OBJECTIVES: Develop a budget model app estimating financial impact of introduction of heart failure diagnostics program. Present economic model as communication app to inform regional healthcare budgeting and decision making for patients with heart failure disease. METHODS: The model was originally developed in MS Excel and transformed into HTML5 app format for delivery purposes. The model utilizes UK hospital episode statistics as a primary data source. Future healthcare budget projections and extent of savings from introduction of heart failure prevention program are estimated from a payer perspective. Model simulation time horizon is 5 years. Efficacy data was informed from published clinical study demonstrating high accuracy of early testing results of a diagnostic campaign. Sensitivity analysis was conducted to estimate parametric uncertainty around model outcomes. RESULTS: Direct medical cost savings following an introduction of a heart failure prevention program are estimated to be GBP 2,320 per patient. Cost savings in outpatient and inpatient settings were GBP 1,673 and 647 respectively. Sensitivity analyses indicated that efficacy and price of a prevention program had the strongest magnitude of impact on model base case results. CONCLUSIONS: Model estimated that diagnostic heart failure prevention program is a cost-saving intervention. A budget impact model app may effectively inform decision making and regional budget planning as it provides technical ability to modify model inputs during presentation to healthcare payers. An economic model powered with web capabilities and dedicated data visualization libraries provide effective means to convey detailed economic data to healthcare payers and providers.