Evidence map›Paper›PMID 39375318›Full record

Observational studyJournal of general internal medicine2024

Social Determinants of Health and Risk-Adjusted Sepsis Mortality in the Nationwide Veterans Affairs Healthcare System.

Sarah Seelye, Jennifer Cano, Cainnear K Hogan, Hallie C Prescott, Jeremy B Sussman

Abstract readObservational Study
In one paragraph

Observational study in Journal of general internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sarah SeelyeVA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA. sarah.seelye@va.gov.ORCID 0000-0001-5098-7470
Jennifer CanoVA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Cainnear K HoganVA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Hallie C PrescottVA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Jeremy B SussmanVA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.

Funding

HSRD VA I01 HX003304U.S. Department of Veterans Affairs VA IIR 20-313
6 · The paper itself

Abstract

importanceTraditional risk prediction and risk adjustment models have focused on clinical characteristics, but accounting for social determinants of health (SDOH) and complex health conditions could improve understanding of sepsis outcomes and our ability to predict outcomes, treat patients, and assess quality of care.

objectiveTo evaluate the impact of SDOH and health scales in sepsis mortality risk prediction and hospital performance assessment.

designObservational cohort study.

settingOne hundred twenty-nine hospitals in the nationwide Veterans Affairs (VA) Healthcare System between 2017 and 2021.

participantsVeterans admitted through emergency departments with community-acquired sepsis. EXPOSURES: Individual- and community-level SDOH (race, housing instability, marital status, Area Deprivation Index [ADI], and rural residence) and two health scales (the Care Assessment Need [CAN] score and Claims-Based Frailty Index [CFI]). MAIN OUTCOMES AND MEASURES: The primary outcome was 90-day mortality from emergency department arrival; secondary outcomes included 30-day mortality and in-hospital mortality.

resultsAmong 144,889 patients admitted to the hospital with community-acquired sepsis, 139,080 were men (96.0%), median (IQR) age was 71 (64-77) years, and median (IQR) ADI was 60 (38-81). Multivariable regression models had good calibration and discrimination across models that adjusted for different sets of variables (e.g., AUROC, 0.782; Brier score, 1.33; and standardized mortality rate, 1.00). Risk-adjusted hospital performance was similar across all models. Among 129 VA hospitals, three hospitals shifted from the lowest or highest quintile of performance when comparing models that excluded SDOH to models that adjusted for all variables. Models that adjusted for ADI reported odds ratios (CI) of 1.00 (1.00-1.00), indicating that ADI does not significantly predict sepsis mortality in this cohort of patients. CONCLUSION AND RELEVANCE: In patients with community-acquired sepsis, adjusting for community SDOH variables such as ADI did not improve 90-day sepsis mortality predictions in mortality models and did not substantively alter hospital performance within the VA Healthcare System. Understanding the role of SDOH in risk prediction and risk adjustment models is vital because it could prevent hospitals from being negatively evaluated for treating less advantaged patients. However, we found that in VA hospitals, the potential impact of SDOH on 90-day sepsis mortality was minimal.

Indexed as

Hospital MortalitySepsisSocial Determinants of HealthUnited States Department of Veterans AffairsAgedAged, 80 and overCohort StudiesEmergency Service, HospitalFemaleHospitals, VeteransHumansMaleMiddle AgedRisk AssessmentUnited StatesVeterans

Identifiers

PMID39375318
PMCPMC11618254

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.