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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Nov 14, 2025
Open Peer Review Period: Nov 17, 2025 - Jan 12, 2026
Date Accepted: Jun 1, 2026
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Cost-Effectiveness Analysis of Chatbot-Supported Remote Patient Monitoring for Anticoagulation Management: Health Economic Evaluation Within a Pilot Crossover Trial

Santos AR, Sampaio F, Guede-Fernandez F, Perelman J, Londral AR

Cost-Effectiveness Analysis of Chatbot-Supported Remote Patient Monitoring for Anticoagulation Management: Health Economic Evaluation Within a Pilot Crossover Trial

J Med Internet Res 2026;28:e85430

DOI: 10.2196/85430

PMID: 42308519

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

  • Ana Rita Santos; 
  • Filipa Sampaio; 
  • Federico Guede-Fernandez; 
  • Julian Perelman; 
  • Ana Rita Londral

ABSTRACT

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. Clinical Trial: ClinicalTrials.gov NCT06423521


 Citation

Please cite as:

Santos AR, Sampaio F, Guede-Fernandez F, Perelman J, Londral AR

Cost-Effectiveness Analysis of Chatbot-Supported Remote Patient Monitoring for Anticoagulation Management: Health Economic Evaluation Within a Pilot Crossover Trial

J Med Internet Res 2026;28:e85430

DOI: 10.2196/85430

PMID: 42308519

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