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.

Importance

Skin cancer is the most common malignancy occurring after organ transplantation. Although previous research has reported an increased risk of skin cancer in solid organ transplant recipients (OTRs), no study has estimated the posttransplant population-based incidence in the United States.

Objective

To determine the incidence and evaluate the risk factors for posttransplant skin cancer, including squamous cell carcinoma (SCC), melanoma (MM), and Merkel cell carcinoma (MCC) in a cohort of US OTRs receiving a primary organ transplant in 2003 or 2008.

Design, Setting, and Participants

This multicenter retrospective cohort study examined 10 649 adult recipients of a primary transplant performed at 26 centers across the United States in the Transplant Skin Cancer Network during 1 of 2 calendar years (either 2003 or 2008) identified through the Organ Procurement and Transplantation Network (OPTN) database. Recipients of all organs except intestine were included, and the follow-up periods were 5 and 10 years.

Main Outcomes and Measures

Incident skin cancer was determined through detailed medical record review. Data on predictors were obtained from the OPTN database. The incidence rates for posttransplant skin cancer overall and for SCC, MM, and MCC were calculated per 100 000 person-years. Potential risk factors for posttransplant skin cancer were tested using multivariate Cox regression analysis to yield adjusted hazard ratios (HR).

Results

Overall, 10 649 organ transplant recipients (mean [SD] age, 51 [12] years; 3873 women [36%] and 6776 men [64%]) contributed 59 923 years of follow-up. The incidence rates for posttransplant skin cancer was 1437 per 100 000 person-years. Specific subtype rates for SCC, MM, and MCC were 812, 75, and 2 per 100 000 person-years, respectively. Statistically significant risk factors for posttransplant skin cancer included pretransplant skin cancer (HR, 4.69; 95% CI, 3.26-6.73), male sex (HR, 1.56; 95% CI, 1.34-1.81), white race (HR, 9.04; 95% CI, 6.20-13.18), age at transplant 50 years or older (HR, 2.77; 95% CI, 2.20-3.48), and being transplanted in 2008 vs 2003 (HR, 1.53; 95% CI, 1.22-1.94).

Conclusions and Relevance

Posttransplant skin cancer is common, with elevated risk imparted by increased age, white race, male sex, and thoracic organ transplantation. A temporal cohort effect was present. Understanding the risk factors and trends in posttransplant skin cancer is fundamental to targeted screening and prevention in this population.