Michael J Hassett
Biographic Data
| ID | 5542631 |
|---|---|
| NAME | Michael J Hassett |
| GIVEN NAMES | Michael J |
| FAMILY NAME | Hassett |
| SIGNATURE | HASSETT M J |
| AFFILIATIONS | Dana-Farber Cancer Institute |
| ORCID | 0000-0003-0754-3510 |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2008 |
| LATEST PUBLICATION YEAR | 2017 |
| H-INDEX | 0 |
Detecting Lung and Colorectal Cancer Recurrence Using Structured Clinical/Administrative Data to Enable Outcomes Research and Population Health Management
INTRODUCTION: Recurrent cancer is common, costly, and lethal, yet we know little about it in community-based populations. Electronic health records and tumor registries contain vast amounts of data regarding community-based patients, but usually lack recurrence status. Existing algorithms that use structured data to detect recurrence have limitations. METHODS: We developed algorithms to detect the presence and timing of recurrence after definitiv…
Validating Billing/Encounter Codes as Indicators of Lung, Colorectal, Breast, and Prostate Cancer Recurrence Using 2 Large Contemporary Cohorts
BACKGROUND: A substantial proportion of cancer-related mortality is attributable to recurrent, not de novo metastatic disease, yet we know relatively little about these patients. To fill this gap, investigators often use administrative codes for secondary malignant neoplasm or chemotherapy to identify recurrent cases in population-based datasets. However, these algorithms have not been validated in large, contemporary, routine care cohorts. OBJEC…
Selecting High Priority Quality Measures For Breast Cancer Quality Improvement
BACKGROUND: Although many quality measures have been created, there is no consensus regarding which are the most important. We sought to develop a simple, explicit strategy for prioritizing breast cancer quality measures based on their potential to highlight areas where quality improvement efforts could most impact a population. METHODS: Using performance data for 9019 breast cancer patients treated at 10 National Comprehensive Cancer Network ins…
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Selecting High Priority Quality Measures For Breast Cancer Quality Improvement
BACKGROUND: Although many quality measures have been created, there is no consensus regarding which are the most important. We sought to develop a simple, explicit strategy for prioritizing breast cancer quality measures based on their potential to highlight areas where quality improvement efforts could most impact a population. METHODS: Using performance data for 9019 breast cancer patients treated at 10 National Comprehensive Cancer Network ins…
Validating Billing/Encounter Codes as Indicators of Lung, Colorectal, Breast, and Prostate Cancer Recurrence Using 2 Large Contemporary Cohorts
BACKGROUND: A substantial proportion of cancer-related mortality is attributable to recurrent, not de novo metastatic disease, yet we know relatively little about these patients. To fill this gap, investigators often use administrative codes for secondary malignant neoplasm or chemotherapy to identify recurrent cases in population-based datasets. However, these algorithms have not been validated in large, contemporary, routine care cohorts. OBJEC…
Detecting Lung and Colorectal Cancer Recurrence Using Structured Clinical/Administrative Data to Enable Outcomes Research and Population Health Management
INTRODUCTION: Recurrent cancer is common, costly, and lethal, yet we know little about it in community-based populations. Electronic health records and tumor registries contain vast amounts of data regarding community-based patients, but usually lack recurrence status. Existing algorithms that use structured data to detect recurrence have limitations. METHODS: We developed algorithms to detect the presence and timing of recurrence after definitiv…
Cancer (3 works) · Global Cancer Incidence and Screening (3 works) · Internal Medicine (3 works) · Internal Medicine (3 works) · Medicine (3 works) · Oncology (3 works) · Oncology (3 works) · Breast cancer (2 works) · Colorectal cancer (2 works) · Computer Science (2 works)