TY - JOUR
T1 - Chart validation of inpatient ICD-9-CM administrative diagnosis codes for ischemic stroke among IGIV users in the Sentinel Distributed Database
AU - Ammann, Eric M.
AU - Leira, Enrique C.
AU - Winiecki, Scott K.
AU - Nagaraja, Nandakumar
AU - Dandapat, Sudeepta
AU - Carnahan, Ryan M.
AU - Schweizer, Marin L.
AU - Torner, James C.
AU - Fuller, Candace C.
AU - Leonard, Charles E.
AU - Garcia, Crystal
AU - Pimentel, Madelyn
AU - Chrischilles, Elizabeth A.
N1 - Funding Information:
Editor: Nan Liu. Funding/support: The results reported herein correspond to the objectives of Mini-Sentinel contract HHSF223200910006I from the U.S. Food and Drug Administration (FDA) and Department of Health and Human Services (HHS). This work was also supported by the Sentinel Coordinating Center, which is funded by the FDA through HHS contract number HHSF223201400030I. Reproducibility: The data files and SAS code used to produce the results presented in this paper were reviewed and verified by the programming staff at the Sentinel Coordinating Center. The SAS code is available upon request from the corresponding author. For legal reasons, the individual-level patient data that served as the basis for our results are not available for public distribution.
Publisher Copyright:
© 2017 the Author(s). Published by Wolters Kluwer Health, Inc.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - The Sentinel Distributed Database (SDD) is a large database of patient-level medical and prescription records, primarily derived from insurance claims and electronic health records, and is sponsored by the U.S. Food and Drug Administration for drug safety assessments. In this chart validation study, we report on the positive predictive value (PPV) of inpatient ICD-9-CM acute ischemic stroke (AIS) administrative diagnosis codes (433.x1, 434.xx, and 436) in the SDD. As part of an assessment of the risk of thromboembolic adverse events following treatment with intravenous immune globulin (IGIV), charts were obtained for 131 potential post-IGIV AIS cases. Charts were abstracted by trained nurses and then adjudicated by stroke experts using pre-specified diagnostic criteria. Case status could be determined for 128 potential AIS cases, of which 34 were confirmed. The PPVs for the inpatient AIS diagnoses recorded in the SDD were 27% overall [95% confidence interval (95% CI): 19-35], 60% (95% CI: 32-84) for principal-position diagnoses, 42% (95% CI: 28-57) for secondary diagnoses, and 6% (95% CI: 2-15) for position-unspecified diagnoses (which in the SDD generally originate from separate physician claims associated with an inpatient stay). Position-unspecified diagnoses were unlikely to represent true AIS cases. PPVs for principal and secondary inpatient diagnosis codes were higher, but still meaningfully lower than estimates from prior chart validation studies. The low PPVs may be specific to the IGIV user study population. Additional research is needed to assess the validity of AIS administrative diagnosis codes in other study populations within the SDD.
AB - The Sentinel Distributed Database (SDD) is a large database of patient-level medical and prescription records, primarily derived from insurance claims and electronic health records, and is sponsored by the U.S. Food and Drug Administration for drug safety assessments. In this chart validation study, we report on the positive predictive value (PPV) of inpatient ICD-9-CM acute ischemic stroke (AIS) administrative diagnosis codes (433.x1, 434.xx, and 436) in the SDD. As part of an assessment of the risk of thromboembolic adverse events following treatment with intravenous immune globulin (IGIV), charts were obtained for 131 potential post-IGIV AIS cases. Charts were abstracted by trained nurses and then adjudicated by stroke experts using pre-specified diagnostic criteria. Case status could be determined for 128 potential AIS cases, of which 34 were confirmed. The PPVs for the inpatient AIS diagnoses recorded in the SDD were 27% overall [95% confidence interval (95% CI): 19-35], 60% (95% CI: 32-84) for principal-position diagnoses, 42% (95% CI: 28-57) for secondary diagnoses, and 6% (95% CI: 2-15) for position-unspecified diagnoses (which in the SDD generally originate from separate physician claims associated with an inpatient stay). Position-unspecified diagnoses were unlikely to represent true AIS cases. PPVs for principal and secondary inpatient diagnosis codes were higher, but still meaningfully lower than estimates from prior chart validation studies. The low PPVs may be specific to the IGIV user study population. Additional research is needed to assess the validity of AIS administrative diagnosis codes in other study populations within the SDD.
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U2 - 10.1097/MD.0000000000009440
DO - 10.1097/MD.0000000000009440
M3 - Article
C2 - 29384925
AN - SCOPUS:85039418392
SN - 0025-7974
VL - 96
JO - Medicine (United States)
JF - Medicine (United States)
IS - 52
ER -