Yannick Meiller

Adaptive knowledge-based system for health care applications with RFID-generated information

Health care organizations are under increased pressure to continually improve their operational efficiency while simultaneously decreasing the overall operating costs with no appreciable degradation in the delivered quality of health care. Given the nature of such an environment where lives are at stake, it is natural to operate under a larger safety factor where risks are kept close to their necessary minimum. RFID tags are increasingly being used in health care organizations to reduce errors and to generally improve the effectiveness of the core processes. We develop an adaptive knowledge-based system framework for health care and illustrate the proposed framework using three example applications from the French health care environment. Specifically, we consider management of bottled gas delivery as well as tracking and tracing surgical equipment and prosthetic ancillaries within a health care environment using the proposed framework with item-level information generated through RFID tags. We use simulation analyses to study the underlying dynamics.

Healthy Ageing Through Internet Counselling in the Elderly: the HATICE randomised controlled trial for the prevention of cardiovascular disease and cognitive impairment

Introduction Cardiovascular disease and dementia share a number of risk factors including hypertension, hypercholesterolaemia, smoking, obesity, diabetes and physical inactivity. The rise of eHealth has led to increasing opportunities for large-scale delivery of prevention programmes encouraging self-management. The aim of this study is to investigate whether a multidomain intervention to optimise self-management of cardiovascular risk factors in older individuals, delivered through an coach-supported interactive internet platform, can improve the cardiovascular risk profile and reduce the risk of cardiovascular disease and cognitive decline. Methods and analysis HATICE is a multinational, multicentre, prospective, randomised, open-label blinded end point (PROBE) trial with 18 months intervention. Recruitment of 2600 older people (≥65 years) at increased risk of cardiovascular disease will take place in the Netherlands, Finland and France. Participants randomised to the intervention condition will have access to an interactive internet platform, stimulating self-management of vascular risk factors, with remote support by a coach. Participants in the control group will have access to a static internet platform with basic health information. The primary outcome is a composite score based on the average z-score of the difference between baseline and 18 months follow-up values of systolic blood pressure, low-density-lipoprotein and body mass index. Main secondary outcomes include the effect on the individual components of the primary outcome, the effect on lifestyle-related risk factors, incident cardiovascular disease, mortality, cognitive functioning, mood and cost-effectiveness. Ethics and dissemination The study was approved by the medical ethics committee of the Academic Medical Center in Amsterdam, the Comité de Protection des Personnes Sud Ouest et Outre Mer in France and the Northern Savo Hospital District Research Ethics Committee in Finland. We expect that data from this study will result in a manuscript published in a peer-reviewed clinical open access journal. Trial registration number ISRCTN48151589.

Radio frequency identification: a case for health care

The use of RFID tags in healthcare applications has been gaining momentum over the past decade. This is partly due to recent advances in information technology and the need to reduce errors while simultaneously improving the efficiency of the system. We, at the RFID European Lab, have been studying various aspects of RFID implementations in healthcare environment over the past several years. The potential for RFID implementations in healthcare environment is enormous. We consider several such opportunities and identify possible extensions.

RFID-Embedded Decision Support for Tracking Surgical Equipment

Healthcare and supply chain management have recently been the two most active areas for RFID applications. The healthcare environment is a natural fit for generating and utilizing instance-level data for decision support. We consider a scenario from the French healthcare environment involving tracking and tracing of surgical equipment within and among hospitals and develop a knowledge-based system for decision support that helps improve the overall performance of the surgical instrument management process while reducing errors. We illustrate the process through the developed healthcare knowledge-based system and evaluate its performance.

MANAGEMENT OF VASCULAR AND LIFESTYLE-RELATED RISK FACTORS FOR ALZHEIMER'S DISEASE AND DEMENTIA IN OLDER ADULTS: A EUROPEAN PERSPECTIVE

E p il ep sy 3 1 3 4 ,2 1 0 .9 1 (0 .7 1 -1 .3 3 ) Mariagnese Barbera, Tiia Ngandu, Francesca Mangialasche, Edo Richard, Cathrien Beishuizen, Sandrine Andrieu, Yannick Meiller, Abraham van de Groep, Carol Brayne, Willem A. van Gool, Hilkka Soininen, Miia Kivipelto, University of Eastern Finland, Kuopio, Finland; National Institute for Health and Welfare, Helsinki, Finland; Aging Research Center, Dept. of Neurobiology, Health Care Sciences and Society, Karolinska Institute, Stockholm, Sweden; Academic Medical Center, Amsterdam, Amsterdam, Netherlands; InsermUMR1027, Toulouse Cedex, France; NOVAPTEN, Paris, France; Vital Health Softwares, Amsterdam, Netherlands; Dept of Public Health and Primary Care, Cambridge, United Kingdom; Karolinska Institutet, Stockholm, Sweden. Contact e-mail: mariagnese.barbera@uef.fi

Improving data sharing in research with context-free encoded missing data.

Lack of attention to missing data in research may result in biased results, loss of power and reduced generalizability. Registering reasons for missing values at the time of data collection, or—in the case of sharing existing data—before making data available to other teams, can save time and efforts, improve scientific value and help to prevent erroneous assumptions and biased results. To ensure that encoding of missing data is sufficient to understand the reason why data are missing, it should ideally be context-free. Therefore, 11 context-free codes of missing data were carefully designed based on three completed randomized controlled clinical trials and tested in a new randomized controlled clinical trial by an international team consisting of clinical researchers and epidemiologists with extended experience in designing and conducting trials and an Information System expert. These codes can be divided into missing due to participant and/or participation characteristics (n = 6), missing by design (n = 4), and due to a procedural error (n = 1). Broad implementation of context-free missing data encoding may enhance the possibilities of data sharing and pooling, thus allowing more powerful analyses using existing data.

Performance Drivers for RFID-Generated Item-Level Information in the Oil Industry

Radio frequency identification (RFID)-generated item-level information provides interesting perspectives to increase operational performance in the oil and natural gas industry. However, costs and benefits of information systems with low-granular item-level information can be very different depending on various factors. We consider item-level information applications, especially RFID solutions, within the oil industry. We discuss why the incorporation of RFID tags in this system cannot be isolated and studied and how several related dimensions need to be considered. Among them, we detail characteristics like item-level identification, the rewritable and contact-less information functions, the existence of distributed sensors, and the overall network architecture. We consider the solutions used or potentially useful in the oil industry and evaluate three types of performance drivers (technical, operational, and strategic) related to these systems. Based on these, we propose five typologies—related to tubes, containers, other items, processes, and people—to characterize various critical empirical scenarios to identify the conditions under which item-level information is valuable in the oil industry. We then illustrate these typologies through potential applications.

Decision Support with RFID for Health Care

The health care environment is rife with issues that are urgently in need of solutions that can readily be addressed using appropriate tools for decision support. Recent developments in RFID technology facilitate this process through continuous provision of instantaneous item-level information. We consider an existing decision support framework and instantiate this framework using an example from the health care domain using RFID-generated item-level information. We illustrate the process by developing a health care knowledge-based system and evaluate its performance.