Statistical Data In Healthcare

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INTRODUCTION Healthcare industry has shown tremendous increase in its growth. With increasing growth health care organizations have become overwhelmed with patient data and the health care industry has been unwilling to upgrade to an electronic format. One of the reasons for this, is that the paper system was functioning effectively due to lesser population but nowadays the healthcare sector offers potential mix of opportunities and challenges. Increasing patient data can result in misdiagnosis and incorrect treatment of the patient's condition. Thus a more effective way than the paper variety is required, one that is capable of storing, retrieving and managing patient data also making it more centralized, robust, flexible and reliable for…show more content…
Thus not just proper diagnosis and treatment of patient is considered important but also deriving statistical data using pervasive availability to healthcare data and its statistical analysis. Statistical data can be benefit healthcare providers and patients also helps in identifying effective treatments and best practices for variety of diseases. Another factor is that the huge amount of data is generated by healthcare transactions on daily basis which are too complex and huge for traditional methods to analyze. Data mining can facilitate and accelerate decision-making by discovering patterns and trends in large amounts of data. Financial pressures have increased the need for healthcare organizations to make decisions based on the analysis of clinical and financial data. Information gained from data mining can persuade cost, revenue, and operating competence while maintaining a high level of…show more content…
With this increasing complexity of healthcare, if rate of technology adoption is slower, medical industry will lag behind these others in implementing effective data mining and analytic strategies. Apart from the above mentioned, a few more sub-factors are also worth mentioning: A.Unsupervised knowledge discovery in medical databases With increasing data in medical databases, medical data mining becomes an essential step in knowledge discovery. Some of these analyses use techniques from the machine learning literature, including propositional rules from databases using rough sets, implementation of these rules in an expert system, use of Bayes models to find similar cases, applying a finite- mixture-augmented naïve-Bayes model to classify cases and constructing decision trees and neural networks to classify cases [3]. B. Identifying High Risk

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