Inpatient Complexity in Radiology-a Practical Application of the Case Mix Index Metric
| Autor: | Sebastian Flacke, Christoph Wald, Thusitha Dananjaya De Silva Mabotuwana, Christopher S. Hall, Shiby Thomas |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
media_common.quotation_subject Population Staffing 030204 cardiovascular system & hematology Centers for Medicare and Medicaid Services U.S Article 030218 nuclear medicine & medical imaging Tertiary Care Centers 03 medical and health sciences 0302 clinical medicine Case mix index Health care medicine Humans Radiology Nuclear Medicine and imaging education Interventional neuroradiology Diagnosis-Related Groups media_common education.field_of_study Inpatients Radiological and Ultrasound Technology Radiology Department Hospital business.industry Length of Stay Payment United States Computer Science Applications Neuroradiography Radiology Metric (unit) business Medicaid |
| Zdroj: | Journal of digital imaging. 30(3) |
| ISSN: | 1618-727X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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