The Paradox of Readmission Prevention Interventions: Missing Those Most in Need

Erik H Hoyer; Blair Golden; Geoff Dougherty; Melissa Richardson; Diane Lepley; Curtis Leung; Amy Deutschendorf; Daniel J Brotman; Rosalyn W Stewart

doi:10.1016/j.amjmed.2021.04.006

The Paradox of Readmission Prevention Interventions: Missing Those Most in Need

Am J Med. 2021 Sep;134(9):1142-1147. doi: 10.1016/j.amjmed.2021.04.006. Epub 2021 May 7.

Authors

Erik H Hoyer¹, Blair Golden², Geoff Dougherty³, Melissa Richardson⁴, Diane Lepley⁴, Curtis Leung⁴, Amy Deutschendorf⁴, Daniel J Brotman², Rosalyn W Stewart⁵

Affiliations

¹ Department of Physical Medicine and Rehabilitation, School of Medicine, Johns Hopkins University, Baltimore, MD; Department of Internal Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD.
² Department of Internal Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD.
³ Heath Services Cost Review Commission, Maryland Department of Health, Baltimore; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
⁴ Department of Care Coordination and Clinical Resource Management, The Johns Hopkins Hospital, Baltimore, MD.
⁵ Department of Internal Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD; Department of Care Coordination and Clinical Resource Management, The Johns Hopkins Hospital, Baltimore, MD; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD; Bloomberg School of Public Health, Department of Population, Family and Reproductive Health. Electronic address: rstewart@jhmi.edut.

PMID: 33971167
DOI: 10.1016/j.amjmed.2021.04.006

Abstract

Background: Post-hospitalization transition interventions remain a priority in preventing rehospitalization. However, not all patients referred for readmission prevention interventions receive them. We sought to 1) define patient characteristics associated with non-receipt of readmission prevention interventions (among those eligible for them), and 2) determine whether these same patient characteristics are associated with hospital readmission at the state level.

Methods: We used state-wide data from the Maryland Health Services Cost Review Commission to determine patient-level factors associated with state-wide readmissions. Concurrently, we conducted a retrospective analysis of discharged patients referred to receive 1 of 3 post-discharge interventions between January 2013 and July 2019-a nurse transition guide, post-discharge phone call, or follow-up appointment in our post-discharge clinic-to determine patient-level factors associated with not receiving the intervention. Multivariable generalized estimating equation logistic regression models were used to calculate the odds of not accepting or not receiving the interventions.

Results: Older age, male gender, black race, higher expected readmission rate, and lower socioeconomic status were significantly associated with 30-day readmission in hospitalized Maryland patients. Most of these variables (age, sex, race, payer type [Medicaid or non-Medicaid], and socioeconomic status) were also associated with non-receipt of intervention.

Conclusions: We found that many of the same patient-level characteristics associated with the highest readmission risk are also associated with non-receipt of readmission reduction interventions. This highlights the paradox that patients at high risk of readmission are least likely to accept or receive interventions for preventing readmission. Identifying strategies to engage hard-to-reach high-risk patients continues to be an unmet challenge in readmission prevention.

Keywords: 30-day readmission; Care coordination; Transition of care.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Aftercare* / methods
Aftercare* / organization & administration
Aftercare* / statistics & numerical data
Aged
Continuity of Patient Care
Female
Humans
Male
Maryland / epidemiology
Patient Acceptance of Health Care / statistics & numerical data*
Patient Discharge
Patient Readmission / statistics & numerical data*
Patient Transfer* / methods
Patient Transfer* / statistics & numerical data
Preventive Health Services / methods*
Risk Assessment
Sex Factors
Socioeconomic Factors