Skip to main content
Erschienen in: Journal of General Internal Medicine 4/2020

28.01.2020 | Original Research

A Novel Approach to Characterizing Readmission Patterns Following Hospitalization for Ambulatory Care-Sensitive Conditions

verfasst von: Denny Fe G. Agana, PhD, MPH, CPH, Catherine W. Striley, PhD, MSW, ACSW, MPE, Robert L. Cook, MD, MPH, Yenisel Cruz-Almeida, PhD, MSPH, Peter J. Carek, MD, MS, Jason L. Salemi, PhD, MPH

Erschienen in: Journal of General Internal Medicine | Ausgabe 4/2020

Einloggen, um Zugang zu erhalten

Abstract

Background

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.

Objective

To characterize readmission rates, patterns, and predictors among patients initially hospitalized with an ACSC.

Design

Retrospective analysis of the 2010–2014 Nationwide Readmissions Database.

Participants

Non-pregnant patients aged 18–64 years old during initial ACSC hospitalization and who were discharged alive (N = 5,007,820).

Main Measures

Frequency and pattern of 30-day all-cause readmissions, grouped as 0, 1, 2+ non-clustered, and 2+ clustered readmissions.

Key Results

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).

Conclusions

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.
Literatur
11.
Zurück zum Zitat Agency for Healthcare Reasearch and Quality. Hospital Guide to Reducing Medicaid Readmissions. August 2014:82. Agency for Healthcare Reasearch and Quality. Hospital Guide to Reducing Medicaid Readmissions. August 2014:82.
12.
Zurück zum Zitat Betancourt J, Tan-McGrory A, Kenst B. Guide to Preventing Readmissions among Racially and Ethnically Diverse Medicare Beneficiaries. September 2015:30. Betancourt J, Tan-McGrory A, Kenst B. Guide to Preventing Readmissions among Racially and Ethnically Diverse Medicare Beneficiaries. September 2015:30.
13.
Zurück zum Zitat Squires D, Anderson C. U.S. Health Care from a Global Perspective: Spending, Use of Services, Prices, and Health in 13 Countries. Issue Brief (Commonwealth Fund). 2015;15:1–15. Squires D, Anderson C. U.S. Health Care from a Global Perspective: Spending, Use of Services, Prices, and Health in 13 Countries. Issue Brief (Commonwealth Fund). 2015;15:1–15.
18.
Zurück zum Zitat Jiang HJ, Wier LM. All-Cause Hospital Readmissions among Non-Elderly Medicaid Patients, 2007: Statistical Brief #89. In: Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville (MD): Agency for Healthcare Research and Quality (US); 2006. http://www.ncbi.nlm.nih.gov/books/NBK53601/. Accessed April 24, 2017. Jiang HJ, Wier LM. All-Cause Hospital Readmissions among Non-Elderly Medicaid Patients, 2007: Statistical Brief #89. In: Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville (MD): Agency for Healthcare Research and Quality (US); 2006. http://​www.​ncbi.​nlm.​nih.​gov/​books/​NBK53601/​. Accessed April 24, 2017.
19.
Zurück zum Zitat De Giorgi A, Boari B, Tiseo R, et al. Hospital readmissions to internal medicine departments: a higher risk for females? Eur Rev Med Pharmacol Sci. 2016;20(21):4557–4564.PubMed De Giorgi A, Boari B, Tiseo R, et al. Hospital readmissions to internal medicine departments: a higher risk for females? Eur Rev Med Pharmacol Sci. 2016;20(21):4557–4564.PubMed
23.
Zurück zum Zitat Alfandre DJ. “I’m Going Home”: Discharges Against Medical Advice. Mayo Clin Proc. 2009;84(3):255–260.CrossRef Alfandre DJ. “I’m Going Home”: Discharges Against Medical Advice. Mayo Clin Proc. 2009;84(3):255–260.CrossRef
Metadaten
Titel
A Novel Approach to Characterizing Readmission Patterns Following Hospitalization for Ambulatory Care-Sensitive Conditions
verfasst von
Denny Fe G. Agana, PhD, MPH, CPH
Catherine W. Striley, PhD, MSW, ACSW, MPE
Robert L. Cook, MD, MPH
Yenisel Cruz-Almeida, PhD, MSPH
Peter J. Carek, MD, MS
Jason L. Salemi, PhD, MPH
Publikationsdatum
28.01.2020
Verlag
Springer International Publishing
Erschienen in
Journal of General Internal Medicine / Ausgabe 4/2020
Print ISSN: 0884-8734
Elektronische ISSN: 1525-1497
DOI
https://doi.org/10.1007/s11606-020-05643-2

Weitere Artikel der Ausgabe 4/2020

Journal of General Internal Medicine 4/2020 Zur Ausgabe

Leitlinien kompakt für die Innere Medizin

Mit medbee Pocketcards sicher entscheiden.

Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag

Update Innere Medizin

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.