JMIR Publications

ABSTRACT

Background:

Digital tools can identify gaps in guideline-directed medical therapy (GDMT) for heart failure, but detection and prescribing do not establish that patients obtain, safely use, and sustain treatment. Translating digital recommendations into care requires explicit responsibility, coordinated follow-up, and verifiable completion criteria.

Objective:

To propose an operational framework linking digitally identified GDMT opportunities to accountable clinical actions and to distinguish care-process completion from confirmed treatment achievement.

Methods:

We developed this conceptual framework through a narrative synthesis of selected literature on digital decision support, GDMT optimization, team-based heart failure care, and implementation science. We examined the distinction between identifying treatment opportunities, documenting prescriptions, and confirming treatment implementation to formulate episode definitions, team responsibilities, completion criteria, and candidate evaluation measures. A synthetic clinical example illustrates application of the framework. No systematic review, primary data collection, or empirical validation of the framework was undertaken.

Results:

This Viewpoint proposes a patient–drug-class episode that connects each treatment opportunity to an accountable clinician or team, a documented decision, a follow-up plan, and evidence of its outcome. The framework addresses identification, clinical adjudication, treatment initiation, medication acquisition, safety monitoring, and persistence. It distinguishes verified treatment achievement, clinically justified or informed decisions not to proceed, and unresolved care. Candidate measures retain episodes with missing follow-up evidence in baseline opportunity denominators and assess workload, safety, and equity alongside prescribing. Published digital and team-based interventions inform the proposal but do not validate the framework. A synthetic clinical example and two operational tables illustrate its application; no new participant data or empirical evaluation of the framework are reported.

Conclusions:

Closing the digital GDMT loop requires accountable follow-through and evidence of treatment implementation over time. The proposed framework offers testable definitions for prospective evaluation. Its clinical benefit, feasibility, measurement reliability, and equity implications require validation before wider implementation. Clinical Trial: Not applicable. This Viewpoint does not report a clinical trial.