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Updated: Jul 6, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Proxy measures for the assessment of psychotic and affective symptoms in studies using electronic health records
Álvaro López-Díaz1, Fernanda Jazmín Palermo-Zeballos2, Luis Gutierrez-Rojas3
1Mental Health Clinical Management Unit, Virgen Macarena University Hospital, Seville, Spain; Translational Psychiatry Research Group (PsyNal), Seville Biomedical Research Centre (IBiS), Spain; Spanish Network for Research in Mental Health, Carlos III Institute (CIBERSAM, ISCIII), Seville, Spain; Department of Psychiatry, School of Medicine, University of Seville, Spain; and First-Episode Psychosis Research Network of Andalusia (Red PEPSur), Spain.
Background:
There is a lack of standardised psychometric data in electronic health record (EHR)-based research. Proxy measures of symptom severity based on patients' clinical records may be useful surrogates in mental health EHR research.
Aims:
This study aimed to validate proxy tools for the short versions of the Positive and Negative Syndrome Scale (PANSS-6), Young Mania Rating Scale (YMRS-6) and Montgomery-Åsberg Depression Rating Scale (MADRS-6).
Method:
A cross-sectional, multicentre study was conducted in a sample of 116 patients with first-episode psychosis from 12 public hospitals in Spain. Concordance between PANSS-6, YMRS-6 and MADRS-6 scores and their respective proxies was evaluated based on information from EHR clinical notes, using a variety of statistical procedures, including multivariate tests to adjust for potential confounders. Bootstrapping techniques were used for internal validation, and an independent cohort from the Treatment and Early Intervention in Psychosis Program (TIPP-Lausanne, Switzerland) for external validation.
Results:
The proxy versions correlated strongly with their respective standardised scales (partial correlations ranged from 0.75 to 0.84) and had good accuracy and discriminatory power in distinguishing between patients in and not in remission (percentage of patients correctly classified ranged from 83.9 to 91.4% and bootstrapped optimism-corrected area under the receiver operating characteristic curve ranged from 0.76 to 0.89), with high interrater reliability (intraclass correlation coefficient of 0.81). The findings remained robust in the external validation data-set.
Conclusions:
The proxy instruments proposed for assessing psychotic and affective symptoms by reviewing EHR provide a feasible and reliable alternative to traditional structured psychometric procedures, and a promising methodology for real-world practice settings.
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