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Senior services in US hospitals and readmission risk in the Medicare population
Alicia I Arbaje1,2,3, Qilu Yu4, Jiangxia Wang5
1Division of Geriatric Medicine and Gerontology, Department of Medicine, Mason F. Lord Building, Center Tower, 7th Floor, 5200 Eastern Avenue, Baltimore, MD 21224, USA.
Background:
There is a little understanding of the association between hospital organizational characteristics and hospital readmissions. We previously developed a Senior Care Services Scale (SCSS) that describes hospital availability of services relevant to the care of older adults.
Objective:
Determine whether hospitals' SCSS scores were associated with risk of readmission among Medicare beneficiaries.
Design:
Retrospective cohort analysis.
Setting And Participants:
Medicare beneficiaries ≥65 years of age (n = 3 553 367), admitted to 5568 US acute-care hospitals in 2006, discharged alive. Medicare data were linked to the American Hospital Association database of hospital characteristics.
Measurements:
All-cause non-elective hospital readmission, or death without readmission, within 30 days of hospital discharge.
Results:
We examined the association between high and low scores of each of two hospital SCSS service groups: inpatient specialty care (IP) and post-acute (PA) community care. There was no association between high IP scores and readmission (RR 1.00, 95% CI 0.98-1.02). Older adults admitted to hospitals with high PA scores had lower risk of experiencing hospital readmission when compared to older adults admitted to hospitals with low PA scores (RR 0.97, 95% CI 0.95-0.98). High PA scores were associated with increased mortality (RR 1.09, 95% CI 1.06-1.13). In sensitivity analyses exploring relationships at 90 days, both the IP and PA subcomponents were associated with older adults' reduced risk of hospital readmission (IP: RR 0.97, 95% CI 0.95-0.99; PA: RR 0.97, 95% CI 0.95-0.99).
Conclusion:
Senior services at the hospital-level represents a modifiable risk factor with important impact. Employing organization-level characteristics in readmission risk prediction tools should be expanded.
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