Healthcare industry is witnessing a rapid implementation of programs based on the use of information and communication technologies. Adopting the Federal American Recovery and Reinvestment Act in 2009 caused it. This legal act introduced the meaningful use criteria that claim that eligible hospitals and professionals should use and have the knowledge of the electronic health record (EHR) technology (EHR incentives and certification, 2016). These drastic changes in the healthcare system bring up the challenges that healthcare organizations are forced to deal with. Because EHR is based on data, hospitals should use data analytics to launch and exploit them to the maximum extent so that the customers receive the best-quality services.
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Studying the Challenge
This case study will focus on the steps taken by Memorial Hermann Healthcare System serving in Houston, Texas. The need to implement EHR was motivated by the desire to provide the patients with the best-quality help. Starting working with electronic health record system, the organization did not have an opportunity to change the computers that the doctors used before, so it faced the challenge of deterioration of the technologies that failed to analyze such enormous volumes of data that the EHR used (Burns, 2015).
One more challenge faced by the healthcare setting was making data available to the patients wherever they were and thus bring the concept of patient self-care to life (Trevor, 2010). Memorial Hermann senior management realized that if they wanted to use the newest technologies effectively, they had to fall upon data analytics because they have found that it is a perfect tool for avoiding event-related medical costs and transforming unavoidable events into avoidable (Romeril, 2015).
Steps Taken to Overcome the Challenge
One of the first steps that the organization has taken was creating a subsystem of the electronic health record that would gather the information about every customer’s feedback about the services provided in their hospitals. This system counts the possibility of the patient’s readmittance. What is more, Memorial Hermann’s team developed a tool that calculates the probability of sepsis or possible complications after diseases based on the overall trends in the cases of patients who had nearly the same medical cases (Burns, 2015).
With the help of this tool and defining the general trends, healthcare setting managed to decrease the level of readmittance for patient with pneumonia, acute myocardial infarction, and heart failure (Memorial Hermann City Medical Center: excellence in heart attack care reduces readmissions, 2011). Taking these steps not only helped improve the level of the hospitals’ productivity and decrease the expenditures but also gave the customers an opportunity to control their state of health based on the concept of self-care, as they knew whether there were some concerns about their health and when they should consult a doctor or have their medical tests.
The most significant step taken by the company to deal with the challenge of incompatibility of the electronic health record systems used by the twelve hospitals of the organization was purchasing software for all the computers, eClinicalWorks. This step made it easier for the doctors to fill the reports and for the IT team to analyze the data because all the hospitals started using unified forms and identical tools for data storage (Caouette, 2013). Launching this system helped to solve the problem of data mismatch that was caused by the fact that the implementation of the EHR at the initial stages was hasty, so there was no time to pay attention to software deterioration.
Analyzing what Memorial Hermann Healthcare System has already done it is hard to escape the conclusion that all the steps taken by the organization have proved to be effective and have positive outcomes for the company. Because it is a system consisting of twelve hospitals it was difficult to guarantee the high level of productivity of the electronic health record system, so the implementation of the unified EHR software and the use of the analytical data effort was the only way to deal with this challenge.
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Burns, E. (2015). EHR systems holding back healthcare data analytic efforts. Web.
Caouette, H. (2013). Memorial Hermann live with 600 providers on eClinicalWorks: Expanding relationship. Web.
EHR incentives and certification. (2016). Web.
Romeril, P. (2015). How to use data to improve hospital drug distribution. Web.
Trevor, R. (2010). Personal Health Informatics: The Evolving Paradigm of Patient Self Care. Communication of the IIMA, 10(1), 27-32.