National Cancer Institute
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Outcomes Research Branch
Cancer Control and Population Sciences


Simulation Modeling to Set Priorities for the Development of Cancer Quality Measures

This project, a component of the Cancer Quality of Care Measures Project, uses simulation modeling to set priorities in the development of quality of care measures for colorectal cancer diagnosis and treatment. Dr. Karen Kuntz (Associate Professor of Decision Science, Harvard School of Public Health) will be primary modeler for this project. Dr. Kuntz has previously collaborated with NCI in developing a CISNET colorectal cancer simulation model. This model mapped key clinical processes that contribute to improved survival among stage I-III colorectal cancer patients:

  • Patients initially diagnosed with stage I-III cancer face a monthly risk of developing metastatic recurrence, which is a function of age at diagnosis, stage, and whether or not the patient received adjuvant chemotherapy.
  • Patients who develop metastatic recurrence have a chance that their metastasis is rescectable, which is a function of whether or not they were receiving post-treatment surveillance.
  • Patients with resectable metastases who are successfully resected and thus have no evidence of disease (NED) face a monthly risk of progressing to nonresectable metatatic disease. This risk is a function of whether or not the patients received chemotherapy following resection.
  • Patients with non-resectable metastatic disease face a cancer-specific hazard rate, which is a function of age at nonresectable metastases and whether or not the patient received chemotherapy following the diagnosis of nonresectable metastases.

In this project, Outcomes Research staff worked with Dr. Kuntz to focus primarily on mapping clinical processes around effectiveness of care. Dr. Kuntz modified the existing simulation model to provide estimates of the contribution of four processes, or nodes, to improved cancer outcomes. She identified those nodes that have a potential for net positive impact on survival or mortality and rank ordered them by degree of impact and improvement potential (i.e., the difference between current practice and optimal practice). Current practice was based on analyses of SEER and SEER-Medicare linked data. Optimal practice was based on reasonable estimates of maximal diffusion of care. The simulation modeling found that process improvement in the receipt of adjuvant chemotherapy after surgery and the receipt of chemotherapy following the diagnosis of nonresectable metastatic disease provided the greatest potential for improving survival for this population. Post-treatment surveillance contributed little to survival within the model.

Last modified:
08 Jan 2008
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