Conducting population behavioral health surveillance by using automated diagnostic and pharmacy data systems.

INTRODUCTION

The Walter Reed Army Institute of Research used the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) to conduct population-based behavioral health surveillance among military-health-system beneficiaries. The study analyzed the effectiveness of using prescribing patterns of psychotropic medications to monitor changes in a community's behavioral health status.

OBJECTIVES

The objectives of this study were to 1) determine the feasibility of tracking psychiatric illnesses by monitoring prescriptions for psychiatric medications; 2) assess how often psychiatric medications are prescribed for patients with no record of psychiatric illness; 3) determine at what types of clinics these medications are prescribed most often and what other diagnoses are attributed to these patients; and 4) analyze data for potential changes in the population's mental health after high-stress events.

METHODS

Correlation analysis and calculations of sensitivity and specificity were used to determine how well prescription medications correlate with outpatient diagnoses and how well they serve as proxies for outpatient diagnoses. A descriptive analysis was conducted of the types of clinics (e.g., primary care, behavioral health, or other specialty clinics) treating patients and the associated percentage of concurrence between prescriptions and diagnostic codes.

RESULTS

In military treatment facilities, a diagnosis of depression or anxiety correlated significantly (r = 0.82) with antidepressant or anxiolytic prescriptions. Sensitivity of prescriptions when compared with outpatient visits was 0.76, and specificity was 0.94. Among those patients who visited a primary care clinic either the day before or the same day as an antidepressant or anxiolytic prescription was filled, 60.1% did not receive a diagnosis of any mental health disorder. Behavioral health clinics had the highest correlation between diagnoses and prescriptions; specialty clinics had the lowest.

CONCLUSIONS

Behavioral health trends in a population can be monitored by automated analysis of prescribing patterns alone. This method might be a rapid indicator of needed mental health interventions after acute stress-inducing events and be more sensitive than tracking diagnoses alone.