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Cited by 80Healthcare Operations and Scheduling OptimizationMobile Health and mHealth ApplicationsEmergency and Acute Care Studies

Improving Attendance at Post–Emergency Department Follow‐up Via Automated Text Message Appointment Reminders: A Randomized Controlled Trial

Open access
Arora, Sanjay, Burner, Elizabeth, Terp, Sophie, Nok Lam, Chun, Nercisian, Aren, Bhatt, Vivek, Menchine, Michael·2015·Academic Emergency Medicine
DOI 10.1111/acem.12503
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Abstract

Objectives: Patients discharged from the emergency department (ED) are often referred for primary care, specialty, or other disease‐specific follow‐up appointments. Attendance at these scheduled follow‐up appointments has been found to improve patient outcomes, decrease ED bounce‐backs, and reduce malpractice risk. Reasons for missing follow‐up visits are complex, but the most commonly reason cited by patients is simply forgetting. In this study the authors evaluated the ability of an automated text message reminder system to increase attendance at post‐ED discharge follow‐up appointments in a predominantly Hispanic safety‐net population. Methods: This was a randomized controlled trial of ED patients with outpatient follow‐up visits scheduled at the time of ED discharge. A total of 374 English‐ and Spanish‐speaking patients with text‐capable mobile phones were enrolled. Patients in the intervention arm received automated, personalized text message appointment reminders including date, time, and clinic location at 7, 3, and 1 day before scheduled visits. A t‐test of proportions was used to compare outcomes between intervention and control groups. Both an intention‐to‐treat (ITT) and a per‐protocol analysis of the data were performed. The ITT more accurately reflects real‐world conditions where errors such as number entry errors are bound to occur. The per‐protocol analysis adds value by isolating the effect of the intervention by comparing patients who actually received it compared with those who did not. Results: In the per‐protocol analysis of the primary outcome, the overall appointment adherence rate was 72.6% in the intervention group compared with 62.1% in the control group (difference between groups = 10.5%, 95% confidence interval [CI] = 0.3% to 20.8%; p = 0.045; number needed to treat = 9.5). In the ITT analysis, the overall appointment attendance rate 70.2% in the intervention group compared with 62.1% in the control group (difference between groups = 8.2%; 95% CI = –1.6% to 17.7%; p = 0.100). In a secondary largely exploratory analysis, the intervention was found to have the most benefit in patients with the lowest baseline follow‐up rate (English speakers with specialty care appointments). Conclusions: Automated text message appointment reminders resulted in improvement in attendance at scheduled post‐ED discharge outpatient follow‐up visits and represent a low‐cost and highly scalable solution to increase attendance at post‐ED follow‐up appointments, which should be further explored in larger sample sizes and diverse patient populations.

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  • In that RCT, patients with the lowest follow-up rate (English speakers with specialty care appointments) benefited the most from the intervention.

    “patients with the lowest follow-up rate (English speakers with specialty care appointments) benefited the most from the intervention.”

    From The Empirical Foundations of Telemedicine Interventions in Primary Care (2016) · cites this paper as [107]

  • In an RCT of automated text messaging for post-emergency follow-up, both intent-to-treat and per-protocol analyses were performed.

    “Both intent to treat and a per-protocol analysis of the data were performed.”

    From The Empirical Foundations of Telemedicine Interventions in Primary Care (2016) · cites this paper as [107]

  • In that RCT, the adherence rate in the intervention group was 72.6%, compared with 62.1% in the control group.

    “The adherence rate in the intervention group was 72.6%, compared with 62.1% in the control group.”

    From The Empirical Foundations of Telemedicine Interventions in Primary Care (2016) · cites this paper as [107]

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Research works printed but not linked: 2

  1. [8]8. Kyriacou DN, Handel D, Stein AC, Nelson RR. Fac- tors affecting outpatient follow-up compliance of emergency department patients. J Gen Intern Med 2005;20:938-42.
  2. [20]20. Sharp DJ, Hamilton W. Non-attendance at general practices and outpatient clinics. BMJ 2001;323:1081- 2.

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Authors
Arora, S., Burner, E., Terp, S., Nok Lam, C., Nercisian, A., Bhatt, V., & Menchine, M.
Affiliations
  • The Department of Emergency Medicine Los Angeles CA
  • University of Southern California (US)
Corresponding author
Arora, Sanjay
ORCID
Venue
Academic Emergency Medicine
Publisher
Wiley
Published
2014-11-11
Volume
22
Issue
1
Pages
31-37
ISSN
  • 1069-6563 (ISSN-L)
  • 1553-2712
DOI
10.1111/acem.12503
OpenAlex
W2054450763
Semantic Scholar
60ca8ccdd80439c8f97af054d82491ca1cc2c205
Cited by
79
References
30
Citations by year
2026: 5 · 2025: 4 · 2024: 2 · 2023: 3 · 2022: 6 · 2021: 5 · 2020: 15 · 2019: 7 · 2018: 12 · 2017: 6 · 2016: 10 · 2015: 3 · 2014: 1
FWCI
11.57
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • Academic Emergency Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › Emergency Medical Services › Healthcare Operations and Scheduling Optimization
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
Keywords
appointment reminders, automated text messaging, emergency department discharge, follow-up appointment attendance, missed appointments, Hispanic patients, safety-net hospitals, primary care follow-up, mobile health, patient reminders
MeSH terms
Adult, Appointments and Schedules, Emergency Service, Hospital, Female, Humans, Male, Medicine, Middle Aged, Patient Compliance, Patient Discharge, Primary Health Care, Reminder Systems, Text Messaging

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