Authors :
Dr. C. J. K. Somaratne; Dr. K. Weraduwage; Dr. A. Raqeeb
Volume/Issue :
Volume 11 - 2026, Issue 4 - April
Google Scholar :
https://tinyurl.com/mu4r8f5h
Scribd :
https://tinyurl.com/5n7328rz
DOI :
https://doi.org/10.38124/ijisrt/26apr834
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Phlebotomy services play a critical role in clinical diagnosis and patient management. Inefficient workflows,
prolonged waiting times, and poor prioritization—particularly among fasting and paediatric patients—can compromise
patient safety, satisfaction, and diagnostic accuracy.
To optimize the functioning of the phlebotomy unit by reducing waiting times, prioritizing vulnerable patient groups,
improving patient flow, and enhancing overall service efficiency.
A quality improvement initiative was implemented at District General Hospital Nawalapitiya beginning in 2022 and
continues as an ongoing project. Initial audits identified prolonged waiting times exceeding two hours, congestion during
early morning hours, and inadequate patient prioritization. Interventions included implementation of an appointment-based
system, prioritization of fasting and paediatric patients, staff reallocation, and improvement of waiting area facilities. Reaudit data were compared to baseline findings.
Post-intervention findings demonstrated a significant reduction in waiting times from >2 hours to approximately 20
minutes. Improvements were noted in patient satisfaction, staff workflow efficiency, and reduction in fasting-related
complications.
[need to insert numerical data: patient satisfaction scores, number of patients per hour, incidence of fainting episodes
if possible].
A structured, patient-centred scheduling system significantly improved phlebotomy unit efficiency, enhanced patient
safety, and reduced unnecessary healthcare burden. This model provides a scalable framework for optimizing outpatient
diagnostic services in similar healthcare settings.
Keywords :
Phlebotomy, Quality Improvement, Patient Flow, Waiting Time Reduction, Healthcare Efficiency.
References :
- World Health Organization. Laboratory Quality Management System Handbook. Geneva: WHO; 2011.
- Institute for Healthcare Improvement. Science of Improvement. IHI; 2019.
- NHS England. Improving Patient Flow in Outpatient Services. 2020.
- American Diabetes Association. Standards of Medical Care in Diabetes. Diabetes care. 2022;45(Suppl 1):S1-S264.
- Ministry of Health Sri Lanka. Healthcare Quality and Safety Framework.Colombo; MoH;2020
Phlebotomy services play a critical role in clinical diagnosis and patient management. Inefficient workflows,
prolonged waiting times, and poor prioritization—particularly among fasting and paediatric patients—can compromise
patient safety, satisfaction, and diagnostic accuracy.
To optimize the functioning of the phlebotomy unit by reducing waiting times, prioritizing vulnerable patient groups,
improving patient flow, and enhancing overall service efficiency.
A quality improvement initiative was implemented at District General Hospital Nawalapitiya beginning in 2022 and
continues as an ongoing project. Initial audits identified prolonged waiting times exceeding two hours, congestion during
early morning hours, and inadequate patient prioritization. Interventions included implementation of an appointment-based
system, prioritization of fasting and paediatric patients, staff reallocation, and improvement of waiting area facilities. Reaudit data were compared to baseline findings.
Post-intervention findings demonstrated a significant reduction in waiting times from >2 hours to approximately 20
minutes. Improvements were noted in patient satisfaction, staff workflow efficiency, and reduction in fasting-related
complications.
[need to insert numerical data: patient satisfaction scores, number of patients per hour, incidence of fainting episodes
if possible].
A structured, patient-centred scheduling system significantly improved phlebotomy unit efficiency, enhanced patient
safety, and reduced unnecessary healthcare burden. This model provides a scalable framework for optimizing outpatient
diagnostic services in similar healthcare settings.
Keywords :
Phlebotomy, Quality Improvement, Patient Flow, Waiting Time Reduction, Healthcare Efficiency.
