A Pilot Randomized Controlled Clinical Trial to Assess Tolerance and Efficacy of Navy Bean and Rice Bran Supplementation for Lowering Cholesterol in Children.

Background: Navy beans and rice bran demonstrate efficacy to regulate serum cholesterol in hypercholesterolemic adults; however, the cardiovascular disease (CVD) protective properties of these foods in children are unknown and merit investigation. Objective: The objectives were to determine whether cooked navy bean powder (NBP) and/or heat-stabilized rice bran (RB) supplementation is tolerable, improves dietary fiber intake in children, and modulates lipid profiles. Methods: Children aged 8 to 13 years at risk for CVD due to abnormal lipids were recruited. Elevated cholesterol levels were defined as total cholesterol ≥180 mg/dL and high-density lipoprotein (HDL) <60 mg/dL; low-density lipoprotein (LDL) ≥100 mg/dL and HDL <60 mg/dL; or non-HDL >100 mg/dL and HDL <60 mg/dL. Participants completed a pilot 4-week, randomized controlled, 4-arm dietary intervention. They consumed study-provided muffins or a smoothie daily that included 0 g NBP or RB (control), 17.5 g NBP, 15 g RB, or a combination 9 g NBP + 8 g RB. Fasting blood was collected at baseline and week 4. Participants also completed 3-day food logs and gastrointestinal health questionnaires. RESULTS: Thirty-eight children completed the trial (n = 9 control, n = 10 NBP, n = 9 RB, and n = 10 NBP + RB groups). Only 3 participants withdrew due to noncompliance of required food consumption. Participants in the intervention groups significantly increased intake of NBP and RB at week 4 (p≤.01). The NBP and NBP + RB groups increased total fiber intake from baseline to week 4 (p=.02 and p=<.01, respectively). HDL-cholesterol was higher in NBP-group participants compared to control at week 4 (P = .02). Conclusion: Increasing NBP and/or RB intake is tolerable for children, and our findings suggest higher daily intakes are needed for a longer duration to induce favorable changes across multiple serum lipid parameters.

A Randomized Controlled Trial to Increase Navy Bean or Rice Bran Consumption in Colorectal Cancer Survivors.

Consumption of navy beans (NB) and rice bran (RB) have been shown to inhibit colon carcinogenesis. Given the overall poor diet quality in colorectal cancer (CRC) survivors and low reported intake of whole grains and legumes, practical strategies to increase consumption merit attention. This study determined feasibility of increasing NB or RB intake in CRC survivors to increase dietary fiber and examined serum inflammatory biomarkers and telomere lengths. Twenty-nine subjects completed a randomized controlled trial with foods that included cooked NB powder (35 g/day), heat-stabilized RB (30 g/day), or no additional ingredient. Fasting blood, food logs, and gastrointestinal health questionnaires were collected. The amount of NB or RB consumed equated to 4-9% of subjects' daily caloric intake and no major gastrointestinal issues were reported with increased consumption. Dietary fiber amounts increased in NB and RB groups at Weeks 2 and 4 compared to baseline and to control (P ≤ 0.01). Telomere length correlated with age and HDL cholesterol at baseline, and with improved serum amyloid A (SAA) levels at Week 4 (P ≤ 0.05). This study concludes feasibility of increased dietary NB and RB consumption to levels associated with CRC chemoprevention and warrants longer-term investigations with both foods in high-risk populations that include cancer prevention and control outcomes.

Analysis of Nursing Clinical Decision Support Requests and Strategic Plan in a Large Academic Health System.

OBJECTIVES: To understand requests for nursing Clinical Decision Support (CDS) interventions at a large integrated health system undergoing vendor-based EHR implementation. In addition, to establish a process to guide both short-term implementation and long-term strategic goals to meet nursing CDS needs. MATERIALS AND METHODS: We conducted an environmental scan to understand current state of nursing CDS over three months. The environmental scan consisted of a literature review and an analysis of CDS requests received from across our health system. We identified existing high priority CDS and paper-based tools used in nursing practice at our health system that guide decision-making. RESULTS: A total of 46 nursing CDS requests were received. Fifty-six percent (n=26) were specific to a clinical specialty; 22 percent (n=10) were focused on facilitating clinical consults in the inpatient setting. "Risk Assessments/Risk Reduction/Promotion of Healthy Habits" (n=23) was the most requested High Priority Category received for nursing CDS. A continuum of types of nursing CDS needs emerged using the Data-Information-Knowledge-Wisdom Conceptual Framework: 1) facilitating data capture, 2) meeting information needs, 3) guiding knowledge-based decision making, and 4) exposing analytics for wisdom-based clinical interpretation by the nurse. CONCLUSION: Identifying and prioritizing paper-based tools that can be modified into electronic CDS is a challenge. CDS strategy is an evolving process that relies on close collaboration and engagement with clinical sites for short-term implementation and should be incorporated into a long-term strategic plan that can be optimized and achieved overtime. The Data-Information-Knowledge-Wisdom Conceptual Framework in conjunction with the High Priority Categories established may be a useful tool to guide a strategic approach for meeting short-term nursing CDS needs and aligning with the organizational strategic plan.

Modeling decision support rule interactions in a clinical setting.

Traditionally, rule interactions are handled at implementation time through rule task properties that control the order in which rules are executed. By doing so, knowledge about the behavior and interactions of decision rules is not captured at modeling time. We argue that this is important knowledge that should be integrated in the modeling phase. In this project, we build upon current work on a conceptual schema to represent clinical knowledge for decision support in the form of if then rules. This schema currently captures provenance of the clinical content, context where such content is actionable (i.e. constraints) and the logic of the rule itself. For this project, we borrowed concepts from both the Semantic Web (i.e., Ontologies) and Complex Adaptive Systems (CAS), to explore a conceptual approach for modeling rule interactions in an enterprise-wide clinical setting. We expect that a more comprehensive modeling will facilitate knowledge authoring, editing and update; foster consistency in rules implementation and maintenance; and develop authoritative knowledge repositories to promote quality, safety and efficacy of healthcare.

A study of diverse clinical decision support rule authoring environments and requirements for integration.

BACKGROUND: Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. METHODS: The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. RESULTS: While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. CONCLUSIONS: A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting.

A multi-layered framework for disseminating knowledge for computer-based decision support.

BACKGROUND: There are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patient data representations, and of workflows. METHODS: We have developed a multi-layered knowledge representation framework for structuring guideline recommendations for implementation in a variety of CDS contexts. In this framework, guideline recommendations are increasingly structured through four layers, successively transforming a narrative text recommendation into input for a CDS system. We have used this framework to implement rules for a CDS service based on three guidelines. We also conducted a preliminary evaluation, where we asked CDS experts at four institutions to rate the implementability of six recommendations from the three guidelines. CONCLUSION: The experience in using the framework and the preliminary evaluation indicate that this approach has promise in creating structured knowledge, to implement in CDS systems, that is usable across organizations.