Validation of a smartphone app to shorten the diagnostic delay in endometriosis: a prospective observational pilot study

• Endometriosis is associated with long diagnostic delay. • A smartphone app could help to speed up the diagnostic process. • The Q1.6 app is user-friendly and collects real-time data on one’s menstrual cycle. • It differentiates between pain patterns in patients with endometriosis and controls. • Future prospective validation will have to prove the real value of the app. Endometriosis is a chronic condition in which endometrium-like tissue is found in extrauterine locations. It is associated with long diagnostic delay and this may result in a longer period of pain or higher stage at diagnosis. A smartphone app could help to speed up the diagnostic process. The objective of this study is to explore whether an app can differentiate pain patterns in patients with endometriosis and controls. Patients with proven endometriosis and participants without a diagnosis of endometriosis kept a digital pain diary with twice-daily entries using the Q1.6 app. The app is a medically registered smartphone application that uses adaptive questioning to collect real-time pain scores for general pain as well as dysuria, dyschezia, and dyspareunia. Twenty-six patients and 105 controls were included. The mean use of the app was 58 days. The number of painful days was higher in participants with endometriosis (23.5 vs 13.3; P < 0.01). Mean pain scores were higher in patients with endometriosis for dysuria (3.3 vs 1.5; P < 0.01), dyschezia (5.3 vs 2.5; P < 0.01), and dyspareunia (4.3 vs 1.8; P < 0.01). A combination of dysuria, dyschezia and/or dyspareunia was more frequently found in patients with endometriosis. This smartphone app seems to be able to differentiate between pain patterns in patients with endometriosis and controls. Future prospective validation in patients with suspected endometriosis will have to prove the real value of the app in shortening the duration of the diagnostic process.