Advances in Research

Background: Recent national surveys indicate that 5% of ambulatory care visits involved patients with mental disorder diagnosis.

Objective: The objective of this study is to demonstrate the use of automated surveillance data for describing the burden of co-morbidity among patients with mental illness.

Methods: We used Emergency Department (ED) visits data from over 650 non-federal hospitals that participated in BioSense from 2008-2011. The variables used in this descriptive analysis are age, gender, and syndromes as defined by BioSense program. The study included only ED visits from people of ≥ 18 years old and with the discharge diagnosis ICD-9-CM codes of mental illness (290 – 312). Co-morbidity was defined broadly as the co-occurrence of other medical condition among patients with mental illness in the same ED visit regardless of the chronological order. We used 89 syndromes as defined by BioSense to identify co-morbid conditions. The percentage was calculated as the number of ED visits with concomitant mental illness associated with co-morbidity divided by the total number of mental illness relevant visits.

Results: From 2008-2011, a total of 4.6 million ED visits (5.4%) reported mental illness out of 85.1 million visits. Among ED visits with concomitant mental illness, the most common co-morbid conditions were cardiovascular (37%), diabetes (11%), and asthma (7%). One third of the broad “other” category was related to chest and abdominal pain co-morbid conditions.

Conclusion: Prevalence and complexity of mental health and co-morbidity underscores the need to prevent, recognize, and address in a timely matter such a serious public health problem. Receiving information quickly using automated data allows local, state, and federal public health decision makers not only to provide timely situational awareness but also monitor healthcare utilization for chronic conditions. BioSense holds large amounts of data that can be utilized for national public health surveillance and practice.