Potential harms associated with routine collection of patient sociodemographic information: A rapid review

Using community-based participatory research methods to build the foundation for an equitable integrated health data system within a Canadian urban context

Health inequalities amplified by the COVID-19 pandemic have disproportionately affected racialized and equity-deserving communities across Canada. In the Municipality of Peel, existing data, while limited, illustrates that individuals from racialized and equity-deserving communities continue to suffer, receive delayed care, and die prematurely. In response to these troubling statistics, grassroots community advocacy has called on health systems leaders in Peel to work with community and non-profit organizations to address the critical data and infrastructure gaps that hinder addressing the social determinants of health in the region. To support these advocacy efforts, we used a community-based participatory research approach to understand how we might build a data collection ecosystem across sectors, alongside community residents and service providers, to accurately capture the data about the social determinants of health. This approach involved developing a community engagement council, defining the problem with the community, mapping what data is actively collected and what is excluded, and understanding experiences of sociodemographic data collection from community members and service providers. Guided by community voices, our study focused on sociodemographic data collection in the primary care context and identified which service providers use and collect these data, how data are used in their work, the facilitators and barriers to data use and collection. Additionally, we gained insight into how sociodemographic data collection could be respectful, safe, and properly governed from the perspectives of community members. From this study, we identify a set of eight recommendations for sociodemographic data collection and highlight limitations. This foundational community-based work will inform future research in establishing data governance in partnership with diverse and equity-deserving communities.

"Addressing the bigger picture": A qualitative study of internal medicine patients' perspectives on social needs data collection and use

BACKGROUND

There is increasing interest in collecting sociodemographic and social needs data in hospital settings to inform patient care and health equity. However, few studies have examined inpatients' views on this data collection and what should be done to address social needs. This study describes internal medicine inpatients' perspectives on the collection and use of sociodemographic and social needs information.

METHODS

A qualitative interpretive description methodology was used. Semi-structured interviews were conducted with 18 patients admitted to a large academic hospital in Toronto, Canada. Participants were recruited using maximum variation sampling for diverse genders, races, and those with and without social needs. Interviews were coded using a predominantly inductive approach and a thematic analysis was conducted.

RESULTS

Patients expressed that sociodemographic and social needs data collection is important to offer actionable solutions to address their needs. Patients described a gap between their ideal care which would attend to social needs, versus the reality that hospital-based teams are faced with competing priorities and pressures that make it unfeasible to provide such care. They also believed that this data collection could facilitate more holistic, integrated care. Patients conveyed a need to have a trusting and transparent relationship with their provider to alleviate concerns surrounding bias, discrimination, and confidentiality. Lastly, they indicated that sociodemographic and social needs data could be useful to inform care, support research to inspire social change, and assist them with navigating community resources or creating in-hospital programs to address unmet social needs.

CONCLUSIONS

While the collection of sociodemographic and social needs information in hospital settings is generally acceptable, there were varied views on whether hospital staff should intervene, as their priority is medical care. The results can inform the implementation of social data collection and interventions in hospital settings.

Collection and Use of Social Determinants of Health Data in Inpatient General Internal Medicine Wards: A Scoping Review

BACKGROUND

There is growing interest in incorporating social determinants of health (SDoH) data collection in inpatient hospital settings to inform patient care. However, there is limited information on this data collection and its use in inpatient general internal medicine (GIM). This scoping review sought to describe the current state of the literature on SDoH data collection and its application to patient care in inpatient GIM settings.

METHODS

English-language searches on MedLine, Embase, Web of Science, CINAHL, Cochrane, and PsycINFO were conducted from 2000 to April 2021. Studies reporting systematic data collection or use of at least three SDoH, sociodemographic, or social needs variables in inpatient hospital GIM settings were included. Four independent reviewers screened abstracts, and two reviewers screened full-text articles.

RESULTS

A total of 8190 articles underwent abstract screening and eight were included. A range of SDoH tools were used, such as THRIVE, PRAPARE, WHO-Quality of Life, Measuring Health Equity, and a biopsychosocial framework. The most common SDoH were food security or malnutrition (n=7), followed by housing, transportation, employment, education, income, functional status and disability, and social support (n=5 each). Four of the eight studies applied the data to inform patient care, and three provided community resource referrals.

DISCUSSION

There is limited evidence to guide the collection and use of SDoH data in inpatient GIM settings. This review highlights the need for integrated care, the role of the electronic health record, and social history taking, all of which may benefit from more robust SDoH data collection. Future research should examine the feasibility and acceptability of SDoH integration in inpatient GIM settings.

Equity-relevant sociodemographic variable collection in emergency medicine: A systematic review, qualitative evidence synthesis, and recommendations for practice

OBJECTIVES

The objective was to conduct a systematic review and qualitative evidence synthesis (QES) to identify best practices, benefits, harms, facilitators, and barriers to the routine collection of sociodemographic variables in emergency departments (EDs).

METHODS

This work is a systematic review and QES. We conducted a comprehensive search of Medline (Ovid), CINAHL (Ebsco), Cochrane Central (OVID), EMBASE (Ovid), and the multidisciplinary Web of Science Core database using peer-reviewed search strategies, complemented by a gray literature search. We included citations containing perspectives on routine sociodemographic variable collection in EDs and recommendations on definitions or processes of collection or benefits, harms, facilitators, or barriers related to the routine collection of sociodemographic variables in EDs. We conducted this systematic review and QES adhering to the Joanna Briggs Institute guidelines. Two reviewers independently selected included studies and extracted data. We conducted a best-fit framework synthesis and paired inductive thematic analysis of the included studies. We generated recommendations based on the QES.

RESULTS

We included 21 unique reports that enrolled 10,454 patients or respondents in our systematic review and QES. Publication dates of included studies ranged from 2011 to 2021. Included citations were published in Australia, Canada, and the United States. We synthesized 11 benefits, 14 potential harms, 15 barriers, and 19 facilitators and identified 14 best practice recommendations from included citations.

CONCLUSIONS

Health systems should routinely collect sociodemographic variables in EDs guided by recommendations that minimize harms and maximize benefits and consider relevant barriers and facilitators. Our recommendations can serve as a guide for the equity-focused reformation of emergency medicine health information systems.

Sensitivity of Pregnancy Field on the COVID-19 Case Report Form Among Pregnancies Completed Through December 31, 2020: Illinois and Tennessee

Purpose

The considerable volume of infections from SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), has made it challenging for health departments to collect complete data for national disease reporting. We sought to examine sensitivity of the COVID-19 case report form (CRF) pregnancy field by comparing CRF data to the gold standard of CRF data linked to birth and fetal death certificates.

Description

CRFs for women aged 15–44 years with laboratory-confirmed SARS-CoV-2 infection were linked to birth and fetal death certificates for pregnancies completed during January 1–December 31, 2020 in Illinois and Tennessee. Among linked records, pregnancy was considered confirmed for women with a SARS-CoV-2 specimen collection date on or prior to the delivery date. Sensitivity of the COVID-19 CRF pregnancy field was calculated by dividing the number of confirmed pregnant women with SARS-CoV-2 infection with pregnancy indicated on the CRF by the number of confirmed pregnant women with SARS-CoV-2 infection.

Assessment

Among 4276 (Illinois) and 2070 (Tennessee) CRFs that linked with a birth or fetal death certificate, CRF pregnancy field sensitivity was 45.3% and 42.1%, respectively. In both states, sensitivity varied significantly by maternal race/ethnicity, insurance, trimester of prenatal care entry, month of specimen collection, and trimester of specimen collection. Sensitivity also varied by maternal education in Illinois but not in Tennessee.

Conclusion

Sensitivity of the COVID-19 CRF pregnancy field varied by state and demographic factors. To more accurately assess outcomes for pregnant women, jurisdictions might consider utilizing additional data sources and linkages to obtain pregnancy status.

Reporting of health equity considerations in cluster and individually randomized trials

Background

The randomized controlled trial (RCT) is considered the gold standard study design to inform decisions about the effectiveness of interventions. However, a common limitation is inadequate reporting of the applicability of the intervention and trial results for people who are “socially disadvantaged” and this can affect policy-makers’ decisions. We previously developed a framework for identifying health-equity-relevant trials, along with a reporting guideline for transparent reporting. In this study, we provide a descriptive assessment of health-equity considerations in 200 randomly sampled equity-relevant trials.

Methods

We developed a search strategy to identify health-equity-relevant trials published between 2013 and 2015. We randomly sorted the 4316 records identified by the search and screened studies until 100 individually randomized (RCTs) and 100 cluster randomized controlled trials (CRTs) were identified. We developed and pilot-tested a data extraction form based on our initial work, to inform the development of our reporting guideline for equity-relevant randomized trials.

Results

In total, 39 trials (20%) were conducted in a low- and middle-income country and 157 trials (79%) in a high-income country focused on socially disadvantaged populations (78% CRTs, 79% RCTs). Seventy-four trials (37%) reported a subgroup analysis across a population characteristic associated with disadvantage (25% CRT, 49% RCTs), with 19% of included studies reporting subgroup analyses across sex, 9% across race/ethnicity/culture, and 4% across socioeconomic status. No subgroup analyses were reported for place of residence, occupation, religion, education, or social capital. One hundred and forty-one trials (71%) discussed the applicability of their results to one or more socially disadvantaged populations (68% of CRT, 73% of RCT).

Discussion

In this set of trials, selected for their relevance to health equity, data that were disaggregated for socially disadvantaged populations were rarely reported. We found that even when the data are available, opportunities to analyze health-equity considerations are frequently missed. The recently published equity extension of the Consolidated Reporting Standards for Randomized Trials (CONSORT-Equity) may help improve delineation of hypotheses related to socially disadvantaged populations, and transparency and completeness of reporting of health-equity considerations in RCTs. This study can serve as a baseline assessment of the reporting of equity considerations.

Potential harms associated with routine collection of patient sociodemographic information: A rapid review

Background

Health systems are recommended to capture routine patient sociodemographic data as a key step in providing equitable person‐centred care. However, collection of this information has the potential to cause harm, especially for vulnerable or potentially disadvantaged patients.

Objective

To identify harms perceived or experienced by patients, their families, or health‐care providers from collection of sociodemographic information during routine health‐care visits and to identify best practices for when, by whom and how to collect this information.

Search Strategy

We searched OVID MEDLINE, PubMed “related articles” via NLM and healthevidence.org to the end of January 2018 and assessed reference lists and related citations of included studies.

Inclusion Criteria

We included studies reporting on harms of collecting patient sociodemographic information in health‐care settings.

Data Extraction and Synthesis

Data on study characteristics and types of harms were extracted and summarized narratively.

Main Results

Eighteen studies were included; 13 provided patient perceptions or experiences with the collection of these data and seven studies reported on provider perceptions. Five reported on patient recommendations for collecting sociodemographic information. Patients and providers reported similar potential harms which were grouped into the following themes: altered behaviour which may affect care‐seeking, data misuse or privacy concerns, discomfort, discrimination, offence or negative reactions, and quality of care. Patients suggested that sociodemographic information be collected face to face by a physician.

Discussion and Conclusions

Overall, patients support the collection of sociodemographic information. However, harms are possible, especially for some population subgroups. Harms may be mitigated by providing a rationale for the collection of this information.