Publications

OBJECTIVE

Although primary care is associated with better outcomes, many individuals with serious mental illness do not receive general medical services. This study examined patient-level factors associated with not having outpatient general medical visits among individuals with serious mental illness in California.

METHODS

The study analyzed administrative, pharmacy, and billing data for 56,895 Medicaid-enrolled adults with serious mental illness treated in community mental health clinics between October 1, 2010, and September 20, 2011. Poisson regression estimated independent associations between predictor variables and outpatient general medical visits.

RESULTS

One-third of participants (34%) had no outpatient general medical visits during the study. In multivariate analyses, younger adults (ages 18-27) were less likely than older groups to have such a visit (adjusted relative risk [ARR]=1.07 and 1.19, respectively, for ages 28-47 and 48-67). Women were more likely than men to have such a visit (ARR=1.29). Compared with whites, blacks were less likely to have an outpatient general medical visit (ARR=.93). Rural dwellers were less likely than urban dwellers to have such a visit (ARR=.64). Persons with drug or alcohol use disorders were less likely than those without such disorders to have an outpatient general medical visit (ARR=.95), and those with schizophrenia were less likely than those with any other psychiatric disorder examined to have such a visit.

CONCLUSIONS

Individuals with serious mental illness had low use of outpatient general medical services. Integrated care models are needed to engage these individuals and eliminate disparities in morbidity and mortality.

BACKGROUND

Ascertainment of hospitalizations is critical to assess quality of care and the effectiveness and adverse effects of various therapies. Smartphones, mobile geolocators that are ubiquitous, have not been leveraged to ascertain hospitalizations. Therefore, we evaluated the use of smartphone-based geofencing to track hospitalizations.

METHODS AND RESULTS

Participants aged ≥18 years installed a mobile application programmed to geofence all hospitals using global positioning systems and cell phone tower triangulation and to trigger a smartphone-based questionnaire when located in a hospital for ≥4 hours. An in-person study included consecutive consenting patients scheduled for electrophysiology and cardiac catheterization procedures. A remote arm invited Health eHeart Study participants who consented and engaged with the study via the internet only. The accuracy of application-detected hospitalizations was confirmed by medical record review as the reference standard. Of 22 eligible in-person patients, 17 hospitalizations were detected (sensitivity 77%; 95% confidence interval, 55%-92%). The length of stay according to the application was positively correlated with the length of stay ascertained via the electronic medical record (=0.53; =0.03). In the remote arm, the application was downloaded by 3443 participants residing in all 50 US states; 243 hospital visits at 119 different hospitals were detected through the application. The positive predictive value for an application-reported hospitalization was 65% (95% confidence interval, 57%-72%).

CONCLUSIONS

Mobile application-based ascertainment of hospitalizations can be achieved with modest accuracy. This first proof of concept may ultimately be applicable to geofencing other types of prespecified locations to facilitate healthcare research and patient care.

Food insecurity (FI) is a documented problem associated with adverse health outcomes among HIV-infected populations. Little is known about the relationship between alcohol use and FI. We assessed whether heavy alcohol use was associated with FI among HIV-infected, antiretroviral therapy (ART)-naïve cohorts in Uganda and Russia. Inverse probability of treatment weighted logistic regression models were used to evaluate the association using cross-sectional baseline data. FI was experienced by half of the Russia cohort (52 %) and by a large majority of the Uganda cohort (84 %). We did not detect an association between heavy alcohol use and FI in either cohort (Russia: AOR = 0.80, 95 % CI 0.46, 1.40; Uganda: AOR = 1.00, 95 % CI 0.57, 1.74) or based on the overall combined estimate (AOR = 0.89, 95 % CI 0.60, 1.33). Future studies should explore the determinants of FI in HIV-infected populations to inform strategies for its mitigation.