Population Health: Five Important Questions to Ask When Integrating Your Data
Guest post by Thomas J. Van Gilder, MD, JD, MPH, chief medical officer and vice president of informatics and analytics, Transcend Insights.
Population health has become a puzzle of processes and technologies to improve health outcomes, enhance the physician-patient experience, and reduce costs. Although the healthcare industry is making great strides toward achieving these goals, a necessary step—the integration of clinical, claims and wellness data—has just begun.
Today, many medical business decisions are based on claims data; yet, robust insights into clinical quality require clinical data. Furthermore, information that is not typically found in healthcare information systems, such as that from wearable devices, and from those who may have little to no contact with the health care system, needs to be incorporated into population health management systems.
Accessibility to clinical, claims and wellness data can provide physicians and care teams with a more complete view of the care delivery system journey and an integrated view of a patient’s data as he or she has engaged the healthcare system. With a broader view of a population’s health and various opportunities to proactively address an individual’s care, a physician or care team can help prevent adverse events or future disease to ultimately improve the health and well-being of the individuals they serve.
As we embark on this journey to complete the population health puzzle, it is important that healthcare systems, physicians and care teams optimize the value of integrating clinical, claims and wellness data by considering the five questions I have outlined below.
- Do you have a reliable, complete and manageable way to access clinical, claims and wellness data?
Clinical data, in its current state, requires an “interoperable platform” to be able to present a single, comprehensive view of a patient’s or population’s health data at the point of care. An interoperable platform connects disparate electronic health record (EHR) systems across a community to collect and provide access to information in a secure and confidential way.
Claims data, traditionally aggregated from health insurers, and now from Accountable Care Organizations, needs to be integrated as well to create a more complete picture of an individual’s or population’s health. Not only does claims data yield rich insights that may not be present in clinical information alone—for example, completed pharmacy transactions—but it can also display health-related activity that occurs outside of any given health system. This could pertain to the use of a non-network urgent care facility or activity that might not be captured in an EHR, such as retail pharmacy vaccinations.
Wellness data generated from things such as immunization campaigns, wellness fairs or wearable health technologies, which seem to be on the rise, can help provide a broader record of an individual’s health so that a physician or care team does not have to rely only on sick encounters. Wellness data can help physicians and care teams identify opportunities in the course of an individual’s health, to intervene earlier and try to prevent some of the complications, or even some of the illnesses, from occurring in the first place.
Therefore, ensuring all of this valuable health information is accounted for to generate a more complete picture of a given patient’s or population’s health, requires accessibility to the data, achieved through community-wide interoperability, and a thoughtful plan for using the data to drive quality improvement, care experience enhancements, and reduced health care costs and utilization—the “Triple Aim.”
- Do you have a way to normalize your data and corroborate your inferences?
Transitioning from data access to achieving the Triple Aim requires that clinical, claims and wellness data make sense together, across various systems and coding schema. In other words, the data must be normalized, duplicate and time-decayed information removed, and data gaps filled in by interpretation or clinical corroboration with other information.
Normalization requires a platform and an approach that first recognizes that clinical, claims and wellness data may conflict or overlap, and provides a systematic way to address these issues. This all requires solid quality assurance activities, software, and staff with sufficient data science skills to be able to bring clinical, claims, and wellness data together and use the integrated data set to provide actionable health intelligence.
Additionally, as standards are becoming more broadly adopted and health systems are becoming more sophisticated in their use of information technology, data normalization will become more seamless. Until then, I believe it will remain a critical issue.