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Predicting Infusion Staffing with Acuity Metrics: Is "The Juice Worth the Squeeze"?


Pamela Tobias
MS, RHIA, CHDA Director of Customer Success, iQueue for Infusion Centers LeanTaaS


Accurately predicting infusion staffing needs is crucial to providing optimal care and maintaining high standards of patient safety.  Oncology infusion centers face unique staffing challenges, however, as patient acuity and related staffing needs can fluctuate rapidly. To address this challenge, infusion centers often utilize patient acuity measures to inform their staffing predictions. But acuity alone may not be the most effective measure. 

As part of their initiative to meet customer requests and optimize their AI-powered iQueue for Infusion Centers solution for actual infusion center needs, data analysis experts and infusion center operations leaders from LeanTaaS created an in-depth study to determine the true effectiveness of patient acuity as a staffing metric. They began with the hypothesis that acuity would be better at predicting the number of nurses needed for adequate daily staffing over visits or hours. Using data from several participating customer infusion centers, they evaluated patient acuity against patient visits and hours for staffing predictions, wait times, and nurse lunch breaks. 

In this session, the Director of Customer Success for iQueue for Infusion Centers presents a deep dive into thus outcomes from a multi-institute, head-to-head research study of three acuity methodologies. Learn which methodology stood out as the most impactful – if any – and take away best future practices for infusion staffing based on those results.

Viewers of this webinar will be able to: 

  • Explain how staffing challenges faced by oncology infusion centers relate to fluctuating patient acuity
  • Analyze the effectiveness of using patient acuity, visits, and hours as metrics to predict infusion center staffing needs
  • Assess the outcomes of LeanTaaS’ research comparing different methodologies for forecasting infusion staffing requirements


Little evidence found to recommend acuity-based staffing predictions
Need for predictive support and tools to optimize daily infusion staffing for today and in the future
We can predict that the nurses will say the day was adequately staffed, the wait times were in an acceptable range, and all of the nurses will get to lunch. And ultimately if we can predict that, then we can make recommendations on what to change to achieve that desired outcome if we are in an unacceptable range.
Pamela Tobias, MS, RHIA, CHDA
Director of Customer Success, Infusion LeanTaaS

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