Editorial

Evidence for building a smarter health and wellness future—Key messages and collected visions from a Joint OECD and NSF workshop☆

Disruptive connected health technologies, or digitalization, are suggested to tackle the healthcare challenges and transform traditional care models. In Finland, the transformation is manifested by the development of various digital hospitals and citizen-centric care models that foster self-care by utilizing connected health technologies. In this paper we introduce qualitative research that uses social practice theory in order to understand how connected health technologies shape a pediatric day surgery practice in future digital hospitals. Major improvement needs were identified to center on discursive actions (i.e., communication that occurs between health professionals and patients), since hospital IT systems, data exchange, and internal and external communication were found to not support pediatric surgery practice as expected. To improve the current situation, we found out that there is a need to change the patient role to be more active, creating data that health professionals could use through their own patient record systems. Connected health solutions allow this type of interaction between things (i.e., communication through mobile apps, medical devices, etc.) and agents (i.e., health professionals). There is an urgent need to improve communication channels such as Chat, WhatsApp, and mobile applications that gather all necessary information and instructions from patients before and after the surgery. However, these solutions cannot be co-created separately from the clinical decision systems that allow discursive actions among healthcare professionals. These solutions, e.g. mobile applications designed to support patients going through the surgery practice, will also significantly impact and change pediatric surgery practice at hospitals.

Healthcare supplements are consumed to increase dietary consumption of nutrients. Consumer usage behaviors for supplements deserves focused attention in light of growing health care concerns and personalized health initiatives. For example, the World Health Organization recommends consuming a minimum of five servings of fruits and vegetables per day, yet the vast majority of adults (60%–87%) worldwide report consuming less. Maintaining adherence for preventative health care practices, such as watching dietary food intake, including adequate fruit and vegetable consumption and supplementing the diet with protein, phytonutrients, and fish oil is often a challenge for consumers, especially if the experience is less than appealing.

This chapter covers research that addresses the opportunities and the challenges for researchers exploring the healthcare supplement category. Case studies that highlight the need for in-context research include preparation and palatability of protein powders, digestive comfort from different omega fish oil treatments, and aroma, swallowing ease, adherence/compliance, and physiological effects of a vitamin, mineral, and phytonutrient tablet product. Most cases cover multiple and generally complementary studies involving a sequence of varied methods and contexts, which together provide more complete understanding and guidance. Research contexts include the laboratory for sensory descriptive profiling in combination with Central Location and Home Use Testing for consumer evaluations.

A more thorough understanding of consumer choice and consumption is achieved by conducting research in varied contexts. Global research findings representing a variety of case studies of different supplement types and research contexts herein suggest that the sensory, hedonic, psychometric, and emotional attributes represent different dimensions that can be used to understand, even influence, consumer choice and consumption behaviors for healthcare supplements.

The Electronic Health Records for Clinical Research (EHR4CR) technological platform has been developed to enable the trustworthy reuse of hospital electronic health records data for clinical research. The EHR4CR platform can enhance and speed up clinical research scenarios: protocol feasibility assessment, patient identification for recruitment in clinical trials, and clinical data exchange, including for reporting serious adverse events. Our objective was to seed a multi-stakeholder ecosystem to enable the scalable exploitation of the EHR4CR platform in Europe, and to assess its economic sustainability.

Market analyses were conducted by a multidisciplinary task force to define an EHR4CR emerging ecosystem and multi-stakeholder value chain. This involved mapping stakeholder groups and defining their unmet needs, incentives, potential barriers for adopting innovative solutions, roles and interdependencies. A comprehensive business model, value propositions, and sustainability strategies were developed accordingly. Using simulation modelling (including Monte Carlo simulations) and a 5-year horizon, the potential financial outcomes of the business model were forecasted from the perspective of an EHR4CR service provider.

A business ecosystem was defined to leverage the EHR4CR multi-stakeholder value chain. Value propositions were developed describing the expected benefits of EHR4CR solutions for all stakeholders. From an EHR4CR service provider’s viewpoint, the business model simulation estimated that a profitability ratio of up to 1.8 could be achieved at year 1, with potential for growth in subsequent years depending on projected market uptake.

By enhancing and speeding up existing processes, EHR4CR solutions promise to transform the clinical research landscape. The ecosystem defined provides the organisational framework for optimising the value and benefits for all stakeholders involved, in a sustainable manner. Our study suggests that the exploitation of EHR4CR solutions appears profitable and sustainable in Europe, with a growth potential depending on the rates of market and hospital adoption.

Chronic diseases are nowadays the leading cause of mortality and morbidity worldwide, being largely promoted by unhealthy lifestyle behaviors. Indeed, sedentariness, poor diet, smoking, and alcohol abuse are common risk factors for cardiovascular disease and other chronic conditions, accounting for a great amount of healthcare costs.

Behavioral informatics interventions have the potential to assist individuals (both patients and healthy consumers) in modifying behaviors to improve physical, mental, or behavioral health. In particular, social media interventions have several advantages, including wide accessibility across geographical barriers, ubiquity, and cost-efficiency. Nowadays, the growth in social networking sites brings new opportunities to disseminate public health interventions and promote large improvements in the field of health behavior change.

This chapter discusses the importance of health behavior change and the numerous theories, models, and frameworks that attempt to explain its processes, as well as provides possible avenues for the use of social media in behavior change interventions.

Unplanned 30-day hospital readmission account for roughly $17 billion in annual Medicare spending. Many factors contribute to unplanned hospital readmissions and multiple models have been developed over the years to predict them. Most researchers have used insurance claims or administrative data to train and operationalize their Readmission Risk Prediction Models (RRPMs). Some RRPM developers have also used electronic health records data; however, using health informatics exchange data has been uncommon among such predictive models and can be beneficial in its ability to provide real-time alerts to providers at the point of care.

We conducted a semi-systematic review of readmission predictive factors published prior to March 2013. Then, we extracted and merged all significant variables listed in those articles for RRPMs. Finally, we matched these variables with common HL7 messages transmitted by a sample of health information exchange organizations (HIO).

The semi-systematic review resulted in identification of 32 articles and 297 predictive variables. The mapping of these variables with common HL7 segments resulted in an 89.2% total coverage, with the DG1 (diagnosis) segment having the highest coverage of 39.4%. The PID (patient identification) and OBX (observation results) segments cover 13.9% and 9.1% of the variables. Evaluating the same coverage in three sample HIOs showed data incompleteness.

HIOs can utilize HL7 messages to develop unique RRPMs for their stakeholders; however, data completeness of exchanged messages should meet certain thresholds. If data quality standards are met by stakeholders, HIOs would be able to provide real-time RRPMs that not only predict intra-hospital readmissions but also inter-hospital cases.

A RRPM derived using HIO data exchanged through may prove to be a useful method to prevent unplanned hospital readmissions. In order for the RRPM derived from HIO data to be effective, hospitals must actively exchange clinical information through the HIO and develop actionable methods that integrate into the workflow of providers to ensure that patients at high-risk for readmission receive the care they need.

There is a critical need for public health interventions to support the independence of older adults as the world's population ages. Health smart homes (HSH) and home-based consumer health (HCH) technologies may play a role in these interventions.

We conducted a systematic review of HSH and HCH literature from indexed repositories for health care and technology disciplines (e.g., MEDLINE, CINAHL, and IEEE Xplore) and classified included studies according to an evidence-based public health (EBPH) typology.

One thousand, six hundred and thirty-nine candidate articles were identified. Thirty-one studies from the years 1998–2011 were included. Twenty-one included studies were classified as emerging, 10 as promising and 3 as effective (first tier).

The majority of included studies were published in the period beginning in the year 2005. All 3 effective (first tier) studies and 9 of 10 of promising studies were published during this period. Almost all studies included an activity sensing component and most of them used passive infrared motion sensors. The three effective (first tier) studies all used a multicomponent technology approach that included activity sensing, reminders and other technologies tailored to individual preferences. Future research should explore the use of technology for self-management of health by older adults; social support; and self-reported health measures incorporated into personal health records, electronic medical records, and community health registries.