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Background Cost-effective interventions to improve diet and physical activity are a public health priority. Alive! is an email-based intervention to increase physical activity, reduce saturated and trans fats and added sugars, and increase fruit and vegetable consumption. It was shown to improve these behaviors in a large randomized controlled trial. Objective (1) To describe the components and behavioral principles underlying Alive!, and (2) to report effects of the intervention on the secondary outcomes: health-related quality of life, presenteeism, self-efficacy, and stage of change. Methods The Alive! behavior change model is designed to elicit healthy behaviors and promote their maintenance. Behavioral strategies include assessments followed by individualized feedback, weekly goal-setting, individually tailored goals and tips, reminders, and promotion of social support. Alive! was tested among non-medical employees of Kaiser Permanente of Northern California, who were randomized to either the intervention group or the wait-list control group. After randomization, intervention group participants chose one topic to undertake for the intervention period: increasing physical activity, increasing fruits and vegetables, or decreasing saturated and trans fats and added sugars. Pre-post questionnaires assessed changes in SF-8 health-related quality of life, presenteeism, self-efficacy, and stage of change. Mixed effects multiple linear regression and ordinal logistic regression models were used, with department as a random effect factor. Analyses were by intention to treat: the 30% (238/787) who did not respond to the follow-up questionnaires were assigned change scores of zero. ResultsParticipants were 19 to 65 years (mean 44.0 +/- 10.6), and 74.3% (585/787) were female. Mean SF-8 Physical quality of life score increased significantly more in the intervention group than in the control group, 1.84 (95% CI 0.96-2.72) vs 0.72 (95% CI -0.15-1.58) respectively, P = .02. SF8 Mental score also improved significantly more in the intervention group than in the control group (P = .02). The odds ratio for improvement in self-assessed health status was 1.57 (95% CI 1.21-2.04, P < .001) for the intervention group compared to the control group. The odds ratio for having a reduction in difficulty accomplishing work tasks because of physical or emotional problems, a measure of presenteeism, was 1.47 (95% CI 1.05-2.05, P = .02) for the intervention group compared to the control group. The odds of having an improvement in self-efficacy for changing diet was 2.05 (95% CI 1.44-2.93) for the intervention vs the control group (P < .001). Greater improvement in stage of change for physical activity (P = .05), fats (P = .06), and fruits/vegetables (P = .006) was seen in the intervention group compared to the control group. Significant effects on diet and physical activity behavior change are reported elsewhere. Conclusions Cost-effective methods that can reach large populations with science-based interventions are urgently needed. Alive! is a fully automated low-cost intervention shown to effect significant improvements in important health parameters. Trial Registration Clinicaltrials.gov NCT00607009; http://clinicaltrials.gov/ct2/show/NCT00607009 (Archived by WebCite at http://www.webcitation.org/5cLpCWcT6)

The Cancer Research Network (CRN) is a consortium of 12 research groups, each affiliated with a nonprofit integrated health care delivery system, that was first funded in 1998. The overall goal of the CRN is to support and facilitate collaborative cancer research within its component delivery systems. This paper describes the CRN's 20-year experience and evolution. The network combined its members' scientific capabilities and data resources to create an infrastructure that has ultimately supported over 275 projects. Insights about the strengths and limitations of electronic health data for research, approaches to optimizing multidisciplinary collaboration, and the role of a health services research infrastructure to complement traditional clinical trials and large observational datasets are described, along with recommendations for other research consortia.

Objective To determine whether novel measures of contextual factors from multi-site electronic health record (EHR) audit log data can explain variation in clinical process outcomes. Materials and Methods We selected one widely-used process outcome: emergency department (ED)-based team time to deliver tissue plasminogen activator (tPA) to patients with acute ischemic stroke (AIS). We evaluated Epic audit log data (that tracks EHR user-interactions) for 3052 AIS patients aged 18+ who received tPA after presenting to an ED at three Northern California health systems (Stanford Health Care, UCSF Health, and Kaiser Permanente Northern California). Our primary outcome was door-to-needle time (DNT) and we assessed bivariate and multivariate relationships with six audit log-derived measures of treatment team busyness and prior team experience. Results Prior team experience was consistently associated with shorter DNT; teams with greater prior experience specifically on AIS cases had shorter DNT (minutes) across all sites: (Site 1: −94.73, 95% CI: −129.53 to 59.92; Site 2: −80.93, 95% CI: −130.43 to 31.43; Site 3: −42.95, 95% CI: −62.73 to 23.17). Teams with greater prior experience across all types of cases also had shorter DNT at two sites: (Site 1: −6.96, 95% CI: −14.56 to 0.65; Site 2: −19.16, 95% CI: −36.15 to 2.16; Site 3: −11.07, 95% CI: −17.39 to 4.74). Team busyness was not consistently associated with DNT across study sites. Conclusions EHR audit log data offers a novel, scalable approach to measure key contextual factors relevant to clinical process outcomes across multiple sites. Audit log-based measures of team experience were associated with better process outcomes for AIS care, suggesting opportunities to study underlying mechanisms and improve care through deliberate training, team-building, and scheduling to maximize team experience. [ABSTRACT FROM AUTHOR]

Abstract Background Although obesity is a risk factor for many chronic diseases, we have only limited knowledge of the magnitude of these associations in young adults. A multiethnic cohort of young adults was established to close current knowledge gaps; cohort demographics, cohort retention, and the potential influence of migration bias were investigated. Methods For this population-based cross-sectional study, demographics, and measured weight and height were extracted from electronic medical records of 1,929,470 patients aged 20 to 39 years enrolled in two integrated health plans in California from 2007 to 2009. Results The cohort included about 84.4% of Kaiser Permanente California members in this age group who had a medical encounter during the study period and represented about 18.2% of the underlying population in the same age group in California. The age distribution of the cohort was relatively comparable to the underlying population in California Census 2010 population, but the proportion of women and ethnic/racial minorities was slightly higher. The three-year retention rate was 68.4%. Conclusion These data suggest the feasibility of our study for medium-term follow-up based on sufficient membership retention rates. While nationwide 6% of young adults are extremely obese, we know little to adequately quantify the health burden attributable to obesity, especially extreme obesity, in this age group. This cohort of young adults provides a unique opportunity to investigate associations of obesity-related factors and risk of cancer in a large multiethnic population.