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      E-health as a sine qua non for modern healthcare

      discussion
      1 , 2 , , 3 , 4
      RMD Open
      BMJ Publishing Group
      autoimmune diseases, arthritis, therapeutics

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          Abstract

          In each era we need to balance between being able to provide care with our “technical skill, scientific knowledge, and human understanding” (Harrison's Principles of Internal Medicine, 1950) to the individual patient and simultaneously ensure that our healthcare serves all. With the increasing demand of healthcare by an aging population and the lack of specialists, accessible healthcare within a reasonable time frame is not always guaranteed. E-health provides solutions for current situations where we do not meet our own aims of good healthcare, such as restrictions in access to care and a reduction in care availability by a reducing workforce. In addition, telemedicine offers opportunities to improve our healthcare beyond what is possible by in person visits. However, e-health is often viewed as an deficient version of healthcare of low quality. We disagree with this view. In this article we will discuss how to position e-health in the current situation of healthcare, given the continuing rapid development of digital technologies and the changing needs of healthcare professionals and patients. We will address the evolution of e-health towards connected and intelligent systems and the stakeholders perspective, aiming to open up the discussion on e-Health.

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          Most cited references30

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          PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies

          Clinical prediction models combine multiple predictors to estimate risk for the presence of a particular condition (diagnostic models) or the occurrence of a certain event in the future (prognostic models). PROBAST (Prediction model Risk Of Bias ASsessment Tool), a tool for assessing the risk of bias (ROB) and applicability of diagnostic and prognostic prediction model studies, was developed by a steering group that considered existing ROB tools and reporting guidelines. The tool was informed by a Delphi procedure involving 38 experts and was refined through piloting. PROBAST is organized into the following 4 domains: participants, predictors, outcome, and analysis. These domains contain a total of 20 signaling questions to facilitate structured judgment of ROB, which was defined to occur when shortcomings in study design, conduct, or analysis lead to systematically distorted estimates of model predictive performance. PROBAST enables a focused and transparent approach to assessing the ROB and applicability of studies that develop, validate, or update prediction models for individualized predictions. Although PROBAST was designed for systematic reviews, it can be used more generally in critical appraisal of prediction model studies. Potential users include organizations supporting decision making, researchers and clinicians who are interested in evidence-based medicine or involved in guideline development, journal editors, and manuscript reviewers.
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            Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation

            Optical sensors on wearable devices can detect irregular pulses. The ability of a smartwatch application (app) to identify atrial fibrillation during typical use is unknown.
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              Telehealth.

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                Author and article information

                Journal
                RMD Open
                RMD Open
                rmdopen
                rmdopen
                RMD Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2056-5933
                2022
                19 September 2022
                : 8
                : 2
                : e002401
                Affiliations
                [1 ]departmentRheumatology , Leiden Universitair Medisch Centrum , Leiden, The Netherlands
                [2 ]departmentRheumatology , Newcastle University Translational and Clinical Research Institute , Newcastle upon Tyne, UK
                [3 ]departmentRheumatology , University Hospital Lausanne (CHUV) , Lausanne, Switzerland
                [4 ]University of Lausanne , Lausanne, Switzerland
                Author notes
                [Correspondence to ] Dr Rachel Knevel; r.knevel@ 123456lumc.nl
                Author information
                http://orcid.org/0000-0002-7494-3023
                http://orcid.org/0000-0002-3276-9581
                Article
                rmdopen-2022-002401
                10.1136/rmdopen-2022-002401
                9486378
                36123014
                629775fb-5a9d-4723-9171-04d09048bd04
                © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 08 July 2022
                : 08 September 2022
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                autoimmune diseases,arthritis,therapeutics
                autoimmune diseases, arthritis, therapeutics

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