Population health management, or PHM, is an important topic in the healthcare industry. By defining different population groups in response to the needs of a given area, care providers can note common problems, identify patients at greatest risk, and implement programs that go beyond reactive medicine. Active strategies to manage issues before they become critical, or to better control them if chronic, is proving to be a smart way to better health.
PHM is also good for care institutions. Research suggests that organizations can recoup investment in four years. The included focus on environmental, social, and cultural factors that affect health can lead to far more efficient overall operations. In other words, PHM can be a key to fiscal health for care providers.
There is one catch. Good PHM requires data analysis that, in turn, needs data to work with. That’s where technology comes in. According to Richard Royer, a former CEO of healthcare consulting firm Primaris who wrote an opinion piece in HealthData Management, the answer for finding the data is electronic healthcare records:
Electronic health records (EHRs) hold much of the data necessary for effective population health management. From EHRs, providers can draw information about the makeup of their overall patient population. They can also stratify risks and organize patients into subpopulations based on their conditions and care needs, which enables healthcare teams to provide groups of patients with targeted support.
When EHR systems are optimized, each patient’s electronic record contains a comprehensive health history that can be used to signal next steps in individual patient care and also population health management.
The data is important, but other technology is necessary as well. Data experts will have to combine all the individual data to determine what population definitions might make sense. After identifying the populations of interest, it will be necessary to find factors that are common to a sufficient percentage of the population and consider how to address them.
Data scientists with the deep statistical experience and knowledge to structure such analyses are, unfortunately, relatively uncommon and generally able to command significant salaries. There’s tremendous competition across many industries to hire such people. This is the second place where technology comes into play.
Increasingly, software tools are offering sophisticated capabilities in data analysis and advanced areas like predictive analytics. Although software doesn’t eliminate the need for human thought and experience, it can supplement in-house expertise and allow a provider to improve the health of its patients while establishing a stronger financial future for itself.
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