Cost-effectiveness analysis of chatbot-supported remote patient monitoring for anticoagulation management: health economic evaluation within a pilot crossover trial (Preprint)

Abstract

<sec> <title>BACKGROUND</title> 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. </sec> <sec> <title>OBJECTIVE</title> 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). </sec> <sec> <title>METHODS</title> 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). </sec> <sec> <title>RESULTS</title> 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. </sec> <sec> <title>CONCLUSIONS</title> 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. </sec> <sec> <title>CLINICALTRIAL</title> ClinicalTrials.gov NCT06423521 </sec>

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