Clinical Informatics: Big Data Analysis - all clear
Over the last two years, reflects Indupuri, companies in the life-sciences industry have been investing more into digital transformation initiatives, with an emphasis on modernizing technology infrastructure. With all of this incoming data, effective data management becomes increasingly important. These strategies can help reduce overall clinical trial cycle times needed to bring emerging research to fruition. Clinical trials are becoming increasingly complex, and the amount of data collected and used to conduct the trials only continues to increase. In addition to this growing data for new research, there is already a plethora of data from past clinical trials that can be harnessed. Big data, advanced analytics, AI and machine learning can help tap into this data, transforming it into valuable insights—accelerating research, and bringing medicine to patients faster. For example, eClinical Solutions works with big pharma companies around the world, many of whom are leveraging data analytics to accelerate development of medicines. Clinical Informatics: Big Data AnalysisClinical Informatics: Big Data Analysis Video
CPHIMS Exam Prep, Chapter -Clinical informatics (Medical Informatics, Health Informatics)
Source: Getty Images By Jessica Kent April 13, - For organizations seeking to improve their population health management capabilities, big data is a critical Indormatics: of the journey. At Lee Health, leaders recognized the need for a solution that would help them build an infrastructure to unify data from these different sources, resulting in improved care management and population health management applications. We want to have Clinical Informatics: Big Data Analysis ability to narrow networks to high-quality, appropriate costs, and get into unique relationships with payers, which present a pathway to long term quality and success.
We need a horizontal platform that connects all of these different verticals that we have across the healthcare landscape, with the express goal of improved outcomes in the populations that we're managing. This will lead to lower costs of care.
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The platform also enables us to conduct predictive risk stratification of populations, which can help us prevent an event from occurring. Providers are able to have that outreach and extension in the community outside of traditional channels.
They have the ability to touch all of the vertical segments in healthcare and work toward better outcomes, through the platform and the team. Setting expectations is another barrier that the organization has had to overcome. Anybody going on this journey should make sure the expectations are clear.
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Understand your top three or four deliverables in each phase, as well as the underlying measures that you're going to use to gauge your success. It is by far not the only thing. You have to have network infrastructures, and you have to have the right contracts with payers to move and perform in value. There are a number of different levers you need to have, and they're all important.
It's about actually connecting the dots across the continuum to create more value in that volume.]
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