A Study on Optimizing Dialyzer Reuse Marking and Total Cell Volume Tracking in Hemodialysis Unit
D. Ashika, Vijaya Parameshwari, Swati Harish Chandra Rai, Amitha P. Marla, I. S. MrudulaAbstract
Background:
In sustainable healthcare management, dialyzer reuse is a vital strategy for cost containment. However, safety depends on monitoring total cell volume (TCV); a drop below 80% of baseline indicates inadequate urea clearance. This study addresses “Information Gaps” caused by poor labeling that risk patient safety.
Objectives:
To assess the baseline accuracy and legibility of dialyzer reuse markings and TCV documentation. To analyze the effectiveness and sustainability of a structured quality improvement framework in reducing noncompliance rates in dialyzer reprocessing records.
Methodology:
A prospective study employed the plan-do-check-act (PDCA) cycle over 2 months in a hemodialysis unit; the intervention evaluated a total of 95 reused dialyzers following implementation across Phase 1 and Phase 2. Key interventions included the introduction of standardized identification stickers bearing reuse counts, revised reuse record formats for better clarity, mandatory entry of technician names on all records, and systematic logging of TCV values directly into patient files. Compliance metrics were derived from direct on-site observations, comprehensive record reviews, and analysis of noncompliance patterns across sequential audits to track progressive improvements.
Results:
Baseline data revealed 25% noncompliance in markings and 6.3% missing TCV records and 100% for both technician identification and completeness of reuse records. Postintervention, the unit achieved 100% compliance across all indicators by February. The June audit confirmed 100% sustainability, proving the protocols were successfully integrated into the institutional culture.
Conclusion:
Standardizing the administrative interface through PDCA effectively eliminates documentation errors and ensures the “80% safety rule” is upheld. This low-cost management model provides a scalable blueprint for operational excellence and the significant mitigation of preventable errors in specialized care units.