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.

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

Results

 

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

Steve Wuench

Steve Wuench  


Senior Manager, Solution Analytics
Healthcare Transformation Services, Philips

 

Steve leads our solutions analytics team which leverages big data and advanced analytics to help hospitals and healthcare systems identify operational and financial performance improvement opportunities. He is experienced in clinical operations, healthcare informatics, healthcare administration, project management, and data analytics. Steve was responsible for implementing revenue cycle workflow management software resulting in a 25% decrease in accounts receivable days by one regional health system. He holds a BBA in economics and finance.

Related capabilities

 

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