OBJECTIVE: To evaluate a telephone-operated, interactive voice response (IVR) system designed to collect use-of-care data from patients with major depression (UAC-IVR). STUDY DESIGN: Patient self-reports from repeated IVR surveys were compared with provider records for 3789 patients with major depression at 41 clinical sites participating in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. METHODS: UAC-IVR responses were examined for consistency and compared with provider records to compute reporting biases and intraclass correlation coefficients. Predictors of inconsistent responses and reporting biases were based on mixed logistic and regression models adjusted for need and predisposing and enabling covariates, and corrected for nesting and repeated measures. RESULTS: Inconsistent responses were found for 10% of calls and 21% of patients. Underreporting biases (-20%) and moderate agreement (intraclass correlation of 68%) were found when UAC-IVR responses were compared with medical records. IVR reporting biases were less for patients after 3 calls or more (experience), for patients with severe baseline symptoms (motivation), and for patients who gave consistent IVR responses (reliability). Bias was unrelated to treatment outcomes or demographic factors. CONCLUSION: Clinical managers should use IVR systems to collect service histories only after patients are properly trained and responses monitored for consistency and reporting biases.
OBJECTIVE: To evaluate a telephone-operated, interactive voice response (IVR) system designed to collect use-of-care data from patients with major depression (UAC-IVR). STUDY DESIGN:Patient self-reports from repeated IVR surveys were compared with provider records for 3789 patients with major depression at 41 clinical sites participating in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. METHODS: UAC-IVR responses were examined for consistency and compared with provider records to compute reporting biases and intraclass correlation coefficients. Predictors of inconsistent responses and reporting biases were based on mixed logistic and regression models adjusted for need and predisposing and enabling covariates, and corrected for nesting and repeated measures. RESULTS: Inconsistent responses were found for 10% of calls and 21% of patients. Underreporting biases (-20%) and moderate agreement (intraclass correlation of 68%) were found when UAC-IVR responses were compared with medical records. IVR reporting biases were less for patients after 3 calls or more (experience), for patients with severe baseline symptoms (motivation), and for patients who gave consistent IVR responses (reliability). Bias was unrelated to treatment outcomes or demographic factors. CONCLUSION: Clinical managers should use IVR systems to collect service histories only after patients are properly trained and responses monitored for consistency and reporting biases.
Authors: T Michael Kashner; Madhukar H Trivedi; Annie Wicker; Maurizio Fava; Stephen R Wisniewski; A John Rush Journal: CNS Neurosci Ther Date: 2009-08-27 Impact factor: 5.243
Authors: T Michael Kashner; Madhukar H Trivedi; Annie Wicker; Maurizio Fava; Kathy Shores-Wilson; Stephen R Wisniewski; A John Rush Journal: Int J Methods Psychiatr Res Date: 2009-09 Impact factor: 4.035
Authors: James H Willig; Marc Krawitz; Anantachai Panjamapirom; Midge N Ray; Christa R Nevin; Thomas M English; Mark P Cohen; Eta S Berner Journal: J Med Syst Date: 2013-01-23 Impact factor: 4.460