Community Mental Health Center Integrated Care Outcomes.

Despite the compelling logic for integrating care for people with serious mental illness, there is also need for quantitative evidence of results. This retrospective analysis used 2013-2015 data from seven community mental health centers to measure clinical processes and health outcomes for patients receiving integrated primary care (n = 18,505), as well as hospital use for the 3943 patients with hospitalizations during the study period. Bivariate and regression analyses tested associations between integrated care and preventive screening rates, hemoglobin A1c levels, and hospital use. Screening rates for body-mass index, blood pressure, smoking, and hemoglobin A1c all increased very substantially during integrated care. More than half of patients with baseline hypertension had this controlled within 90 days of beginning integrated care. Among patients hospitalized at any point during the study period, the probability of hospitalization in the first year of integrated care decreased by 18 percentage points, after controlling for other factors such as patient severity, insurance status, and demographics (p < .001). The average length of stay was also 32% shorter compared to the year prior to integrated care (p < .001). Savings due to reduced hospitalization frequency alone exceeded $1000 per patient. Data limitations restricted this study to a pre-/post-study design. However, the magnitude and consistency of findings across different outcomes suggest that for people with serious mental illness, integrated care can make a significant difference in rates of preventive care, health, and cost-related outcomes.

Domain Analysis of Integrated Data to Reduce Cost Associated with Liver Disease.

Liver cancer, the fifth most common cancer and second leading cause of cancer-related death among men worldwide, is plagued by not only lack of clinical research, but informatics tools for early detection. Consequently, it presents a major health and cost burden. Among the different types of liver cancer, hepatocellular carcinoma (HCC) is the most common and deadly form, arising from underlying liver disease. Current models for predicting risk of HCC and liver disease are limited to clinical data. A domain analysis of existing research related to screening for HCC and liver disease suggests that metabolic syndrome (MetS) may present oppportunites to detect early signs of liver disease. The purpose of this paper is to (i) provide a domain analysis of the relationship between HCC, liver disease, and metabolic syndrome, (ii) a review of the current disparate sources of data available for MetS diagnosis, and (iii) recommend informatics solutions for the diagnosis of MetS from available administrative (Biometrics, PHA, claims) and laboratory data, towards early prediction of liver disease. Our domain analysis and recommendations incorporate best practices to make meaningful use of available data with the goal of reducing cost associated with liver disease.