Why data and technology solutions are essential to the success of value-based care payment models

Over the past few years, every risk-taking supplier has understood the value of accurate, reliable data to drive action and efficiency.

Unfortunately, many healthcare organizations struggle to collect and integrate diverse and vital information due to care delivery silos and a lack of data sharing between them.

However, there is an opportunity for healthcare organizations to make better use of their data through digital technology solutions, reducing friction on their path to value.

Here are two key strategies healthcare organizations can use to free up their data and deliver better value-based care:

1. Better understanding of patients at risk: A clear understanding of patients at risk for poor outcomes can go a long way toward improving efficiency in value-based care.

Traditionally, patients covered by value-based care contracts have been segmented by age, disease, or zip code to understand their vulnerability to disease progression and illness. But there is more information that healthcare organizations can gather to more deeply address patients’ unique vulnerabilities, such as whether they have any behavioral health issues or social risk factors.

More sophisticated risk stratification information can be achieved through improved data integration between health plans, providers, and community benefit organizations. Integrating medical and behavioral data into a holistic care plan provides a unique opportunity to triangulate interventions and services that will provide the greatest impact.

For example, because we know that stress and anxiety can affect hormone balance and blood sugar regulation, diabetes management should include considerations for stress reduction and anxiety management. However, it is not uncommon for these insights to be stored in separate data warehouses, thereby limiting the comprehensiveness of the care planning process.

2. Use longitudinal insights to support whole person care: When providers intervene based on the data presented, knowing whether that intervention made a difference is critical. Technology that retrieves and analyzes patient data for changes over a long period of time can help address this challenge.

Digital health technologies, such as remote patient monitoring, can offer detailed patient information to the care team about the effectiveness of interventions. One example is the sharing of home blood glucose monitoring data, which provides real-time views of how well targeted interventions such as dietary adjustments or stress-reduction therapies are improving health status. Gaining insight into a patient’s lifestyle, daily habits and overall adherence to their care plan longitudinally allows organizations to invest in value-based care interventions that show the greatest return on outcomes and costs.

At the patient level, providers are tasked with preventing adverse outcomes by expanding and optimizing patient touch points. Several technical capabilities can enable this goal. Virtual care can expand the number and effectiveness of patient touch points, providing additional data and information to drive provider action.

Predictive modeling can provide real-time risks of adverse patient outcomes, allowing providers to take preventative action. And a connected digital health ecosystem around the patient can bring wearable technology and continuous data collection to facilitate longitudinal predictive capabilities.

Ultimately, these technical capabilities enable a whole-person model of care across the lifespan, thereby creating long-lasting and trusted patient-provider relationships.

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