Date of Award

Spring 5-8-2020

Document Type

DNP Project

Project Team Faculty Member

Mary Lee Barron PhD, APRN, FNP-BC, FAANP

Project Team Faculty Member

Frank Lyerla PhD, RN, FHIMSS

Keywords

Nurse Leader Perception, Data Optimization, Data Accessibility, BCMA, Report Usability, Medication Administration Safety

Abstract

Background: The integration of health information technology (HIT) is an expectation during the healthcare delivery process to ensure quality and accuracy. Data generated from HIT can help facilitate quality initiatives. HIT such as Barcode Medication Administration (BCMA) has been successfully introduced in the healthcare industry with a demonstrated positive impact on patient safety. A small test of change was implemented on a Medical Surgical (MS) and Intensive Care Unit (ICU) which included automated daily BCMA compliance reports sent to leadership compared to the current standard process.

Objectives: To examine impact of reports on the BCMA compliance data. To examine leadership perception of reports on accessibility and usability of BCMA compliance data.

Methods: Daily automated reports were developed and sent to nursing leadership. A detailed weekly report was developed and disseminated at leadership request. The System Usability Scale (SUS) was used to evaluate the daily and weekly report’s perceived usability from nursing leadership.

Results: BCMA compliance showed slight improvement in both units (0.40%-1.61%). MS compliance improved during daily automated reports while ICU improved showed after detailed, weekly reports. Results of the SUS showed large range in variation of usability scores for daily (42.5-90) and weekly (57.5-92.5) reports per leader. Both reports scored average usability (daily=60, weekly=79.16).

Conclusions: Preliminary results of this test of change showed a small increase in BCMA compliance, which can translate to thousands of additional scans annually. Perceived usability scores increased when more detailed data was made available in weekly reports for trending analysis.

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