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Lessons from the Field
Timely delivery of laboratory efficiency information, Part I: Developing an interactive turnaround time dashboard at a high-volume laboratory
Submitted: 18 December 2018 | Published: 29 April 2020
About the author(s)
Naseem Cassim, National Health Laboratory Service (NHLS), Johannesburg, South Africa; and, Department of Molecular Medicine and Haematology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South AfricaManfred E. Tepper, National Health Laboratory Service (NHLS), Johannesburg,, South Africa
Lindi M. Coetzee, National Health Laboratory Service (NHLS), Johannesburg, South Africa; and, Department of Molecular Medicine and Haematology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
Deborah K. Glencross, National Health Laboratory Service (NHLS), Johannesburg, South Africa; and, Department of Molecular Medicine and Haematology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
Abstract
Background: Mean turn-around time (TAT) reporting for testing laboratories in a national network is typically static and not immediately available for meaningful corrective action and does not allow for test-by-test or site-by-site interrogation of individual laboratory performance.
Objective: The aim of this study was to develop an easy-to-use, visual dashboard to report interactive graphical TAT data to provide a weekly snapshot of TAT efficiency.
Methods: An interactive dashboard was developed by staff from the National Priority Programme and Central Data Warehouse of the National Health Laboratory Service, Johannesburg, South Africa, during 2018. Steps required to develop the dashboard were summarised in a flowchart. To illustrate the dashboard, one week of data from a busy laboratory for a specific set of tests was analysed using annual performance plan TAT cut-offs. Data were extracted and prepared to deliver an aggregate extract, with statistical measures provided, including test volumes, global percentage of tests that were within TAT cut-offs and percentile statistics.
Results: Nine steps were used to develop the dashboard iteratively with continuous feedback for each step. The data warehouse environment conformed and stored laboratory information system data in two formats: (1) fact and (2) dimension. Queries were developed to generate an aggregate TAT data extract to create the dashboard. The dashboard successfully delivered weekly TAT reports.
Conclusion: Implementation of a TAT dashboard can successfully enable the delivery of near real-time information and provide a weekly snapshot of efficiency in the form of TAT performance to identify and quantitate bottlenecks in service delivery.
Keywords
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