Thomas Rohleder1, Brian Bailey2, Brian Crum3, Timothy Faber3, Brandon Johnson4, LeTesha Montgomery3, Rachel Pringnitz3. 1. Process Improvement Office, Vanderbilt University Medical Center, Nashville, Tennessee, USA. rohleder@mayo.edu 2. Process Improvement Office, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 3. Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA. 4. Essentia Health, Information Services, Duluth, Minnesota, USA.
Abstract
PURPOSE: Contact centers for patient and referring physician are important to large medical-centers such as the Mayo Clinic's Central Appointment Office (CAO). The aim of this case study is to report the process and results of a major process improvement effort, designed to simultaneously improve service quality and efficiency. DESIGN/METHODOLOGY/APPROACH: Discrete-event simulation and optimization are used and linked to significant service improvements. FINDINGS: The process improvement efforts led to about a 70 percent improvement in patient service performance as measured by average answering-speed (ASA) and average abandonment rate (AAR). This was achieved without adding additional staff, despite call volume increasing by 12 percent. Evaluating process improvement projects is difficult owing to the "phased" implementation of changes. Thus, there is no true control against which to compare. Additionally, the results are based on a single case study. RESEARCH LIMITATIONS/IMPLICATIONS: Evaluation of process improvement projects is difficult due to the "phased" implementation of changes. Thus, there is no true control to compare against. PRACTICAL IMPLICATIONS: Contact center data and operations research methods, such as discrete-event simulation and optimization, can be integrated with change management, which results in significant process improvements in medical call-centers. ORIGINALITY/VALUE: Structured quantitative modeling of contact centers can be an important extension to traditional quality and process improvement techniques.
PURPOSE: Contact centers for patient and referring physician are important to large medical-centers such as the Mayo Clinic's Central Appointment Office (CAO). The aim of this case study is to report the process and results of a major process improvement effort, designed to simultaneously improve service quality and efficiency. DESIGN/METHODOLOGY/APPROACH: Discrete-event simulation and optimization are used and linked to significant service improvements. FINDINGS: The process improvement efforts led to about a 70 percent improvement in patient service performance as measured by average answering-speed (ASA) and average abandonment rate (AAR). This was achieved without adding additional staff, despite call volume increasing by 12 percent. Evaluating process improvement projects is difficult owing to the "phased" implementation of changes. Thus, there is no true control against which to compare. Additionally, the results are based on a single case study. RESEARCH LIMITATIONS/IMPLICATIONS: Evaluation of process improvement projects is difficult due to the "phased" implementation of changes. Thus, there is no true control to compare against. PRACTICAL IMPLICATIONS: Contact center data and operations research methods, such as discrete-event simulation and optimization, can be integrated with change management, which results in significant process improvements in medical call-centers. ORIGINALITY/VALUE: Structured quantitative modeling of contact centers can be an important extension to traditional quality and process improvement techniques.
Authors: Allyson M Best; Cinnamon A Dixon; W David Kelton; Christopher J Lindsell; Michael J Ward Journal: Am J Emerg Med Date: 2014-05-20 Impact factor: 2.469