White papers
The financial case for an AI workforce in providers’ revenue cycle operations
AI workforce solutions have shown significant promise in improving efficiency and effectiveness of revenue cycle management teams, who facilitate reimbursement and payments at healthcare providers in the US. In this white paper, we put forward a novel, quantitative framework that will help leaders assess the financial impacts of these solutions.
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Trust through evidence: Evidence generation for AI solutions in healthcare
Evidence standards are not fully established for digital health solutions in general, let alone for the rapidly evolving role of artificial intelligence (AI) in healthcare. This white paper clarifies the unique evidence requirements of AI solutions, and has been written for the benefit of developers, healthcare systems and providers.
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Generating economic evidence for digital health solutions
Economic evidence is arguably the most crucial type of evidence for digital health innovators. It is vital for decision makers to determine whether a digital health solution (DHS) can be funded through investment, adopted by patients and clinicians and reimbursed by payors. It is not currently a standard part of evidence generation in digital health. All major health systems are facing the converging pressures of growing demand for healthcare, increased costs and labour shortages. DHS can be part of the solution, but they need to provide value for money to cash-strapped health systems. Innovators must be able to demonstrate value for money. This white paper explores the need for economic evidence, challenges in generating this type of evidence and how to conduct economic evaluations using different methodologies.
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