Use of data systems to address social determinants of health: a need to do more

The Association Between Social Determinants of Health and Distal Radius Fracture Outcomes

PURPOSE

The purpose of this study was to determine if adverse social determinants of health (SDOH) are associated with differential complication rates following surgical fixation of distal radius fractures and assess which SDOH domain (economic, educational, social, health care, or environmental) is most associated with postoperative complications.

METHODS

Using a national administrative claims database, we conducted a retrospective cohort analysis of patients undergoing open treatment for an isolated distal radius fracture between 2010 and 2020. Patients were stratified based on the presence/absence of at least one SDOH code and propensity score matched to create two cohorts balanced by age, sex (male or female), insurance type, and comorbidities. Social determinants of health examined included economic, educational, social, health care, and environmental factors. Multivariable logistic regression analyses were performed to assess the isolated effect of SDOH on 90-day and 1-year complication rates.

RESULTS

After propensity matching, 57,025 patients in the adverse SDOH cohort and 57,025 patients in the control cohort were included. Patients facing an adverse SDOH were significantly more likely to experience 90-day complications, including emergency department visits (Odds ratio (OR): 3.18 [95% confidence interval (CI): 3.07-3.29]), infection (OR: 2.37 [95% CI: 2.12-2.66]), wound dehiscence (OR: 2.06 [95% CI: 1.72-2.49]), and 1-year complications, including complex regional pain syndrome (OR: 1.35 [95% CI: 1.15-1.58]), malunion/nonunion (OR: 1.18 [95% CI: 1.08-1.29]), and hardware removal (OR: 1.13 [95% CI: 1.07-1.20]). Additionally, patients facing an adverse SDOH had a significantly increased risk of 90-day complications, regardless of fracture severity, and patients with economic and social challenges had the highest odds of both 90-day and 1-year postoperative complications.

CONCLUSIONS

Social determinants of health are associated with increased complications following distal radius fracture fixation, even when controlling for demographic and clinical factors. We recommend routine screening for adverse SDOH and inclusion of SDOH data into health records to not only inform quality improvement initiatives and risk adjustment for outcome-based quality measurements but also to allow providers to begin to discuss and address such barriers during the perioperative period.

TYPE OF STUDY/LEVEL OF EVIDENCE

Prognosis II.

Mini-Review on Capacity-Building for Data-Driven Early Childhood Systems: The Consortium for Pre-primary Data and Measurement in Sub-Saharan Africa

Low- and middle-income countries (LMIC) are increasing investments in early childhood development programs, including early childhood education. As programs reach scale, there is increasing demand for evidence on impacts of investments. Little work to date has examined capacity required to effectively use data at scale in LMIC, including opportunities and barriers to integrating data into ongoing program implementation and tracking child development and quality of services at scale. Below, we outline the rationale and approach of the Consortium for Pre-primary Data and Measurement in Sub-Saharan Africa, focused on building capacity for data-driven decision-making in early childhood systems. Themes from the first phase include the importance of building diverse groups of stakeholders to define priorities for data and measurement, the need for coordinated and strategic investments in data and measurement, and the value of long-term investments in government/civil society/university partnerships to generate locally relevant data on early childhood education.

Development and Validation of a County-Level Social Determinants of Health Risk Assessment Tool for Cardiovascular Disease

PURPOSE

Social determinants of health (SDoH) have been linked to a variety of health conditions, but there are no multivariate measures of these determinants to estimate the risk of morbidity or mortality in a community. We developed a score derived from multivariate measures of SDoH that predicts county-level cardiovascular disease (CVD) mortality.

METHODS

Using county-level data from 3,026 US counties, we developed a score considering variables of neighborhood socioeconomic status, food/lifestyle environment, and health care resource availability and accessibility to predict the 3-year average (2015-2017) age-adjusted county-level mortality rate for all CVD. We used one 50% random sample to develop the score and the other to validate the score. A Poisson regression model was developed to estimate parameters of variables while accounting for intrastate correlation.

RESULTS

The index score was based on 7 SDoH factors: percentage of the population of minority (nonwhite) race, poverty rate, percentage of the population without a high school diploma, grocery store ratio, fast-food restaurant ratio, after-tax soda price, and primary care physician supply. The area under the curve for the development and validation groups was similar, 0.851 (95% CI, 0.829-0.872) and 0.840 (95% CI, 0.817-0.863), respectively, indicating excellent discriminative ability. The index had better predictive performance for CVD burden than other area-level indexes: poverty only (area under the curve= 0.808, P <.001); the Centers for Disease Control and Prevention's Social Vulnerability Index (CDC-SVI) (area under the curve =0.786, P <.001); and the Agency for Healthcare Research and Quality's Socioeconomic Status (AHRQ-SES) index (area under the curve =0.835, P = .03).

CONCLUSIONS

Our validated multivariate SDoH index score accurately classifies counties with high CVD burden and therefore has the potential to improve CVD risk prediction for vulnerable populations and interventions for CVD at the county level.

Public health management: systemic analysis of social determinants of health in Brazilian municipalities

The health sector is considered extremely important by governments and multilateral international organisms, due to its implication to life, as well as material and human struggling involved. This study adopts a systematical approach in order to question if the mortality outcomes in medium Brazilian cities explain or may be explained by factors considered external to the public health service, expressed by health social determinants. Therefore, this study aims to investigate health conditions in public health management in medium Brazilian cities. The scenario adopted contains 192 cities with a population contingent between 100 000 and 500 000 inhabitants, between the years 2007 and 2011. The database produced, containing 30 indicators representing conceptual models referenced, allowed the elaboration of an operational model of health social determinants from a Bayesian network. As result, we elaborated a model of health system formed by six factors, showing associations that allow a better comprehension about relations among health social determinants and health conditions, producing contextualized information, able to subsidize the formulation of strategies by managers of Sistema Único de Saúde.

Applying a health equity tool to assess a public health nursing guideline for practice in sexually transmitted infection assessment in British Columbia

SETTING

There is a multitude of health equity tools but little guidance on how to effectively use these tools in public health nursing practice. In BC, public health nurses who are certified in sexually transmitted infection care utilize guidelines authorized by the nursing regulatory body.

INTERVENTION

As part of the Equity Lens in Public Health (ELPH) research project, an assessment of the nursing guideline, Sexually Transmitted Infection (STI) Assessment Decision Support Tool, was undertaken using the Assessing Equity in Clinical Practice Guidelines health equity assessment tool. The chosen tool is intended for use by health care providers, is broadly applicable to clinical practice guidelines, can be used retrospectively, and falls within the category of equity checklists and audits.

OUTCOMES

Overall, the tool was useful in assessing the inclusion and omission of an equity focus in the guideline. However, there were several challenges: the identification of an appropriate health equity tool; the absence of an evaluation of the chosen tool; the tool's focus on chronic disease versus communicable disease; and the difficulty of obtaining client perspectives.

IMPLICATIONS

For an improved equity lens in the STI Assessment Decision Support Tool, future revisions should be equity focused and include perspectives from affected populations, an emphasis on the determinants of health that perpetuate inequities for populations who experience a disproportionate burden of STI, information on provincially available resources, and service delivery models that improve timely and equitable access to treatment and care.

Challenges faced with the implementation of Web-Based Data Query Systems for population health: development of a questionnaire based on expert consensus

BACKGROUND

State health agencies (SHA) and local health agencies (LHA) face several challenges with the dissemination of local health data using Web-Based Data Query Systems (WDQS). To help guide future research, this study aimed to utilize expert consensus to identify the most relevant items that contribute to these challenges.

METHODS

A total of 17 researchers and public health professionals agreed to participate in a three-round Delphi process. In round 1, four topics were represented on a 42-item questionnaire using a 5-point Likert scale, along with free-text responses. Free-text responses were analyzed leading to a series of items for a second Delphi round. Participants were given an opportunity to revise results in round 3 for items that did not meet consensus in round 1 or round 2. Consensus on expert opinions was defined at interquartile range (IQR) ≤ 1.

RESULTS

The experts reached consensus on a total of 21 (50%) of the 42 items presented in the initial questionnaire. Eleven of the 15 (73%) of the items extracted from the free-text responses met consensus. Items in consensus from this pilot study were used to develop an instrument for a broader survey across Behavioral Risk Factor Surveillance System (BRFSS) coordinators across all 50 US states.

CONCLUSION

Experts confirmed that software development costs, inadequate human resources, data sharing gaps, a lack of political support, and poor data quality contribute significantly to challenges in their data implementation. The findings from this pilot study inform us of items of public health significance that will help guide future research.

Detecting Spatial Patterns of Disease in Large Collections of Electronic Medical Records Using Neighbor-Based Bootstrapping

We introduce a method called neighbor-based bootstrapping (NB2) that can be used to quantify the geospatial variation of a variable. We applied this method to an analysis of the incidence rates of disease from electronic medical record data (International Classification of Diseases, Ninth Revision codes) for ∼100 million individuals in the United States over a period of 8 years. We considered the incidence rate of disease in each county and its geospatially contiguous neighbors and rank ordered diseases in terms of their degree of geospatial variation as quantified by the NB2 method. We show that this method yields results in good agreement with established methods for detecting spatial autocorrelation (Moran's I method and kriging). Moreover, the NB2 method can be tuned to identify both large area and small area geospatial variations. This method also applies more generally in any parameter space that can be partitioned to consist of regions and their neighbors.

Excess Readmission vs Excess Penalties: Maximum Readmission Penalties as a Function of Socioeconomics and Geography

BACKGROUND

The Hospital Readmission Reduction Program (HRRP) penalizes hospitals with "excess" readmissions up to 3% of Medicare reimbursement. Approximately 75% of eligible hospitals received penalties, worth an estimated $428 million, in fiscal year 2015.

OBJECTIVE

To identify demographic and socioeconomic disparities between matched and localized maximum-penalty and no-penalty hospitals.

DESIGN

A case-control study in which cases included were hospitals to receive the maximum 3% penalty under the HRRP during the 2015 fiscal year. Controls were drawn from no-penalty hospitals and matched to cases by hospital characteristics (primary analysis) or geographic proximity (secondary analysis).

SETTING

A selectiion of 3383 US hospitals eligible for HRRP.

PARTICIPANTS

Thirty-nine case and 39 control hospitals from the HRRP cohort.

MEASUREMENTS

Socioeconomic status variables were collected by the American Community Survey. Hospital and health system characteristics were drawn from Centers for Medicare and Medicaid Services, American Hospital Association, and Dartmouth Atlas of Health Care. The statistical analysis was conducted using Student t tests.

RESULTS

Thirty-nine hospitals received a maximum penalty. Relative to controls, maximum-penalty hospitals in counties with lower SES profiles are defined by increased poverty rates (19.1% vs 15.5%, 𝑃 = 0.015) and lower rates of high school graduation (82.2% vs 87.5%, 𝑃 = 0.001). County level age, sex, and ethnicity distributions were similar between cohorts.

CONCLUSIONS

Cases were more likely than controls to be in counties with low socioeconomic status; highlighting potential unintended consequences of national benchmarks for phenomena underpinned by environmental factors; specifically, whether maximum penalties under the HRRP are a consequence of underperforming hospitals or a manifestation of underserved communities.

[Monitoring social determinants of health]

Public health surveillance is the systematic and continuous collection, analysis, dissemination and interpretation of health-related data for planning, implementation and evaluation of public health initiatives. Apart from the health system, social determinants of health include the circumstances in which people are born, grow up, live, work and age, and they go a long way to explaining health inequalities. A surveillance system of the social determinants of health requires a comprehensive and social overview of health. This paper analyses the importance of monitoring social determinants of health and health inequalities, and describes some relevant aspects concerning the implementation of surveillance during the data collection, compilation and analysis phases, as well as dissemination of information and evaluation of the surveillance system. It is important to have indicators from sources designed for this purpose, such as continuous records or periodic surveys, explicitly describing its limitations and strengths. The results should be published periodically in a communicative format that both enhances the public's ability to understand the problems that affect them, whilst at the same time empowering the population, with the ultimate goal of guiding health-related initiatives at different levels of intervention.

From healthcare to health: A proposed pathway to population health

Innovations in payment are encouraging clinical-community partnerships that address health determinants. However, little is known about how healthcare systems transform and partner to improve population health. We synthesized views of population health experts from nine organizations and illustrated the resulting model using examples from four health systems. The transformation requires a foundation of primary care, connectors and integrators that span the boundaries, sharing of goals among participants, aligned funding and incentives, and a supporting infrastructure, all leading to a virtuous cycle of collaboration. Policies are needed that will provide funding and incentives to encourage spread beyond early adopter organizations.

New spatially continuous indices of redlining and racial bias in mortgage lending: links to survival after breast cancer diagnosis and implications for health disparities research

Racial health disparities continue to be a serious problem in the United States and have been linked to contextual factors, including racial segregation. In some cases, including breast cancer survival, racial disparities appear to be worsening. Using the Home Mortgage Disclosure Act (HMDA) database, we extend current spatial analysis methodology to derive new, spatially continuous indices of (1) racial bias in mortgage lending and (2) redlining. We then examine spatial patterns of these indices and the association between these new measures and breast cancer survival among Black/African American women in the Milwaukee, Wisconsin metropolitan area. These new measures can be used to examine relationships between mortgage discrimination and patterns of disease throughout the United States.

Measurement of Health Disparities, Health Inequities, and Social Determinants of Health to Support the Advancement of Health Equity

Reduction of health disparities and advancement of health equity in the United States require high-quality data indicative of where the nation stands vis-à-vis health equity, as well as proper analytic tools to facilitate accurate interpretation of these data. This article opens with an overview of health equity and social determinants of health. It then proposes a set of recommended practices in measurement of health disparities, health inequities, and social determinants of health at the national level to support the advancement of health equity, highlighting that (1) differences in health and its determinants that are associated with social position are important to assess; (2) social and structural determinants of health should be assessed and multiple levels of measurement should be considered; (3) the rationale for methodological choices made and measures chosen should be made explicit; (4) groups to be compared should be simultaneously classified by multiple social statuses; and (5) stakeholders and their communication needs can often be considered in the selection of analytic methods. Although much is understood about the role of social determinants of health in shaping the health of populations, researchers should continue to advance understanding of the pathways through which they operate on particular health outcomes. There is still much to learn and implement about how to measure health disparities, health inequities, and social determinants of health at the national level, and the challenges of health equity persist. We anticipate that the present discussion will contribute to the laying of a foundation for standard practice in the monitoring of national progress toward achievement of health equity.

Impact of socioeconomic status measures on hospital profiling in New York City

BACKGROUND

Current 30-day readmission models used by the Center for Medicare and Medicaid Services for the purpose of hospital-level comparisons lack measures of socioeconomic status (SES). We examined whether the inclusion of an SES measure in 30-day congestive heart failure readmission models changed hospital risk-standardized readmission rates in New York City (NYC) hospitals.

METHODS AND RESULTS

Using a Centers for Medicare & Medicaid Services (CMS)-like model, we estimated 30-day hospital-level risk-standardized readmission rates by adjusting for age, sex, and comorbid conditions. Next, we examined how hospital risk-standardized readmission rates changed relative to the NYC mean with inclusion of the Agency for Healthcare Research and Quality (AHRQ)-validated SES index score. In a secondary analysis, we examined whether inclusion of the AHRQ SES index score in 30-day readmission models disproportionately impacted the risk-standardized readmission rates of minority-serving hospitals. Higher AHRQ SES scores, indicators of higher SES, were associated with lower odds (0.99) of 30-day readmission (P<0.019). The addition of the AHRQ SES index did not change the model's C statistic (0.63). After adjustment for the AHRQ SES index, 1 hospital changed status from worse than the NYC average to no different than the NYC average. After adjustment for the AHRQ SES index, 1 NYC minority-serving hospital was reclassified from worse to no different than average.

CONCLUSIONS

Although patients with higher SES were less likely to be admitted, the impact of SES on readmission was small. In NYC, inclusion of the AHRQ SES score in a CMS-based model did not impact hospital-level profiling based on 30-day readmission.

Linear and non-linear associations of gonorrhea diagnosis rates with social determinants of health

Identifying how social determinants of health (SDH) influence the burden of disease in communities and populations is critically important to determine how to target public health interventions and move toward health equity. A holistic approach to disease prevention involves understanding the combined effects of individual, social, health system, and environmental determinants on geographic area-based disease burden. Using 2006–2008 gonorrhea surveillance data from the National Notifiable Sexually Transmitted Disease Surveillance and SDH variables from the American Community Survey, we calculated the diagnosis rate for each geographic area and analyzed the associations between those rates and the SDH and demographic variables. The estimated product moment correlation (PMC) between gonorrhea rate and SDH variables ranged from 0.11 to 0.83. Proportions of the population that were black, of minority race/ethnicity, and unmarried, were each strongly correlated with gonorrhea diagnosis rates. The population density, female proportion, and proportion below the poverty level were moderately correlated with gonorrhea diagnosis rate. To better understand relationships among SDH, demographic variables, and gonorrhea diagnosis rates, more geographic area-based estimates of additional variables are required. With the availability of more SDH variables and methods that distinguish linear from non-linear associations, geographic area-based analysis of disease incidence and SDH can add value to public health prevention and control programs.

Beyond Sexual Partnerships: The Lack of Condom Use during Vaginal Sex with Steady Partners

PURPOSE

The purpose of this paper is to identify independent correlates of the lack of condom use when engaging in vaginal sex with steady partners among HIV-negative African American adults. The conceptual model includes proximal as well as more distal domains.

METHODS

Cross-sectional data were collected between May 2009 and August 2011. Recruitment involved active and passive recruitment strategies. Computer-assisted, individual interviews were conducted with 1,050 African American adults. Multivariate logistic regression was used to identify independent predictors of a lack of condom use with steady partners in the past 30 days.

RESULTS

In multivariate analysis, being older than 35, being partnered, perceiving having a steady partner as important, and ever having been homeless were associated positively with the odds of a lack of condom use during vaginal sex with steady partners in the past 30 days. On the other hand, reporting more than one steady partner in the past 30 days, having health insurance during the past 12 months, and perceived neighborhood social cohesion were negatively associated.

CONCLUSIONS

These findings highlight the need for HIV risk-reduction prevention and intervention efforts that consider distal as well as proximal domains. Such a perspective allows for a broader sociological inquiry into health disparities that moves beyond epidemiological factors that commonly guide public health research.

[SOCIO STRUCTURAL FACTORS AND HIV/AIDS STIGMA: EXPERIENCES FROM PUERTO RICANS LIVING WITH HIV/AIDS ACCESING HEALTH SERVICES.]

HIV/AIDS stigma continues affecting the provision of health services to people living with HIV/AIDS, as well as their physical and mental well-being. Scientific literature has highlighted the importance of understanding stigma manifestations that surpass one-on-one social interactions. For that reason, social research in Puerto Rico and elsewhere has highlighted the importance of understanding the Socio-Structural Factors (SSF) that foster HIV/AIDS stigma. With the objective of exploring the SSF that influence stigma manifestations related to HIV/AIDS, we conducted 9 focus groups composed by women and men on HIV/AIDS treatment that had experienced social stigma related to the disease. Participants identified SSF that they understood were related to stigma such as a) development of housing projects for people with HIV/AIDS, b) decentralization of health related services, and c) health services administrative protocols that fostered exclusion. Results evidence the importance of addressing SSF when developing stigma related interventions for this population.