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

Adi Berliner Senderey,Gabriella Lawrence,Hilla Zysman,Yael Hallak,Ran Balicer,Dan Ariely,Tamar Kornitzer,Sreeram V Ramagopalan

doi:10.1371/journal.pone.0234817

Abstract

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.

Highlights

Unattended medical appointments are a frequent event
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, 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)
We examined whether a change in the narrative of the current short message service (SMS) reminder increased members’ engagement compared to the SMS reminder currently in use, and whether specific strategic narratives are more effective than others

Summary

Introduction

Hospital outpatient clinics have reported no-show rates of 19.3%-43.0% globally [1]. These events negatively impact care quality worldwide, causing major disruptions to clinical management, delays in scheduled care, and reduced patient contentedness. There is strong evidence that even simple SMS reminders are effective in reducing non-attendance compared to no reminders at all, though their impact is small [3, 12,13,14]; the reminders’ performance is considered sub-optimal. Simple straightforward reminders implicitly assume that one key reason a patient does not attend their appointment is due to forgetfulness. There is vast evidence suggesting that other reasons for non-attendance without notification are more prominent and that a more holistic approach to this issue is needed [17,18,19,20]

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