Big Data seems to be all you hear in the healthcare industry lately. Data is being generated from many sources leading us to become overwhelmed with the sheer amount available. With consistent advancements in technology more and more nuggets of data are being produced. New data sources can be exciting to explore and discover and while obtaining more data can be beneficial overall, it is easy to overlook the obvious – consolidating this into valuable insights is the whole point. The data can be an organization’s biggest asset, but only if put to good use.
Combining the elements of patient portals and traditional sources like claims and lab data with data available from wearables and self-reported social data, healthcare organizations have access to a wealth of information. Where should you begin to make an initial impact on the health of your population?
Start with Structured Data:
Traditional data is often the first information analyzed for population health management because it’s readily available and generally exists in a structured format. Further, it often spans the full continuum of care as people generally use one payer for their health needs and all encounters (prescriptions filled, ER visit, etc.) are recorded.
While claims data can be very valuable for accurate, consistent information about your population, according to a Health IT Analytics, it can also have limitations and can’t be relied on alone for population health management. The article illustrates that data can sometimes be outdated (months or years old) and doesn’t necessarily have clinical interaction details. Oftentimes, information can be limited to billable aspects of each encounter.
This structured data often misses the silent population. A person in your population who may be at risk for prediabetes will not be identified by analyzing these traditional data sources. Biometric data could indicate the first signs of prediabetes but is not shown on claims, therefore missing the opportunity to intervene at the earliest stages.
Incorporate Longitudinal Clinical Insight
Longitudinal clinical data is a key piece of the population health puzzle. This information can provide a very insightful overview of populations and disease progression. It could help identify early risk factors for diseases, determine if a certain medication is the right course of action based on disease stage, or even help identify different food or drug allergies. What’s more, this information can help inform better patient engagement strategies with the proper analysis.
Some data can help place a patient into the corresponding Care Pathways stage. Differentiating between Care Pathways stages, like a newly diagnosed or a long term patient, can help provide the clinical support and services in tune with each stage. By providing the correct support and care, better patient engagement will be achieved in turn improving outcomes and decreasing avoidable spend.
Augment Clinical Data with Social Determinants of Health
These data include information about patients outside of the clinical setting that could have an impact on their health: income, language proficiency, unemployment rates, education, violence rates, etc. This information, if accessible and analyzed effectively, can help providers predict patient outcomes.
Data from wearable devices can provide the final link between clinical results and patients’ social settings by providing insight into actual behavior. Popular wearable healthcare devices on the market today are tracking steps, sleep and heart rate; they’re producing a new wave of data that give providers a better understanding of patients’ lifestyles beyond the doctor’s office. While it’s new, fairly unstructured and fairly underutilized currently, we predict this information will become more valuable in coming years. These devices provide a continuous and frequent data stream and an inside look at a daily lifestyle habits for each patient.
It’s easy to be overwhelmed by the amount of data assets your organization possesses, and even more confused about where to start to make it useful. The fact is, with the proliferation of technologies on the market, we can expect more information to be available in the years to come.
When combined in the correct ways, this data can have a powerful impact on a population. Merging clinical data with socioeconomic, demographic and consumer data, could help uncover trends that trigger specific events. These data streams may also determine other clinical reasons and provide insights on how best to apply total population health. Individuals living in an area with poor access to urgent care may result in an increased number of ER visits or if consumer data shows a certain population prefers text messages over phone calls, prescription refill reminders could be via text to increase medication adherence.
Having a program in place that can learn from the data that individuals provide is essential. Looking at different populations in different lenses to design a program that engages and enrolls will improve upon desired outcomes and provide the best tools for their lifestyle.
Partner with an organization that can help turn your data into actionable insight to positively impact the health of your population. Learn how Health Dialog uses powerful analytics and predictive models to improve people’s lives and reduce the cost of healthcare: https://www.healthdialog.com/solutions/analytics-and-care-pathways