Economic evaluation of a digital symptom checker for endometriosis using a Markov decision process model

Digital symptom checkers (SCs) are increasingly used to support early symptom recognition and care-seeking, yet evidence on their cost-effectiveness remains limited. We conducted an economic evaluation of a digital SC for endometriosis, a prevalent but underdiagnosed condition, as a case study. We developed a Markov decision process model to compare the digital SC with the standard of care from a societal perspective. Over a 40-year horizon, the digital SC reduced diagnostic delay by 4. 36 years, generated 0. 049 quality-adjusted life years (QALYs) per person, saved 5196. 22 in costs, and produced an incremental net monetary benefit (INMB) of 10, 089. 00 at a 100, 000/QALY threshold. Probabilistic sensitivity analysis confirmed the robustness of these findings, with an INMB of 12, 398. 92 (95% CI: 11, 893. 11–12, 904. 72). Scenario analyses showed that the SC remained cost-effective under a wide range of assumptions, with the greatest value realized when sensitivity and specificity were ≥0. 7, compliance exceeded 45%, and a time horizon of at least 10 years. This study provides the first economic evaluation of a digital SC for endometriosis and illustrates when and how digital SCs can deliver value to patients and health systems.