Comparison Between Short Text Messages and Phone Calls to Reduce No-Show Rates in Outpatient Medical Appointments: A Randomized Trial

Predictors of Subspecialty Appointment Scheduling and Completion for Patients Referred From a Pediatric Primary Care Clinic

Failure to complete subspecialty referrals decreases access to subspecialty care and may endanger patient safety. We conducted a retrospective analysis of new patient referrals made to the 14 most common referral departments at Boston Children's Hospital from January 1 to December 31, 2017. The sample included 2031 patient referrals. The mean wait time between referral and appointment date was 39.6 days. In all, 87% of referrals were scheduled and 84% of scheduled appointments attended, thus 73% of the original referrals were completed. In multivariate analysis, younger age, medical complexity, being a non-English speaker, and referral to a surgical subspecialty were associated with a higher likelihood of referral completion. Black and Hispanic/Latino race/ethnicity, living in a Census tract with Social Vulnerability Index (SVI) ≥ 90th percentile, and longer wait times were associated with a lower likelihood of appointment attendance. Future interventions should consider both health care system factors such as appointment wait times and community-level barriers to referral completion.

Reducing No-Show Appointments in Preanesthesia Screening

PURPOSE

Preanesthesia screening is critical to evaluate the patient's medical and surgical history before any procedure or surgery to assess for risks and to optimize outcomes during the perioperative period. The purpose of this quality improvement project was to decrease the number of missed appointments in the outpatient preanesthesia and surgical screening clinic and the impact on provider satisfaction.

DESIGN

The design of this quality improvement project was pre and post design. Automated and live phone calls reminders were provided for patients scheduled in the outpatient preanesthesia. Data were collected to compare missed appointment rates from a 3-month period before the project implementation and a 3-month period afterward.

METHODS

Predata collection included the number of no-shows in the electronic health record system from the previous 3 months. Participants included all adult patients who are scheduled for a preanesthesia surgical screening appointment. Provider satisfaction was assessed using a 5-question survey, pre and postinnovation.

FINDINGS

Reminder systems had a statistically significant impact on reducing the number of no-shows in the preanesthesia and surgical screening clinic. No significant impact was shown in provider satisfaction.

CONCLUSIONS

Implementation of a reminder system can help to reduce no-show rates in clinics. Patient no-shows overload the health system by reducing the productivity of providers and waste resources including use of clinic staff, longer wait times for other patients, and the timing providers put into chart preparation.

Behavioural economic interventions to reduce health care appointment non-attendance: a systematic review and meta-analysis

BACKGROUND

Appointment non-attendance - often referred to as "missed appointments", "patient no-show", or "did not attend (DNA)" - causes volatility in health systems around the world. Of the different approaches that can be adopted to reduce patient non-attendance, behavioural economics-oriented mechanisms (i.e., psychological, cognitive, emotional, and social factors that may impact individual decisions) are reasoned to be better suited in such contexts - where the need is to persuade, nudge, and/ or incentivize patients to honour their scheduled appointment. The aim of this systematic literature review is to identify and summarize the published evidence on the use and effectiveness of behavioural economic interventions to reduce no-shows for health care appointments.

METHODS

We systematically searched four databases (PubMed/Medline, Embase, Scopus, and Web of Science) for published and grey literature on behavioural economic strategies to reduce no-shows for health care appointments. Eligible studies met four criteria for inclusion; they were (1) available in English, Spanish, or French, (2) assessed behavioural economics interventions, (3) objectively measured a behavioural outcome (as opposed to attitudes or preferences), and (4) used a randomized and controlled or quasi-experimental study design.

RESULTS

Our initial search of the five databases identified 1,225 articles. After screening studies for inclusion criteria and assessing risk of bias, 61 studies were included in our final analysis. Data was extracted using a predefined 19-item extraction matrix. All studies assessed ambulatory or outpatient care services, although a variety of hospital departments or appointment types. The most common behaviour change intervention assessed was the use of reminders (n = 56). Results were mixed regarding the most effective methods of delivering reminders. There is significant evidence supporting the effectiveness of reminders (either by SMS, telephone, or mail) across various settings. However, there is a lack of evidence regarding alternative interventions and efforts to address other heuristics, leaving a majority of behavioural economic approaches unused and unassessed.

CONCLUSION

The studies in our review reflect a lack of diversity in intervention approaches but point to the effectiveness of reminder systems in reducing no-show rates across a variety of medical departments. We recommend future studies to test alternative behavioural economic interventions that have not been used, tested, and/or published before.

The Effect of the 2021 Irish Cyber-Attack on Otolaryngology Outpatient Non-attendance at a Model 4 Hospital in the Post-COVID Era

Aim

This study investigates the rate of non-attendance at ENT outpatient appointments in the post-COVID era and the effect of the 2021 Irish cyber-attack on non-attendance.

Methods

A retrospective review of the rates of non-attendance in a post-COVID pre-cyber-attack era wherein patients received an automated text message reminder about their appointment was compared to a post-cyber-attack era wherein the text message reminder system was disabled. In addition, these were compared with rates of non-attendance prior to when the reminder system was introduced. Three periods were compared, two weeks prior to the introduction of the text reminder system, two weeks pre-cyber-attack, and two weeks post-cyber-attack.

Results

Period 1 measured rates of non-attendance prior to the introduction of the text reminder system. Period 2 measured rates of non-attendance at outpatient appointments and consisted of nine clinic days, with two clinics per day. Period 3 similarly measured rates of non-attendance at outpatient appointments and consisted of 10 clinic days, with two clinics per day. The text reminder service was disabled during this collection period because of the cyber-attack. The average non-attendance rate was 16.99% for period 1, 13.00% for period 2, and 16.13% for period 3. A Fisher Exact Test was carried out on data with a p-value set at <0.05. Results reached statistical significance.

Conclusion

Our data shows non-attendance at ENT outpatient appointments increased without the text reminder system. Over two weeks after the attack, non-attendance increased by approximately 3%, which was statistically significant.