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Ryan Bengtson, SVP of Clinical Innovation at Waystar

S E E YO U R R E V C YC L E D I F F E R E N T LY

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In our previous whitepaper, Unlocking the Value of Social Determinant Insight,

we examined the central role that patient-specific social determinants have on health and healthcare costs and how addressing these issues in addition to clinical efforts has profound impact. This second white paper focuses on strategies and tactics to convert social determi-nant insight into action. Success in a value-based healthcare environment requires a holistic view of a patient’s health needs, including their social determinants of health (SDOH). Waystarv calls this holistic view Whole Patient Insight® – an SDOH risk profile for an individual patient along key dimensions such as food insecurity, transportation access, financial resources, health literacy and home stability.

The first and most basic application is to incorporate SDOH insight into exist-ing approaches for stratifying and segmenting a population. A single list of clinically similar patients might be broken down into finer segments – those with minimal social determinant issues, those with significant challenges and those in the middle. This segmentation can then be used to inform which patients would be the best candidates for certain interventions or should be enrolled in specific programs.

The sooner that social determinant risk is known, the better – ideally before the patient shows up in an exam room, costs are incurred and certainly before claim information is flowing from the insurer. Early social determinant insight can prioritize new risk-pool members for proactive health assessment and outreach, realizing that those with higher social challenges will be more complex should they have health issues. Similarly, those with low risks might be better served with less intrusive communications and more self-direct-ed programs. Effectively leveraging SDOH insight generally falls into three categories of use: population segmentation, care workflow and patient engagement.

Population segmentation

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Care workflow

One example of this approach in practice is the work of Geisinger Health within a diabetes pop-ulation. A Geisinger program for patients with diabetes demonstrated that changing the nutri-tion for a subset of ’food insecure’ patients resulted in over a 2 point drop in A1C levels (every one point drop in A1C levels corresponds to a more than 20% decrease in chance of death and seri-ous complications from diabetes). The cost of their program is approximately $2,200 per patient per year. By targeting the “right” patients, Geisinger saw the payer-side benefit reaching $6,000 per patient per month – a greater than 30x financial return.

Geisinger saw the payer-side benefit reaching $6,000 per patient per month

In the second category, care workflow, the addition of these sociodemographic risk measures enables identification of patients that are likely to have excess lengths of stay or are at greater risk for readmissions. In one retrospective analysis of a major health system, patients with high home instability risk were 32% more likely to exceed the geometric mean length of stay. Those patients with high

transportation risk had 41% more excess inpa-tient days than those with low transportation risk The analysis also uncovered that over 50% of actual readmissions were rooted in SDOH challenges, yet one-third of those were not identified by clinically-driven readmission risk tools. Clearly, the SDOH issues foreshadowed cost and value concerns.

Transportation risk impacts excess length of stayPatients identified as having high transportation stress had (on average) 41% more excess days

than those with low transportation stress. This is an average difference of 0.81 days in length of stay.

High Transportation Risk

Low Transportation Risk

# of Excess Days Over GMLOS

0 1 2

1.97

2.78

3

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By proactively identifying inpatients with specific types of SDOH risks, the care team can determine which patients may require specialized focus and support. This insight can, in these examples, improve discharge planning and readmission management through more targeted communication and deployment of follow-up programs. In a survey of clinicians, 88% noted that they have significant numbers of programs to support patients but are pressed to make the connection consistently due to a lack of awareness of the patient situation.

SDoH stratification identifies readmission riskPatients identified as high SDOH risk accounted for 54% of overall readmissions.

Over 30% of these readmissions would have been overlooked by using clinical risk measures alone. A patient’s life at home impacts their ability to recover and maintain health.

High ClinRisk

11% Rate of Readmission

11% of Indexed Admissions 143 Actual Readmits

69% of Indexed Admissions 410 Actual Readmits

5% Rate of Readmission

36% Rate of Readmission

10% of Indexed Admissions 456 Actual Readmits

10% of Indexed Admissions 202 Actual Readmits

18% Rate of ReadmissionLow Clin

Risk

Low SDOH Risk High SDOH Risk

Clin

ical

Ris

k

Social Determinant Risk

Patient engagement

Having identified higher risk patients and tailoring a care plan to meet their individual clinical and social needs, SDOH insight can frame ongoing patient communication and engagement. By understanding an individu-al’s socioeconomic challenges, providers and payers can customize communication plans for maximum effectiveness. This includes the type of communication (e.g., phone call, text, email, etc.), the content of the communica-tion and the timing. In one example, Waystar partnered with CareWire, a provider of mobile communication solutions for patient engage-ment, to leverage social determinant informa-tion for no show management. CareWire uses the SDOH insight from Waystar to tailor pa-tient-specific communications by determin-

ing which program offers they are most likely to respond to and when. This use of Waystar’s Value-Based Risk Analytics solution resulted in a 48% reduction in missed appointments.

Another example is the work being done at Gateway Health among their 600,000 Medi-care and Medicaid managed care members to improve patient engagement. By improving their SDOH data collection capabilities and using that insight to inform communication strategies, Gateway has achieved significant improvement in chronic disease control measures including blood pressure and medication adherence. Gateway is now outperforming the majority of Medicaid plans in the country, hitting the 75th percentile in

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certain Medicaid performance measures – re-sults Gateway attributes to their increased engagement rates.

Changing the impact that a clinical community has on its patients while remaining within the economic model of the evolving value-based healthcare system, requires understanding the whole patient. There are proven strategies to convert this insight to value, with significant and sustainable returns.

As is proving to be the norm for all data applications, practical application of SDOH insight requires it be delivered to care team members within their native systems and in a format and structure that is easy to understand and apply. Integrating the information into standard workflow processes is key to successful adoption and full realization of value.