Health Plans: Achieving Member-Centricity with Clinical Data

In today’s healthcare industry, there is a growing emphasis on patient engagement and experience. With government programs helping to accelerate change and member attrition a continued challenge, health plans are seeking ways to achieve multi-purpose member-centricity. This means implementing programs to improve health outcomes and reduce the cost of care while ensuring member needs and the patient experience are at the center of all decisions and actions.

To be truly member-centric, payers must consider the diverse needs of the populations they manage, including their physical and mental health conditions, cultural backgrounds, socioeconomic status, and more. This means gathering as much information on each member as possible, preparing programs tailored to the needs of their populations, and coordinating care with multi-faceted care teams from primary care to specialty care to community resources.

On the technology front, one major trend is the adoption of integrated data and analytics to better understand and manage populations. Tapping into longitudinal patient data to view a person’s medical history allows care teams to identify areas for improvement, anticipate future needs, and educate people on how to self-manage their health.

Sample applications for the longitudinal record include:

Care Coordination: Care managers use clinical data to assess a patient’s medical history, diagnoses, medications, and treatment plans. This information helps them coordinate care among various healthcare providers, ensuring that the patient receives appropriate and integrated services.

Chronic Disease Management: Clinical data provides insights into a patient’s chronic conditions, their progression, and treatment responses. Care managers use this data to develop personalized care plans, monitor health indicators, and intervene promptly to prevent exacerbations and complications.

Medication Management: Clinical data helps care managers reconcile a patient’s medication list, including prescribed drugs, dosages, and potential interactions. With this information, they can identify medication adherence issues and work with providers to optimize drug regimens.

Preventive Care Planning: Care managers leverage clinical data to identify patients who are due for preventive screenings, vaccinations, and health assessments. By proactively addressing these preventive measures, they aim to reduce the risk of diseases and improve overall health outcomes.

Hospital Readmission Reduction: Clinical data assists care managers in identifying high-risk patients who have a higher likelihood of hospital readmission as well as manage recent hospital discharges to reduce avoidable readmissions. With timely information from clinical sources, care managers can implement targeted interventions.

Clinical data serves as the foundation for informed decision-making and personalized care planning in care management. When health plans make use of longitudinal, timely clinical data—spanning across many sources and care sites—there is enormous potential to drive meaningful change for patients and the industry at large.

Easier Said than Done

Despite the tremendous growth of clinical data sources and increasing accessibility, clinical data is incredibly challenging to use directly extracted from the electronic health record (EHR) or via third party vendors. There is a lack of standardization caused by variation in source documentation and significant silos that still exist across the industry. A complex patient might see +5 providers annually and each provider might be using a different EHR, capturing data differently, and only managing their piece of the overall care journey. This makes building the longitudinal record very challenging.

Quality Longitudinal Records for Payers

Automation, standards adherence, and timeliness are critical capabilities to consider when looking to apply technology to solve these problems. A solution that does not generate actionable information at the time that it is needed does not generate value. A solution that does not adhere to data terminology and exchange standards does not enable true interoperability.

Availity Fusion, our automated Upcycling Data™ engine, generates high-quality longitudinal patient records in seconds per patient. Clinical data from disparate encounters and sources is normalized to national standards and intelligently deduplicated and summarized to produce a longitudinal record. This data can enable specific clinical workflows or broad enterprise analytics via standard APIs. Availity Fusion powers health plans with a strategic asset to support targeted care management, predictive analytics, population health reporting, and more—ultimately enabling better, faster decisions and an improved member experience.

Takeaways

Clinical data has the potential to disrupt the healthcare space and reengineer outdated processes to be more patient-centric. At Availity, we are committed to accelerating payer and provider access to actionable data that can drive better decisions and better outcomes. Availity Fusion’s automated clinical data Upcycling solution creates a powerful data asset for clinical workflows and enterprise analytics. Download our Clinical Data Integration Buyer’s Guide today to learn more.