JMIR Publications

ABSTRACT

Background:

Reproductive health conditions such as endometriosis, uterine fibroids and polycystic ovary syndrome affect a large proportion of women and people who menstruate worldwide. Prevalence estimates for these conditions range from 5-40% of women of reproductive age. Long diagnostic delays, up to 12 years, are common and contribute to health complications and increased healthcare costs. Symptom checker apps provide users with information and tools to better understand their symptoms and thus have the potential to reduce the time to diagnosis for reproductive health conditions.

Objective:

This study aims to evaluate the accuracy of three symptom checkers developed by Flo Health assessing symptoms of endometriosis, uterine fibroids and polycystic ovary syndrome (PCOS) against current medical guidelines.

Methods:

Independent general practitioners were recruited to create clinical case vignettes of simulated users for the purpose of testing each condition symptom checker; vignettes created for each condition contained a mixture of condition-positive and condition-negative outcomes. A second panel of general practitioners then reviewed, approved, and modified (if necessary) each vignette. A third group of general practitioners reviewed each vignette case and designated a final classification. Vignettes were then entered into the symptom checkers by a fourth, different, group of general practitioners. The outcomes of each symptom checker were then compared with the final classification of each vignette to produce accuracy metrics including percent agreement, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).

Results:

A total of 24 cases were created per condition. Overall, exact matches between the vignette general practitioner classification and the symptom checker outcome was 83.3% for endometriosis, 83.3% for uterine fibroids, and 87.5% for PCOS. For each symptom checker: sensitivity was reported as 81.8% for endometriosis, 84.6% for uterine fibroids, and 100% for PCOS; specificity was reported as 84.6% for endometriosis, 81.8% for uterine fibroids, and 75% for PCOS; PPV was reported as 81.8% for endometriosis, 84.6% for uterine fibroids, 80% for PCOS; NPV was reported as 84.6% for endometriosis, 81.8% for uterine fibroids, and 100% for PCOS.

Conclusions:

The single condition symptom checkers have high levels of accuracy for endometriosis, uterine fibroids and PCOS. Given long delays in diagnosis for many reproductive health conditions, which lead to increased medical costs and potential health complications for individuals and healthcare providers, innovative health apps and symptom checkers hold the potential to improve care pathways.