Why the study?
Economic evaluations of digital health technologies remain scarce in early development stages, where early-stage assessments are needed to inform development and adoption decisions.
Is a chatbot-supported remote patient monitoring solution for anticoagulation management cost-effective and does it improve time in therapeutic range compared to standard of care in postoperative cardiac surgery patients?
Is a chatbot-supported remote patient monitoring solution for anticoagulation management cost-effective and does it improve time in therapeutic range compared to standard of care in postoperative cardiac surgery patients?
Enables informed early refinement of Tier C DHTs; extends scarce RCT economic evidence for NICE framework compliance.
BACKGROUND Digital health technologies (DHTs) are increasingly integrated into clinical practice, yet economic evaluations remain scarce, particularly in early development stages. Within the NICE Evidence Standards Framework, Tier C DHTs comprise technologies with direct clinical implications and measurable health outcomes, for which robust economic evidence is essential. Early-stage assessments are particularly important to inform subsequent development, refinement, and adoption decisions across the digital health lifecycle. OBJECTIVE This study aims to explore the feasibility of integrating a full trial-based economic evaluation within an early-stage pilot comparing a chatbot-supported remote patient monitoring (RPM) solution for anticoagulation management with standard of care (SOC). METHODS A cost-effectiveness analysis was performed alongside a pilot crossover trial among adult cardiac surgery patients receiving vitamin K antagonists. Participants were allocated to two 6-month sequences (SOC→RPM or RPM→SOC). The intervention consisted of a rule-based chatbot integrated with home-based international normalized ratio self-testing using portable coagulometers to support communication and therapy management. Effectiveness was measured as time in therapeutic range (TTR), and costs were estimated from the Portuguese National Health Service and a limited societal perspective over a 1-year horizon. The analysis (i) applied a within-patient cost-effectiveness approach to estimate incremental costs, incremental TTR, and incremental cost-effectiveness ratios (ICERs). Uncertainty was explored through non-parametric bootstrapping (5,000 replications) and deterministic sensitivity analyses. Complementary comparisons examined differences between sequences (analysis ii), between periods (analysis iii), and within each sequence (analysis iv). RESULTS A total of 19 patients were included in the analyses. In the analysis (i), RPM improved anticoagulation control, with a mean within-patient increase of 10.43 percentage points in time in TTR. The mean incremental costs were €198.61 from the SNS perspective and €270.05 from the limited societal perspective. The corresponding ICERs were €19.03 and €25.88 per additional percentage point of TTR gained. Sensitivity analyses produced consistent estimates across parameter variations. Complementary analyses (ii–iv) suggested that RPM tended to be more cost-effective when implemented after the initial 6-month postoperative period. CONCLUSIONS This proof-of-concept study demonstrates that full trial-based economic evaluation can be feasibly embedded within an early-stage Tier C DHT. The intervention showed improved anticoagulation control alongside higher costs, providing initial insights on its cost-effectiveness profile. Positioned within the digital health evidence continuum, such assessments can function as a learning stage within the lifecycle. To address the persistent adoption–evidence gap, tier- and stage-aligned frameworks are needed to guide the economic evaluation of DHTs. This study contributes to that goal by providing a set of recommendations specifically for Tier C DHTs. CLINICALTRIAL ClinicalTrials.gov NCT06423521
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Santos et al. (2026) studied this question.
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