Case mix
Hospital Operations
Definition. Case mix is the composition of the patients treated by a provider in terms of their diagnoses, severity and resource needs.
Explanation
Case mix is measured with patient classification systems, most commonly diagnosis-related groups, which group patients with similar clinical characteristics and expected resource use (Fetter et al., 1980). Each group carries a weight, and the average weight is the provider’s case mix index.
Case mix is used to set prospective payments, to compare costs and lengths of stay fairly between hospitals and to adjust quality indicators for risk. Busse et al. (2011) note that classification systems also create incentives for upcoding and for selecting profitable patients, which payers must monitor.
Related concepts
Length of stay Quality indicator Benchmarking
Read on The Health Topics
- Predictive Quality: An Introduction 101
- Resource, Quality and Data-Driven Management in the Oncology Hospital: An Introduction (101) for Physicians
- How to Use Directed Acyclic Graphs (DAGs): A Guide for Health Management Researchers
- Intensive Care Costs Across Four European Countries
- Variable Taxonomy in Oncology Operations and Management Research: Roles, Relationships and Effects
- The Capacity Problem in Oncology and How to Solve It
References
Busse, R., Geissler, A., Quentin, W., & Wiley, M. (Eds.). (2011). Diagnosis-related groups in Europe: Moving towards transparency, efficiency and quality in hospitals. Open University Press.
Fetter, R. B., Shin, Y., Freeman, J. L., Averill, R. F., & Thompson, J. D. (1980). Case mix definition by diagnosis-related groups. Medical Care, 18(2 Suppl), 1–53.
Cite this entry: Kurutkan, M. N. (2026). Case mix. In The Health Topics glossary. https://healthtopic.org/glossary/case-mix/
Articles that discuss this concept
9 articles on The Health Topics use this concept. The list updates as new articles are published.
- How to Use Directed Acyclic Graphs (DAGs): A Guide for Health Management Researchers 3
- Resource, Quality and Data-Driven Management in the Oncology Hospital: An Introduction (101) for Physicians 2
- Epidemiology of Healthcare Quality: Key Insights & Impacts 1
- Regression Methodology for ROC Curve Estimation 1
- Transforming Electronic Health Records into Predictive Tools 1
- Medical AI’s 97 Percent Lie: The story of the driving school “champion” 1
- Managing an Oncology Hospital as a System: Patient Journey, Process, Bottleneck and Capacity 1
- The Capacity Problem in Oncology and How to Solve It 1
- Variable Taxonomy in Oncology Operations and Management Research: Roles, Relationships and Effects 1