Joel D Kallich
Biographic Data
| ID | 5541678 |
|---|---|
| NAME | Joel D Kallich |
| GIVEN NAMES | Joel D |
| FAMILY NAME | Kallich |
| SIGNATURE | KALLICH J D |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2001 |
| LATEST PUBLICATION YEAR | 2015 |
| H-INDEX | 0 |
An Evaluation of Algorithms for Identifying Metastatic Breast, Lung, or Colorectal Cancer in Administrative Claims Data
BACKGROUND: Administrative health care claims data are used for epidemiologic, health services, and outcomes cancer research and thus play a significant role in policy. Cancer stage, which is often a major driver of cost and clinical outcomes, is not typically included in claims data. OBJECTIVES: Evaluate algorithms used in a dataset of cancer patients to identify patients with metastatic breast (BC), lung (LC), or colorectal (CRC) cancer using c…
Imputing Physical Health Status Scores Missing Owing to Mortality
BACKGROUND: Having missing data complicates the statistical analysis of health-related quality-of-life (HRQOL) data and, depending on the extent and nature of missing data, can introduce significant bias in treatment comparisons. OBJECTIVE: We evaluated the bias associated with 4 different imputation methods for estimating physical health status (PHS) scores missing as a result of mortality. METHODS: A simulation study was conducted in which we s…
No prominent works on this page.
Imputing Physical Health Status Scores Missing Owing to Mortality
BACKGROUND: Having missing data complicates the statistical analysis of health-related quality-of-life (HRQOL) data and, depending on the extent and nature of missing data, can introduce significant bias in treatment comparisons. OBJECTIVE: We evaluated the bias associated with 4 different imputation methods for estimating physical health status (PHS) scores missing as a result of mortality. METHODS: A simulation study was conducted in which we s…
An Evaluation of Algorithms for Identifying Metastatic Breast, Lung, or Colorectal Cancer in Administrative Claims Data
BACKGROUND: Administrative health care claims data are used for epidemiologic, health services, and outcomes cancer research and thus play a significant role in policy. Cancer stage, which is often a major driver of cost and clinical outcomes, is not typically included in claims data. OBJECTIVES: Evaluate algorithms used in a dataset of cancer patients to identify patients with metastatic breast (BC), lung (LC), or colorectal (CRC) cancer using c…
Medicine (2 works) · Advanced Causal Inference Techniques (1 work) · Algorithm (1 work) · Breast cancer (1 work) · Breast Cancer Treatment Studies (1 work) · Cancer (1 work) · Chronic Disease Management Strategies (1 work) · Colorectal cancer (1 work) · Diagnosis code (1 work) · Disease (1 work)