EHR implementation

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EHR implementation would achieve MSN Informatics program outcome #2, which is to evaluate applications that acquire, process and report clinical and financial information to enhance patient care. (ASU, 2018). EHR allows integration of analytical software for data mining which can be used to assess and evaluate quality improvements. Data mining is a set of techniques that helps to study patterns in data that can automatically be found, identified, validated and used to predict trends of certain conditions. (He, Wang & Li, 2009). Patient data continue to increase, and data mining can help optimize the efficiency and quality of many organizations. Data mining can also be used to decrease costs by increasing efficiencies, improve patient quality of life, and most importantly save the lives of more patients. Another use of data mining is to improve customer experience and satisfaction and increase product safety and usability. It has proven effective in areas such as predictive medicine, customer relationship management, detection of fraud and abuse, management of healthcare and measuring the effectiveness of certain treatments. There may be privacy concerns though since massive amounts of patient data is being shared during the mining process and this worries patients because their personal information can fall into the wrong hands. However, due to the beneficial results of data mining, experts believe that this is a risk worth taking. The ultimate goal is healthcare is not so much to protech privacy, but to save lives and shifting from paper to electronic health records has played a major part in achieving this goa

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