Healthcare Information System and Data Mining

Abstract:

This paper is to integrate information technology and medical-related technologies to develop a healthcare information system for comprehensive geriatric assessment. This system not only can process geriatric consultation services and ensure that all patient’s information are stored in standardized format , but also provide medical personnel for statistical analysis and processing purposes. This paper uses the Apriori algorithm of data mining for helping doctors to find out the relationship of geriatric syndrome. The systems of this paper can improve increase the timeliness and accuracy of patient care and administration information, increase service capacity, reduce personnel costs, and improve the quality of patient care in geriatric medicine. Furthermore, making the theories and applications of medical informatics will be more extensive and convenient for researcher and healthcare-related industry.

• Periodical: Applied Mechanics and Materials (Volumes 55-57)
• Pages: 561-566
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.55-57.561
• Online since: May 2011
• Authors: Nai Wen Kuo
• Keywords: Association Rule, Data Mining (DM), Healthcare Information System

References

[1] Liang-Kung Chen: The health challenges of aging society, Taipei Veterans General Hospital Magazine, Vol. 144 (2009), pp.2-8.

[2] Dowliing A.F. JR. : Do hospital staff interfere with computer system implementation?, HealthCare Management Review, Vol. 5 (1980), pp.23-32.

[3] Janine A. Overcash, Jason Beckstead, Martine Extermann and Sara cob: The abbreviated comprehensive geriatric assessment (aCGA): a retrospective analysis, Critical Reviews in Oncology/Hematology, Vol. 54, no. 2 (2005), pp.129-136.

DOI: 10.1016/j.critrevonc.2004.12.002

[4] Edward MF Leung: Team approach and comprehensive geriatric assessment, Geriatrics and Gerontology International, Vol. 4 (2004), pp.41-44.

[5] Gray L, Moore K, Smith R, Dorevitch M.: Supply of inpatient geriatric medical services in Australia, Internal Medical Journal , Vol. 37(2007), p.270–273.

DOI: 10.1111/j.1445-5994.2007.01317.x

[6] Stuck AE, Siu AL, Wieland GD, Adams J, Rubenstein LZ. : Comprehensive geriatric assessment: A meta-analysis of controlled trials, Lancet, Vol. 342 (1993), p.1032–1036.

DOI: 10.1016/0140-6736(93)92884-v

[7] Gray L. : Geriatric consultation: Is there a future ? , Age and Ageing, Vol. 36 (2007), p.1–2.

[8] Huub A.A.M. Maas et al.: Comprehensive Geriatric assessment and its clinical impact in oncology, European Journal of Cancer, Vol. 43 (2007), pp.2161-2169.

[9] David Solomon: National institutes of health consensus development conference statement: geriatric assessment methods for clinical decision-making, Journal of the American Geriatrics Society, Vol. 36 (1988), pp.342-347.

DOI: 10.1111/j.1532-5415.1988.tb02362.x

[10] Delen Dursun : Analysis of cancer data: a data mining approach, Expert Systems, Vol. 26, no. 1 (2009), pp.100-112.

DOI: 10.1111/j.1468-0394.2008.00480.x

[11] Nai-Wen Kuo and Yao-Yu Chung: Construction of Comprehensive Geriatric Assessment Information System – A Case Study of Medical Center in Taiwan, 2010 INFORMS Service Science Conference, Taipei, Taiwan, July 7-10 (2010), pp.255-261.

[12] Nai-Wen Kuo : A System Planning for Healthcare Services, 2010 International Colloquium on Computing, Communication, Control, and Management (CCCM 2010), Yangzhou , China, August 20- 22 (2010), pp.442-446.

[13] Sherman, F. T. : Functional assessment: easy-to-use screening tools speed initial office work-up, Geriatrics, Vol. 56, no. 8 (2001), pp.36-40.