Accuracy and complexities of using automated clinical data for capturing chemotherapy administrations: implications for future research.
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 < 65 and > 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.
Aiello Bowles
Erin J
EJ
Group Health Center for Health Studies, Group Health Cooperative, Seattle, Washington 98101, USA. aiello.e@ghc.org
Tuzzio
Leah
L
Ritzwoller
Debra P
DP
Williams
Andrew E
AE
Ross
Tyler
T
Wagner
Edward H
EH
Neslund-Dudas
Christine
C
Altschuler
Andrea
A
Quinn
Virginia
V
Hornbrook
Mark
M
Nekhlyudov
Larissa
L
D000368:Aged; D000970:Antineoplastic Agents / Q000008:administration & dosage*; D016001:Confidence Intervals; D039702:Current Procedural Terminology; D003625:Data Collection / Q000379:methods; D005260:Female; D006279:Health Maintenance Organizations; D006801:Humans; D038801:International Classification of Diseases; D016347:Medical Records Systems, Computerized; D008875:Middle Aged; D010051:Ovarian Neoplasms / Q000188:drug therapy*; D012042:Registries; D012680:Sensitivity and Specificity; D014481:United States
D000970:Antineoplastic Agents