A Guide to Successful Outcomes Using Population Health Analytics
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A Guide to Successful Outcomes Using Population Health Analytics

By Healthcare Tech Outlook | Monday, April 29, 2019

Population Health AnalyticsThe healthcare sector is embracing value-based care, and health organizations are beginning to adjust to this change by implementing new ways to monitor and manage population health. EHR systems were designed to provide a centralized location for patient data including lab results, medical images, appointment notes, and many others. But the data resides in EHR with very little analysis. This urges a need for tools that can perform a more in-depth analysis of health information, and population health analytics becomes the best solution. It is capable of analyzing large sets of patient data to detect patients who may be considered high risk for complications. But there is a lot of curiosity and concern about implementing population health management strategy and getting robust population health analytics in place. Firms should consider the following steps to ensure the successful implementation of population health analytics.

Organizations planning to embrace population health analytics must understand the objective that is trying to achieve including identifying high-risk patients, the gap in care, improving health outcomes, and cost savings. Setting a clear direction for the population health analytics initiative is the first thing to have. Patient data is the most critical aspect of the initiative without which population health analytics cannot be done. Health organizations must ensure that all the relevant data is available to the analytics tools so that they can perform analysis. The data must be stored in different systems including EHRs, PACS and laboratory information systems.

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An analytics tool’s primary purpose is to highlight relevant insights from the data that the system can ingest. Ideal analytics tools should have advanced data processing capabilities, data visualization capabilities, drill down features, data modeling and ability to support multiple data sources.

Healthcare firms are continuously being asked to embrace new technology tools. They must invest in providing end users with the appropriate training and processes to succeed in the operationalization of population health analytics. Being able to execute the implementation successfully can support hospitals on their journey to improve patient outcomes and reduce costs.

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