• 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:
    1. Business strategies to address the current complexities of payment fraud and integrity
    2. Technology systems currently used to detect and address fraud, waste, and abuse
    3. 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
    1. Redefine the current value proposition and operational model across all stakeholders
    2. Future plans of investment in AI and other tools as part of strategic planning