ArticleJAMA network open2022
Association of Use of Electronic Appointment Reminders With Waiting Times in the Veterans Affairs Health System.
Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- Article
- Text message reminders for visit adherence among non-communicable disease patients in Haiti: A pilot study.PLOS global public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Electronic appointment reminder systems are increasingly used across health systems. However, their association with patients' waiting times for their appointments, a measure of timely access to care, has yet to be assessed. Objective: To assess the associations between the introduction of an electronic appointment reminder system and the number of days patients had to wait from appointment booking to appointment completion in patients in the Veterans Affairs Health System. Design, Setting, and Participants: Cohort study of patients who completed appointments from January 1, 2018, to October 13, 2018, inclusive in all 130 Veterans Affairs (VA) health centers in the US. The study population comprised a census of all patients who received care at any VA health center during the period of the study for outpatient, procedural, rehabilitation, or radiology services. Data were analyzed from May 15, 2021, to December 15, 2021. Exposures: Phased introduction of an electronic appointment reminder system (VEText) in 6 waves spread across the study period. Main Outcomes and Measures: The unit of observation in this study was a completed appointment made by any such patients. Observations were excluded if the appointment was booked before but completed after the exposure, or if data were duplicated, missing, or incomplete. For each completed appointment, the number of days between which the appointment was booked and when it was completed. Results: The number of observations after exclusion comprised 39.5 million completed appointments from 5.1 million patients (91.1% male) with a mean (SD) age of 62.57 (16.24) years. The adoption of VEText was associated with an estimated reduction in patient waiting time by a mean of 6.51 days (95% CI, 5.51-7.52 days). Adoption of VEText was also associated with an increase of 8.54 (95% CI, 7.65-9.44) days of additional waiting per incomplete booking. Conclusions and Relevance: Results of this study suggest that appointment reminder systems may be associated with decreases in the mean number of days patients in the VA system have to wait for their appointments but can potentially lengthen waiting times for patients who miss their bookings. Further study is warranted to assess whether these findings may be generalizable to other populations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.