Understanding the Value of Community Vital Signs in Primary Care

Social determinants of health (e.g. the income, education, and environment of patients) may exert greater influence on health outcomes than traditional clinical factors (e.g. lab results, diagnoses, and family history). Calls for integrating primary care and public health are therefore increasing, but merging these domains of care is logistically difficult. Research is lacking on the incremental benefit of adding public health data at the practice level-- in improving either health outcomes or care delivery. This proof of concept pilot will merge data from electronic health records (EHRs) with community vital signs, a set of metrics that describes key community resources that affect health. The investigators will identify resource poor communities, or cold spots, based on four variables (education, poverty, life expectancy, and access to healthy foods) at the census tract level - referred to as a community vital sign. The hypothesis is that patients coming from cold spots are more likely to have worse health outcomes and that clinicians will deliver better care if they know a patient's community context and his/her specific social needs. This study will involve 12 primary care practices in Northern Virginia that care for more than 170,000 patients. Patient addresses will be geocoded for each practice and determine which patients reside in cold spots for each community vital sign. The variation for each community vital sign for each practice's patients will be calculated and a bivariate and regression analyses will be used to determine whether coming from a cold spot is associated with worse clinical quality metrics. 15 clinicians will be alerted when they see a patient from a cold spot, patients will complete a social needs survey, and clinicians will prospectively document through surveys whether such knowledge affects interpersonal interactions (such as time spent with patients and the use of clearer language) or clinical management (such as referrals to care coordination or community resources). By pragmatically integrating community vital signs into care, this innovative proposal will seek to understand which community data clinicians value, how these data might influence care, and how best to incorporate these data into clinical and population care.

Sex

All

Minimum age

18 Years

Maximum age

99 Years

Inclusion Criteria:

* Aims 1a and 1b: Patients seen at one of the 12 study practices
* Aims 2 and 3: Clinicians at one of the 12 study practices

Exclusion Criteria:

* Aims 1a and 1b: Patients outside of the age range
* Aims 2 and 3: Clinicians involved with the design of the research protocol.