O-085 Patients support through a mobile application improves ART outcomes across all age groups
Authors: Raanani H , Israel R , Averbach D 
Published: June 2023

Study question

Assess the effectiveness of fertility treatment companion mobile application, which provides tracking, adherence tools, education and community support, in improving ART outcomes

Summary answer

Results showed that patients use of mobile application during treatment had significantly improved ART outcomes compared to the CDC average, across all age groups

What is known already

Growing numbers of adults use digital health tools to diagnose and manage their health conditions. Direct-to-consumer, interactive, diagnostic apps with information and personalization capabilities beyond those of static search engines are rapidly growing in use (M. Millenson et al. 2018).

A very limited amount of research has been conducted on mobile application’s ability to impact ART outcomes (I. Robertson, etc. 2021). Existing studies include small control groups and limited data.

To date, though sparse, most research has focused on mobile applications’ and internet-based technologies' ability to mitigate the psychological effects of infertility (Meyers & Domar, 2021).Study design, size, duration:

Retrospective analysis conducted using Embie mobile application’s database (EMU) between Jan 1, 2021 and Dec 31, 2022. Study group included 6449 cycles by 5067 users self-reported in real-time.

EMU stimulation cycle cancelation rates and pregnancy outcomes, at week 20 of pregnancy, were compared to CDC 2020 preliminary report of LBR and stimulation cycle cancellation rates, divided into 4 age groups; &lt;35, 35-37, 38-40 and &gt;40.

EMU population included 53% U.S., 47% out of U.S.

Participants/materials, setting, methods

Participants are fertility clinic patients globally who voluntarily downloaded the mobile application via the App or Play stores.

The application provides ART cycle protocol tracking and monitoring, eggs retrieved, embryo, transfer and pregnancy results, etc, along with educational articles and community support.

Self-reported data is entered in real-time by the user. We cleared, merged and analyzed using python, then compared the CDC report by age group. Chi square significance performed comparing two proportions (with continuity correction).

Main results and the role of chance

4426 EMU of stimulation cycles analyzed 2319, 903, 683, 521 by age respectively.

EMU stimulation cancelation rates 2.76%, 3.54%, 6.00%, 7.49% respectively.

2073 EMU transfer cycles analyzed 1078, 431, 336, 228 by age respectively.

Ongoing EMU pregnancy at 20 weeks was observed in 618, 252, 170, 75 respectively.

Ongoing EMU pregnancy rates at 20 weeks 57.33%, 58.47%, 50.60%, 32.89% respectively.

Delta CDC/EMU stimulation cycle cancellation rate 5% vs 2.76%, 7.20 vs 3.54%, 10.10% vs 6.00%, 14.20% vs 7.49% respectively.

Delta CDC LBR per transfer data vs EMU ongoing pregnancy 49.80% vs 57.33%, 45.50% vs 58.47%, 40.40%vs 50.60%, 23.90% vs 32.89% respectively.

Delta CDC LBR per transfer data to EMU U.S. users’ only ongoing pregnancy 49.80% vs 62.86%, 45.50% vs 65.77%, 40.40% vs 58.17%, 23.90% vs 43.62% respectively.

Statistically significant analysis by chi square score showed all delta measurements to be significant (p &lt; 0.0001).

Limitations, reasons for caution

Self-reported data may not be as reliable as data collected in a clinical setting. However, the use of a large cohort reduces the impact of a single error. Additionally, LBR were compared to ongoing pregnancy at 20 weeks, which can influence the outcomes at a low rate.

Wider implications of the findings

Our results suggest that fertility treatment mobile applications can significantly improve ART outcomes and patient's experience. Clinics should consider adopting such tools as an adjunct to care.

The ability to collect and analyze big data globally in real-time will impact future ART research, medical understanding and improvement of patient’s fertility treatment.

Trial registration number

not applicable