Understanding the Value of Community Vital Signs in Primary Care
| Status: | Active, not recruiting |
|---|---|
| Conditions: | Breast Cancer, Prostate Cancer, Colorectal Cancer, Cervical Cancer, Cervical Cancer, Cancer, Cancer, Cancer, Cancer, Peripheral Vascular Disease, Women's Studies |
| Therapuetic Areas: | Cardiology / Vascular Diseases, Oncology, Reproductive |
| Healthy: | No |
| Age Range: | 18 - 99 |
| Updated: | 4/13/2017 |
| Start Date: | October 2015 |
| End Date: | December 2017 |
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.
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.
The investigators will integrate community vital signs into clinical data, identify cold
spots, and determine prospectively how clinicians use these community data at the point of
care and for populations of patients. The investigators hypothesize that (1) the patients in
a primary care practice live in a range of communities with different social determinants of
health, including cold spots that lack health-promoting resources, (2) community vital signs
are associated with patient health outcomes (e.g., being up-to-date with preventive care,
control of chronic conditions, morbidity), and (3) knowing that a patient resides in a cold
spot will help clinicians improve patient care.
Aim 1a: Determine community vital sign cold spots in the catchment area of 12 primary care
practices.
Aim 1b: Determine whether patients residing in cold spots experience worse outcomes, such as
receiving inadequate care, worse chronic disease control, or higher morbidity.
Aim 2: Determine whether knowing a patient's community vital signs and social needs at the
point of care will change clinical management; and explore how practices could use community
vital signs for population care.
Aim 3: Identify other community vital signs that practices would find useful for managing
patients.
spots, and determine prospectively how clinicians use these community data at the point of
care and for populations of patients. The investigators hypothesize that (1) the patients in
a primary care practice live in a range of communities with different social determinants of
health, including cold spots that lack health-promoting resources, (2) community vital signs
are associated with patient health outcomes (e.g., being up-to-date with preventive care,
control of chronic conditions, morbidity), and (3) knowing that a patient resides in a cold
spot will help clinicians improve patient care.
Aim 1a: Determine community vital sign cold spots in the catchment area of 12 primary care
practices.
Aim 1b: Determine whether patients residing in cold spots experience worse outcomes, such as
receiving inadequate care, worse chronic disease control, or higher morbidity.
Aim 2: Determine whether knowing a patient's community vital signs and social needs at the
point of care will change clinical management; and explore how practices could use community
vital signs for population care.
Aim 3: Identify other community vital signs that practices would find useful for managing
patients.
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.
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