Subscribe to RSS
Dig Deeper: A Case Report of Finding (and Fixing) the Root Cause of Add-On Laboratory FailuresFunding None.
Background Venipunctures and the testing they facilitate are clinically necessary, particularly for hospitalized patients. However, excess venipunctures lead to patient harm, decreased patient satisfaction, and waste.
Objectives We sought to identify contributors to excess venipunctures at our institution, focusing on electronic health record (EHR)-related factors. We then implemented and evaluated the impact of an intervention targeting one of the contributing factors.
Methods We employed the quality improvement (QI) methodology to find sources of excess venipunctures, specifically targeting add-on failures. Once an error was identified, we deployed an EHR-based intervention which was evaluated with retrospective pre- and postintervention analysis.
Results We identified an error in how the EHR evaluated the ability of laboratories across a health system to perform add-on tests to existing blood specimens. A review of 195,263 add-on orders placed prior to the intervention showed that 165,118 were successful and 30,145 failed, a failure rate of 15.4% (95% confidence interval [CI]: 15.1–15.6). We implemented an EHR-based modification that changed the criteria for add-on testing from a health-system-wide query of laboratory capabilities to one that incorporated only the capabilities of laboratories with feasible access to existing patient samples. In the 6 months following the intervention, a review of 87,333 add-on orders showed that 77,310 were successful, and 10,023 add-on orders failed resulting in a postintervention failure rate of 11.4% (95% CI: 11.1, 11.8) (p < 0.001).
Conclusion EHR features such as the ability to identify possible add-on tests are designed to reduce venipunctures but may produce unforeseen negative effects on downstream processes, particularly as hospitals merge into health systems using a single EHR. This case report describes the successful identification and correction of one cause of add-on laboratory failures. QI methodology can yield important insights that reveal simple interventions for improvement.
Protection of Human and Animal Subjects
This study was designated as Quality Improvement and thus nonhuman subject research by the Colorado Multiple Institutional Review Board (COMIRB).
Received: 31 December 2021
Accepted: 28 July 2022
Accepted Manuscript online:
29 July 2022
Article published online:
21 September 2022
© 2022. Thieme. All rights reserved.
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
- 1 Dale JC, Pruett SK. Phlebotomy–a minimalist approach. Mayo Clin Proc 1993; 68 (03) 249-255
- 2 Salisbury AC, Reid KJ, Alexander KP. et al. Diagnostic blood loss from phlebotomy and hospital-acquired anemia during acute myocardial infarction. Arch Intern Med 2011; 171 (18) 1646-1653
- 3 Thavendiranathan P, Bagai A, Ebidia A, Detsky AS, Choudhry NK. Do blood tests cause anemia in hospitalized patients? The effect of diagnostic phlebotomy on hemoglobin and hematocrit levels. J Gen Intern Med 2005; 20 (06) 520-524
- 4 Dale JC, Howanitz PJ. Patient satisfaction in phlebotomy: a College of American Pathologists′ Q-Probes study. Lab Med 1996; 27 (03) 188-192
- 5 Rudin RS, Friedberg MW, Shekelle P, Shah N, Bates DW. Getting value from electronic health records: research needed to improve practice. Ann Intern Med 2020; 172 (11, Suppl): S130-S136
- 6 Orenstein EW, Boudreaux J, Rollins M. et al. Formative usability testing reduces severe blood product ordering errors. Appl Clin Inform 2019; 10 (05) 981-990
- 7 What is a Pareto Chart? Analysis & Diagram | ASQ. (2022). Accessed May 4, 2022 at: https://asq.org/quality-resources/pareto
- 8 Nelson LS, Davis SR, Humble RM, Kulhavy J, Aman DR, Krasowski MD. Impact of add-on laboratory testing at an academic medical center: a five year retrospective study. BMC Clin Pathol 2015; 15: 11