Description

Infertility, recognized as a disease by the WHO, is defined as the failure to achieve successful pregnancy after at least 12 months of regular unprotected intercourse in women younger than age 35, or within 6 months in women 35 or older. The worldwide prevalence of infertility is high, affecting approximately 12-18% of couples. Through detailed medical history for risk factors, assessment of ovulatory function, structure and patency of the female reproductive tract, and semen analysis of the male partner, the cause of infertility can be ascertained in most patients and allows determination of appropriate therapeutic options.

Despite the high prevalence of infertility, only a small proportion of patients seek care, and an even smaller number continue care after the initial evaluation. Several studies have examined underlying reasons for early discontinuation of infertility care, namely prior to initiation of treatment. In a study from the Netherlands examining drop-out rates at different stages of fertility care, nearly half of the patients who discontinued care withdrew before initiating any treatment; 6.0% did not return after the first visit, 3.4% dropped out during the diagnostic work-up, and 35.7% dropped out after finishing the diagnostic workup. In a cohort of 434 infertile couples residing in urban United States, Eisenberg et al found that 13% did not pursue any infertility treatment after the initial consultation with a reproductive endocrinologist. When compared to patients pursuing treatment, these patients were typically older, less educated, of lower socioeconomic status, and had a higher baseline depression score. Of note, psychological factors are associated with higher drop-out rates even in patients with insurance coverage for infertility treatments. This data highlights that the initial evaluation and diagnostic work-up process is a critical stage of fertility care that engages patients and influences their decision to pursue treatment.

Although the barriers to pursuing fertility treatments have been studied, there is less information on the precise barriers to completing the diagnostic work-up. This first step can be cumbersome as it includes laboratory tests and radiographic or ultrasound imaging to evaluate the fallopian tube patency and uterine cavity in the female partner, blood tests and semen analysis in the male partner, and more recently, genetic carrier screening in both partners. What adds to the complexity of this testing is the need for time-sensitive and menstrual-cycle dependent testing which is required for the physician to recommend a personalized treatment plan. Poor communication or lack of understanding of the instructions can lead to missed testing windows, especially follicular phase appointments for blood tests and imaging studies. From a patient's perspective, each month that passes represents a missed opportunity to become pregnant further contributing to the higher levels of anxiety and stress associated with infertility diagnosis.

Based on contextual inquiry and grounded in patient needs, the work-up period was identified as an opportunity to optimize patient interactions with their physician. It was hypothesized that the implementation of a novel digital health platform to improve communication with patients regarding their diagnostic work-up will improve completion rates and overall patient retention. To this effect, the Fast Track to Fertility (FTF) program was created, which was developed using AI and natural language processing (NLP) to accurately provide semi-automated two-way text message communications to send reminders regarding the timing of tests, location of testing sites, and related educational materials. A detailed description of the discovery, pilot, and semi-automation phases of this innovative program has been published previously. A text-based approach was selected as it does not require downloading an app, supports real-time two-way engagement in a private setting, and has been shown to reduce racial disparities in care for reproductive-age women in our department.

The initial pilot program coupled with the iterative development phases resulted in an approximately 50% reduction in the time taken to complete the fertility work-up (from 97 days to 41 days) with high patient net promoter scores (>70%). In addition, high patient willingness to participate in this program (70%) and high accuracy of the AI-augmented texting (up to 80%) was observed, resulting in workflow improvement for staff and providers. However, it is not clear if these favorable outcomes were at least in part related to selection bias, as patients had to opt into the program and were not randomized. A secondary analysis on the barriers to infertility workup completion demonstrated that more Black women and those without fertility benefits both declined to enroll in the FTF program and did not initiate the infertility workup.

The goal of this proposed quality improvement initiative is to perform a randomized controlled quality improvement study on the updated FTF program (FTF v2.0). Since the initial pilot study was published, the FTF Program has been reworked. The platform now uses an algorithmic approach to text messaging (rather than AI) and incorporates several educational videos to increase patient knowledge and autonomy in the workup and treatment of infertility. Through this initiative, the aim is to measure the impact of the FTF program on infertility workup completion, fertility treatment initiation, pregnancy, and live birth.