Population health management refers to the effort to improve patient outcomes for specific groups of people, helping remove healthcare inequities. Those working in population health management assess what may be risky for the health of an individual in a specific population, while also collecting and analyzing data to improve healthcare programs for these demographics. But one necessary component is necessary for this field to get the results it needs. Can you guess it? It’s technology.
Data collection is very important to population health management. To collect data, population health management (PHM) software is used. This software gathers data on social determinants of health (economic and social conditions that influence a person’s health) and compares it to a patient in a population’s data to determine their needs. This data is often collected from a variety of sources, including EHRs, insurance claims, and patient self-reported data. With this data, organizations can identify patterns of those belonging to a specific population such as commonalities in medical history, similar lifestyle choices, and more.
There are many benefits to population health management software. For example, using this software allows healthcare providers to tailor their care to their patients, while also being able to see how the trends of specific groups compare with broader population trends. Additionally, the data collected with population health software can be used to identify high-risk individuals in a population and will help providers properly allocate resources towards the care for these groups. The data provided by population health software also allows healthcare providers to make more informed decisions, helping improve the quality of their services.
Because population health management software relies on the collection and analysis of data, it is intrinsically tied to the field of data science. However, that means it is also susceptible to the vulnerabilities of the field. For example, a common issue in data science is the unequal distribution of data. More data might be collected from specific groups, while other groups, such as racial minorities and those of lower socioeconomic statuses, find themselves underrepresented in the data. The resulting analysis of this data is then skewed. Therefore, it is important for those working in population healthcare management to make sure the data they collect represents everyone in the population. Additionally, there should be an equal distribution of data collection. There should not be more population health management software built toward certain groups over the other.
Overall, population health management software is a technology that can strengthen the results of population health management. By making sure its efforts are focused on achieving positive results for all populations, not just selected ones, this technology can help close the healthcare gap, once and for all.