Imagine your doctor's computer system could see not just your blood pressure numbers, but also whether you're having trouble affording food, finding stable housing, or getting to appointments. A new study tested whether giving doctors this kind of 'social risk' information could help them manage chronic conditions better. In a large network of primary care clinics, six were given special tools in their electronic health records. These tools alerted doctors when a patient was overdue for a screening about life challenges like food or housing insecurity. For patients with uncontrolled high blood pressure or diabetes—or who frequently missed appointments—the tools offered additional support. Over 12 months, blood pressure control improved in all clinics, but it improved significantly more in the clinics that had the social risk alerts. Control of blood sugar for diabetes, however, didn't show a difference. The clinics with the special tools were also much more likely to screen for and document these social risks. While different clinics used the tools in different ways, the overall finding is clear: when doctors have a better picture of the life challenges their patients face, they might be better equipped to help them manage conditions like high blood pressure.
Could tracking patients' life struggles help doctors control high blood pressure? A new study suggests yes.
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What this means for you:
Helping doctors see patients' life struggles like food insecurity led to better blood pressure control. What this means for you:
Helping doctors see patients' life struggles like food insecurity led to better blood pressure control. View Original Abstract ↓
PURPOSE: Health care systems increasingly incorporate social risk data into electronic health records (EHRs) to address needs like food, housing, and transportation insecurity. This study evaluated whether EHR-integrated social clinical decision support (SCDS) tools improved control of blood pressure (BP) and hemoglobin A (HbA) and increased social risk-informed care and documentation in community-based clinics.
METHODS: We conducted a cluster randomized trial in a large primary care network. This pragmatic trial was designed to assess tool impact in real-world clinic conditions. Six clinics received SCDS tools embedded in the EHR; 44 clinics served as controls. The tools supported clinic-wide workflows and targeted decision support. A screening alert was triggered for adult patients lacking up-to-date social risk screening. Additional components were activated for patients with uncontrolled hypertension or diabetes, or with a diagnosis of either condition combined with a visit no-show rate of at least 50%. Primary outcomes were BP and HbA control. Secondary outcomes included social risk screening and documentation. Generalized linear mixed models accounted for patient clustering. We also examined use patterns of individual tool components.
RESULTS: Blood pressure control improved over 12 months in both arms, with significantly greater improvement in intervention clinics. Control of HbA showed no significant differences. Intervention clinics had significantly greater odds of social risk screening and documentation. Use of individual SCDS tool components varied widely across clinics.
CONCLUSION: Access to EHR-integrated SCDS tools was associated with increased documentation of social risks and greater improvements in BP control. These findings support embedding social risk data into clinical workflows to enhance chronic disease management in primary care.