D8.1 – Report presenting the result of the costeffectiveness analysis of the digital health platform La Meva Salut

D8.1 – Report presenting the result of the cost-effectiveness analysis of the digital health platform La Meva Salut

Since the pandemic, millions of people across Europe have grown used to booking appointments, checking prescriptions and messaging their doctor through an app rather than a waiting room. But do these digital health tools actually make care better, cheaper and fairer — and do they reach everyone equally? This report tackles that question by examining La Meva Salut (MyHealth), the public eHealth platform used across Catalonia, and its teleconsultation service eConsulta, to understand how citizens really use it and what it means for a primary care system under growing pressure.

Drawing on an exceptionally large set of anonymised, individual-level records from the Catalan Agency for Health Quality and Evaluation (AQuAS) — covering nearly 80% of the Catalan population and over 797 million data points between 2015 and 2023 — the report links platform usage with demographic, healthcare and medication data to build a detailed picture of who uses digital care and to what effect. It combines descriptive and clustering techniques, econometric and survival models, inequality indices, causal difference-in-differences analysis, text mining of patient messages, and reinforcement learning. The central takeaway is nuanced: eConsulta modestly reduces face-to-face primary care visits but only slightly changes overall costs, while persistent inequalities remain, with older adults, men and some migrant groups engaging less. The evidence points less towards automatic savings and more towards how digital tools should be designed and targeted to deliver genuine value and equity.

What the deliverable contains:

• An analysis of how patients have used MyHealth and eConsulta over time, including post-pandemic uptake and distinct clusters of users
• An assessment of the digital divide in eHealth, measuring access gaps linked to age, gender, income, nationality and chronic illness
• A causal evaluation of eConsulta’s impact on primary care workload, face-to-face visits and healthcare costs
• Text-mining and sentiment analysis of patient–professional messages to identify drivers of dissatisfaction
• A reinforcement-learning exploration of how a personalised consultation policy could further reduce in-person visits