Identifying a Cohort of Patients With Early-Stage Breast Cancer
A Comparison of Hospital Discharge and Primary Data
Bibliographic Data
| ID | 9103659 |
|---|---|
| Authors | Jeffrey N Jonkman (0000-0001-6413-7303, Mississippi State University, corresponding author), Sharon‐Lise T Normand (0000-0001-7027-4769, Harvard University), Sharon-Lise T Normand, Robert Wolf (0000-0001-5069-1709), Catherine Borbas (Education & Research Foundation), Edward Guadagnoli (Harvard University) |
| Year | 2001 |
| Volume | 39 |
| Issue | 10 |
| Pages | 1105-1117 |
| Publication date | 2001-10-01 |
| Peer Reviewed | Yes |
| 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 | 10.1097/00005650-200110000-00008 |
| PMID | 11567173 |
| OpenAlex | W2325317077 |
| Language | EN |
| References cited | 24 |
BACKGROUND: Hospital discharge data are a potential source of information for quality of care; however, they lack detailed clinical data. OBJECTIVES: To assess the usefulness of hospital discharge data for describing patterns of care. RESEARCH DESIGN: Cohort study comparing hospital discharge data with data collected from medical records and patients. PATIENTS: Women diagnosed with early-stage breast cancer in Massachusetts and Minnesota (1993-1995). MEASURES: The percentage of patients in the primary data set who did not match a record in the discharge data set, and the percentage of patients in the discharge data set who did not match a record in the primary data set. Odds ratios for appearing in one data set, but not the other according to patient and hospital characteristics. RESULTS: For patients in the primary data set, 26.9% from Massachusetts and 13.2% from Minnesota did not match a record in the discharge data set. In both states, factors associated with failure to match to the discharge data included receipt of breast conserving surgery, shorter length of stay, and treatment hospital. For patients in the discharge data set, 43.4% in Massachusetts and 30.3% in Minnesota did not match a patient in the primary data set. In both states, factors associated with failure to match to the primary data included treatment hospital and the presence of positive lymph nodes. CONCLUSIONS: Hospital discharge data were fairly sensitive when linked to patients with early-stage breast cancer who were identified through hospital records. The discharge data lacked specificity, however. If discharge data are used to characterize patterns care for inpatients with early stage disease, estimates are likely to be inaccurate due to the inclusion of unsuitable patients in the denominator used to calculate procedure rates
Breast cancer · Cancer · Cohort · Data quality · Data set · Hospital discharge · Intensive care medicine · Logistic regression · Medical record · Minimum Data Set · Odds · Operations management · Receipt · Stage (stratigraphy) · Statistics · Breast Cancer Treatment Studies · Computer Science · Emergency Medicine · Global Cancer Incidence and Screening · Internal Medicine · Medicine · Nursing · Patient Satisfaction in Healthcare
Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases
Treating early-stage breast cancer
How Accurate are Hospital Discharge Data for Evaluating Effectiveness of Care
Use of Medicare Hospital and Physician Data to Assess Breast Cancer Incidence
Quality of Hospital Discharge and Physician Data for Type of Breast Cancer Surgery
Minimal Increase in Use of Breast-Conserving Surgery from 1986 to 1990
Dissemination of Clinical Results
Agreement of Medicare Claims and Tumor Registry Data for Assessment of Cancer-Related Treatment
Accuracy and Completeness of Medicare Claims Data for Surgical Treatment of Breast Cancer
The Sensitivity of Medicare Claims Data for Case Ascertainment of Six Common Cancers
| Citation velocity | historical |
|---|---|
| Highly cited | No |