Evidence map›Paper›PMID 42138148›Full record

ArticleJournal of clinical nursing2026

Nursing-Sensitive Process Indicators Predicting 30-Day Readmission in Chronic Heart Failure.

Mohammad Sahebkar, Mohammad Reza Ghasemi

Abstract read
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Article in Journal of clinical nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Mohammad SahebkarSchool of Nursing, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada.ORCID https://orcid.org/0000-0001-9577-9018
Mohammad Reza GhasemiDepartment of Nursing, Nursing and Midwifery School, Iranian Research Center on Healthy Aging, Sabzevar University of Medical Sciences, Sabzevar, Iran.ORCID https://orcid.org/0000-0002-6061-7067

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AIM(S): To identify nursing-sensitive process indicators documented during hospitalization and at discharge that predict 30-day hospital readmission among adults with chronic heart failure (CHF).

designA retrospective case-control study.

methodsThis study included 640 adults hospitalized with CHF at two cardiac referral centres in Sabzevar, Iran, between February 2020 and April 2024. Cases were patients readmitted within 30 days of discharge (n = 320), and controls were patients without readmission during this period (n = 320). Data were extracted from medical records on nursing-sensitive process indicators, including in-hospital falls, fall-risk identification at admission, structured nursing education at discharge, nursing-led post-discharge follow-up, patient knowledge of prescribed medications, polypharmacy (≥ 4 medications at discharge), and medication dosing frequency. Sociodemographic and clinical characteristics were also collected.

resultsIn-hospital falls, identification of fall risk at admission, poor knowledge of prescribed medications, polypharmacy, and complex medication dosing schedules were associated with higher odds of 30-day readmission. In contrast, receipt of structured nursing education at discharge was associated with a significantly lower likelihood of 30-day readmission.

conclusionNursing-sensitive process indicators are significant and independent predictors of 30-day hospital readmission among adults with CHF. Strengthening fall prevention strategies, improving medication-related education, and enhancing discharge preparation represent actionable nursing interventions to reduce avoidable 30-day readmission. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Targeted nursing interventions focused on fall prevention, medication management, and structured discharge education may improve discharge readiness, enhance continuity of care, and reduce preventable 30-day readmission in patients with CHF. PROBLEM ADDRESSED: Unplanned 30-day readmission following hospitalization for chronic heart failure remains a persistent challenge for healthcare quality and patient safety. MAIN

findingsSeveral nursing-sensitive process indicators, particularly fall-related indicators and discharge education, independently predicted readmission risk. RESEARCH IMPACT: The findings support the integration of targeted nursing-led interventions in cardiac and medical units to reduce readmission risk. REPORTING

methodThis study was reported in accordance with the STROBE guidelines for observational studies. PATIENT OR PUBLIC CONTRIBUTION: No patient or public involvement was included in the design, conduct, or reporting of this study.

Indexed as

Heart FailurePatient ReadmissionAccidental FallsAgedCase-Control StudiesChronic DiseaseFemaleHumansIranMaleMiddle AgedPatient DischargeRetrospective Studiescase–control studyheart failurenurse‐sensitive process indicatorsnursing educationpatient readmission

Identifiers

PMID42138148
PMCPMC13432194

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.