By Bob Abrahamson, Vice President, Product Management, SCIO Health Analytics
Twitter: @SCIOanalytics
Good chefs often keep adding ingredients into a recipe to go from merely edible to appetizing to scrumptious and beyond. Healthcare organizations can do the same when it comes to getting the most out of data.
Provider organizations, for example, hold massive amounts of patient data within their electronic health records (EHRs). These databases typically include data such as biometric information, which offers the deep, specific insights into a patient’s health status that can affect treatment, especially around chronic conditions. As such, EHRs offers an acceptable – if not tantalizing – data meal.
The problem? EHR data only covers care that has been delivered within your own organization, practice or institution. As a result, when relying on EHR data alone, you may not know when care gaps have been filled by other providers outside of your organization or network.
You can, however, can get more satisfaction out of your data by adding the following ingredients:
Ingredient #1: Claims data. This data, which emanates from payors, offers a view of all care delivered throughout the continuum. As such, you can get a more complete picture of a patient’s care journey. However, with claims data, there is typically a three-month lag between care delivery and claims data becoming visible. So, what appears to be care gaps may have been filled elsewhere during that time. More data might still be needed.
Ingredient #2: Social Determinants. When you add in socioeconomic, psychographic, and other data that shows who patients are, how they live, and what motivates them, you gain a much deeper understanding of patients and how to most appropriately manage and deliver care.
Ingredient #3: Next-generation Analytics. With descriptive, predictive and prescriptive analytics, your organization can aggregate the right data and build a more complete, longitudinal view of each patient’s current health, risk and cost profile. For example, going beyond basic risk stratification with Impactability analytics, helps organizations identify not only who is at highest risk, but who is also most impactable (greatest opportunity to avoid an emergency department or inpatient visit).
Ingredient #4: Futuristic Vision. By embracing predictive analytics, you can determine whether the effect of proposed changes will be positive or negative and determine which of several potential courses the organization should follow.
Ingredient #5: Personas. Viewing patient profiles against pre-built personas that classify patients with similar attributes can help your organization understand the makeup of your population in order to design and execute effective care programs, appropriately communicate and engage with patients. And, if a self-funded healthcare organization, personas support aligning benefit products to support the needs of the population.
Ingredient #6: Visual Tools. Placing these scores into easy-to- interpret dashboards makes for quick analysis and data-driven decision making.
By adding all these ingredients into the mix, your healthcare organizations can get just what they came to the data table for: A new level of clarity around care and outcomes and how to use data to help you understand the clinical and financial impact of dedicating or not dedicating resources to certain areas. And, with this more complex data feast you can truly understand the real risk of your at-risk populations, helping leadership set priorities for improvement and understand whether current investments are delivering the projected results.
This blog was based on “Combining claims, EHR data creates a Rosetta Stone for population health,” an article that previously appeared in Healthcare, Business & Technology.
This article was originally published on SCIO Health Analytics and is republished here with permission.