Paving the way for precision medicine v2.0 in intensive care by profiling necroinflammation in biofluids

Current clinical diagnosis is typically based on a combination of approaches including clinical examination of the patient, clinical experience, physiologic and/or genetic parameters, high-tech diagnostic medical imaging, and an extended list of laboratory values mostly determined in biofluids such as blood and urine. One could consider this as precision medicine v1.0. However, recent advances in technology and better understanding of molecular mechanisms underlying disease will allow us to better characterize patients in the future. These improvements will enable us to distinguish patients who have similar clinical presentations but different cellular and molecular responses. Treatments will be able to be chosen more "precisely", resulting in more appropriate therapy, precision medicine v2.0. In this review, we will reflect on the potential added value of recent advances in technology and a better molecular understanding of necrosis and inflammation for improving diagnosis and treatment of critically ill patients. We give a brief overview on the mutual interplay between necrosis and inflammation, which are two crucial detrimental factors in organ and/or systemic dysfunction. One of the challenges for the future will thus be the cellular and molecular profiling of necroinflammation in biofluids. The huge amount of data generated by profiling biomolecules and single cells through, for example, different omic-approaches is needed for data mining methods to allow patient-clustering and identify novel biomarkers. The real-time monitoring of biomarkers will allow continuous (re)evaluation of treatment strategies using machine learning models. Ultimately, we may be able to offer precision therapies specifically designed to target the molecular set-up of an individual patient, as has begun to be done in cancer therapeutics

The Meaningful Use of Cloud Computing in Healthcare

This dissertation focuses on the meaning of cloud computing for healthcare and its meaningful use in the healthcare industry. If used in a meaningful way, cloud computing is argued to be able to provide major benefits to the healthcare industry. Surprisingly, the benefits promised by using cloud computing often do not hold in practice, and the deployment of cloud computing services in healthcare organizations could lead to countereffects for healthcare. Although existing research studies cover a wide range of domains in healthcare, they often do not explain the way in which cloud computing could support healthcare in a systematic manner. In reply to that insufficiency in the research, this dissertation aims to investigate the phenomenon of cloud computing in healthcare organizations and to answer the following overarching research question: How can cloud computing support healthcare organizations in a meaningful way (i.e., meaningful use)? This dissertation conducted four research studies by employing established explorative research methods. The dissertation begins with a study (study 1) that investigates the basic properties of cloud computing services and their specific meanings for the healthcare industry, and suggests concrete directions for studies related to the meaningful use of cloud computing in healthcare. Study 2 focuses on the identification of industry-specific factors for the adoption of cloud computing services in healthcare, and studies 3 and 4 on an investigation of the way in which cloud computing supports collaborative activities in healthcare, respectively. Both focuses belong to research directions suggested by study 1. By addressing the overarching research question, this dissertation could deepen our understanding of the use of information technology (IT) artefacts that advances information systems theories, not only regarding cloud computing itself but also in terms of more general health IT levels