- As healthcare professionals continue to develop meaningful patient engagement strategies, they should consider using risk stratification to determine how and with which patients providers will engage.
Risk stratification is “the process of assigning a health risk status to a patient, and using the patient’s risk status to direct and improve care,” according to the American Academy of Family Physicians (AAFP).
“The goal of [risk stratification] is to help patients achieve the best health and quality of life possible by preventing chronic disease, stabilizing current chronic conditions, and preventing acceleration to higher-risk categories and higher associated costs.”
Delivering high-quality patient care at the lowest possible cost will be crucial as healthcare continues toward more value-based payment models.
Healthcare professionals can determine how they will target patient engagement strategies by understanding patient needs and which will require more provider attention. These patient engagement strategies will ideally lead to healthier patients who cost the industry less money.
Why is risk stratification important?
In patient engagement, risk stratification means determining which patients are most at-risk of developing a costly condition, of costing the organization money, or of seeing a pre-existing healthcare condition worsen. Providers can use risk stratification to better target their patient engagement efforts.
For example, a young and healthy patient will likely not need extensive patient engagement from her provider. This low-risk population will usually benefit from annual check-ups, preventive care, and providers who are openly available on the patient portal and other preferred communication media for potential health emergencies.
However, a diabetic patient will need more sophisticated patient engagement, complete with strong patient-provider communication, regular check-ups, medication management, and care coordination.
Risk stratification in patient engagement essentially means targeting activation efforts appropriately, according to a report on the matter from the Commonwealth Fund.
“The success of population health management depends, in part, on accurately identifying patients at high risk for poor health outcomes as well as preventable and costly health events,” the report authors explained. “Risk-stratification approaches typically focus on clinical markers.”
Even so, healthcare providers should not simply put their patients into risk categories. Stratification must be done in conjunction with identifying care goals for certain patient populations, according to a 2016 report from Chilmark Health.
“Risk stratification will need to provide insights into which patients will respond to which interventions at the right time in order to provide value to healthcare organizations,” the report said. “Risk stratification efforts must be coupled to both the downstream outcomes desired by the organization and the actual interventions the organization offers.”
Using patient data for risk stratification
Healthcare professionals rely on healthcare big data to effectively stratify patients. Using claims data and health history, clinicians can identify high-cost patients or patients at risk of becoming high-cost from developing a chronic illness.
“The cultural transition by clinicians to a more risk-based form of contracting will require more attention and training to optimize use of analytics for care management and risk stratification, which will need to be part of an overall data governance strategy,” the Chilmark report stated.
However, healthcare professionals are also tapping into a new set of big data to help determine patient risk. Notably, the social determinants of health are playing a large role in value-based care.
Most of a patient’s life is lived outside of the realm of clinical care. As such, much of patient health and wellness is determined by a set of outside influences, such as environment, socioeconomic status, race, gender, and other factors. Patients from certain backgrounds may be more at-risk of developing a chronic condition down the road regardless of their current clinical state.
For example, a young patient may have no clinical markers putting him at-risk of a respiratory condition later in life. However, social determinant data might reveal that the patient lives in an urban area with considerable air pollution that can have adverse medical effects.
Currently, clinical and claims data are most prominent in risk stratification, but social determinant and behavioral data are coming to the forefront of population health and patient engagement, Chilmark said.
“Social data is likely to take a back seat to integration of clinical and behavioral data followed by more extensive use of patient-generated data in the next two to three years,” the report pointed out.
Some industry leaders are also looking at the commercially-available Patient Activation Measure (PAM), which scores patients on a 100-point scale for patient ability to self-manage health.
Research from the Commonwealth Fund found that patients in the bottom 25 percent of PAM scores are more likely to develop a costly chronic condition down the road, potentially because they are currently unable to manage their own health.
“A patient’s activation score, or self-management skill level, helps predict future risk of developing a chronic disease and using expensive and avoidable medical services,” the investigators found. “By stratifying populations by patient activation scores, health care delivery systems can identify and help those patients with limited self-management skills in time to prevent poor outcomes and unnecessary utilization.”
Stratifying patients by impactability
As many healthcare professionals look at risk stratification scores for patient engagement, others are looking at a different determinant: impactability scores.
Impactability scores investigate the likelihood of a patient responding positively to a patient engagement intervention. A patient with a high health risk may not have a high impactability score.
Some industry experts say providers should triage their efforts to meet patients who are predisposed to a positive response to interventions.
Community Care of North Carolina (CCNC) has noted that there is in fact little overlap between high-risk patient populations and high-impact patient populations.
“Within the NC Medicaid population, we see only a 53 percent overlap between the top 5000 patients with highest impactability scores and the top 5000 patients with highest risk of inpatient admission,” the CCNC said in a report.
“Highly impactable patients are characterized by both clinical complexity and abnormal utilization patterns,” the organization continued. “Eighty percent have three or more chronic conditions and 70 percent have mental illness.”
Understanding patient impactability in engagement efforts is a fledgling effort, and there is little evidence indicating that the measures should entirely replace risk stratification. However, healthcare providers would benefit from considering both patient measures when determining their patient engagement strategies.
Ensuring the right patient receives the right intervention at the right time is the end goal of patient engagement. Determining how much of a clinical or financial risk a patient will pose on a healthcare organization will be important for determining who receives more extensive patient engagement efforts.
Ultimately, this will lead to healthcare efficiency. Providers will be more efficient about where they spend their labor.
Additionally, it will result in a lean patient engagement effort organization-wide. Providers will also reduce healthcare costs by engaging their high-risk patients, keeping those patients healthier and reducing unnecessary or inappropriate healthcare utilization.