When we think of where the healthcare industry is headed, we think of the major push towards interoperability and value-based care. Interoperability in the sense of achieving cross-platform accessibility, and value-based care in terms alternative payment models like capitation which incentivize care-based financial models. Major strides are being made, from new legislation to new standards and payment models that focus on interoperability and value-based care. One of the more exciting avenues is population health management (PHM), a method of analytics which allows providers to provide better care and reduce costs.
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What is Population Health Management?
Population health management is the aggregation of data from multiple sources, such as electronic health records, quality reporting systems, and accountable care organizations, which are analyzed with the goal of reducing cost and providing better care. Health care analysts look at the data and come up with factors that may contribute to the quality of care and cost. Some of these may be:
- Effectiveness in payment models for providers, such as capitation and fee-for-service
- Patient cost across a multitude of departments and fields
- Data from quality reporting systems (PQRS) and incentive programs (Meaningful Use)
- Pattern analysis between different departments on how to provide cost-effective care
- Factors that inhibit or contribute to interoperability
The results of a PHM analysis comes in the form of creating practical solutions. Solutions such as identifying a high-risk population that benefits from increased care, or highlighting expensive treatments which may be crippling a practice’s budget. A PHM analysis is a way of organizing data so that it’s easily actionable for providers.
Overall Goals of Population Health Management
We look at population health management as a step towards providing better care while reducing cost. A successful PHM analysis takes data from financial, clinical, and workplace sources and combines them to give providers a practical solution.
The practical solutions are given by PHM analytics often come in “care gaps”. Gaps in care usually occur when healthcare standards aren’t met. This can come in the form of a data mismatch due to lack of communication, an overcompensation of treatments, and improper use of electronic health records (EHRs), etc. When care gaps are identified through PHM analytics, they can be fixed, saving providers time and money.
How PHM Works with EHRs
While population health management may be a complex method of providing better care, it all comes down to data. Accurate data is the key to a proper population health management, and accurate data comes from sources that can properly manage and quantify information. PrognoCIS EHR is designed to comprehensively record healthcare information, from comprehensive patient records to financial data. PrognoCIS features support for the quality reporting systems (PQRS), and incentive programs (Meaningful Use), which may be key components into a comprehensive PHM analysis.
We project PHM to be an invaluable asset in the future of healthcare. PHM promises to improve interoperability and push healthcare towards a value-based system. By quantifying the data into actionable tasks that improve patient care, PHM bridges the gap between patient interaction and electronic health systems.