Article Details

A Comparative Analysis on Using Various Applications and Techniques of Data Mining and Data Warehousing In a Healthcare Management |

Vijay S. Jondhale, Dr. Sagar S. Jambhorkar, in International Journal of Information Technology and Management | IT & Management


Data mining as one ofmany constituents of health care has been used intensively and extensively inmany organizations around the globe as an efficient technique of findingcorrelations or patterns among dozens of fields in large relational databasesto results into more useful health information. In healthcare, data mining isbecoming increasingly popular and essential. Data mining applications cangreatly benefits all parties involved in health care industry. The huge amountsof data generated by healthcare transactions are too complex and voluminous tobe processed and analyzed by traditional methods. Data mining provides themethodology and technology to transform huge amount of data into usefulinformation for decision making. This paper illustratesdata mining will enable clinicians and managers to find valuable new patternsin data, leading to potential improvement of resource utilization and patienthealth. As the patterns are based on recent clinical practice, they representthe ultimate in evidence-based care. Healthcare presentsunique challenges for the architect of a data warehouse. Integrated healthsystems are shifting its focus away from the acute care setting and movingtowards cross-continuum care management. Improving healthcare quality whilereducing costs requires the elimination of unnecessary variation in the careprocess. This paper describes the lessons learned during the business casedevelopment for the project. Topics include establishing the need for a datawarehouse, understanding data warehousing in healthcare, justifying the cost ofa data warehouse, building the team, and setting achievable goals. With continuous advancesin technology, increasing number of clinicians are using electronic medicalrecords to accumulate substantial amounts of data about their patients with theassociated clinical conditions and treatment details. The ‘hidden’relationships and patterns within these information would further our medicalknowledge including its efficiencies and deficiencies. Methodologies that arebeing used in parallel industries with increasing effectivity need to bemodified and applied to discover this knowledge. This paper discusses, at ahigh level, the various methodologies that may be used, along with theelaboration of the various terminologies associated with data warehousing andknowledge discovery in databases (KDD). The healthcareenvironment is generally perceived as being ‘information rich’ yet ‘knowledgepoor’. There is a wealth of data available within the healthcare systems.However, there is a lack of effective analysis tools to discover hiddenrelationships and trends in data. Knowledge discovery and data mining havefound numerous applications in business and scientific domain. Valuableknowledge can be discovered from application of data mining techniques inhealthcare system.