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Inpatient Complexity in Radiology—a Practical Application of the Case Mix Index Metric

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Abstract

With ongoing healthcare payment reforms in the USA, radiology is moving from its current state of a revenue generating department to a new reality of a cost-center. Under bundled payment methods, radiology does not get reimbursed for each and every inpatient procedure, but rather, the hospital gets reimbursed for the entire hospital stay under an applicable diagnosis-related group code. The hospital case mix index (CMI) metric, as defined by the Centers for Medicare and Medicaid Services, has a significant impact on how much hospitals get reimbursed for an inpatient stay. Oftentimes, patients with the highest disease acuity are treated in tertiary care radiology departments. Therefore, the average hospital CMI based on the entire inpatient population may not be adequate to determine department-level resource utilization, such as the number of technologists and nurses, as case length and staffing intensity gets quite high for sicker patients. In this study, we determine CMI for the overall radiology department in a tertiary care setting based on inpatients undergoing radiology procedures. Between April and September 2015, CMI for radiology was 1.93. With an average of 2.81, interventional neuroradiology had the highest CMI out of the ten radiology sections. CMI was consistently higher across seven of the radiology sections than the average hospital CMI of 1.81. Our results suggest that inpatients undergoing radiology procedures were on average more complex in this hospital setting during the time period considered. This finding is relevant for accurate calculation of labor analytics and other predictive resource utilization tools.

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Acknowledgments

The authors would like to acknowledge the contributions of Patricia Doyle (Director of Radiology) and Bruce Ota (Radiology Administrator) for all their support and guidance on this work.

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Authors and Affiliations

  1. Radiology Solutions, Philips Healthcare, 3000 Minuteman Rd, Andover, MA, 01810, USA

    Thusitha Mabotuwana & Christopher S. Hall

  2. Department of Radiology, Lahey Hospital & Medical Center, 41 Burlington Mall Road, Burlington, MA, 01805, USA

    Sebastian Flacke & Christoph Wald

  3. Enterprise Information Technology Department, Lahey Health, 41 Burlington Mall Road, Burlington, MA, 01805, USA

    Shiby Thomas

Authors
  1. Thusitha Mabotuwana
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  2. Christopher S. Hall
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  3. Sebastian Flacke
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  4. Shiby Thomas
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  5. Christoph Wald
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Correspondence to Thusitha Mabotuwana.

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Mabotuwana, T., Hall, C.S., Flacke, S. et al. Inpatient Complexity in Radiology—a Practical Application of the Case Mix Index Metric. J Digit Imaging 30, 301–308 (2017). https://doi.org/10.1007/s10278-017-9944-y

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  • DOI: https://doi.org/10.1007/s10278-017-9944-y

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