In our last blog post, we talked about high-acuity patients, such as those with chronic conditions, who are at high risk for admissions and readmissions. These patients, who drive a disproportionate amount of health care costs, need to be closely monitored post-discharge and targeted for intervention to keep them on the road to recovery. Using data analytics, providers can target the highest-risk patients for in-home care.
The fourth and final step in population health management (PHM) is expanding chronic disease management to the full attributed population.
Physicians are being asked to care for patients proactively. Providers have traditionally treated high-acuity patients one office visit at a time. This model worked okay in a fee-for-service setting, where providers aren’t held financially accountable for adverse events, such as hospitalizations.
But when providers are incentivized to keep patients healthy rather than treat them when they become ill, waiting for chronic patients to present at the clinic or the emergency department is a recipe for failure.
Disease management principles can be applied to patients before they become ill. Chronic disease management can be directed toward chronic patients to identify them, engage them and intervene on their behalf. Such programs have resulted in significant improvement in the cost and quality of care of high-risk, chronically ill populations.
Analytics are particularly important when implementing chronic disease management programs within value-based care settings, helping providers account for and monitor their entire patient population. Running every patient through analytics allows managers to identify their highest-cost patients and processes, find unnecessary care pattern variations and identify gaps in care.
By aggregating claims and clinical data — and then applying analytical tools — patients can be stratified by risk: high, medium or low. This in turn can help providers appropriately direct their interventions and resources.
Providers are increasingly leveraging data and analytics to evolve into data-driven, value-based organizations. By using technology to evaluate the cost and quality of care provided by physicians to optimize their networks, manage care transitions to prevent readmissions, invest in in-home interventions and expand chronic disease management, they are driving the paradigm shift to more holistic — and resourceful — health care.
For an in-depth discussion on the four steps to population health management, download our white paper The Four Steps of Population Health Management.