We review the origins and history of community psychiatry and the challenges posed to it by advancing technology and the neoliberal political economy and society that have prevailed since the 1990s. We summarise both achievements and shortcomings and argue that the term ‘community’ fails to acknowledge the gap between its original ambition and the outcomes of its implementation. We argue that, because of the changes that have taken place, the implementation of community psychiatry's objectives as conceived originally is likely to continue to fail. To sharpen current awareness and thinking and optimise future policy discourse and service strategies we revisit the concept of ‘metacommunity’. This is a historical descriptive label that aims to encapsulate the fundamental transformations that have taken place. These in turn demand of psychiatrists and other mental health providers both more socially critical thinking and mental health activism in the public sphere. Ultimately, beyond both community and metacommunity psychiatry, what is required is a democratic psychiatry.

Older adults with a chronic health condition (e.g. hypertension) use various self-management methods. Healthcare technologies have the potential to support health self-management. However, it is necessary to understand the acceptance of these technologies as a precursor to older adults’ adoption and integration into their health plan. Our focus was on the factors older adults with hypertension initially consider when introduced to three new healthcare technologies that might support their health self-management. We compared their considerations for a blood pressure monitor, an electronic pillbox and a multifunction robot to simulate incrementally more complex technologies. Twenty-three participants (aged 65–84) completed four questionnaires and a semi-structured interview. The interview transcripts were analysed using a thematic analysis approach. We identified the factors that were frequently mentioned among the participants for each of the three healthcare technologies. The factors that older adults initially considered were familiarity, perceived benefits, perceived ease of use, perceived need for oneself, relative advantage, complexity and perceived need for others. Upon further reflection, participants considered advice acceptance, compatibility, convenience, facilitating conditions, perceived usefulness, privacy, subjective norm, and trust. We integrated the factors that older adults considered into the Healthcare Technology Acceptance Model (H-TAM), which elucidates the complexity of healthcare technology acceptance and provides guidance for future explorations.

Long-term behaviour changes are critical to answering societal and individual challenges surrounding areas such as sustainability and health. Current understanding of how to bring about sustained behaviour is focused on the identification of Behaviour Change Techniques (BCTs) without explicit guidance on how these should be matched with technological solutions. Based on this gap we set out to answer the research question: What is the relationship between BCTs and interactive immersive technologies with respect to long-term, sustainable behaviour? To this end, we report a literature review on technology trends in the fields of human computer interaction, human robot interaction, and game design. Based on this review we develop three main contributions with implications for design theory and practice. First, we propose a number of characteristics and mechanisms in emerging immersive technologies. Second, we highlight technological pathways connected to specific BCT clusters likely to be disrupted: technology as a conveyor of information, an augmenter of feedback, and as an embodiment of empathy. Third, we explore these connections between BCT clusters and the actual technological interventions.

Objectives: Health technology assessment (HTA) yields information that can be ideally used to address deficiencies in health systems and to create a wider understanding of the impact of different policy considerations around technology reimbursement and use. The structure of HTA programs varies across different jurisdictions according to decision-maker needs. Moreover, conducting HTA requires specialized skills. Effective decision making should include multiple criteria (medical, economic, technical, ethical, social, legal, and cultural) and requires multi-disciplinary teams of experts working together to produce these assessments. A workshop explored the multi-disciplinary skills and competencies required to build an effective and efficient HTA team, with a focus on low- and middle-income settings.

Methods: This proceeding summarizes main points from a workshop on capacity building, drawing on presentations and group discussions among attendees including different points of view.

Results and Conclusions: The workshop and thus this study would have benefited from a larger variety of stakeholders. Therefore, the conclusions arising from the workshop are not the opinion of a representative sample of HTA professionals. Nonetheless, organizations and speakers were carefully selected to provide a valuable approach to this theme. Thus, these proceedings highlight some of the gaps and needs in the education and training programs offered worldwide and calls for further investigation.

Objectives: The EuroScan International Network is a global network of publicly funded early awareness and alert (EAA) systems for health technologies. We describe the EuroScan member agency systems and methods, and highlight the potential for increased collaboration.

Methods: EuroScan members completed postal questionnaires supplemented with telephone interviews in 2012 to elicit additional information and check equivalence of responses. Information was updated between March and May 2013.

Results: Fifteen of the seventeen member agencies responded. The principal purpose of agencies is to inform decisions on coverage or reimbursement of health services and decisions on undertaking secondary research. The main users of information are national governments; health professionals; health services purchasers, commissioners, and decision makers; and healthcare providers. Most EuroScan agencies are small with almost half having fewer than two whole time equivalent staff. Ten agencies use both active and passive identification approaches, four use only active approaches. Most start identification in the experimental or investigational stages of the technology life cycle. All agencies assessed technologies when they are between the investigational and established, but under diffusion stages. Barriers to collaboration revolve around different system aims, purposes, and requirements; a lack of staff, finance, or opportunity; language differences; and restrictions on dissemination.

Conclusions: Although many barriers to collaboration were identified, the majority of agencies were supportive of increased collaboration either involving the whole EuroScan Network or between individual agencies. Despite differences in the detailed identification processes, members thought that this was the most feasible phase to develop additional collaboration.

Objectives: The aim of this study was to assess the accuracy of the English National Horizon Scanning Centre (NHSC) in identifying and filtering pharmaceutical developments using end user and international collaborator databases of emerging technologies as proxies for new drugs of likely significance to health services and/or patients.

Methods: We used the NHSC information system and the list of National Institute for Health and Clinical Excellence (NICE) technology appraisals to estimate the false positive rate for NHSC identification, filtration, and reporting. We assessed the sensitivity of NHSC identification and filtration of pharmaceuticals for NICE technology appraisals from 1999 to the end of December 2010, and for pharmaceuticals entered into the EuroScan International Network database.

Results: We estimate that overall NHSC identification, filtration and reporting had a positive predictive value of 0.39 (95 percent CI, 0.36 to 0.43) and a false positive rate of 60 percent. Using NICE appraisals and EuroScan's database as proxies for pharmaceuticals of significance, we estimate the NHSC sensitivity over the 10-year period at 0.92 (95 percent CI, 0.89 to 0.95) and 0.89 (95 percent CI, 0.82 to 0.96) respectively.

Conclusions: Our results suggest that the NHSC has performed well in terms of sensitivity over the past decade, but that the false positive rate of 60 percent may indicate that the filtration criteria for pharmaceuticals could be tightened for increased efficiency. Future evaluations of EAA systems should include an element of external review and explore the level of accuracy acceptable to funders and customers of such systems.

Objectives: The aim of this study was to benchmark the proposal forms used by a sample of Italian hospitals to inform the budget process for the adoption of new technology to understand the relationship with the guidelines provided by the Health Technology Assessment (HTA) literature.

Methods: A literature review was first undertaken to identify the frameworks developed to support decision making regarding new technology at a hospital level. A checklist of criteria drawn up according to five main perspectives (technology, patient, organization, economics, and level of evidence) has been formalized to review and compare the collected proposal forms.

Results: The “technology” perspective appears to have been broadly covered. The “patient” perspective has focused to clinical issues and partially neglects other dimensions such as patient satisfaction and potential adverse events. The “organization” dimension has paid little attention to change management. The “economics” dimension has been broadly covered, even though a sensitivity analysis has not been considered. The “level of evidence” that is required for submitting the proposal form is little.

Conclusions: The proposal forms used to inform the budget process regarding the adoption of new technology are accountable for a limited set of dimensions from among those proposed in literature. Further research is required to understand how to render technology assessment multidimensional, multidisciplinary, evidence-based, and accountable at a hospital level.

Objectives: This study investigated the benefits of and barriers to user involvement in medical device technology development and evaluation.

Methods: A structured review of published literature in peer-reviewed journals was conducted.

Results: This literature review revealed that the main benefits of user involvement were an increased access to user needs, experiences, and ideas; improvements in medical device designs and user interfaces; and an increase in the functionality, usability, and quality of the devices. On the other hand, resource issues, particularly those of time and money were found the key impediments to involving users in the development and evaluation of medical device technologies. This study also has categorized both the benefits of and barriers to user involvement.

Conclusions: The involvement of users in medical device technology development and evaluation requires resources, which are limited; however, this involvement is essential from both users and manufacturers perspectives.

Objectives: Early warning systems are an integral part of many health technology assessment programs. Despite this finding, to date, there have been no quantitative evaluations of the accuracy of predictions made by these systems. We report a study evaluating the accuracy of predictions made by the main United Kingdom early warning system.

Methods: As prediction of impact is analogous to diagnosis, a method normally applied to determine the accuracy of diagnostic tests was used. The sensitivity, specificity, and predictive values of the National Horizon Scanning Centre's prediction methods were estimated with reference to an (imperfect) gold standard, that is, expert opinion of impact 3 to 5 years after prediction.

Results: The sensitivity of predictions was 71 percent (95 percent confidence interval [CI], 0.36–0.92), and the specificity was 73 percent (95 percent CI, 0.64–0.8). The negative predictive value was 98 percent (95 percent CI, 0.92–0.99), and the positive predictive value was 14 percent (95 percent CI, 0.06–0.3).

Conclusions: Forecasting is difficult, but the results suggest that this early warning system's predictions have an acceptable level of accuracy. However, there are caveats. The first is that early warning systems may themselves reduce the impact of a technology, as helping to control adoption and diffusion is their main purpose. The second is that the use of an imperfect gold standard may bias the results. As early warning systems are viewed as an increasingly important component of health technology assessment and decision making, their outcomes must be evaluated. The method used here should be investigated further and the accuracy of other early warning systems explored.

Objectives: This preliminary study had two objectives: a) charting the considerations relevant to decisions about acquisition of new medical technology at the hospital level; and b) creating a basis for the development of a research tool that will examine the function of the Israeli health system in assessment of new medical technologies.

Methods: A comprehensive literature review and in-depth interviews with decision makers at different levels allowed formulation of criteria considered by decision makers when they decide to purchase and use (or disallow the use) of new medical technology. The resulting questionnaire was sent to medical center directors, along with a letter explaining the goals of the study. The questionnaire included 31 possible considerations for decision making concerning the acquisition of new medical technology by medical centers. The interviewees were asked to indicate the relevance of each consideration in the decision-making process.

Results: The most relevant criteria for the adoption of new technologies related to the need for a large capital investment, clinical efficacy of the technology as well as its influence on side effects and complication rates, and a formal approval by the Ministry of Health. Most interviewees stated that pressures exerted by the industry, by patients, or by senior physicians in the hospital are less relevant to decision making. Very small and usually not statistically significant differences in the ranking of hospital directors were found according to the hospitals' ownership, size, or location.

Conclusions: The present study is a basis for a future study that will map and describe the function of hospital decision makers within the area of new technology assessment and the decision-making process in the adoption of new healthcare technologies.