The vulnerable individuals in a health system’s patient population are at risk of becoming some of the organization’s most complex and costly members. Because vulnerability can be determined by long-term health status and social determinants of health (versus acute episodes), managing risk for these patients relies on a whole-person approach to care. Fee-for-service reimbursement hasn’t incentivized this comprehensive approach to care, but, under value-based payment models, health systems are increasingly rewarded for care that keeps patients well.
The first challenge in addressing the needs of vulnerable patients is identifying those patients. Analytics-driven technologies can help health systems understand who is vulnerable in their populations and take actions to control risk for these patients.
Download
As value-based payment models continue to incentivize care for the whole patient (versus acute, or episodic, care), health systems are beginning to more effectively address the most vulnerable patients in their populations.
By identifying the social determinants of health, or variables that contribute to overall health (e.g., financial, legal, environmental, and behavioral factors, as well as lack of transportation, substance abuse, and education and literacy issues), health systems can focus on vulnerable populations’ needs; this focus will be an increasingly critical step in population health management (PHM) and improving outcomes and lowering costs.
In healthcare, we often target care management efforts on the most medically complex patients (those with the most comorbidities). A successful population health vision, however, doesn’t focus solely on complex care management, particularly as payment shifts towards value-based models. The ongoing shift away from fee-for-service reimbursement towards value-based care incentivizes organizations to care for the whole patient and understand all the factors (including social determinants of health) contributing to an individual’s health or wellness. This requires understanding where a patient lands on the continuum of wellness and what contributes to that individual’s health or illness.
Vulnerable patients, due to the determinants that shape their health status, often need ongoing community support. For example, a patient without transportation to a primary care provider (PCP) might miss follow-up and preventive appointments without a care manager to coordinate that access. If the health system identifies this patient as vulnerable, the care manager can connect with community resources (e.g., community health workers and ride services) to arrange assistance for the patient.
The first challenge in prioritizing care for vulnerable patients is understanding who those patients are. Definitions of vulnerable patients differ by use case and may further differ by organization and location (e.g., if a natural disaster impacts a population’s ability to access care, the local health system may consider that population vulnerable).
Populations that might seem clearly vulnerable don’t always meet an organization’s criteria for vulnerability. For example, patients on Medicaid might qualify by some definitions as vulnerable. According to a Kaiser Family Foundation study, however, if an organizations defines vulnerability by access to care, Medicaid patients may use health services too often to qualify as vulnerable.
With little agreement across the healthcare industry about which patients to include as vulnerable, health systems must leverage analytics-driven technology to identify the social determinants that contribute to vulnerability in their populations and the barriers that may impact an individual’s ability to maintain optimal health.
Tools, such as the Health Catalyst® Population Builder, that leverage analytics to understand a population, and interface easily with other data sources, can help health systems identify and define who’s vulnerable in their populations. These technologies allow health systems to create and manage the definitions of the population for intervention.
If a care manager needs to reach out to a specific subpopulation of high-risk patients to alert them to take particular action, she can use the Population Builder to define the target population, integrate that definition into workflow tools to predict risk, and develop patient-centered care plans for the identified population.
For example, a young adult male, age 21, has a history of ED visits for anxiety. He doesn’t have insurance, so doesn’t have a PCP. The young man goes to the ED when he is sick and has had four visits within the last month for anxiety. Using Population Builder, a health system can identify patients who are vulnerable for ED anxiety-related ED use, such as this patient, based on variables including high ED use, age group, lack of a PCP, and prescription for antianxiety medication. By identifying such vulnerable populations, health systems can act, such as recommending behavioral health support, to reduce the risk of ED visits.
Aided by technology and analytics to identify vulnerable patients and associated health determinants, health systems can treat the whole person, not just the diagnosis. A healthcare organization must agree on defining which variables and determinants will identify groups who are the most vulnerable in its specific population. The organizations will include these factors as they develop algorithms utilizing tools, such as the Population Builder, to target the right rising-risk patients for care management and long-term community support. Leveraging technology will help health systems realize their PHM goals and achieve the IHI Triple Aim of improving the patient experience, the health of populations, and reducing per capita costs of care.
Would you like to learn more about this topic? Here are some articles we suggest:
Would you like to use or share these concepts? Download this presentation highlighting the key main points.
Click Here to Download the Slides
https://www.slideshare.net/slideshow/embed_code/key/432mZl4cXGWC0t
