Predictors of Use of Monitored Anesthesia Care for Outpatient Gastrointestinal Endoscopy in a Capitated Payment System.

BACKGROUND & AIMS: Use of monitored anesthesia care (MAC) for gastrointestinal endoscopy has increased in the Veterans Health Administration (VHA) as in fee-for-service environments, despite the absence of financial incentives. We investigated factors associated with use of MAC in an integrated health care delivery system with a capitated payment model. METHODS: We performed a retrospective cohort study using multilevel logistic regression, with MAC use modeled as a function of procedure year, patient- and provider-level factors, and facility effects. We collected data from 2,091,590 veterans who underwent outpatient esophagogastroduodenoscopy and/or colonoscopy during fiscal years 2000-2013 at 133 facilities. RESULTS: The adjusted rate of MAC use in the VHA increased 17% per year (odds ratio for increase, 1.17; 95% confidence interval, 1.09-1.27) from fiscal year 2000 through 2013. The most rapid increase occurred starting in 2011. VHA use of MAC was associated with patient-level factors that included obesity, obstructive sleep apnea, higher comorbidity, and use of prescription opioids and/or benzodiazepines, although the magnitude of these effects was small. Provider-level and facility factors were also associated with use of MAC, although again the magnitude of these associations was small. Unmeasured facility-level effects had the greatest effect on the trend of MAC use. CONCLUSIONS: In a retrospective study of veterans who underwent outpatient esophagogastroduodenoscopy and/or colonoscopy from fiscal year 2000 through 2013, we found that even in a capitated system, patient factors are only weakly associated with use of MAC. Facility-level effects are the most prominent factor influencing increasing use of MAC. Future studies should focus on better defining the role of MAC and facility and organizational factors that affect choice of endoscopic sedation. It will also be important to align resources and incentives to promote appropriate allocation of MAC based on clinically meaningful patient factors.

Randomized Controlled Trial of a Collaborative Care Intervention for Mood Disorders by a National Commercial Health Plan.

OBJECTIVE: Few individuals with mood disorders have access to evidence-based collaborative chronic care models (CCMs) because most patients are seen in small-group practices (<20 providers) with limited capacity to deliver CCMs. In this single-blind randomized controlled trial, we determined whether a CCM delivered nationally in a U.S. health plan improved 12-month outcomes among enrollees with mood disorders compared with usual care. METHODS: Aetna insurance enrollees (N=238), mostly females (66.1%) with a mean age of 41.1 years, who were recently hospitalized for unipolar major depression or bipolar disorder provided informed consent, completed baseline assessments, and were randomly assigned to usual care or CCM. The CCM included 10 sessions of the Life Goals self-management program and brief contacts by phone by a care manager to determine symptom status. Primary outcomes were changes over 12 months in depression symptoms (nine-item Patient Health Questionnaire [PHQ-9]) and mental health-related quality of life (Short Form-12). RESULTS: Adjusted mean PHQ-9 scores were lower by 2.34 points (95% confidence level [CL]=-4.18 to -0.50, p=0.01), indicating improved symptoms, and adjusted mean SF-12 mental health scores were higher by 3.21 points (CL=-.97 to 7.38, p=0.10), indicating better quality of life, among participants receiving CCM versus usual care. CONCLUSIONS: Individuals receiving CCM compared with usual care had improved clinical outcomes, although substantial attrition may limit the impact of health plan-level delivery of CCMs. Further research on the use of health plan-level interventions, such as CCMs, as alternatives to practice-based models is warranted.

Using item response theory with health system data to identify latent groups of patients with multiple health conditions.

A critical step toward tailoring effective interventions for heterogeneous and medically complex patients is to identify clinically meaningful subgroups on the basis of their comorbid conditions. We applied Item Response Theory (IRT), a potentially useful tool to identify clinically meaningful subgroups, to characterize phenotypes within a cohort of high-risk patients. This was a retrospective cohort study using 68,400 high-risk Veteran's Health Administration (VHA) patients. Thirty-one physical and mental health diagnosis indicators based on ICD-9 codes from patients' inpatient, outpatient VHA and VA-paid community care claims. Results revealed 6 distinct subgroups of high-risk patients were identified: substance use, complex mental health, complex diabetes, liver disease, cancer with cardiovascular disease, and cancer with mental health. Multinomial analyses showed that subgroups significantly differed on demographic and utilization variables which underscored the uniqueness of the groups. Using IRT models with clinical diagnoses from electronic health records permitted identification of diagnostic constellations among otherwise undifferentiated high-risk patients. Recognizing distinct patient profiles provides a framework from which insights into medical complexity of high-risk patients can be explored and effective interventions can be tailored.