Using i2b2 to Bootstrap Rural Health Analytics and Learning Networks.

We demonstrate that the open-source i2b2 (Informatics for Integrating Biology and the Bedside) data model can be used to bootstrap rural health analytics and learning networks. These networks promote communication and research initiatives by providing the infrastructure necessary for sharing data and insights across a group of healthcare and research partners. Data integration remains a crucial challenge in connecting rural healthcare sites with a common data sharing and learning network due to the lack of interoperability and standards within electronic health records. The i2b2 data model acts as a point of convergence for disparate data from multiple healthcare sites. A consistent and natural data model for healthcare data is essential for overcoming integration issues, but challenges such as those caused by weak data standardization must still be addressed. We describe our experience in the context of building the West Virginia/Kentucky Health Analytics and Learning Network, a collaborative, multi-state effort connecting rural healthcare sites.

Research Partnerships with Healthcare Providers in Rural Community Health Centers: Needs and Challenges in Diabetes Research.

Kentucky has among the highest rates of diabetes and obesity in the United States. The Kentucky Diabetes and Obesity Collaborative (KDOC) was designed to develop a novel research infrastructure that can be used by researchers focusing on obesity and diabetes among patients cared for by Federally Qualified Health Centers (FQHC) serving rural Kentucky. Focus groups were carried out to develop an understanding of the needs and interests of FQHC practitioners and staff regarding participation in KDOC. Focus groups were conducted with 6 FQHCs and included a total of 41 individuals including health care providers, administrative staff and clinical staff. The discussions ranged in time from 30 to 70 minutes and averaged 45 minutes. Analysis of the transcripts of the focus groups revealed 4 themes: 1) contextual factors, 2) infrastructure, 3) interpersonal relationships, and 4) clinical features. The participants also noted four requirements that should be met for a research project to be successful in rural primary care settings: 1) there must be a shared understanding of health priorities of rural communities between the researcher and the practices/providers; 2) the proposed research must be relevant to clinics and their communities; 3) research and recommendations for evidence-based interventions need to reflect the day-to-day challenges of rural primary care providers; and 4) there needs to be an understanding of community norms and resources. Although research-clinic partnerships were viewed favourably overall, challenges in data integration to support both research and clinical outcomes were identified.

Potential effects of active parental consent: Enrolling teen smokers into a school-based cessation program.

INTRODUCTION: Research on effective teen smoking cessation interventions is critical to reducing the tobacco-related disease burden and risk of lifetime negative health outcomes for youth. However, informed consent procedures requiring active parental consent may restrict or influence teen participation in critical teen cessation programs. METHODS: Not On Tobacco (N-O-T) is a teen smoking cessation intervention that has been implemented under both active parental consent and passive parental consent conditions. The present study determined if there are differences in characteristics of youth enrolled under each condition. Data were available for active consent (n = 968) and passive consent (n = 4,924) participants aged 14-18 who completed the N-O-T program between 1998 and 2006 across several states. RESULTS: Participants enrolled under active consent conditions were more likely to be older, White/non-Hispanic, live in father-only or grandparent-headed household, start smoking at an earlier age, smoke more on weekdays, have previous unsuccessful quit attempts, and have siblings and friends who smoke. Additional differences were found between active and passive consent conditions in motivation to quit smoking, confidence in quitting, and stage of change. DISCUSSION: Results highlight important differences between youth who enroll in a smoking cessation program under active and passive consent conditions, often a distinguishing feature of research and non-research implementation.