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Objective: Introducing the Special Topic of Methods of Information in Medicine on pervasive healthcare, with selected papers from the Pervasive Healthcare Conference at Tampere, Finland, January 30 to February 1, 2008.Methods: Describing pervasive healthcare as field. Reporting about the content of the selected papers in this Special Topic. Developing and evaluating physiological measurement techniques, assistive care ambient notification and reminding systems, ambulatory monitoring, architectures and platforms for personalized home-health tele-monitoring, means of privacy-protecting health-sensitive information, and establishing a clinical proof-of-concept methodology.Results and Conclusions: Pervasive healthcare is an emerging field with considerable technological breadth and expected strong impact for the quality and efficiency of healthcare in an aging society. However, this field is still a nascent one, with a good deal of exploratory research. There is also hypothesis-based and empirical research, which tests the assumptions or feasibility of a solution using clinical evidence, but most such trials at this time are preliminary and small. The emergence of a truly evidence-based outcomes assessment will take some time, but is in the making. [ABSTRACT FROM AUTHOR]

Objectives: In 2002 a decision was reached to set up a nation-wide electronic health record system in Finland. The legal framework of actors with the necessary mandate was approved in the parliament in December 2006. A set of standards and norms have been selected that all health care actors need to follow. Functional specifications of the services were completed in 2006. Setting up the centralized health IT services begins in 2007. Centralization of patient record data allows the reorganization of health service providers to take place at local and regional levels according to need. The services allow users to access patient records securely from anywhere with the provision that they have the right to access private patient data.Methods: The functionality of the services and the necessary infrastructure has been agreed to in projects and working groups involving users, experts, key stakeholders and vendors.Results: The legal framework was approved in the parliament in December 2006. The functional specifications of the centralized health IT services were finalized in 2006.Conclusions: The implementation of the services will start in 2007. [ABSTRACT FROM AUTHOR]

Healthcare systems deal with only a part of the health continuum as they are organized to diagnose and treat patients. The Connected Health paradigm covers the continuum and includes the healthy and at risk individuals and chronically ill patients. The current system has been characterized as health profession centric; patients seek medical care which is delivered by healthcare professionals. In Connected Health, individuals are equal partners with healthcare professionals and take part in managing their health, wellness and care. Connected Health can be construed as being made up of one vertical layer providing privacy, security and interoperability services so that the users are able to use and trust the services and of five interacting horizontal layers as follows. The bottom layer houses the communications infrastructure, data stores (e.g. EHRs and PHRs) etc. The second layer health IT applications that enable and support the services on the third layer. The third layer is the one where health services are delivered. These cover the health continuum from end-to-end. The services span, e.g., wellness, self-management, retail clinics, policlinics, surgical operations and intensive care. The users see these as one integrated and accessible bundle. The fourth layer deals with reimbursement of health services. Providers can be paid on fee for service, capitation or pay for performance basis or a combination of these. The fifth layer sets the laws, regulations and policies that govern how health services are delivered and consumed. Health systems are already costly. Changes in demographics, our lifestyles and innovations in life sciences, medicine and technology are enabling new and improved care for all, which adds pressure to increase health expenditures. [ABSTRACT FROM PUBLISHER]

The article discusses various reports published within the issue, including one by I. Korhonen and J. E. Bardram on early operational definition of computing, ubiquitous communication and intelligent user-friendly interfaces and another by J. Schumm on the works of scientists that lead to the improvement in measurement techniques.

Although Europe 'produces' excellent science, it has not been equally successful in translating scientific results into commercially successful companies in spite of European and national efforts invested in supporting the translation process. The Idea-to-Market process is highly complex due to the large number of actors and stakeholders. ITECH was launched to propose recommendations which would accelerate the Idea-to-Market process of health technologies leading to improvements in the competitiveness of the European health technology industry in the global markets. The project went through the following steps: defining the Idea-to-Market process model; collection and analysis of funding opportunities; identification of 12 gaps and barriers in the Idea-to-Market process; a detailed analysis of these supported by interviews; a prioritization process to select the most important issues; construction of roadmaps for the prioritized issues; and finally generating recommendations and associated action plans. Seven issues were classified as in need of actions. Three of these are part of the ongoing Medical Device Directive Reform (MDR), namely health technology assessment, post-market surveillance and regulatory process, and therefore not within the scope of ITECH. Recommendations were made for eHealth taxonomy; Education and training; Clinical trials and Adoption space and Human Factors Engineering (HFE).

Health-related behaviors are among the most significant determinants of health and quality of life. Improving health behavior is an effective way to enhance health outcomes and mitigate the escalating challenges arising from an increasingly aging population and the proliferation of chronic diseases. Although it has been difficult to obtain lasting improvements in health behaviors on a wide scale, advances at the intersection of technology and behavioral science may provide the tools to address this challenge. In this paper, we describe a vision and an approach to improve health behavior interventions using the tools of behavioral informatics, an emerging transdisciplinary research domain based on system-theoretic principles in combination with behavioral science and information technology. The field of behavioral informatics has the potential to optimize interventions through monitoring, assessing, and modeling behavior in support of providing tailored and timely interventions. We describe the components of a closed-loop system for health interventions. These components range from fine grain sensor characterizations to individual-based models of behavior change. We provide an example of a research health coaching platform that incorporates a closed-loop intervention based on these multiscale models. Using this early prototype, we illustrate how the optimized and personalized methodology and technology can support self-management and remote care. We note that despite the existing examples of research projects and our platform, significant future research is required to convert this vision to full-scale implementations.

Adverse and suboptimal health behaviors and habits are responsible for approximately 40 % of preventable deaths, in addition to their unfavorable effects on quality of life and economics. Our current understanding of human behavior is largely based on static "snapshots" of human behavior, rather than ongoing, dynamic feedback loops of behavior in response to ever-changing biological, social, personal, and environmental states. This paper first discusses how new technologies (i.e., mobile sensors, smartphones, ubiquitous computing, and cloud-enabled processing/computing) and emerging systems modeling techniques enable the development of new, dynamic, and empirical models of human behavior that could facilitate just-in-time adaptive, scalable interventions. The paper then describes concrete steps to the creation of robust dynamic mathematical models of behavior including: (1) establishing "gold standard" measures, (2) the creation of a behavioral ontology for shared language and understanding tools that both enable dynamic theorizing across disciplines, (3) the development of data sharing resources, and (4) facilitating improved sharing of mathematical models and tools to support rapid aggregation of the models. We conclude with the discussion of what might be incorporated into a "knowledge commons," which could help to bring together these disparate activities into a unified system and structure for organizing knowledge about behavior.

Background: There is a strong will and need to find alternative models of health care delivery driven by the ever-increasing burden of chronic diseases., Objective: The purpose of this 1-year trial was to study whether a structured mobile phone-based health coaching program, which was supported by a remote monitoring system, could be used to improve the health-related quality of life (HRQL) and/or the clinical measures of type 2 diabetes and heart disease patients., Methods: A randomized controlled trial was conducted among type 2 diabetes patients and heart disease patients of the South Karelia Social and Health Care District. Patients were recruited by sending invitations to randomly selected patients using the electronic health records system. Health coaches called patients every 4 to 6 weeks and patients were encouraged to self-monitor their weight, blood pressure, blood glucose (diabetics), and steps (heart disease patients) once per week. The primary outcome was HRQL measured by the Short Form (36) Health Survey (SF-36) and glycosylated hemoglobin (HbA1c) among diabetic patients. The clinical measures assessed were blood pressure, weight, waist circumference, and lipid levels., Results: A total of 267 heart patients and 250 diabetes patients started in the trial, of which 246 and 225 patients concluded the end-point assessments, respectively. Withdrawal from the study was associated with the patients' unfamiliarity with mobile phones—of the 41 dropouts, 85% (11/13) of the heart disease patients and 88% (14/16) of the diabetes patients were familiar with mobile phones, whereas the corresponding percentages were 97.1% (231/238) and 98.6% (208/211), respectively, among the rest of the patients (P=.02 and P=.004). Withdrawal was also associated with heart disease patients' comorbidities—40% (8/20) of the dropouts had at least one comorbidity, whereas the corresponding percentage was 18.9% (47/249) among the rest of the patients (P=.02). The intervention showed no statistically significant benefits over the current practice with regard to health-related quality of life—heart disease patients: beta=0.730 (P=.36) for the physical component score and beta=-0.608 (P=.62) for the mental component score; diabetes patients: beta=0.875 (P=.85) for the physical component score and beta=-0.770 (P=.52) for the mental component score. There was a significant difference in waist circumference in the type 2 diabetes group (beta=-1.711, P=.01). There were no differences in any other outcome variables., Conclusions: A health coaching program supported with telemonitoring did not improve heart disease patients' or diabetes patients' quality of life or their clinical condition. There were indications that the intervention had a differential effect on heart patients and diabetes patients. Diabetes patients may be more prone to benefit from this kind of intervention. This should not be neglected when developing new ways for self-management of chronic diseases., Trial Registration: ClinicalTrials.gov NCT01310491; http://clinicaltrials.gov/ct2/show/NCT01310491 (Archived by WebCite at http://www.webcitation.org/6Z8l5FwAM).