DOI QR코드

DOI QR Code

Open Platform for Improvement of e-Health Accessibility

의료정보서비스 접근성 향상을 위한 개방형 플랫폼 구축방안

  • Lee, Hyun-Jik (Division of Convergence Computer & Media, Mokwon University) ;
  • Kim, Yoon-Ho (Division of Convergence Computer & Media, Mokwon University)
  • 이현직 (목원대학교 융합컴퓨터미디어학부) ;
  • 김윤호 (목원대학교 융합컴퓨터미디어학부)
  • Received : 2017.10.10
  • Accepted : 2017.11.25
  • Published : 2017.11.30

Abstract

In this paper, we designed the open service platform based on integrated type of individual customized service and intelligent information technology with individual's complex attributes and requests. First, the data collection phase is proceed quickly and accurately to repeat extraction, transformation and loading. The generated data from extraction-transformation-loading process module is stored in the distributed data system. The data analysis phase is generated a variety of patterns that used the analysis algorithm in the field. The data processing phase is used distributed parallel processing to improve performance. The data providing should operate independently on device-specific management platform. It provides a type of the Open API.

본 논문에서는 개개인의 복합적 속성과 요구를 반영한 통합된 개인 맞춤형 서비스와 지능정보기술을 기반으로 의료서비스 접근성을 향상시킬 수 있는 개방형 서비스플랫폼의 구축방안에 대하여 설계하였다. 먼저, 데이터 수집 및 저장단계는 데이터 추출, 변환, 로딩을 반복하며 신속하고 정확하게 처리한다. ETL 모듈로부터 생성된 데이터는 분산 파일 시스템에 저장한다. 데이터 분석단계는 스토리지에 저장된 과거 의료 데이터들을 기반으로 기계학습과 데이터 마이닝 분야에서 사용되고 있는 분석 알고리즘을 적용하여 다양한 패턴들을 생성한다. 데이터 처리단계에서는 데이터를 신속히 처리해야 하므로 보통 작업을 병렬 및 분산 처리하여 성능을 향상시킨다. 데이터 제공방식은 디바이스별 운영하는 플랫폼에 독립적으로 동작해야 하며, 데이터 전송 시 네트워크 부하가 적고, 다양한 형태의 서비스를 제공하기 위하여 Open API 형태로 제공한다.

Keywords

References

  1. Kohn LT, Corrigan JM, Donaldson MS, "To Err Is Human: Building a Safer Health System", National Academies Press Washington DC, 2000.
  2. Institute of Medicine, "Crossing the Quality Chasm: A New Health System for the 21st Century", National Academies Press Washington DC, 2001.
  3. Zhan C, Miller MR, "Excess length of stay, charges, and mortality attributable to medical injuries during hospitalization", JAMA, 2003.
  4. National Committee for Quality Assurance, "The State of Health Care Quality", NCQA, 2010.
  5. Casalino LP, Dunham D, Chin MH, Bielang R, Kistner EO, Karrison TG, Ong MK, Sarkar U, McLaughlin MA, Meltzer DO, "Frequency of failure to inform patients of clinically significant outpatient test results", Arch Intern Med, 2009.
  6. Schuster MA, McGlynn EA, Brook RH, "How good is the quality of health care in the United States?", Milbank Q, 1998.
  7. Egan BM, Zhao Y, Axon RN, "US trends in prevalence, awareness, treatment, and control of hypertension, 1988-2008", JAMA, 2010.
  8. Saydah SH, Fradkin J, Cowie CC, "Poor control of risk factors for vascular disease among adults with previously diagnosed diabetes", JAMA, 2004.
  9. Talmadge E. King, Margaret B. Wheeler, "Medical Management of Vulnerable and Underserved Patients", McGraw-Hill, 2007.
  10. Chang-Hun O, Yong-Hee Jeon, "Design and Implementation of Electronic Medical Management", Journal of KIIT, Vol. 10, No. 10, Oct. 2012.
  11. Hoste Kenneth, Aashish Phansalkar, Lieven Eeckhout, Andy Georges, Lizy K. John, Koen De Bosschere, "Performance Prediction Based on Inherent Program Similarity", In Proc. of the 15th International Conference on Parallel Architectures and Compilation Techniques, ACM, 2006.
  12. E. Rahm, Hong Hai Do, "Data Cleansing: Problems and Current Approaches", IEEE Bulletin on Data Engineering, 2000.
  13. P. Vassiliadis, A Simitsis, "Extraction, Transformation, and Loading", Encyclopedia of Database Systems, 2009.
  14. R. Catell, "Scalable SQL and NoSQL Data Stores", ACM SIGMOD Record, 2011.
  15. N. Hurst, "Visual Guide to NoSQL Systems", 2010.

Cited by

  1. A Study on the Policy Trends for the Revitalization of Medical Big Data Industry vol.18, pp.4, 2017, https://doi.org/10.14400/jdc.2020.18.4.325