Dataset Information

The PhenX Toolkit: Measurement Protocols for Assessment of Social Determinants of Health.

ABSTRACT:

Introduction

Social determinants are structures and conditions in the biological, physical, built, and social environments that affect health, social and physical functioning, health risk, quality of life, and health outcomes. The adoption of recommended, standard measurement protocols for social determinants of health will advance the science of minority health and health disparities research and provide standard social determinants of health protocols for inclusion in all studies with human participants.

Methods

A PhenX (consensus measures for Phenotypes and eXposures) Working Group of social determinants of health experts was convened from October 2018 to May 2020 and followed a well-established consensus process to identify and recommend social determinants of health measurement protocols. The PhenX Toolkit contains data collection protocols suitable for inclusion in a wide range of research studies. The recommended social determinants of health protocols were shared with the broader scientific community to invite review and feedback before being added to the Toolkit.

Results

Nineteen social determinants of health protocols were released in the PhenX Toolkit (https://www.phenxtoolkit.org) in May 2020 to provide measures at the individual and structural levels for built and natural environments, structural racism, economic resources, employment status, occupational health and safety, education, environmental exposures, food environment, health and health care, and sociocultural community context.

Conclusions

Promoting the adoption of well-established social determinants of health protocols can enable consistent data collection and facilitate comparing and combining studies, with the potential to increase their scientific impact.

SUBMITTER: Krzyzanowski MC

PROVIDER: S-EPMC10505248 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

The PhenX Toolkit: Measurement Protocols for Assessment of Social Determinants of Health.

Krzyzanowski Michelle C MC Ives Cataia L CL Jones Nancy L NL Entwisle Barbara B Fernandez Alicia A Cullen Theresa A TA Darity William A WA Fossett Mark M Remington Patrick L PL Taualii Maile M Wilkins Consuelo H CH Pérez-Stable Eliseo J EJ Rajapakse Nishadi N Breen Nancy N Zhang Xinzhi X Maiese Deborah R DR Hendershot Tabitha P TP Mandal Meisha M Hwang Stephen Y SY Huggins Wayne W Gridley Lauren L Riley Amanda A Ramos Erin M EM Hamilton Carol M CM

American journal of preventive medicine 20230317 3

<h4>Introduction</h4>Social determinants are structures and conditions in the biological, physical, built, and social environments that affect health, social and physical functioning, health risk, quality of life, and health outcomes. The adoption of recommended, standard measurement protocols for social determinants of health will advance the science of minority health and health disparities research and provide standard social determinants of health protocols for inclusion in all studies with ...[more]

PMID: 36935055

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Project description:BackgroundResearch clearly demonstrates social determinants of health (SDOH) impact health outcomes. Provider consideration of patient SDOH in prevention and treatment planning is critical for improved health care quality and health equity. Despite awareness of the connections between SDOH and improved population health, research demonstrates few providers document patient SDOH.ObjectiveThis qualitative study aimed to better understand the barriers and facilitators of SDOH assessment, documentation, and referral in different health care settings and roles.MethodsIndividual semistructured interviews were conducted with practicing health care providers in South Carolina between August 25, 2022, and September 2, 2022. Participants were recruited via community partners' web-based newsletters or listservs using a purposive sampling design. An interview guide with 19 questions was used to explore the following research question: How do SDOH impact patient health and what are the facilitators and barriers experienced by multidisciplinary health care providers assessing and documenting patient SDOH?ResultsParticipants (N=5) included a neonatal intensive care unit registered nurse, a nurse practitioner, a certified nurse midwife, a family and preventive medicine physician, and a counselor (licensed clinical social worker) with careers spanning 12 to 32 years. Participant responses are presented according to the following 5 themes: participants' understanding of SDOH for the patient population, assessment and documentation practices, referrals to other providers and community-based resources, barriers and facilitators of SDOH assessment and documentation, and SDOH assessment and documentation training preferences. Overall, participants were aware of the importance of including patient SDOH in assessment and intervention but noted a variety of institutional and interpersonal barriers to assessment and documentation, including time constraints, perceptions of stigma around discussion of SDOH, and limited referral protocols.ConclusionsIncentivizing inclusion of patient SDOH in health care must be facilitated from the top down, so assessment and documentation can be universally implemented in a pragmatic way that works for providers in a variety of roles and settings for the betterment of health care quality, health equity, and improved population health outcomes. Partnering with community organizations can serve to augment health care organizations' resource and referral availability for addressing patients' social needs.

Project description:BackgroundThe Pooled Cohort Equations (PCEs) do not accurately estimate atherosclerotic cardiovascular disease (ASCVD) risk in certain populations. The 2018 AHA/ACC cholesterol guideline identified risk-enhancing factors as a supplement to PCEs-based risk assessment. However, the role of each risk-enhancing factor in ASCVD risk assessment has not been well quantified. Further, social determinants of health (SDOH) are not included in the PCEs nor considered as risk-enhancing factors in the US cholesterol guideline. We sought to evaluate ASCVD risk associated with each risk-enhancing factor and commonly collected SDOH including education, income, and employment status, and to assess if adding risk-enhancing factors and SDOH to the PCEs improve ASCVD risk prediction.MethodsWe included individuals aged 40 to 75 years, without ASCVD or diabetes at baseline, and with low-density lipoprotein cholesterol 70-189 mg/dL from two contemporary prospective cohort studies (MESA and REGARDS) and from Kaiser Permanente Southern California (KPSC). The primary endpoint was incident ASCVD defined as nonfatal myocardial infarction, fatal coronary heart disease, or fatal or nonfatal stroke over a 10-year period (median follow-up 10 years). We used Cox proportional hazards models to estimate associations between risk-enhancing factors and SDOH with ASCVD. We also assessed changes in model performance after adding risk-enhancing factors and SDOH to the PCEs.ResultsWe included 13,863 adults (mean age 60.7 years) from the prospective cohorts and 307,931 adults (mean age 54.8 years) from KPSC. Risk-enhancing factors including hypercholesterolemia, hypertriglyceridemia, metabolic syndrome, and chronic kidney disease were associated with a higher ASCVD risk, independent of 10-year risk estimated by the PCEs. Low education, low income, and unemployment were also associated with higher ASCVD risk. While adding individual risk-enhancing factors or SDOH to the PCEs had limited impact on model performance, adding multiple risk-enhancing factors and SDOH simultaneously led to modest improvements in discrimination (C-index increased by up to 0.07), calibration (integrated Brier score reduced by up to 2.3%), and net reclassification improvement up to 41.4%.ConclusionsThese findings suggest including SDOH and risk-enhancing factors may improve ASCVD risk assessment.

Project description:OBJECTIVE: To summarize knowledge and identify gaps in evidence about the relationship between social determinants of health (SDH) and postsepsis outcomes. DATA SOURCES: We conducted a comprehensive search of PubMed/Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, and the Cochrane Library. STUDY SELECTION: We identified articles that evaluated SDH as risk factors for mortality or readmission after sepsis hospitalization. Two authors independently screened and selected articles for inclusion. DATA EXTRACTION: We dual-extracted study characteristics with specific focus on measurement, reporting, and interpretation of SDH variables. DATA SYNTHESIS: Of 2,077 articles screened, 103 articles assessed risk factors for postsepsis mortality or readmission. Of these, 28 (27%) included at least one SDH variable. Inclusion of SDH in studies assessing postsepsis adverse outcomes increased over time. The most common SDH evaluated was race/ethnicity (n = 21, 75%), followed by payer type (n = 10, 36%), and income/wealth (n = 9, 32%). Of the studies including race/ethnicity, nine (32%) evaluated no other SDH. Only one study including race/ethnicity discussed the use of this variable as a surrogate for social disadvantage, and none specifically discussed structural racism. None of the studies specifically addressed methods to validate the accuracy of SDH or handling of missing data. Eight (29%) studies included a general statement that missing data were infrequent. Several studies reported independent associations between SDH and outcomes after sepsis discharge; however, these findings were mixed across studies. CONCLUSIONS: Our review suggests that SDH data are underutilized and of uncertain quality in studies evaluating postsepsis adverse events. Transparent and explicit ontogenesis and data models for SDH data are urgently needed to support research and clinical applications with specific attention to advancing our understanding of the role racism and racial health inequities in postsepsis outcomes.

Dataset Information

The PhenX Toolkit: Measurement Protocols for Assessment of Social Determinants of Health.

Introduction

Methods

Results

Conclusions

Publications

The PhenX Toolkit: Measurement Protocols for Assessment of Social Determinants of Health.

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