Evaluation of algorithms to identify delirium in administrative claims and drug utilization database.

PURPOSE: To evaluate the performance of delirium-identification algorithms in administrative claims and drug utilization data.
METHODS: We used data from a prospective study of 184 older adults who underwent aortic valve replacement at a single academic medical center to evaluate the following delirium-identification algorithms: (1) International Classification of Diseases (ICD) diagnosis codes for delirium; (2) antipsychotics use; (3) either ICD diagnosis codes or antipsychotics use; and (4) both ICD diagnosis codes and antipsychotics use. These algorithms were evaluated against a validated bedside assessment, the Confusion Assessment Method, and a validated delirium severity scale, the CAM-S.
RESULTS: Delirium occurred in 66 patients (36%), of which 14 (21%) had hyperactive or mixed features and 15 (23%) had severe delirium. ICD diagnosis codes for delirium were present in 15 patients (8%). Antipsychotics were used in 13 patients (7%). ICD diagnosis codes alone and antipsychotics use alone had comparable sensitivity (18% vs. 18%) and specificity (98% vs. 99%). Defining delirium using either ICD diagnosis codes or antipsychotics use, sensitivity improved to 30% with little change in specificity (97%). This algorithm showed higher sensitivity for hyperactive or mixed delirium (64%) and severe delirium (73%). Requiring both ICD diagnosis codes and antipsychotics use resulted in perfect specificity but low sensitivity (6%).
CONCLUSION: Delirium-identification algorithms in claims data have low sensitivity and high specificity. Defining delirium using ICD diagnosis codes or antipsychotics use performs better than considering either type of information alone. This information should inform the design and interpretation of claims-based comparative effectiveness and safety research.