A Novel Approach to Characterizing Readmission Patterns Following Hospitalization for Ambulatory Care-Sensitive Conditions
Adult
Aged, 80 and over
Adolescent
Middle Aged
Patient Readmission
Patient Discharge
United States
3. Good health
Hospitalization
Young Adult
03 medical and health sciences
0302 clinical medicine
Risk Factors
Ambulatory Care
Humans
Retrospective Studies
DOI:
10.1007/s11606-020-05643-2
Publication Date:
2020-01-28T22:59:35Z
AUTHORS (6)
ABSTRACT
Little is known about the frequency, patterns, and determinants of readmissions among patients initially hospitalized for an ambulatory care-sensitive condition (ACSC). The degree to which hospitalizations in close temporal proximity cluster has also not been studied. Readmission patterns involving clustering likely reflect different underlying determinants than the same number of readmissions more evenly spaced.To characterize readmission rates, patterns, and predictors among patients initially hospitalized with an ACSC.Retrospective analysis of the 2010-2014 Nationwide Readmissions Database.Non-pregnant patients aged 18-64 years old during initial ACSC hospitalization and who were discharged alive (N = 5,007,820).Frequency and pattern of 30-day all-cause readmissions, grouped as 0, 1, 2+ non-clustered, and 2+ clustered readmissions.Approximately 14% of patients had 1 readmission, 2.4% had 2+ non-clustered readmissions, and 3.3% patients had 2+ clustered readmissions during the 270-day follow-up. A higher Elixhauser Comorbidity Index was associated with increased risk for all readmission groups, namely with adjusted odds ratios (AORs) ranging from 1.12 to 3.34. Compared to patients aged 80 years and older, those in younger age groups had increased risk of 2+ non-clustered and 2+ clustered readmissions (AOR range 1.27-2.49). Patients with chronic versus acute ACSCs had an increased odds ratio of all readmission groups compared to those with 0 readmissions (AOR range 1.37-2.69).Among patients with 2+ 30-day readmissions, factors were differentially distributed between clustered and non-clustered readmissions. Identifying factors that could predict future readmission patterns can inform primary care in the prevention of readmissions following ACSC-related hospitalizations.
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