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By Trevor L. Strome

This ebook explains why purposes working on cloud would possibly not convey an analogous provider reliability, availability, latency and total caliber to finish clients as they do while the functions are working on conventional (non–virtualized, non–cloud) configurations, and explains what might be performed to mitigate that threat.

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Extra resources for Healthcare Analytics for Quality and Performance Improvement

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CHAPTER 2 Fundamentals of Healthcare Analytics If you always do what you always did, you will always get what you always got. —Albert Einstein Effective healthcare analytics requires more than simply extracting information from a database, applying a statistical model, and pushing the results to various end users. The process of transforming data captured in source systems such as electronic medical records (EMRs) into information that is used by the healthcare organization to improve quality and performance requires specific knowledge, appropriate tools, quality improvement (QI) methodologies, and the commitment of management.

If a BI infrastructure is already in place, an analytics strategy can help to identify any gaps that exist in BI that might need to be addressed to fully enable the desired analytics requirements of the HCO. Purpose of an Analytics Strategy 31 strategy also helps to guide day-to-day decisions regarding systems, people, tools, and techniques, with the long-term goal of enabling analytics to provide information and insight regarding the most pressing problems facing the HCO. HCOs should develop a strategy for analytics to ensure that the information resources of the organization are aligned with the activities necessary for achieving the HCO’s quality and performance goals.

Integration. Combining multiple source systems into a connected EDW is the process of integration. Without proper integration, an EDW would be nothing more than a collection of data points without any clear logic linking them. Integration can occur through a process of Extraction/Transformation/Load (ETL), which, in the most typical scenario, copies data from the source system(s), applies logic to transform it to the analysis needs of the organization, and loads it into an EDW. Other forms of integration, including virtualization, which defines a single interface that links to every point of data in the HCO, are increasingly common as volumes of data expand and new approaches to data management are required.

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