Table of Contents Author Guidelines Submit a Manuscript
Journal of Healthcare Engineering
Volume 2 (2011), Issue 2, Pages 197-222
http://dx.doi.org/10.1260/2040-2295.2.2.197
Research Article

Simulation Modeling of a Check-in and Medication Reconciliation Ambulatory Clinic Kiosk

Blake Lesselroth,1,2 William Eisenhauer,1 Shawn Adams,1,2 David A. Dorr,2 Christine Randall,1 Paulette Channon,1 Kas Adams,1 Victoria Church,1 Robert Felder,1 and David Douglas1

1Oregon Veterans Affairs Medical Center, 3710 SW US Veterans Hospital Drive, Portland, Oregon, 97239, USA
2Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, Oregon, 97239, USA

Received 1 August 2010; Accepted 1 January 2011

Copyright © 2011 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Gaps in information about patient medication adherence may contribute to preventable adverse drug events and patient harm. Hence, health-quality advocacy groups, including the Joint Commission, have called for the implementation of standardized processes to collect and compare patient medication lists. This manuscript describes the implementation of a self-service patient kiosk intended to check in patients for a clinic appointment and collect a medication adherence history, which is then available through the electronic health record. We used business process engineering and simulation modeling to analyze existing workflow, evaluate technology impact on clinic throughput, and predict future infrastructure needs. Our empiric data indicated that a multi-function healthcare kiosk offers a feasible platform to collect medical history data. Furthermore, our simulation model showed a non-linear association between patient arrival rate, kiosk number, and estimated patient wait times. This study provides important data to help administrators and healthcare executives predict infrastructure needs when considering the use of self-service kiosks.