managing waiting times to predict no-shows and cancelations at a children’s hospital

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ID: 236694
2016
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Ranked #29 of 58 articles by views in research journal of environmental toxicology

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Abstract
Purpose: Since long waits in hospitals have been found to be related to high rates of no-shows and cancelations, managing waiting times should be considered as an important tool that hospitals can use to reduce missed appointments. The aim of this study is to analyze patients’ behavior in order to predict no-show and cancelation rates correlated to waiting times. Design/methodology/approach: This study is based on the data from a US children’s hospital, which includes all the appointments registered during one year of observation. We used the call-appointment interval to establish the wait time to get an appointment. Four different types of appointment-keeping behavior and two types of patients were distinguished: arrival, no-show, cancelation with no reschedule, and cancelation with reschedule; and new and established patients. Findings: Results confirmed a strong impact of long waiting times on patients’ appointment-keeping behavior, and the logarithmic regression was found as the best-fit function for the correlation between variables in all cases. The correlation analysis showed that new patients tend to miss appointments more often than established patients when the waiting time increases. It was also found that, depending on the patients’ appointment distribution, it might get more complicated for hospitals to reduce missed appointments as the waiting time is reduced. Originality/value: The methodology applied in our study, which combines the use of regression analysis and patients’ appointment distribution analysis, would help health care managers to understand the initial implications of long waiting times and to address improvement related to patient satisfaction and hospital performance.
Reference Key
rodrguez-garca2016journalmanaging Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Miguel Rodríguez-García;Aldo A McLean-Carranza;J. Carlos Prado-Prado;Pablo Domínguez-Caamaño
Journal research journal of environmental toxicology
Year 2016
DOI
10.3926/jiem.2075
URL
http://www.jiem.org/index.php/jiem/article/view/2075
Keywords
management engineeringsocial sciencescommercebusiness

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