Social determinants of health
Customizing patient care
ur work in health care is only part of what contributes to overall health. Social Determinants of Health (SDoH)—people’s education, employment, finances, legal status, literacy skills, English fluency, transportation, housing, and, most importantly, their neighborhood—can be just as important. SDoH factors contribute to health disparities in Minnesota; our communities with high SDoH burdens experience higher rates of disease and disabilities. Social inequities also contribute to disparate medical quality scores; those of us who see patients with high SDoH burdens have lower scores.
The challenge is to identify these issues in our patients and determine how to respond as individual physicians and as members of health care institutions to promote health. Struggling with these issues at Minnesota Community Care (previously known as West Side Community Health Services), we have taken some steps to quantify, explore, understand, and respond to SDoH.
About our clinic
As a Federally Qualified Health Center (FQHC) with 17 locations in Ramsey County, Minnesota Community Care (MCC) provides comprehensive primary health care services to a population that disproportionately shoulders the burden of health disparities in our community. In 2017, of 36,338 patients, 98 percent had incomes below 200 percent of the federal poverty level, 71 percent were women and children, 42 percent were medically uninsured, and over 56 percent did not speak English as a first language. In addition, 86 percent were from communities of color, predominantly Hispanic/Latino, Black/African American, and Asian (mostly Hmong). MCC services are available to all; patients with incomes less than 300 percent of poverty level are offered a sliding fee program. No one is turned away for lack of insurance or inability to pay for services. Anecdotally, we know that many of our patients struggle with SDoH issues, but other than race/ethnicity, preferred language, and country of origin (often known collectively as RELO), we had not collected specific data to quantify these issues.
Working with these underserved populations led us to seek additional information and develop a focused response. In 2016, we began to develop a data system that provided direction to more effectively impact the communities served and to identify strategies in specific clinical indicators and health systems that could overcome the barriers that facilitated inequitable health care. Through the Disparities Leadership Program at Harvard University, we decided to expand our identification and understanding of SDoH that may be affecting our quality metrics and contributing to our health disparities and health inequities. We adopted the Kotter Model for Leading Change as a blueprint for change and to translate understanding of disparities into realistic solutions. Dr. John Kotter observed organizations execute their strategies for over 40 years, extracted the success factors, and developed them into a methodology. (See www.tinyurl.com/mp-kotter.)
The Kotter Model shows eight steps toward leading change:
This model challenged us throughout the improvement project, from assessing varying accomplishments—or lack of progress—and as we completed the project. While we initially assessed that the system resided at “generate short-term wins,” the team later determined that, in some aspects, the first step of “creating a sense of urgency” had not yet been created. The Kotter Model was instrumental in guiding our progress toward a deeper level of cultural assessment and uncovering system barriers that critically impacted the communities we served.
We are looking for new, innovative ways to partner with other organizational and societal advocacy groups.
Preparing for PRAPARE
With the system now ready for change, the first goal we set included developing a sophisticated data infrastructure to identify social determinant disparities with the hope that we could target our services to identified special populations. Prior to this goal, we had used a data structure that produced system-level data to support reportable measures, such as diabetes, asthma, and cancer screenings. This system did not include the infrastructure to include disparity reporting, including race, ethnicity, language, and country of origin (RELO), and SDoH data with insecurities such as food, housing, transportation, legal services, safety of household, and neighborhood.
In an alignment of timing, the National Association of Community Health Centers (NACHC) began dissemination of the PRAPARE (Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences) tool. The tool consists of a set of national core measures as well as a set of measures for community priorities. It was informed by research, the experience of existing social risk assessments, and stakeholder engagement. Core measures include personal information about education, employment, income, literacy skills, and safety; insecurities in housing, utilities, food, and transportation; and factors such as social integration and stress. (See www.tinyurl.com/mp-prapare.)
We customized the PRAPARE tool based on patient engagement and stakeholder assessment and created an adjusted tool to collect the measures. Data collection began in June of 2017, focusing on adult populations as a pilot project and then expanding to all family practice sites. Because the PRAPARE tool has not yet been validated in pediatric populations, we continue to focus on adults.
The results to date quantify the extent of SDoH for 3,756 adults who have completed the form. Most of the adults who completed the form were middle-aged women with a range of ethnicities/races, education, and insurance. About 10 to 18 percent of respondents reported having insecurities in housing, utilities, food, clothing, childcare, and phone service. About 9 to 18 percent had difficulties accessing needed medical, mental health, and dental care. Many respondents reported low levels of contact with people whom they care about and are close to: 41 percent said they interacted with others just one to three times per week, while 48 percent said their contacts occurred less than weekly. When asked about stress, 55 percent reported they were somewhat stressed, and 22 percent had a lot of stress. To explore how these SDoH factors may affect quality of care, we are examining how these issues are related to our quality metrics, and, therefore, may be affecting our quality measures. [Note: MCC reports to the federal government using the Uniform Data System (UDS), and to Minnesota’s Statewide Quality Reporting and Measurement System (SQRMS) through MN Community Measurement.]
Data on two fronts
For this article, we examine one preventive health service measure (cervical cancer screening) and one chronic disease measure (A1C as a measure of control for diabetes mellitus).
Our overall cervical cancer screening rate is 55.2 percent, which is the percentage of women 23 to 64 years of age who have had pap smear in the previous three years. The highest rates are in Hispanic White women (65 percent), younger women (57 percent <40 years of age), and those who are uninsured on our discount program (54 percent). The lowest rates are in women who report a lot of stress versus no stress (48 percent versus 59 percent); in women who connect with people they care about less than weekly versus more than three times a week (53 percent versus 61 percent); and in women who report unstable housing versus stable housing (35 percent versus 56 percent). There are no differences in rates for education and literacy.
We Minnesota physicians continue our dedication to improving health of Minnesotans.
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Chris Singer, MAN, RN, CPHQ, is chief operating officer at Minnesota Community Care. She has over 20 years of experience in clinical care leadership focused on improving quality for patients in a variety of health care settings. She has a clinical background as a registered nurse and holds an MA degree in nursing from Bethel University with a focus on health systems leadership as well as certifications in health care quality and leadership.