A Critical Analysis on Efficacy of Clinical Decision Support Systems in Health Care Domain

Abstract:

Clinical Practice guidelines strongly relies on evidence based medical literature. In Health care domain decision support systems are playing a competent role in diagnosis and treatment from multiple diseases. Among different Hospitals all over the world the Information technology domain emphasis key roles in improvement of patient health care to great extent. The Concept of Data Mining (DM) and Decision Support systems (DSS) in medical domain provides an efficient mechanism to extract the multiple records of patient treatment diagnostics from previously stored records in Data base (DB) or Data Ware House (DWH) and compare these guidelines to perform strong analysis that results in efficient decision making. Along the previously mentioned techniques the era of Telemedicine has also being developed that results in generation of multiple techniques in diagnosis of multiple diseases and health improvement using Mobile Health care systems specially worth full for the rural areas where latest medical facilities are unavailable at the point of need. The required information in Database or in Data Ware House might be the historical data of patient or the health based summery of different patients in diverse stages. Now these days the emergence of distributed decision support systems in health care domain covers the health care treatment procedures in more comprehensive manner including surgical procedures and radiological treatment. In this paper we are going to analyze the multiple health care diagnosis procedures and treatment techniques using various decision support systems designed and implemented by various researchers all over the world and compare the effectiveness and efficiency of each decision support system in health care domain. Our research study is also helpful for physicians and health care practioners in analyzing multiple scenarios related to interesting pattern recognitions and intelligent decision making.

• Periodical: Advanced Materials Research (Volumes 383-390)
• Pages: 4043-4050
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.383-390.4043
• Online since: November 2011
• Authors: Mohammad Raza Perwez, Naveed Ahmad, Muhammad Sajid Javaid, Muhammad Ehsan ul Haq
• Keywords: Clinical Guidelines, Data Mining (DM), Data Warehouse (DW), Decision Support System (DSS), OLAP

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