TY - JOUR
T1 - Overview and classification of evaluation metrics of appointment scheduling systems
AU - Mazaheri Habibi, Mohammad Reza
AU - Mohammad Abadi, Fahimeh
AU - Tabesh, Hamed
AU - Vakili Arki, Hasan
AU - Abu-Hanna, Ameen
AU - Eslami, Saeid
N1 - Publisher Copyright: © 2024, Published by Frontiers in Health Informatics.
PY - 2024
Y1 - 2024
N2 - Introduction: This study reviews the several metrics used to evaluate the performance of appointment scheduling systems. Material and Methods: The articles in English were searched using PubMed, Scopus, and Web of Science databases and Google scholar search engine until July 23, 2023. We used queueing theory to classify evaluation metrics. Results: Out of 23403 articles, 75 papers were prepared for detailed analysis. We classify evaluation metrics of appointment scheduling system along with their definition and frequency of use. A total of 24 measures containing twelve (%50), seven (%29), and five (%21) were related to the categories of arrivals (patient), queue (at clinic), and server (physician) were found, respectively. Conclusion: To the best of our knowledge, this paper was one of the first studies collecting and classifying all evaluation metrics of appointment scheduling system in order to help other researchers. Most metrics pertained to patients which may highlight the importance of the patient’s perspective in evaluating appointment scheduling systems.
AB - Introduction: This study reviews the several metrics used to evaluate the performance of appointment scheduling systems. Material and Methods: The articles in English were searched using PubMed, Scopus, and Web of Science databases and Google scholar search engine until July 23, 2023. We used queueing theory to classify evaluation metrics. Results: Out of 23403 articles, 75 papers were prepared for detailed analysis. We classify evaluation metrics of appointment scheduling system along with their definition and frequency of use. A total of 24 measures containing twelve (%50), seven (%29), and five (%21) were related to the categories of arrivals (patient), queue (at clinic), and server (physician) were found, respectively. Conclusion: To the best of our knowledge, this paper was one of the first studies collecting and classifying all evaluation metrics of appointment scheduling system in order to help other researchers. Most metrics pertained to patients which may highlight the importance of the patient’s perspective in evaluating appointment scheduling systems.
KW - Ambulatory Care Facilities
KW - Appointments and Schedules
KW - Evaluation Metrics
KW - Queueing Theory
UR - http://www.scopus.com/inward/record.url?scp=85186851060&partnerID=8YFLogxK
U2 - 10.30699/fhi.v13i0.573
DO - 10.30699/fhi.v13i0.573
M3 - Article
SN - 2676-7104
VL - 13
JO - Frontiers in Health Informatics
JF - Frontiers in Health Informatics
M1 - 192
ER -