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It’s how you say it: Systematic A/B testing of digital messaging cut hospital no-show rates

Failure to attend hospital appointments has a detrimental impact on care quality. Documented efforts to address this challenge have only modestly decreased no-show rates. Behavioral economics theory has suggested that more effective messages may lead to increased responsiveness. In complex, real-wor...

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Autores principales: Berliner Senderey, Adi, Kornitzer, Tamar, Lawrence, Gabriella, Zysman, Hilla, Hallak, Yael, Ariely, Dan, Balicer, Ran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7310733/
https://www.ncbi.nlm.nih.gov/pubmed/32574181
http://dx.doi.org/10.1371/journal.pone.0234817
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author Berliner Senderey, Adi
Kornitzer, Tamar
Lawrence, Gabriella
Zysman, Hilla
Hallak, Yael
Ariely, Dan
Balicer, Ran
author_facet Berliner Senderey, Adi
Kornitzer, Tamar
Lawrence, Gabriella
Zysman, Hilla
Hallak, Yael
Ariely, Dan
Balicer, Ran
author_sort Berliner Senderey, Adi
collection PubMed
description Failure to attend hospital appointments has a detrimental impact on care quality. Documented efforts to address this challenge have only modestly decreased no-show rates. Behavioral economics theory has suggested that more effective messages may lead to increased responsiveness. In complex, real-world settings, it has proven difficult to predict the optimal message composition. In this study, we aimed to systematically compare the effects of several pre-appointment message formats on no-show rates. We randomly assigned members from Clalit Health Services (CHS), the largest payer-provider healthcare organization in Israel, who had scheduled outpatient clinic appointments in 14 CHS hospitals, to one of nine groups. Each individual received a pre-appointment SMS text reminder five days before the appointment, which differed by group. No-show and advanced cancellation rates were compared between the eight alternative messages, with the previously used generic message serving as the control. There were 161,587 CHS members who received pre-appointment reminder messages who were included in this study. Five message frames significantly differed from the control group. Members who received a reminder designed to evoke emotional guilt had a no-show rates of 14.2%, compared with 21.1% in the control group (odds ratio [OR]: 0.69, 95% confidence interval [CI]: 0.67, 0.76), and an advanced cancellation rate of 26.3% compared with 17.2% in the control group (OR: 1.2, 95% CI: 1.19, 1.21). Four additional reminder formats demonstrated significantly improved impact on no-show rates, compared to the control, though not as effective as the best performing message format. Carefully selecting the narrative of pre-appointment SMS reminders can lead to a marked decrease in no-show rates. The process of a/b testing, selecting, and adopting optimal messages is a practical example of implementing the learning healthcare system paradigm, which could prevent up to one-third of the 352,000 annually unattended appointments in Israel.
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spelling pubmed-73107332020-06-26 It’s how you say it: Systematic A/B testing of digital messaging cut hospital no-show rates Berliner Senderey, Adi Kornitzer, Tamar Lawrence, Gabriella Zysman, Hilla Hallak, Yael Ariely, Dan Balicer, Ran PLoS One Research Article Failure to attend hospital appointments has a detrimental impact on care quality. Documented efforts to address this challenge have only modestly decreased no-show rates. Behavioral economics theory has suggested that more effective messages may lead to increased responsiveness. In complex, real-world settings, it has proven difficult to predict the optimal message composition. In this study, we aimed to systematically compare the effects of several pre-appointment message formats on no-show rates. We randomly assigned members from Clalit Health Services (CHS), the largest payer-provider healthcare organization in Israel, who had scheduled outpatient clinic appointments in 14 CHS hospitals, to one of nine groups. Each individual received a pre-appointment SMS text reminder five days before the appointment, which differed by group. No-show and advanced cancellation rates were compared between the eight alternative messages, with the previously used generic message serving as the control. There were 161,587 CHS members who received pre-appointment reminder messages who were included in this study. Five message frames significantly differed from the control group. Members who received a reminder designed to evoke emotional guilt had a no-show rates of 14.2%, compared with 21.1% in the control group (odds ratio [OR]: 0.69, 95% confidence interval [CI]: 0.67, 0.76), and an advanced cancellation rate of 26.3% compared with 17.2% in the control group (OR: 1.2, 95% CI: 1.19, 1.21). Four additional reminder formats demonstrated significantly improved impact on no-show rates, compared to the control, though not as effective as the best performing message format. Carefully selecting the narrative of pre-appointment SMS reminders can lead to a marked decrease in no-show rates. The process of a/b testing, selecting, and adopting optimal messages is a practical example of implementing the learning healthcare system paradigm, which could prevent up to one-third of the 352,000 annually unattended appointments in Israel. Public Library of Science 2020-06-23 /pmc/articles/PMC7310733/ /pubmed/32574181 http://dx.doi.org/10.1371/journal.pone.0234817 Text en © 2020 Berliner Senderey et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Berliner Senderey, Adi
Kornitzer, Tamar
Lawrence, Gabriella
Zysman, Hilla
Hallak, Yael
Ariely, Dan
Balicer, Ran
It’s how you say it: Systematic A/B testing of digital messaging cut hospital no-show rates
title It’s how you say it: Systematic A/B testing of digital messaging cut hospital no-show rates
title_full It’s how you say it: Systematic A/B testing of digital messaging cut hospital no-show rates
title_fullStr It’s how you say it: Systematic A/B testing of digital messaging cut hospital no-show rates
title_full_unstemmed It’s how you say it: Systematic A/B testing of digital messaging cut hospital no-show rates
title_short It’s how you say it: Systematic A/B testing of digital messaging cut hospital no-show rates
title_sort it’s how you say it: systematic a/b testing of digital messaging cut hospital no-show rates
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7310733/
https://www.ncbi.nlm.nih.gov/pubmed/32574181
http://dx.doi.org/10.1371/journal.pone.0234817
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