Self-management support for chronic disease in primary care: frequency of patient self-management problems and patient reported priorities, and alignment with ultimate behavior goal selection.

BackgroundTo enable delivery of high quality patient-centered care, as well as to allow primary care health systems to allocate appropriate resources that align with patients' identified self-management problems (SM-Problems) and priorities (SM-Priorities), a practical, systematic method for assessing self-management needs and priorities is needed. In the current report, we present patient reported data generated from Connection to Health (CTH), to identify the frequency of patients' reported SM-Problems and SM-Priorities; and examine the degree of alignment between patient SM-Priorities and the ultimate Patient-Healthcare team member selected Behavioral Goal.MethodsCTH, an electronic self-management support system, was embedded into the flow of existing primary care visits in 25 primary care clinics and was used to assess patient-reported SM-Problems across 12 areas, patient identified SM-Priorities, and guide the selection of a Patient-Healthcare team member selected Behavioral Goal. SM-Problems included: BMI, diet (fruits and vegetables, salt, fat, sugar sweetened beverages), physical activity, missed medications, tobacco and alcohol use, health-related distress, general life stress, and depression symptoms. Descriptive analyses documented SM-Problems and SM-Priorities, and alignment between SM-Priorities and Goal Selection, followed by mixed models adjusting for clinic.Results446 participants with ≥ one chronic diseases (mean age 55.4 ± 12.6; 58.5% female) participated. On average, participants reported experiencing challenges in 7 out of the 12 SM-Problems areas; with the most frequent problems including: BMI, aspects of diet, and physical activity. Patient SM-Priorities were variable across the self-management areas. Patient- Healthcare team member Goal selection aligned well with patient SM-Priorities when patients prioritized weight loss or physical activity, but not in other self-management areas.ConclusionParticipants reported experiencing multiple SM-Problems. While patients show great variability in their SM-Priorities, the resulting action plan goals that patients create with their healthcare team member show a lack of diversity, with a disproportionate focus on weight loss and physical activity with missed opportunities for using goal setting to create targeted patient-centered plans focused in other SM-Priority areas. Aggregated results can assist with the identification of high frequency patient SM-Problems and SM-Priority areas, and in turn inform resource allocation to meet patient needs.Trial registrationClinicalTrials.gov ID: NCT01945918

Utilizing RxNorm to Support Practical Computing Applications: Capturing Medication History in Live Electronic Health Records

RxNorm was utilized as the basis for direct-capture of medication history data in a live EHR system deployed in a large, multi-state outpatient behavioral healthcare provider in the United States serving over 75,000 distinct patients each year across 130 clinical locations. This tool incorporated auto-complete search functionality for medications and proper dosage identification assistance. The overarching goal was to understand if and how standardized terminologies like RxNorm can be used to support practical computing applications in live EHR systems. We describe the stages of implementation, approaches used to adapt RxNorm's data structure for the intended EHR application, and the challenges faced. We evaluate the implementation using a four-factor framework addressing flexibility, speed, data integrity, and medication coverage. RxNorm proved to be functional for the intended application, given appropriate adaptations to address high-speed input/output (I/O) requirements of a live EHR and the flexibility required for data entry in multiple potential clinical scenarios. Future research around search optimization for medication entry, user profiling, and linking RxNorm to drug classification schemes holds great potential for improving the user experience and utility of medication data in EHRs.Comment: Appendix (including SQL/DDL Code) available by author request. Keywords: RxNorm; Electronic Health Record; Medication History; Interoperability; Unified Medical Language System; Search Optimizatio

Effectiveness and Content Analysis of Interventions to Enhance Oral Antidiabetic Drug Adherence in Adults with Type 2 Diabetes : Systematic Review and Meta-Analysis

We thank Frederic Bergeron, information scientist, for assistance in search strategies. We thank American Journal Experts for editing the text. Source of financial support: This study was funded by the Laval University Chair on Adherence to Treatments. This Chair is supported by nonrestricted grants from AstraZeneca Canada, Merck Canada, Sanofi Canada, and Pfizer Canada and from the Prends soin de toi program (a Quebec provincial program for the improvement of public health).Peer reviewedPostprin

Issues in evaluating the costs and cost-effectiveness of Cognitive Behavioural Therapy for overweight/obese adolescents, CHERE Working Paper 2009/1

Economic evaluation is the systematic assessment of the costs and consequences of alternative courses of action. In health and healthcare, the results can be used to inform clinicians and policy makers about the relative cost-effectiveness of options under consideration [1]. Many economic evaluations are undertaken alongside randomised controlled trials (RCTs); the advantages of this approach are that i) prospective, accurate data can be collected on costs and effects and ii) appropriate outcome measures for use in economic evaluation can be chosen. The outcome of an economic evaluation is usually described as a ratio of the costs and effects ? often called the incremental cost-effectiveness ratio (ICER). The ICER is determined by calculating the differences in the costs and effects of both intervention and control groups and dividing the former by the latter. In designing an economic evaluation, the important questions to resolve are: which costs should be included and which outcome measures are most appropriate for estimating the cost-effectiveness ratio? In 2005, the Australian Technology Network of Universities funded the Centre for Metabolic Fitness (CMF) through a competitive, peer-reviewed process. The aims of the centre are to develop and evaluate diet and exercise interventions to counteract metabolic syndrome and assess their acceptability by target community groups. Metabolic syndrome is a cluster of metabolically determined risk factors associated with obesity (e.g. hypertension, impaired blood glucose etc). A number of collaborative projects have been developed within the centre, one of which is the CHOOSE HEALTH project. As part of this project, the effectiveness of cognitive behavioural therapy (CBT) as an intervention for overweight or obese adolescents has been trialled at the University of RMIT by Leah Brennan and the University of South Australia by Margarita Tsiros, as part of their post-graduate studies1. Subsequently, it has been decided to add an economic component to this work. Trials of the effectiveness and cost-effectiveness of different means of delivering cognitive behaviourally based weight management programs are planned2. This paper reports the results of investigations into the two questions which need to be addressed prior to undertaking a formal economic evaluation of the CHOOSE HEALTH program: i) what costs should be included and ii) which measures of outcome are suitable for estimating an ICER in this context. The paper is organised in four sections. Following the introduction (section 1) and brief descriptions of the background to and context in which the program was planned (section 2), details of the RMIT trial design and results are provided in section 3. In the final section (section 4), a cost model is presented and the implications of the outcomes used in the initial trials of the effectiveness are discussed in relation to designing a prospective economic evaluation of the CHOOSE HEALTH program.costs, economic evaluation, cognitive behavioural therapy (CBT), adolescent obesity, Australia

Student Nurse Perceptions of Effective Medication Administration Education

Nursing faculty strive to educate students in a manner that prevents errors, promoting quality, patient-centered care. This endeavor is dependent upon meaningful and effective education that incorporates educational experiences reflective of the service sector. Anecdotal reports from clinical faculty and student nurses suggest that academic medication administration education may not optimally prepare students for safe entry into clinical practice. The aim of this phenomenologic qualitative research is to understand student nurse perceptions regarding teaching strategies and learning activities that prepared them for safe medication administration in acute care clinical settings. Focus group interviews resulted in two broad themes that are identified as Effective Education and Gaps in Education. Within these broad themes, findings revealed that students value faculty demonstrations, peer-learning opportunities, and repetitive practice with timely feedback. Study findings also pointed to educational gaps. Students reported needing to learn communication and conflict resolution strategies that would help them manage real-world interruptions, distractions, and computer generated alerts. Study findings recommend implementing relevant decision-support technology within academic lab learning activities

Options for basing Dietary Reference Intakes (DRIs) on chronic disease endpoints: report from a joint US-/Canadian-sponsored working group.

Dietary Reference Intakes (DRIs) are used in Canada and the United States in planning and assessing diets of apparently healthy individuals and population groups. The approaches used to establish DRIs on the basis of classical nutrient deficiencies and/or toxicities have worked well. However, it has proved to be more challenging to base DRI values on chronic disease endpoints; deviations from the traditional framework were often required, and in some cases, DRI values were not established for intakes that affected chronic disease outcomes despite evidence that supported a relation. The increasing proportions of elderly citizens, the growing prevalence of chronic diseases, and the persistently high prevalence of overweight and obesity, which predispose to chronic disease, highlight the importance of understanding the impact of nutrition on chronic disease prevention and control. A multidisciplinary working group sponsored by the Canadian and US government DRI steering committees met from November 2014 to April 2016 to identify options for addressing key scientific challenges encountered in the use of chronic disease endpoints to establish reference values. The working group focused on 3 key questions: 1) What are the important evidentiary challenges for selecting and using chronic disease endpoints in future DRI reviews, 2) what intake-response models can future DRI committees consider when using chronic disease endpoints, and 3) what are the arguments for and against continuing to include chronic disease endpoints in future DRI reviews? This report outlines the range of options identified by the working group for answering these key questions, as well as the strengths and weaknesses of each option

Improving Palliative Care with Deep Learning

Improving the quality of end-of-life care for hospitalized patients is a priority for healthcare organizations. Studies have shown that physicians tend to over-estimate prognoses, which in combination with treatment inertia results in a mismatch between patients wishes and actual care at the end of life. We describe a method to address this problem using Deep Learning and Electronic Health Record (EHR) data, which is currently being piloted, with Institutional Review Board approval, at an academic medical center. The EHR data of admitted patients are automatically evaluated by an algorithm, which brings patients who are likely to benefit from palliative care services to the attention of the Palliative Care team. The algorithm is a Deep Neural Network trained on the EHR data from previous years, to predict all-cause 3-12 month mortality of patients as a proxy for patients that could benefit from palliative care. Our predictions enable the Palliative Care team to take a proactive approach in reaching out to such patients, rather than relying on referrals from treating physicians, or conduct time consuming chart reviews of all patients. We also present a novel interpretation technique which we use to provide explanations of the model's predictions.Comment: IEEE International Conference on Bioinformatics and Biomedicine 201

The processes of reform in Victoria’s alcohol and other drug sector, 2011-2014

This paper explores issues and concerns related to the 2014 alcohol and other drug sector recommissioning process in Victoria. Overview In mid-2014, the Victorian Alcohol and Drug Association approached the Drug Policy Modelling Program, at the National Drug and Alcohol Research Centre, University of New South Wales to undertake a project exploring and describing issues and concerns related to the 2014 alcohol and other drug sector recommissioning process in Victoria. This project commenced in July 2014 and concluded in November 2014. Policy documents and allied material were reviewed, and 20 stakeholders from 18 alcohol and other drug sector organisations were consulted. These stakeholders were CEOs/senior managers during the reform period

Constructing validated clinical tools to enable the development of a new evidence base for personalised nutrition practice in obesity management

This project focused on evaluating, constructing and integrating standardised clinical data-collection tools for obesity management in personalised nutrition practice. A mixed methods research design including surveys and interviews was used. A collaborative Delphi survey method was undertaken with purposefully selected stakeholder participants, who then contributed to the construction of four new tools. The project comprised of two research questions: 1. Is it possible and ethical to standardise a personalised approach to nutrition practice? 2. If so, what tools can be constructed and validated to help individual health history data collection, clinical decision making and clinical outcome analysis to enable the development of a case-by-case evidence base for personalised nutrition practice in the management of obesity? Theoretical frameworks that influenced the project include: the functional medicine approach, clinical psychoneuroimmunology (cPNI), the interdisciplinary approach of systems science, pathophysiological mechanistic reasoning and translational bioinformatics. The project focused on personalised nutrition practice, which is primarily centred on nutritional therapy but also draws on the practice of dietitians, nutritionists, functional medicine and cPNI practitioners. The research project had five stages included in the overall design. The first was a literature review undertaken to inform the project approach and tool development. The second stage involved gathering, categorising and evaluating existing tools. Surveys and interviews assessed practitioner experiences of using tools, while interviews with statisticians and academics evaluated their experiences and views on tool development to inform the development of new tools. The third stage was the Delphi method: a multi-staged, collaborative survey resulting in the development of four new clinical tools. The fourth stage was a pilot trial which aimed to achieve face validity and measure feasibility and utility for each of the four tools. The final stage included a survey and interviews which aimed to evaluate ways standardised tools could be successfully embedded into personalised nutrition practice. The findings showed that there were few ethical concerns with utilising standardised data-collection tools in nutrition practice, but there were numerous ethical considerations in relation to the development of a case-by-case evidence base for personalised nutrition practice. It was possible to construct new tools aimed at standardising individual health history data collection and clinical outcome analysis in order to support clinical decision making, but it was not possible to validate these tools. This project has been the first of its kind: a synthesis of different nutritional practice approaches to support the development of robust translational bioinformatics tools using pathophysiological reasoning. The results have created new knowledge in terms of understanding, defining and developing an evidence-based personalised nutrition practice approach. This could lead to major change initiatives and enhance and strengthen the nutrition profession

Lifting the Burden of Addiction: Philanthropic Opportunities to Address Substance Use Disorders in the United States

Substance use disorders (SUDs), also known as substance abuse or addiction, affect an estimated 20 million or more adolescents and adults in the U.S. This guidance provides philanthropic funders with the tools & information to reduce immediate harm from substance use disorders and reduce the burden of the disorder over the long term. This includes reducing the damage the disorder causes to people with SUDs and their loved ones, reducing the overall incidence of SUDs, and reducing SUD-related costs to society. We present four strategies for philanthropic funders who want to help:- Save lives and reduce SUD-related illness and homelessness- Improve access to evidence-based treatment- Improve SUD care by changing systems and policies- Fund innovation to improve prevention and treatmen