Over the past few years, any risk-bearing provider has understood the value of accurate, trustworthy data to drive action and performance.
Unfortunately, many healthcare organizations struggle to aggregate and coalesce diverse and vital information due to care delivery silos and the lack of data exchange between them.
There is an opportunity, however, for healthcare organizations to make better use of their data through digital technology solutions, reducing friction on their journey to value.
Here are two core strategies healthcare organizations can use to liberate their data and better enable value-based care:
1. Better understand patients at risk: A clear understanding of patients at risk of poor outcomes can go a long way to improve performance in value-based care.
Traditionally, patients covered under value-based care contracts are segmented by age, disease, or ZIP code, to understand their vulnerabilities to disease progression and illness. But there is more information healthcare organizations can gather to more deeply address patients’ unique vulnerabilities, such as if they have any behavioral health conditions or social risk factors.
More sophisticated risk stratification information can be achieved through enhanced integration of data among health plans, providers and community benefit organizations. Integrating medical and behavioral data into one holistic care plan provides a unique opportunity to triangulate interventions and services that will provide the greatest impact.
For example, since we know that stress and anxiety can impact hormonal balance and blood glucose regulation, managing diabetes should then include considerations on stress reduction and anxiety management. However, it’s not uncommon for these insights to be stored in separate data repositories, thus limiting the comprehensiveness of the care planning process.
2. Use longitudinal insights in support of whole person care: When providers intervene based on the data presented, knowing whether that intervention made a difference is crucial. Technology that mines 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 regarding the effectiveness of interventions. One example is home blood glucose monitoring data exchange, which provides real time views into how well targeted interventions like dietary adjustments or stress reduction therapies are improving health status. Gaining views into a patient’s lifestyle, daily habits, and overall adherence to their care plan longitudinally enables organizations to invest in value-based care interventions that show the greatest return on outcomes and cost.
At the patient-level, providers are tasked with preventing adverse outcomes through expanding and optimizing touchpoints with the patient. Several technical capabilities can enable this goal. Virtual care can expand the number and efficiency of patient touchpoints, giving additional data and information to drive provider actions.
Predictive modeling can provide real-time risks of adverse outcomes for patients, enabling providers to take preventive action. And a connected, digital health ecosystem around the patient can bring wearable technology and continuous data-gathering to facilitate longitudinal predictive opportunities.
Ultimately, these technical capabilities enable a whole person model of care across their lifetime, thus creating long lasting and trusted patient-provider relationships.