Avoiding the Unintended Consequences of Screening for Social Determinants of Health

Garg, Arvin; Boynton-Jarrett, Renée; Dworkin, Paul H.

doi:10.1001/jama.2016.9282

Cited by 348 publications

(269 citation statements)

References 6 publications

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“…Concerns exist that screening for social issues that cannot be addressed may cause unintended harm in the doc- tor-patient relationship. 35 Thus, evidence is still needed to assess the association of screening for SDH with patient health outcomes and quality of life. Yet, as SDH increasingly move under the umbrella of health and health care, it will be important to ensure screening practices are methodologically sound and evidence-based.…”

Section: Discussionmentioning

confidence: 99%

Screening for Social Determinants of Health in Michigan Health Centers

et al. 2017

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Objective: Through an academic-community partnership with a statewide consortium of health centers (HCs) in Michigan, we characterize the current scope of screening for social determinants of health (SDH).Methods: We requested copies of forms used to screen for SDH at the 39 HC organizations in Michigan. Using content analysis, we examined variation in screening domains and processes. We present descriptive analyses of HC characteristics and patient demographics.Results: We received screening documentation from 23 of the 39 HCs (59%), representing 167 delivery sites. We found broad empiric consensus regarding a core set of 13 SDH screening domains that align with nationally recommended screening guidelines. Two additional domains, Culture and Functional Status, were screened for by <40% of HCs. While patient self-report is the most frequent mode of SDH screening (41%), many HCs use staff members to administer the screening documents.Conclusions: HCs across a large and diverse state are screening for SDH and largely agree on core SDH screening domains. Using existing empiric data from frontline providers can inform potential best practices in SDH screening. (J Am Board Fam Med 2017;30:418 -427.)

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Section: Discussionmentioning

confidence: 99%

Screening for Social Determinants of Health in Michigan Health Centers

et al. 2017

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“…One opportunity is to incorporate standardized information on demographic and social determinants in electronic health records in order to target ways to improve quality 15 However, differences exist between EHR systems in large, well-resourced clinical practices compared with less well-resourced FQHC sites in their ability to support population health management and "meaningful use" to track and address disparities. 18,19 If patient, family, and community focus and shared decision making were implemented equally in these two types of settings, social determinants of health information could both improve public health, 16,17,20 and reduce the disparities that otherwise would arise with the adoption of Big Data technology.…”

Section: Opportunity I: To Incorporate Social Determinants Informatiomentioning

confidence: 99%

Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century

Zhang

Pérez‐Stable²,

Bourne³

et al. 2017

Ethn Dis

167

138

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Addressing minority health and health disparities has been a missing piece of the puzzle in Big Data science. This article focuses on three priority opportunities that Big Data science may offer to the reduction of health and health care disparities. One opportunity is to incorporate standardized information on demographic and social determinants in electronic health records in order to target ways to improve quality of care for the most disadvantaged populations over time. A second opportunity is to enhance public health surveillance by linking geographical variables and social determinants of health for geographically defined populations to clinical data and health outcomes. Third and most importantly, Big Data science may lead to a better understanding of the etiology of health disparities and understanding of minority health in order to guide intervention development. However, the promise of Big Data needs to be considered in light of significant challenges that threaten to widen health disparities. Care must be taken to incorporate diverse populations to realize the potential benefits. Specific recommendations include investing in data collection on small sample populations, building a diverse workforce pipeline for data science, actively seeking to reduce digital divides, developing novel ways to assure digital data privacy for small populations, and promoting widespread data sharing to benefit under-resourced minority-serving institutions and minority researchers. With deliberate efforts, Big Data presents a dramatic opportunity for reducing health disparities but without active engagement, it risks further widening them.Ethn.Dis;2017;27(2):95-106; doi:10.18865/ed.27.2.95.

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“…Similar to the unintended consequences of exploring SDOH described by Garg and his colleagues (Garg, Boynton, & Dworkin, 2016), leaners may feel overwhelmed by social complexity, inability to relate due to personal experience or become disconnected due to feeling that many issues have no clear solution or path toward resolution. Expectations must be established from the outset that these VF cases are not expected to provide the same experience as interacting with a live patient.…”

Section: Challenges Intrinsic To the Approachmentioning

confidence: 92%

”It Feels Like Being a Real Doctor:” The Virtual Family Approach in Medical Education

Robison¹,

Rajasekaran²,

Berman³

et al. 2017

MedEdPublish

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The majority of health outcomes are determined by social determinants of health (SDOH) while medical care is responsible for as little as 20% of health outcomes. This article is an introduction to the Virtual Family (VF) approach to case based instruction; a novel strategy for addressing SDOH in medical school. The VF theoretical framework is presented and practical considerations and challenges for implementation of the VF approach at three different medical schools are offered. VFs are defined as representations of families or social groups that are not real. "Virtual," in this instance, refers to people or things that do not physically exist. The VF approach allows students and educators to adjust the "lens" of a case's focus to view the relevant determinants. The VF approach is presented as an extension of the virtual patient approach. Theoretical support for the VF approach is argued drawing on principles from modeling and simulation, effective story design, establishing a sense of human presence, serious gaming, visual design, identity leveraging, and flow theory. Challenges and benefits of the approach are described. Measures of efficacy designed to match learning goals are proposed. The VF approach is presented as practical, accessible, economical, and potentially powerful.

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Avoiding the Unintended Consequences of Screening for Social Determinants of Health

Cited by 348 publications

References 6 publications

Screening for Social Determinants of Health in Michigan Health Centers

Screening for Social Determinants of Health in Michigan Health Centers

Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century

”It Feels Like Being a Real Doctor:” The Virtual Family Approach in Medical Education

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