AUTOMATION IN CLINICAL DIAGNOSTIC LABORATORIES IN PAKISTAN: A NARRATIVE REVIEW OF WORKFLOW TRANSFORMATION AND OUTCOMES.

Abstract

Background: Total laboratory automation (TLA) integrates pre-analytic, analytic, and post-analytic processes and has been shown to improve throughput and reduce errors in clinical laboratories worldwide. Objective: To evaluate the impact of automation on sample handling, testing throughput, turnaround time (TAT), error rates, and result reporting in Pakistani clinical diagnostic laboratories. Methods: We performed a narrative review of published studies, institutional reports, and indexed articles (2018–2024) describing TLA implementation or automation outcomes in Pakistan and adjacent evidence from international studies where Pakistani data were limited. Results: Pakistani institutions that have implemented TLA report consistent improvements: reduced pre-analytic errors and faster TAT (Shia International Hospital: chemistry TAT reduced from 4 h to 1–2 h; immunoassays from 6–7 h to 3–4 h) and measurable decreases in error frequency. A national professional journal and institutional evaluations also reported improved workflow efficiency and greater capacity following automation. Several analytical platform evaluations (Alinity systems) demonstrated reliable analytical performance and high throughput suitable for TLA integration. Challenges reported in Pakistan include capital cost, infrastructure and power stability, and workforce training needs. Conclusion: Evidence from Pakistan supports that automation improves laboratory efficiency, accuracy, and reporting speed, but scaling will require targeted investments in infrastructure, training, and quality-management frameworks.