Chart validation of inpatient ICD-9-CM administrative diagnosis codes for acute myocardial infarction (AMI) among intravenous immune globulin (IGIV) users in the Sentinel Distributed Database.

BACKGROUND

The Sentinel Distributed Database (SDD) is a large database of patient-level administrative health care records, primarily derived from insurance claims and electronic health records, and is sponsored by the US Food and Drug Administration for medical product safety evaluations. Acute myocardial infarction (AMI) is a common study endpoint for drug safety studies that rely on health records from the SDD and other administrative databases.

PURPOSE: In this chart validation study, we report on the positive predictive value (PPV) of inpatient International Classification of Diseases, Ninth Revision, Clinical Modification AMI administrative diagnosis codes (410.x1 and 410.x0) in the SDD.

METHODS

As part of an assessment of thromboembolic adverse event risk following treatment with intravenous immune globulin, charts were obtained for 103 potential post-intravenous immune globulin AMI cases. Charts were abstracted by trained nurses and physician-adjudicated based on prespecified diagnostic criteria.

RESULTS

Acute myocardial infarction status could be determined for 89 potential cases. The PPVs for the inpatient AMI diagnoses recorded in the SDD were 75% overall (95% CI, 65-84%), 93% (95% CI, 78-99%) for principal-position diagnoses, 88% (95% CI, 72-97%) for secondary diagnoses, and 38% (95% CI, 20-59%) for position-unspecified diagnoses (eg, diagnoses originating from separate physician claims associated with an inpatient stay). Of the confirmed AMI cases, demand ischemia was the suspected etiology more often for those coded in secondary or unspecified positions (72% and 40%, respectively) than for principal-position AMI diagnoses (21%).

CONCLUSIONS

The PPVs for principal and secondary AMI diagnoses were high and similar to estimates from prior chart validation studies. Position-unspecified diagnosis codes were less likely to represent true AMI cases.