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Using social risks to predict unplanned hospital readmission and emergency care among hospitalized Veterans.
Cornell, Portia Y; Hua, Cassandra L; Buchalksi, Zachary M; Chmelka, Gina R; Cohen, Alicia J; Daus, Marguerite M; Halladay, Christopher W; Harmon, Alita; Silva, Jennifer W; Rudolph, James L.
Afiliación
  • Cornell PY; Center of Innovation for Long Term Services and Supports, Providence VA Medical Center, Providence, Rhode Island, USA.
  • Hua CL; Centre for the Digital Transformation of Health, University of Melbourne, Melbourne, Victoria, Australia.
  • Buchalksi ZM; Department of Public Health, Zuckerberg College of Health Sciences, University of Massachusetts, Lowell, Massachusetts, USA.
  • Chmelka GR; Center of Innovation for Long Term Services and Supports, Providence VA Medical Center, Providence, Rhode Island, USA.
  • Cohen AJ; National Social Work Program, Care Management and Social Work, Patient Care Services, Department of Veterans Affairs, Washington, DC, USA.
  • Daus MM; Tomah VA Medical Center, Tomah, Wisconsin, USA.
  • Halladay CW; Department of Health Services, Policy and Practice, Brown University, Providence, Rhode Island, USA.
  • Harmon A; Department of Family Medicine, Alpert Medical School of Brown University, Providence, Rhode Island, USA.
  • Silva JW; Rocky Mountain Regional Medical Center, Aurora, Colorado, USA.
  • Rudolph JL; Center of Innovation for Long Term Services and Supports, Providence VA Medical Center, Providence, Rhode Island, USA.
Health Serv Res ; 2024 Jul 07.
Article en En | MEDLINE | ID: mdl-38972911
ABSTRACT

OBJECTIVES:

(1) To estimate the association of social risk factors with unplanned readmission and emergency care after a hospital stay. (2) To create a social risk scoring index. DATA SOURCES AND

SETTING:

We analyzed administrative data from the Department of Veterans Affairs (VA) Corporate Data Warehouse. Settings were VA medical centers that participated in a national social work staffing program. STUDY

DESIGN:

We grouped socially relevant diagnoses, screenings, assessments, and procedure codes into nine social risk domains. We used logistic regression to examine the extent to which domains predicted unplanned hospital readmission and emergency department (ED) use in 30 days after hospital discharge. Covariates were age, sex, and medical readmission risk score. We used model estimates to create a percentile score signaling Veterans' health-related social risk. DATA EXTRACTION We included 156,690 Veterans' admissions to a VA hospital with discharged to home from 1 October, 2016 to 30 September, 2022. PRINCIPAL

FINDINGS:

The 30-day rate of unplanned readmission was 0.074 and of ED use was 0.240. After adjustment, the social risks with greatest probability of readmission were food insecurity (adjusted probability = 0.091 [95% confidence interval 0.082, 0.101]), legal need (0.090 [0.079, 0.102]), and neighborhood deprivation (0.081 [0.081, 0.108]); versus no social risk (0.052). The greatest adjusted probabilities of ED use were among those who had experienced food insecurity (adjusted probability 0.28 [0.26, 0.30]), legal problems (0.28 [0.26, 0.30]), and violence (0.27 [0.25, 0.29]), versus no social risk (0.21). Veterans with social risk scores in the 95th percentile had greater rates of unplanned care than those with 95th percentile Care Assessment Needs score, a clinical prediction tool used in the VA.

CONCLUSIONS:

Veterans with social risks may need specialized interventions and targeted resources after a hospital stay. We propose a scoring method to rate social risk for use in clinical practice and future research.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Health Serv Res Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Health Serv Res Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos