Accuracy and Complexities of Using Automated Clinical Data for Capturing Chemotherapy Administrations
Implications for Future Research
Bibliographic Data
| ID | 9100736 |
|---|---|
| Authors | Erin J Aiello Bowles (0000-0001-6287-7391, Group Health Cooperative, corresponding author), Leah Tuzzio (0000-0002-3298-904X, Group Health Cooperative, corresponding author), Debra P Ritzwoller (0000-0001-7116-8458, Kaiser Permanente), Andrew E Williams (0000-0002-0908-0364), Tyler Ross (0000-0002-0092-4890, Group Health Cooperative, corresponding author), Edward H Wagner (0000-0001-5856-6021, Health Center, corresponding author), Christine Neslund-Dudas, Christine Neslund‐Dudas (0000-0002-2506-1964, Kaiser Permanente), Andrea Altschuler (0000-0003-3880-0735, Kaiser Permanente), Virginia Quinn, Virginia P Quinn (0000-0002-6476-3336, Kaiser Permanente), Mark Hornbrook, Mark C Hornbrook (0000-0001-6087-0698, Kaiser Permanente Center for Health Research, corresponding author), Larissa Nekhlyudov (0000-0001-6747-4209, Kaiser Permanente) |
| Year | 2009 |
| Volume | 47 |
| Issue | 10 |
| Pages | 1091-1097 |
| Publication date | 2009-10-01 |
| 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/mlr.0b013e3181a7e569 |
| PMID | 19648826 |
| PMCID | PMC2764807 |
| OpenAlex | W2052458682 |
| Language | EN |
| Citations received | 2 |
| References cited | 8 |
BACKGROUND: Chemotherapy data are important to almost any study on cancer prognosis and outcomes. However, chemotherapy data obtained from tumor registries may be incomplete, and abstracting chemotherapy directly from medical records can be expensive and time consuming. METHODS: We evaluated the accuracy of using automated clinical data to capture chemotherapy administrations in a cohort of 757 ovarian cancer patients enrolled in 7 health plans in the HMO Cancer Research Network. We calculated sensitivity and specificity with 95% confidence intervals of chemotherapy administrations extracted from 3 automated clinical data sources (Health Care Procedure Coding System, National Drug Codes, and International Classification of Diseases) compared with tumor registry data and medical chart data. RESULTS: Sensitivity of all 3 data sources varied across health plans from 79.4% to 95.2% when compared with tumor registries, and 75.0% to 100.0% when compared with medical charts. The sensitivities using a combination of 3 data sources were 88.6% (95% confidence intervals: 85.7-91.1) compared with tumor registries and 89.5% (78.5-96.0) compared with medical records; specificities were 91.5% (86.4-95.2) and 90.0% (55.5-99.7), respectively. There was no difference in accuracy between women aged or = 65 years. Using one set of codes alone (eg, Health Care Procedure Coding System alone) was insufficient for capturing chemotherapy data at most health plans. CONCLUSIONS: While automated data systems are not without limitations, clinical codes used in combination are useful in capturing chemotherapy more comprehensively than tumor registry and without the need for costly medical record abstraction. Key Words: validation of automated clinical data, chemotherapy, medical chart, tumor registry, ovarian cancer
Cancer · Cancer registry · Chemotherapy · Clinical trial · Coding (social sciences) · Cohort · Confidence interval · Diagnosis code · Intensive care medicine · Medical record · Statistics · Electronic Health Records Systems · Global Cancer Incidence and Screening · Internal Medicine · Machine Learning in Healthcare · Medicine · Oncology
| Unique citing works | 2 |
|---|---|
| Citations per year | 0,14 |
| Citation span | 2012 - 2016 (5) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |