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- Industry: Healthcare Payers
- Study Type: Insurance Payment and Fraud Study
- Client: A leading Healthcare Consultancy Firm
Background & Key Objectives
- To interpret how healthcare executives experience and strategize around payments in healthcare operations.
- To discover how healthcare organizations leverage artificial intelligence (AI) and machine learning (ML) techniques to aid decision-making and enhance customer experience.
Methodology & Approach
- Rigorous interviews were conducted targeting leaders in Claims Payments in the Healthcare Payer firms across the US, Germany, France, Japan, India, and Singapore.
- Survey was structured as a mix of quantitative and qualitative with an Length of Interview of 30 minutes.
- The survey questionnaire/discussion guide was structured to include the following data points:
- Business strategies to address the current complexities of payment fraud and integrity
- Technology systems currently used to detect and address fraud, waste, and abuse
- Use of AI or other methods, detection of fraud, waste, and abuse in pre-payment and post-payment operations drawing from providers’ payments and consumer payments, etc.
- We deployed a team of specialist healthcare researchers with experience in primary research and data reading/analysis skills.
- Data was shared in Excel/SPSS format
Our Solution
- Our assistance helped the end client comprehend the process of strategizing around healthcare operations payments.
- This study aided the client in understanding the current landscape of payment integrity and fraud analysis by the payers/insurers
- Redefine the current value proposition and operational model across all stakeholders
- Future plans of investment in AI and other tools as part of strategic planning