Architecture Design of Healthcare Software-as-a- Service Platform for Cloud-Based Clinical Decision Support Service
2
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Objectives: To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. Methods: We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft’s Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform- as-a-Service (PaaS) was used. Results: The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. Conclusions: We expect that cloudbased HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs.
Abstract
Objectives: To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. Methods: We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft’s Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform- as-a-Service (PaaS) was used. Results: The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. Conclusions: We expect that cloudbased HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs.
참고문헌 (23)
- Kanagaraj G, "Proposal of an open-source cloud computing system for exchanging medical images of a hospital information system", Proceedings of 2011 3rd International Conference on Trendz in Information Sciences and Computing (TISC), pp.144~149 (2011)
- Padhy RP, "Design and implementation of a cloud based rural healthcare information system model", Univers J Appl Comput Sci Technol, 2(1), pp.149~157 (2012)
- Yoon D, "Adoption of electronic health records in Korean tertiary teaching and general hospitals", Int J Med Inform, 81(3), pp.196~203 (2012)
- He C, "A cloud computing solution for hospital information system", Proceedings of 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS), pp.517~520 (2010)
- Kagadis GC, "Cloud computing in medical imaging", Med Phys, 40(7), pp.070901~ (2013)
- Kaushal DS, "Cloud computing services in med-ical healthcare solutions", Int J Res, 1(4), pp.312~324 (2014)
- Kuo AM, "Opportunities and challenges of cloud computing to improve health care services", J Med Internet Res, 13(3), pp.67~ (2011)
- "EMR Adoption Model 2014" (2014)[URL]
- "Clinical decision support: more than just ‘Alerts’ tipsheet" (2014)[URL]
- "Context-aware knowledge retrieval (infobutton) decision support service implementation guide" (2014)[URL]
- "HL7 Version 3 Standard:Decision Support Service (DSS)" (2011)[URL]
- "The Forrester WaveTM: platform-as-a-service for app dev and delivery professionals, Q2 2011" (2011)[URL]
- Heiser J, "Assessing the security risks of cloud computing" (2008), Gartner Inc
- Could Security Alliance, "The Notorious nine: cloud computing top threats in 2013" (2013), Cloud Security Alliance
- Catteddu D, "Cloud computing: benefits, risks and recommendations for information security" (2009), European Network and Information Security Agency
- Armbrust M, "Above the clouds: a Berkeley view of cloud computing. Berkeley (CA): Department of Electrical Engineering and Computer Sciences" (2009), University of California at Berkeley
- Karthikeyan N, "Cloud based emergency health care information service in India", J Med Syst, 36(6), pp.4031~4036 (2012)
- Pandey S, "An autonomic cloud environment for hosting ECG data analysis services", Future Gener Comput Syst, 28(1), pp.147~154 (2012)
- Hsieh JC, "A cloud computing based 12-lead ECG telemedicine service", BMC Med Inform Decis Mak, 12, pp.77~ (2012)
- Fong EM, "Mobile cloud-computing-based healthcare service by noncontact ECG monitoring", Sensors(Basel), 13(12), pp.16451~16473 (2013)
- Hussain M, "Cloud-based smart CDSS for chronic diseases", Health Technol, 3(2), pp.153~175 (2013)
- Fernandez-Cardenosa G, "Analysis of cloud-based solutions on EHRs systems in different scenarios", J Med Syst, 36(6), pp.3777~3782 (2012)
- Dixon BE, "A pilot study of distributed knowledge management and clinical decision support in the cloud", Artif Intell Med, 59(1), pp.45~53 (2013)
