Effects of a clinical decision support system and patient portal for preventing medication-related falls in older fallers:Protocol of a cluster randomized controlled trial with embedded process and economic evaluations (ADFICE_IT)

BackgroundFalls are the leading cause of injury-related mortality and hospitalization among adults aged ≥ 65 years. An important modifiable fall-risk factor is use of fall-risk increasing drugs (FRIDs). However, deprescribing is not always attempted or performed successfully. The ADFICE_IT trial evaluates the combined use of a clinical decision support system (CDSS) and a patient portal for optimizing the deprescribing of FRIDs in older fallers. The intervention aims to optimize and enhance shared decision making (SDM) and consequently prevent injurious falls and reduce healthcare-related costs.MethodsA multicenter, cluster-randomized controlled trial with process evaluation will be conducted among hospitals in the Netherlands. We aim to include 856 individuals aged ≥ 65 years that visit the falls clinic due to a fall. The intervention comprises the combined use of a CDSS and a patient portal. The CDSS provides guideline-based advice with regard to deprescribing and an individual fall-risk estimation, as calculated by an embedded prediction model. The patient portal provides educational information and a summary of the patient’s consultation. Hospitals in the control arm will provide care-as-usual. Fall-calendars will be used for measuring the time to first injurious fall (primary outcome) and secondary fall outcomes during one year. Other measurements will be conducted at baseline, 3, 6, and 12 months and include quality of life, cost-effectiveness, feasibility, and shared decision-making measures. Data will be analyzed according to the intention-to-treat principle. Difference in time to injurious fall between the intervention and control group will be analyzed using multilevel Cox regression.DiscussionThe findings of this study will add valuable insights about how digital health informatics tools that target physicians and older adults can optimize deprescribing and support SDM. We expect the CDSS and patient portal to aid in deprescribing of FRIDs, resulting in a reduction in falls and related injuries

Health informatics

Health informatics (also referred to as medical informatics or biomedical informatics) is an interdisciplinary field that deals with health-related data in healthcare and with the technologies that are used to support healthcare services. While the goal of some health informatics systems is to automate processes, the more common goal is to help clinicians, patients, policymakers, and others to manage health information, and to communicate that information efficiently and effectively to end users. Thus, there is considerable overlap between the fields of health informatics and health communication, and this intriguing intersection between the two fields opens many opportunities for innovation. Health communication is often visible in health informatics in the area of patient communication. Examples of this include patient self-management tools that support behavior change. Correspondingly, health informatics is often visible in health communication in the use of computational methods and “big data” to build on communication theory. Future research in health communication will likely involve more and more intensive use of information technology. This can bring exciting new possibilities for both interventions and analytical techniques, yet researchers should ensure that information technology interventions respect participants' privacy and guarantee their safety. Investigating the effect of information technology on communications between healthcare professionals and with patients also offers interesting opportunities for collaborative research

Combining user-centered design and behavioral theory to enhance health technologies: A personas-based approach for a primary-care based multifactorial falls risk assessment tool

Introduction: Multifactorial falls risk assessment tools (FRATs) can be an effective falls prevention method for older adults, but are often underutilized by health care professionals (HCPs). This study aims to enhance the use and implementation of multifactorial FRATs by combining behavioral theory with the user-centered design (UCD) method of personas construction. Specifically, the study aimed to (1) construct personas that are based on external (i.e., needs, preferences) and intrinsic user characteristics (i.e., behavioral determinants); and (2) use these insights to inform requirements for optimizing an existing Dutch multifactorial FRAT (i.e., the ‘Valanalyse’).Methods: Survey data from HCPs (n = 31) was used to construct personas of the ‘Valanalyse.’ To examine differences between clusters on 68 clustering variables, a multivariate cluster analysis technique with non-parametric analyses and computational methods was used. The aggregated external and intrinsic user characteristics of personas were used to inform key design and implementation requirements for the ‘Valanalyse,’ respectively, whereby intrinsic user characteristics were matched with appropriate behavior change techniques to guide implementation.Results: Significant differences between clusters were observed in 20 clustering variables (e.g., behavioral beliefs, situations for use). These variables were used to construct six personas representing users of each cluster. Together, the six personas helped operationalize four key design requirements (e.g., guide treatment-related decision making) and 14 implementation strategies (e.g., planning coping responses) for optimizing the ‘Valanalyse’ in Dutch geriatric, primary care settings.Conclusion: The findings suggest that theory- and evidence-based personas that encompass both external and intrinsic user characteristics are a useful method for understanding how the use and implementation of multifactorial FRATs can be optimized with and for HCPs, providing important implications for developers and eHealth interventions with regards to encouraging technology adoption

Genomics of tolerance to abiotic stress in the Triticeae

Genomics platforms offer unprecedented opportunities to identify, select and in some cases clone the genes and the quantitative trait loci (QTLs) that govern the tolerance of Triticeae to abiotic stresses and, consequently, grain yield. Transcriptome profiling and the other \u201comics\u201d platforms provide further information to unravel gene functions and validate the role of candidate genes. This review provides a synopsis of the main results on the studies that have investigated the genomics of Triticeae crops under conditions of abiotic constraints. With their rich biodiversity and high functional plasticity in response to environmental stresses, Triticeae crops provide an ideal ground for taking full advantage of the opportunities offered by genomics approaches. Ultimately, the practical impact of the knowledge and materials generated through genomics-based approaches will depend on their integration and exploitation within the extant breeding programs