An Evaluation of Algorithms for Identifying Metastatic Breast, Lung, or Colorectal Cancer in Administrative Claims Data
Bibliographic Data
| ID | 9104402 |
|---|---|
| Authors | Joanna L Whyte (CSL (United States), corresponding author), Nicole M Engel-Nitz, Nicole Engel-Nitz (Optum (United States)), April Teitelbaum (Optum (United States)), Gabriel Gomez Rey (Optum (United States)), Joel D Kallich, Joel Kallich (0000-0002-5016-4703, Amgen (United States)) |
| Year | 2015 |
| Volume | 53 |
| Issue | 7 |
| Pages | e49-e57 |
| Publication date | 2015-07-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/mlr.0b013e318289c3fb |
| PMID | 23524464 |
| OpenAlex | W1975822581 |
| Language | EN |
| Citations received | 2 |
| References cited | 10 |
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 claims data. METHODS: Clinical data on BC, LC, or CRC patients (between January 1, 2007 and March 31, 2010) were linked to a health care claims database. Inclusion required health plan enrollment ≥3 months before initial cancer diagnosis date. Algorithms were used in the claims database to identify patients' disease status, which was compared with physician-reported metastases. Generic and tumor-specific algorithms were evaluated using ICD-9 codes, varying diagnosis time frames, and including/excluding other tumors. Positive and negative predictive values, sensitivity, and specificity were assessed. RESULTS: The linked databases included 14,480 patients; of whom, 32%, 17%, and 14.2% had metastatic BC, LC, and CRC, respectively, at diagnosis and met inclusion criteria. Nontumor-specific algorithms had lower specificity than tumor-specific algorithms. Tumor-specific algorithms' sensitivity and specificity were 53% and 99% for BC, 55% and 85% for LC, and 59% and 98% for CRC, respectively. CONCLUSIONS: Algorithms to distinguish metastatic BC, LC, and CRC from locally advanced disease should use tumor-specific primary cancer codes with 2 claims for the specific primary cancer >30-42 days apart to reduce misclassification. These performed best overall in specificity, positive predictive values, and overall accuracy to identify metastatic cancer in a health care claims database
Algorithm · Breast cancer · Cancer · Colorectal cancer · Diagnosis code · Disease · Family medicine · Health care · Lung cancer · Metastasis · Population · Stage (stratigraphy) · Breast Cancer Treatment Studies · Economic and Financial Impacts of Cancer · Global Cancer Incidence and Screening · Internal Medicine · Medicine · Oncology
| Citations per year | 0.25 |
|---|---|
| Citation span | 2018 - 2019 (2) |
| Highly cited | No |