar 

  39. Razzaque, A., Karolak, M.: Knowledge management and electronic health record facilitate clinical support to improve healthcare quality. In: International Conference on E-business, Management and Economics (2011)

    Google Scholar 

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Correspondence to Yoshimasa Masuda .

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Masuda, Y., Shepard, D.S., Yamamoto, S., Toma, T. (2019). Clinical Decision-Support System with Electronic Health Record: Digitization of Research in Pharma. In: Chen, YW., Zimmermann, A., Howlett, R., Jain, L. (eds) Innovation in Medicine and Healthcare Systems, and Multimedia. Smart Innovation, Systems and Technologies, vol 145. Springer, Singapore. https://doi.org/10.1007/978-981-13-8566-7_5

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