The Effect of Healthcare Data Analytics Training on Knowledge Management: A Quasi-Experimental Field Study

Byeong Jo Kim,Maria Tomprou

doi:10.3390/joitmc7010060

Abstract

This study aims to provide practice-oriented evidence regarding the implementation of healthcare data analytics and its impact on the use of new data analytics tools and relevant analytical skills improvement. A quasi-experimental pre-test/post-test controlled study was conducted in a large medical system in the eastern United States. Healthcare data analytics training program participants (N = 21) and a comparison group comprising trainee-identified peers completing comparable work (N = 27) were compared at the start of training and one year later. Results showed that both trainees and peers demonstrated improved healthcare data analytics skills over time, related to concomitant increases in their healthcare data analytics-related learning and performance goals. This study suggests that healthcare organizations aiming at successfully implementing a new data analytics infrastructure should provide well-designed training that enables trainees to develop specific learning and performance goals as well as improve relevant skills and ability to use new tools.

Highlights

Since healthcare data analytics training had no effect on post-test healthcare data analytics skills, our results suggest that increased healthcare data analytics skills were attributable to a broader increase in employee motivation to support the healthcare data analytics initiative rather than to the direct effects of healthcare data analytics training
We recommend that future research adopts multi-wave methodologies to better understand the challenges of healthcare data analytics implementation
Using practice-oriented evidence, this study conducted a quasi-experimental pre/post-test study to examine the effect of data-analytics training and broader enterprisewide organizational change in implementing healthcare data analytics

Summary

Introduction

Data analytics in healthcare systems can help derive insights ranging from systematic waste of resources to predicting trends, improving outreach, and managing the spread of diseases. It can improve areas ranging from business management to patient care quality and diagnosis, to name just a few. As part of the larger practice of attending to the quality of evidence used in management decisions [4,5], colleges have developed new programs and courses and firms have invested in new positions and infrastructure to promote the use of such healthcare data analytics. Though relatively recent and limited, academic research suggests that the use of healthcare data analytics is positively related to organizational performance, such as asset utilization and market value [6], return on investment (ROI)

Objectives

Methods

Results

Discussion

Conclusion