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

Abstract

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.

An Innovative Individual-Level Socioeconomic Measure Predicts Critical Care Outcomes in Older Adults: A Population-Based Study

“…50 The HOUSES index provides a unique opportunity to study the effect of individual-level SES on a variety of health care outcomes but has only been used once previously in the ICU setting. 44 This article is unique as it examines the interaction or effect modification between age and HOUSES index on critical illness outcomes. We used a cutoff age of 50 years and demonstrated that some outcomes showed significant differences associated with the interaction between age and SES status.…”

“…34,[37][38][39][40][41][42][43] The HOUSES index has also been used once previously in an ICU cohort to examine rates of advance care planning, health care utilization, and discharge disposition. 44 To focus on the main outcomes (eg, association of HOUSES with ICU outcomes) and avoid distraction, we did not report association of other SES measures with ICU outcomes, and Juhn et al demonstrated moderate to good correlation of HOUSES with other SES measures (eg, education, income, Hollingshead index, and Nakao-Treas index), which was not surprising given that each SES measure may reflect different aspects of SES. More importantly, HOUSES tended to show stronger association with health outcomes (eg, overweight, low birth weight) and behavioral risk factor (eg, smoking exposure) in a dose-response manner, compared to other SES measures.…”

Mobile home residence as a risk factor for adverse events among children in a mixed rural–urban community: A case for geospatial analysis

“…Since its original validation, it has been widely used for clinical and epidemiological studies concerning a broad range of health outcomes and behaviors as well as health care delivery in children and adults. 6,[29][30][31][32][33][34][35][36][37][38][39][40][41][42][43] Identifying Areas of Observed and Expected Case Density for AEs…”

In a Search for Equity: Do Direct Payments under the Common Agricultural Policy Induce Convergence in the European Union?

“…The marginal results of the EU funding onto the convergence of economically lagging regions was also found by Pellegrini et al, [21], showing the estimated time of about 50-75 years under the current financial support mechanism. Gagliardi and Percoco [22] found spatial effects of EU cohesion policy, documenting the noticeable economic growth in rural regions around big urban agglomerations and no significant effects on purely rural regions, raising the questions about the effectiveness of direct payments under CAP umbrella in corresponding to the goals stated in CAP, especially increasing convergence and sustainability of rural regions, as the abovementioned growth should be associated with relocation of economic activities from urban agglomerations to its outskirts due to lower operating costs there and increasing individual housing trend [23]. The divergence, induced by EU funding, which biggest part is being allocated to CAP, between richer urban agglomerations economies and poorer rural regions was documented also by Wójcik [24].…”