Until recently, technology-enabled efforts to improve population health relied heavily on the use of claims data alone. While there is evidence this approach has merit, there is also a new opportunity to take these efforts to the next level. The increased availability of other types of useful data—namely clinical data from electronic medical records and other systems—can help healthcare organizations fine-tune their analytics. As a result, they can better segment populations, improve quality, increase patient engagement – to successfully address population health needs.
Claims and clinical data naturally complement one another. Claims data has unmatched value in a complex and quickly evolving healthcare marketplace because it offers a retrospective look at what actually happened. In addition to revealing health facts about individuals and where to focus population health resources, claims data shows whether prescriptions were filled or if recommended lab tests were completed. Although the popular notion is there is a significant lag, new technologies allow claims data to be collected and assessed in a timely fashion – sometimes in less than 15 days. This generally gives providers sufficient time to react to a patient’s health needs. On its own, however, claims data does not provide the complete picture of a patient’s health when compared with a combination of the two types of data.
Claims data combined with clinical data provides very specific value when comparing recommended care against evidence-based practices. It may determine an individual in a specific stage of heart failure is not on the most appropriate medication. The combination of data may also help identify food, drug or substance allergies. The different types of data may identify a patient with early risk factors before these issues lead to acute events and hospitalizations. Because clinical data is clinician-validated, it requires less time and effort than payer data to confidently assert a member has a specific condition or the provider needs to take a specific action to improve care and population health results.
The process of taking volumes of claims and clinical data and turning them into actionable, meaningful insight is complex. Organizations looking to undertake these efforts, or partner with a technology firm to do so, should consider the following strategies.
Start with a broad set of data
The amount of data available in the healthcare industry today is large and growing exponentially. It also crosses many different care settings and comes in a wide variety of formats. As a result, data collection efforts should include more than just medical and pharmacy claims and clinical data from EMRs. The efforts should include information from personal health records, lab values, Continuity of Care Documents (CCD), consumer reported data (such as that found in health risk assessments), and even consumer lifestyle and behavior data. The latter is especially useful in determining a patient’s preferences for outreach, support and enabling a successful population health program.
Refine the data into actionable insight that can be used in a variety of ways
Physicians and care team members need rapid access to insight as close as possible to the point of care. This can be accomplished through multiple avenues, including clinical decision support (CDS) across a broad range of conditions. Advanced CDS goes further, to identify potential gaps in care and specific opportunities to improve treatment.
Stratification should also be performed against data. This can identify where each patient is along the full spectrum of health. Empowered with this data, providers can offer each patient appropriate care for his or her unique needs and risk factors. Data can also be used in the care setting to track quality metrics and help physicians better understand their performance.
Use this insight to drive greater coordination of care
Taking this approach one step further, data-driven insight should be used to inform care teams. These teams include care managers and health coaches, and even family care-givers and patients themselves. This ensures everyone is on the same page in supporting the patient. Bi-directional data exchange should be enabled in real-time to allow for the creation of dynamic care plans. With the right technology, these care plans can easily be adjusted as a patient’s needs change.
Align solutions with the unique workflow of providers
It’s critical to consider the unique workflows of all of these individuals—care managers, physicians, nurses and health coaches. CDS should always be readily available, to maximize its usefulness. This includes when a physician is prescribing a new medication or when a care manager is placing a call to an individual recently discharged from the hospital. Making this process as easy as possible will also drive greater population health success. Additional steps such as requiring physicians to log into an EMR and using a separate platform to document patient data can hinder these efforts.
Create targeted patient engagement strategies
Beyond empowering care teams, this data can also be used as a platform to drive better patient engagement, which is key to a successful population health program. For example, consumer data married with claims/clinical data may identify the most appropriate timing and vehicle for outreach. It could determine whether an individual will respond more positively to one-on-one health coaching or to self-service engagement tools. This approach will also help drive operational efficiencies by allowing organizations to allocate resources where they have the most impact.
Create robust reporting to optimize population health programs
At an organizational level, the insight gained from combining clinical and claims data can be used to gauge the effectiveness of quality improvement and population health management efforts. As such, it can reveal where organizations have been successful in driving change. It also shows where there are still opportunities to improve.
Develop a foundation for population health improvement
With all of the different programs, resources and technologies now available to support population health, our industry is truly entering a new era. At the same time, robust healthcare data is becoming more readily available. By leveraging the combined value of clinical and claims data, organizations will have a strong foundation for population health improvement strategies. However, it is only through the transformation of this data into meaningful insight, that quality, cost and patient satisfaction goals can be met, and healthcare organizations can thrive in a quickly evolving ecosystem.
