Paving the COWpath: data-driven design of pediatric order sets

Y Zhang,R Padman,J E Levin

doi:10.1136/amiajnl-2013-002316

Abstract

Evidence indicates that users incur significant physical and cognitive costs in the use of order sets, a core feature of computerized provider order entry systems. This paper develops data-driven approaches for automating the construction of order sets that match closely with user preferences and workflow while minimizing physical and cognitive workload. We developed and tested optimization-based models embedded with clustering techniques using physical and cognitive click cost criteria. By judiciously learning from users' actual actions, our methods identify items for constituting order sets that are relevant according to historical ordering data and grouped on the basis of order similarity and ordering time. We evaluated performance of the methods using 47,099 orders from the year 2011 for asthma, appendectomy and pneumonia management in a pediatric inpatient setting. In comparison with existing order sets, those developed using the new approach significantly reduce the physical and cognitive workload associated with usage by 14-52%. This approach is also capable of accommodating variations in clinical conditions that affect order set usage and development. There is a critical need to investigate the cognitive complexity imposed on users by complex clinical information systems, and to design their features according to 'human factors' best practices. Optimizing order set generation using cognitive cost criteria introduces a new approach that can potentially improve ordering efficiency, reduce unintended variations in order placement, and enhance patient safety. We demonstrate that data-driven methods offer a promising approach for designing order sets that are generalizable, data-driven, condition-based, and up to date with current best practices.

Highlights

AND SIGNIFICANCE As technology assumes an increasingly critical role in healthcare delivery, recent literature indicates that the interaction of technology and humans in healthcare settings warrants a thorough investigation.[1]
Poor usability of health information technology (IT) causes new types of medical errors that are unique to the technology era, through insufficient customization of the systems to workflow in the care delivery setting, end user information overload, and lack of adequate knowledge about user behaviors.[1,2,3,4]
We examine an unintended, adverse consequence of implementing computerized physician order entry (CPOE) systems—the excessive physical and cognitive workload imposed on users.[5]

Summary

Introduction

AND SIGNIFICANCE As technology assumes an increasingly critical role in healthcare delivery, recent literature indicates that the interaction of technology and humans in healthcare settings warrants a thorough investigation.[1] Poor usability of health information technology (IT) causes new types of medical errors that are unique to the technology era, through insufficient customization of the systems to workflow in the care delivery setting, end user information overload, and lack of adequate knowledge about user behaviors.[1,2,3,4] In this paper, we examine an unintended, adverse consequence of implementing computerized physician order entry (CPOE) systems—the excessive physical and cognitive workload imposed on users.[5] This is a significant contributor to poor judgment, inaccuracies, and erroneous actions that may lead to adverse outcomes in the clinical care setting.[6] Poor usability stems from the lack of coordination between technology and human practices.[6,7,8,9] Previous research indicates that knowledge of user behaviors can have a profound impact on achieving health IT use, and incorporating this knowledge into the design of health IT systems is vital for enhancing their usability.[1]

Methods

Results

Conclusion