Date of Degree
Summer 2025
Document Type
DNP Scholarly Project
Academic Department
School of Nursing
Degree Type
Doctoral
Degree Name
Doctor of Nursing Practice
First Advisor
Dr. Sandra Cleveland
Second Advisor
Dr. Lydia Forsythe
Third Advisor
Dr. Kelly Manda
Abstract
Problem: In a short-term rehabilitation (STR) setting, misclassification of planned hospital transfers as unplanned readmissions among elderly cardiovascular patients inflated CMS-reported readmission rates, distorted performance metrics, and led to financial penalties under the Hospital Readmissions Reduction Program (HRRP). A gap analysis revealed a 14% misclassification rate, significantly higher than the CMS benchmark of 8.65%, which was attributed to inconsistent documentation and a lack of standardized classification criteria.
Aim of the Project: To reduce transfer misclassification by 20% through the implementation of a standardized electronic health record (EHR) template and targeted staff education, thereby improving CMS compliance and documentation integrity in STR care transitions.
Review of the Evidence: Twelve studies, including one systematic review and two quasi-experimental designs, support the use of structured documentation and coordinated discharge planning to reduce readmission rates. While many lacked direct evaluation of classification accuracy, evidence indicates that embedded EHR templates can reduce documentation errors by up to 20% (Ebbers et al., 2022), reinforcing the viability of low-resource, high-impact interventions in STR settings.
Project Design: A 12-week Plan-Do-Study-Act (PDSA) cycle guided the implementation of a revised EHR template. The OhioHealth Change Management Model informed stakeholder engagement, staff readiness assessment, and communication strategies to support sustainable change.
Intervention: The CLC Admission Coordinator’s Note, with embedded health factor fields, was introduced to support accurate classification. Staff were trained on CMS readmission guidelines and the use of templates. Dashboards tracked documentation completion and classification accuracy in real time.
Significant Findings/Outcomes: Post-intervention, documentation completion reached 100%, misclassification dropped to 0%, and the readmission rate declined from 14% to 11%. Staff reported improved workflow integration with no increased burden. Estimated cost savings ranged from $15,000 to $25,000 in avoided CMS penalties.
Implications for Nursing: This project underscores nursing’s leadership in data-driven quality improvement. Structured documentation fosters accurate reporting, protects reimbursement, and strengthens interdisciplinary care coordination.
Recommended Citation
Hicks, Aeshia, "Optimizing Transfer Classification: Enhancing Accuracy and Reducing Readmission Rate Penalties for Cardiovascular Care in Short-Term Rehab" (2025). Doctor of Nursing Practice (DNP) Scholarly Project. 36.
https://fuse.franklin.edu/dnp-project/36
Rights
Copyright, all rights reserved
Included in
Business Commons, Education Commons, Nursing Commons, Other Medicine and Health Sciences Commons, Rehabilitation and Therapy Commons
