Assessing health disparities in children using a modified housing-related socioeconomic status measure: a cross-sectional study

Ryu, Euijung; Wi, Chung Il; Crow, Sheri; Armasu, Sebastian M.; Wheeler, Philip H.; Sloan, Jeff A.; Yawn, Barbara P.; Beebe, Timothy J.; Williams, Arthur R.; Juhn, Young J.

doi:10.1136/bmjopen-2016-011564

Cited by 15 publications

(18 citation statements)

References 18 publications

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“…Several authors suggest that recording socioeconomic data in healthcare records would provide new opportunities for health research. [13, 16, 73, 99, 102, 104] The linked health and socioeconomic data would evidence the nature and extent of health inequities [35] and also help researchers to study the aetiological mechanisms of social health determinants, [45, 46, 60, 82, 89, 98, 103] and identify the population subgroups in which they are most relevant. [101] The data might improve understanding of how social factors affect disease incidence, [103] individual health outcomes, [100] and outcomes of clinical care.…”

Section: Resultsmentioning

confidence: 99%

A systematic review of reasons for and against asking patients about their socioeconomic contexts

Moscrop

Ziébland

Roberts

et al. 2019

Int J Equity Health

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Background People’s social and economic circumstances are important determinants of their health, health experiences, healthcare access, and healthcare outcomes. However, patients’ socioeconomic circumstances are rarely asked about or documented in healthcare settings. We conducted a systematic review of published reasons for why patients’ socioeconomic contexts (including education, employment, occupation, housing, income, or wealth) should, or should not , be enquired about. Methods Systematic review of literature published up to and including 2016. A structured literature search using databases of medicine and nursing (pubmed, embase, global health), ethics (Ethicsweb), social sciences (Web of Science), and psychology (PsychINFO) was followed by a ‘snowball’ search. Eligible publications contained one or more reasons for: asking patients about socioeconomic circumstances; collecting patients’ socioeconomic information; ‘screening’ patients for adverse socioeconomic circumstances; or linking other sources of individual socioeconomic data to patients’ healthcare records. Two authors conducted the screening: the first screened all references, the second author screened a 20% sample with inter-rater reliability statistically confirmed. ‘Reason data’ was extracted from eligible publications by two authors, then analysed and organised. Results We identified 138 eligible publications. Most offered reasons for why patients’ should be asked about their socioeconomic circumstances. Reasons included potential improvements in: individual healthcare outcomes; healthcare service monitoring and provision; population health research and policies. Many authors also expressed concerns for improving equity in health. Eight publications suggested patients should not be asked about their socioeconomic circumstances, due to: potential harms; professional boundaries; and the information obtained being inaccurate or unnecessary. Conclusions This first summary of literature on the subject found many published reasons for why patients’ social and economic circumstances should be enquired about in healthcare settings. These reasons include potential benefits at the levels of individuals, health service provision, and population, as well as the potential to improve healthcare equity. Cautions and caveats include concerns about the clinician’s role in responding to patients’ social problems; the perceived importance of social health determinants compared with biomedical factors; the use of average population data from geographic areas to infer the socioeconomic experience of individuals. Actual evidence of outcomes is lacking: our review suggests hypotheses that can be tested in future research.

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Section: Resultsmentioning

confidence: 99%

A systematic review of reasons for and against asking patients about their socioeconomic contexts

Moscrop

Ziébland

Roberts

et al. 2019

Int J Equity Health

View full text Add to dashboard Cite

show abstract

“…Although the HOUSES index has been used to evaluate health outcomes in multiple outpatient and inpatient settings in both adults and children, it has never been used in the critical care setting. 4,22,[24][25][26]28,29,31,44,45 Using the HOUSES index, we measured patient's SES in quartiles within our ICU cohort and studied several primary and secondary end points and whether differences in quality of death and dying existed among 4 socioeconomic groups, using previously established measures. 20,46 We were able to abstract education data from the EMR; however, education data are still self-reported data, and we could not verify the date when this variable was last updated, unlike the address which would be updated on each admission to the hospital.…”

Section: Discussionmentioning

confidence: 99%

An Individual Housing-Based Socioeconomic Status Measure Predicts Advance Care Planning and Nursing Home Utilization

Barwise

Juhn

et al. 2018

Am J Hosp Palliat Care

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Background: Socioeconomic status (SES) is an important determinant of disparities in health care and may play a role in end-of-life care and decision-making. The SES is difficult to retrospectively abstract from current electronic medical records and data sets. Objective: Using a validated SES measuring tool derived from home address, the HOUsing-based SocioEconomic Status index, termed HOUSES we wanted to determine whether SES is associated with differences in end-of-life care and decision-making. Design/Setting/Participants: This cross-sectional study utilized a cohort of Olmsted County adult residents admitted to 7 intensive care units (ICUs) at Mayo Rochester between June 1, 2011, and May 31, 2014. Measurements: Multiple variables that reflect decision-making and care at end of life and during critical illness were evaluated, including presence of advance directives and discharge disposition. The SES was measured by individual housing-based SES index (HOUSES index; a composite index derived from real property as a standardized z-score) at the date of admission to the ICU which was then divided into 4 quartiles. The greater HOUSES, the higher SES, outcomes were adjusted for age, 24-hour Acute Physiology and Chronic Health Evaluation III score, sex, race/ethnicity, and insurance. Results: Among the eligible 4134 participants, the addresses of 3393 (82%) were successfully geocoded and formulated into HOUSES. The adjusted odds ratios comparing HOUSES 1 versus 2, 3, and 4 demonstrated lower likelihood of advance directives −0.77(95% CI: 0.63-0.93) and lower likelihood of discharge to home −0.60(95% CI: 1.0.5-0.72). Conclusion: Lower SES, derived from a composite index of housing attributes, was associated with lower rates of advance directives and lower likelihood of discharge to home.

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“…We used stratified sampling (based on area and housing type) 13–15 to select 220 households per site. Fieldworkers used a random walk and a specified skip pattern in a designated area to select households.…”

Section: Methodsmentioning

confidence: 99%

Household coverage, quality and costs of care provided by community health worker teams and the determining factors: findings from a mixed methods study in South Africa

et al. 2020

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ObjectiveCommunity health workers (CHWs) are undertaking more complex tasks as part of the move towards universal health coverage in South Africa. CHW programmes can improve access to care for vulnerable communities, but many such programmes struggle with insufficient supervision. In this paper, we assess coverage (proportion of households visited by a CHW in the past year and month), quality of care and costs of the service provided by CHW teams with differing configurations of supervisors, some based in formal clinics and some in community health posts.ParticipantsCHW, their supervisors, clinic staff, CHW clients.MethodsWe used mixed methods (a random household survey, focus group discussions, interviews and observations of the CHW at work) to examine the performance of six CHW teams in vulnerable communities in Sedibeng, South Africa.ResultsA CHW had visited 17% of households in the last year, and we estimated they were conducting one to two visits per day. At household registration visits, the CHW asked half of the questions required. Respondents remembered 20%–25% of the health messages that CHW delivered from a visit in the last month, and half of the respondents took the action recommended by the CHW. Training, supervision and motivation of the CHW, and collaboration with other clinic staff, were better with a senior nurse supervisor. We estimated that if CHW carried out four visits a day, coverage would increase to 30%–90% of households, suggesting that some teams need more CHW, as well as better supervision.ConclusionHousehold coverage was low, and the service was limited. Support from the local facility was key to providing a quality service, and a senior supervisor facilitated this collaboration. Greater investment in numbers of CHW, supervisors, training and equipment is required for the potential benefits of the programme to be delivered.

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Assessing health disparities in children using a modified housing-related socioeconomic status measure: a cross-sectional study

Cited by 15 publications

References 18 publications

A systematic review of reasons for and against asking patients about their socioeconomic contexts

A systematic review of reasons for and against asking patients about their socioeconomic contexts

An Individual Housing-Based Socioeconomic Status Measure Predicts Advance Care Planning and Nursing Home Utilization

Household coverage, quality and costs of care provided by community health worker teams and the determining factors: findings from a mixed methods study in South Africa

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