In the rapidly evolving landscape of healthcare, digital health technologies are becoming increasingly integral. These technologies, ranging from digital therapeutics to wearable health monitors and AI-driven diagnostic tools, promise to revolutionize patient care, improve outcomes, and enhance the efficiency of healthcare delivery.
However, alongside their potential benefits comes the necessity for rigorous economic evaluation to ensure their sustainable integration into healthcare systems. Due to the variety in digital health technologies the scope of an evaluation will vary depending on the product, and the NICE Evidence Standards Framework provides a comprehensive overview of the evidence requirements (see our article). Regardless of the required evidence standards, Budget Impact Models (BIMs) are often required as they provide a critical tool for healthcare policymakers and providers when analysing the expected changes in the health expenditure of the budget holder of implementing a digital product.
Understanding Budget Impact Models
A BIM is a financial analysis tool designed to estimate the economic implications of adopting a new healthcare intervention within a specific budget context. Unlike cost-effectiveness analysis, which focuses on the value derived from healthcare interventions in terms of cost per quality-adjusted life year (QALY) gained, BIMs are concerned with only budgetary impact required for the implementation of new technologies. They provide a framework for projecting the affordability and fiscal feasibility of new interventions over a defined period, considering various factors such as population demographics, disease prevalence, and existing healthcare practices.
The Necessity of BIMs in Digital Health
Cost Management and Allocation: Digital health technologies often require substantial initial investments for development, deployment, and maintenance. BIMs help healthcare providers and policymakers to anticipate these costs and plan budgets accordingly. By forecasting expenses and potential savings, BIMs ensure that financial resources are allocated efficiently, preventing budget overruns and ensuring the long-term viability of digital health projects.
Evidence-Based Decision Making: The adoption of digital health technologies should be grounded in robust evidence. BIMs provide a detailed financial analysis that aids decision-makers in understanding the economic implications of new technologies. This evidence-based approach helps justify investments in digital health by demonstrating their potential financial benefits and sustainability.
Assessment of Financial Risks and Benefits: Implementing new digital health technologies involves financial risks, including potential unforeseen costs and variable adoption rates among patients and healthcare providers. BIMs help identify and quantify these risks, offering insights into potential financial benefits such as reduced hospital admissions, shorter lengths of stay, and improved patient outcomes. This comprehensive assessment ensures that stakeholders are well-informed about the economic impact of their decisions.
Scalability and Adaptability: Healthcare systems vary widely in terms of resources, population needs, and existing infrastructure. BIMs are adaptable tools that can be customized to reflect the specific conditions of different healthcare markets. This scalability makes them invaluable for assessing the budget impact of digital health technologies across diverse settings, ensuring that these innovations can be effectively scaled to meet local needs.
Facilitating Stakeholder Engagement: The successful implementation of digital health technologies requires collaboration among various stakeholders, including healthcare providers, payers, policymakers, and patients. BIMs facilitate transparent communication by providing a clear, quantifiable picture of the financial implications of new technologies. This transparency fosters trust and cooperation among stakeholders, promoting a shared commitment to the successful adoption of digital health solutions.
Regulatory and Reimbursement Considerations: For digital health technologies to be widely adopted, they must be supported by appropriate regulatory frameworks and reimbursement policies. BIMs provide the economic data necessary to influence policy decisions and secure funding from payers. By demonstrating the budgetary feasibility and potential cost savings of new technologies, BIMs play a crucial role in shaping supportive policies and reimbursement strategies.
Summary
As digital health technologies continue to transform healthcare, the importance of budget impact models cannot be overstated to demonstrate the potential budgetary benefit they can have to a healthcare system. By supporting cost management, evidence-based decision-making, risk assessment, scalability, stakeholder engagement, and regulatory considerations, BIMs are essential tools for the successful integration of digital health innovations into healthcare systems. Ensuring their use will help realize the full potential of digital health technologies to improve patient care and optimize healthcare delivery.
DHT.health can support digital health technology innovators to build budget impact models to demonstrate the budgetary benefit of their products. We provide an end-to-end service in which we can also assess the existing evidence, generate any additional evidence required to populate the model and also communicate the findings of such research.
Related Links:
NICE Evidence Standards Framework: https://www.nice.org.uk/about/what-we-do/our-programmes/evidence-standards-framework-for-digital-health-technologies
NHS BIM Development: https://innovation.nhs.uk/innovation-guides/development/budget-impact-model/
Jamshidi HR, et al. "Budget impact analyses": a practical policy making tool for drug reimbursement decisions: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177634/
Budget impact analysis: health economic studies (GOV.COM Guidance): https://www.gov.uk/guidance/budget-impact-analysis-health-economic-studies