Clinical decisions are more promising and evidence-based, hence, big data analytics to assist clinical decision-making has been expressed for a variety of clinical fields. Due to the sheer size and ...availability of healthcare data, big data analytics has revolutionized this industry and promises us a world of opportunities. It promises us the power of early detection, prediction, prevention, and helps us to improve the quality of life. Researchers and clinicians are working to inhibit big data from having a positive impact on health in the future. Different tools and techniques are being used to analyze, process, accumulate, assimilate, and manage large amount of healthcare data either in structured or unstructured form. In this review, we address the need of big data analytics in healthcare: why and how can it help to improve life?. We present the emerging landscape of big data and analytical techniques in the five sub-disciplines of healthcare, i.e., medical image analysis and imaging informatics, bioinformatics, clinical informatics, public health informatics and medical signal analytics. We present different architectures, advantages and repositories of each discipline that draws an integrated depiction of how distinct healthcare activities are accomplished in the pipeline to facilitate individual patients from multiple perspectives. Finally, the paper ends with the notable applications and challenges in adoption of big data analytics in healthcare.
Machine learning has become a pivotal tool for many projects in computational biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical researchers often do not have ...enough experience to run a data mining project effectively, and therefore can follow incorrect practices, that may lead to common mistakes or over-optimistic results. With this review, we present ten quick tips to take advantage of machine learning in any computational biology context, by avoiding some common errors that we observed hundreds of times in multiple bioinformatics projects. We believe our ten suggestions can strongly help any machine learning practitioner to carry on a successful project in computational biology and related sciences.
Background: Development and provision of health and social care, based on the principles of Prudent healthcare1, centred around individual’s needs continues to be the vision of Welsh Government (WG). ...Amongst the multitude of challenges, meeting the needs and expectations of ‘High-need, High-cost’1,2 population with complex needs, is currently affecting UK healthcare economy the greatest. Provision of care and partnerships amongst citizens and care-providers in more coordinated and integrated fashion is fundamental to achievement and demonstration of outcomes.Objective: In recognition of the policy direction on integrated working practices, development of joint Health and Social care a Welsh Community Care Information Solution (WCCIS) is currently underway. Development and re-design of systems, processes, forms and care recording, which are consistent across and within care settings is recognised to be critical in addressing the aforementioned challenges and realising a range of additional benefits3.Highlights: Senior sponsorship and endorsement of approach to review and standardise of clinical record and process across Wales, from the Therapy Adviser to WG and Welsh Therapies Advisory Committee (WTAC) and clinical informatics leadership steer NHS Wales Informatics Service (NWIS) has enabled National consensus on:a) Standardised therapy core data items: data definition, recording and collection of informationb) Standardised and clinically assured set of Uni professional and Multi professional clinical templates, clinical reference data and in progress alignment with SNOMED-CTc) Specification for current and future information and reporting requirementsd) Model for effective communication between and with health and social care.This is a significant clinical and behavioural transformational change. An unintended consequence in form of increased trust in professional competencies and skills has been noted. Inter-professional integration in defining and specifying standards for clinical records has utilised in developing national standards for various assessments such as Foot Assessment and clinical record for Diabetic patients by the ‘Gold Standard’ Podiatrists, adopted by Diabetologists.Transferability: Here in NHS Wales the clinical leadership and ownership of the above approach by frontline clinical staff is leading to development of first in class ‘Clinical Interoperability’ across range of professions. In complement the model has the potential to safely and effectively blur the professional boundaries, through utilisation and sharing of standardised information, assured to be compliant with clinical, professional, information governance standards.Approach and the products on offering from NHS Wales are portable, these should be of interest and application beyond the health and care boundaries of UK. Provision of evidence based care, similar epidemiological state and common challenges affecting the developed world healthcare services strengthens the above argument.Clinical and Policy leaders have an opportunity at hand to collaborate with NWIS in scaling and overcoming the challenges by adopting an alternative bottom up approach empowering clinicians4 critical to success 5 to lead and catalyse whole system wide transformation. In recognition of the discovery of potential ‘winning formula’ interest from colleagues in New Zealand, Northern Ireland, Academy of Royal Medical Colleges etc is being progressed.
This Handbook provides a complete compendium of methods for evaluation of IT-based systems and solutions within healthcare. Emphasis is entirely on assessment of the IT-system within its ...organizational environment. The author provides a coherent and complete assessment of methods addressing interactions with and effects of technology at the organizational, psychological, and social levels.It offers an explanation of the terminology and theoretical foundations underlying the methodological analysis presented here. The author carefully guides the reader through the process of identifying relevant methods corresponding to specific information needs and conditions for carrying out the evaluation study. The Handbook takes a critical view by focusing on assumptions for application, tacit built-in perspectives of the methods as well as their perils and pitfalls.
*Collects a number of evaluation methods of medical informatics*Addresses metrics and measures*Includes an extensive list of anotated references, case studies, and a list of useful Web sites
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