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Reducing avoidable readmissions  using predictive analytics

Facing new demands for readmissions reduction and potential penalties, a large regional medical center was looking to better understand what changes were required to adapt to the new healthcare landscape while continuing to deliver quality patient care across the community.


They turned to Philips for help in lowering readmission rates, avoiding CMS penalties, and enhancing care coordination across the community.

The Philips team completed a comprehensive analysis of the community and state patient data. They provided change recommendations based on best practices and what would be best for the hospital.”

Roger Weems, Vice President and Partner

Healthcare Transformation Services, Philips

Our approach


A collaborative approach is most effective in developing a comprehensive readmissions strategy. Our consultants worked closely with the client staff to help them:


  • Measure readmissions rates
  • Identify root causes of readmissions
  • Generate predictive algorithms to detect high-risk patients
  • Develop a comprehensive readmissions reduction strategy to better manage patient care across the community

The Solution


Our consultants interviewed many stakeholders from the medical center as well as from many of the community care providers. This process provided a strong understanding of the challenges and areas of opportunity. They discussed the patient journey in depth - from pre-treatment education to admission, from treatment and transitions to discharge.


Our data scientists analyzed readmissions data, conducted extensive stakeholder interviews, and applied advanced, predictive analytics and modeling to develop a comprehensive readmissions reduction strategy engaging a broad network of community care providers.

Predictive modeling can help to plan for and manage readmissions risk

predictive modeling diagram



The client embraced the recommended readmissions reduction strategy and initiatives. Project results have been effective and include:


  • The client implemented the readmissions reduction strategy
  • Recommendations were employed by the connected community providers – hospitals, long-term care providers, referral physicians, and others
  • The client expects to lower 30-day readmissions across the entire care system*


* Long-term results are pending.

Meet our team

Becca Dobler

Becca Dobler

Analytics Lead


Becca brings expertise in data analytics and performance improvement in clinical operations, care coordination, patient flow, and care management. She has designed tools to track project benefits, staff accountability, and length of stay reduction.

Tim Oldiges

Tim Oldiges, MBA

Senior Consultant, Analytics


Tim provides data analytics and solution development expertise, helping hospitals identify financial and operational performance improvement opportunities. His experience spans HIE, accountable care solutions, learning management systems, population health reporting, and analytics.

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*Results from case studies are not predictive of results in other cases. Results in other cases may vary.

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