BackgroundThe consequences of lifestyle-related disease represent a major burden for the individual as well as for society at large. Individual preventive health checks to the general population have been suggested as a mean to reduce the burden of lifestyle-related diseases, though with mixed evidence on effectiveness. Several systematic reviews, on the other hand, suggest that health checks targeting people at high risk of chronic lifestyle-related diseases may be more effective. The evidence is however very limited. To effectively target people at high risk of lifestyle-related disease, there is a substantial need to advance and implement evidence-based health strategies and interventions that facilitate the identification and management of people at high risk. This paper reports on a non-randomized pilot study carried out to test the acceptability, feasibility and short-term effects of a healthcare intervention in primary care designed to systematically identify persons at risk of developing lifestyle-related disease or who engage in health-risk behavior, and provide targeted and coherent preventive services to these individuals.MethodsThe intervention took place over a three-month period from September 2016 to December 2016. Taking a two-pronged approach, the design included both a joint and a targeted intervention. The former was directed at the entire population, while the latter specifically focused on patients at high risk of a lifestyle-related disease and/or who engage in health-risk behavior. The intervention was facilitated by a digital support system. The evaluation of the pilot will comprise both quantitative and qualitative research methods. All outcome measures are based on validated instruments and aim to provide results pertaining to intervention acceptability, feasibility, and short-term effects.DiscussionThis pilot study will provide a solid empirical base from which to plan and implement a full-scale randomized study with the central aim of determining the efficacy of a preventive health intervention.Trial registrationRegistered at Clinical Trial Gov (Unique Protocol ID: TOFpilot2016). Registered 29 April 2016. The study adheres to the SPIRIT guidelines.Electronic supplementary materialThe online version of this article (10.1186/s12875-018-0820-8) contains supplementary material, which is available to authorized users.

The design of patient-centred e-health services embodies an inherent tension between the concerns of clinicians and those of patients. Clinicians' concerns are related to professional issues to do with diagnosing and curing disease in accordance with accepted medical standards. In contrast, patients' concerns typically relate to personal experience and quality of life issues. It is about their identity, their hopes, their fears and their need to maintain a meaningful life. This divergence of concerns presents a fundamental challenge for designers of patient-centred e-health services. We explore this challenge in the context of chronic illness and telecare. Based on insights from medical phenomenology as well as our own experience with designing an e-health service for patients with chronic heart disease, we emphasise the importanceand difficultyof aligning the concerns of patients and clinicians. To deal with this, we propose a set of concepts for analysing concerns related to the design of e-health services: A concern is (1) meaningful if it is relevant and makes sense to both patients and clinicians, (2) actionable if clinicians or patientsat least in principleare able to take appropriate action to deal with it, and (3) feasible if it is easy and convenient to do so within the organisational and social context. We conclude with a call for a more participatory and iterative approach to the design of patient-centred ehealth services.

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Within healthcare, information systems are increasingly developed to enable automatic analysis of the large amounts of data that are accumulated. A prerequisite for the practical use of such data analysis is the veracity of the output, that is, that the analysis is clinically valid. Whereas most research focuses on the technical configuration and clinical precision of data analysis systems, the purpose of this article is to investigate how veracity is achieved in practice. Based on a study of a project in Denmark aimed at developing an algorithm for stratification of citizens in preventive healthcare, this article confirms that achieving veracity requires close attention to the clinical validity of the algorithm. It also concludes, however, that the veracity in practice hinges critically on the citizens' ability to report high-quality data and the ability of the health professionals to interpret the outcome in the context of existing care practices.

Abstract. We examine an important part of the medical record that has not been studied extensively: physicians' clinical notes. These notes constitute an explanatory medical narrative that documents the patient's illness trajectory by combining each physician's notes into a common text. Although several prior CSCW studies have addressed the role of the medical record in patient care, they have not dealt specifically with the role, structure, and content of these notes. In this article, we present a detailed analysis of a set of physicians' clinical notes recording the acute hospitalization and subsequent treatment of a patient with chronic heart disease. We show that clinical notes are highly structured and conventionalized texts that promote conciseness while at the same time allowing physicians to express themselves in a precise and nuanced way. Based on this analysis, we argue that physicians' clinical notes form the core of the medical record. They serve both as a 'tool for thinking' for the individual physician, enabling him or her to make sense of the patient's past history and current condition, and as a coordinative artifact used by physicians, nurses, and other health care professionals. We conclude by discussing the implications of this research for the design of Electronic Medical Record (EMR) systems.

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In its promise to contribute to considerable cost savings and improved patient care through efficient analysis of the tremendous amount of data stored in electronic health records (EHR), there is currently a strong push for the proliferation of artificial intelligence (AI) in health-care. We identify, through a study of AI being used to predict patient no-show's, that for the AI to gain full potential there lies a need to balance the introduction of AI with a proper focus on the patients and the clinicians' interests. We call for a Participatory Design (PD) approach to understand and reconfigure the socio-technical setup in health-care, especially where AI is being used on EHR data that are manually being submitted by health-care personnel. CCS Concepts: • Human-centered computing → Participatory design; Empirical studies in collaborative and social computing.