Bridging gaps between registry-holders, Health Technology Assessment (HTA) producers and users is one of the aims of the European Network for HTA (EUnetHTA) Joint Action 3. In this context, a post-launch evidence generation tool is being developed, including a quality standards tool for registries in HTA. The standards tool for registries in HTA will enable, among others, registry owners to consistently collect high quality registry data, and HTA agencies to use proper registry data collected by others as evidence for their assessments. The objective is to present the first draft version of the tool structure, which is going to be piloted during the forthcoming months.

A review and description of the currently available first version (November 2017) sections, items and criteria for HTA studies.

The tool is divided in three sections; “Methodological Information”, “Essential Standards” and “Additional Requirements”. The first section enables users to analyze not only the ability of the registry to answer to research questions but also to check the registry transparency. The second section encloses the essential elements of good practice and evidence quality (therefore all of them must be met before an HTA report can use the registry data). Finally, the third section includes elements of good practice and evidence quality useful to consider in planning and evaluating registries for specific purposes. Although suggestions are defined, the third section item requirements could depend on the individual HTA agency perspectives and needs.

There is a clear growing availability and requirement for real world data for health technology assessment. A piloted and robust registry standards tool for HTA can provide a relevant basis to improve both the evidence generation but also to make more trustful and excellent evaluations.

We aimed to pilot the evaluation of the PEGASO system, a smartphone-based intervention (apps/wearables/game) to improve lifestyles and increase awareness.

We conducted a before-after quasi-experimental pilot controlled study. Teenagers aged 13–16 in a 2:1 (intervention: comparative group [IG:CG]) basis from Spain, Italy and the United Kingdom were recruited. The IG had access to the apps and game for six months, and to smart sensors for the last two months. Schools were recruited by convenience sampling. Participants in both groups undertook (i) anthropometric measurements, (ii) diet (KIDMED), physical activity (PAQ-A) and sleep (HELENA study) validated questionnaires, and (iii) ad-hoc lifestyles knowledge questionnaire. PEGASO, if used, continuously recorded diet and physical activity. User experience was assessed through focus groups.

Five hundred and fifty-eight participants were included (IG:365 / CG:193). The mean (standard deviation; SD) age was 14.8 (0.8), and 52.3 percent were girls. At baseline, mean scores (SD) of KIDMED, PAQ-A and weekday and weekend sleep hours were 5.60 (2.41), 2.48 (0.66), 8.34 (1.07) and 9.99 (1.66), respectively. The percentage of correct answers of lifestyle's knowledge was 65.2 percent (range 13–100 percent). The IG and CG did not show differences for main outcome variables. At six months, a higher percentage of participants in the IG reported an increase of at least one point in the adherence to Mediterranean Diet (43.8 percent vs. 35.4). No differences were observed for other lifestyles. Focus group results showed a predisposition of adolescents to use mHealth for health promotion; the platform was considered to be useful and complete and personalized suggestions were positively valued. Participants reported few limited interest ion the game and several technical issues.

Although participants were motivated and excited about their involvement in the study, and that PEGASO was something desirable for them, the system only showed some impact in specific areas – namely, diet – and could improve some its technological features. Several challenges and opportunities are associated with the implementation of mHealth.

RedETS, created in 2006, is the Spanish network of health technology assessment agencies. The objective of this work is to describe and assess the quality of the full economic evaluation reports on medical devices (FEEMD) carried out by RedETS.

The FEEMD were identified through the RedETS website publications database. Assessments about screening technologies were not included. The characteristics of FEEMD were analyzed using a formal RedETS HTA quality checklist. The characteristics extracted were analyzed through a descriptive univariate analysis.

Results : Twenty-six FEEMD were found. The publication years were distributed quite uniformly over time (approximately 2/year), although 7 were published in 2008 and 7 in 2013. Thirteen studies analyzed cost-utility, ten cost-effectiveness but not utility, and three both. The most frequent medical devices (MD) class analyzed were “In vitro diagnosis MD” (n = 8) and Class III products (8). The most frequent sources to analyze effectiveness were literature (22) and data collected through ad hoc studies (6). The main sources of unit costs were official public tariffs (14), manufacturers direct values (10) analytical accounting of one/more centers or regions (11) and DRGs (7). In relation to the modelling used, 14 evaluations performed Markov models and 7 decision trees. The perspective of 23 studies was that of the National Health System (NHS), and the rest corresponded to the perspective of a specific region (2) or social perspective (1). All studies analyzing time horizons greater than 1.5 years, except for 1, applied discount rates in the modelling. All studies included a sensitivity analysis.

The economic evaluations of MD published by the RedETS accomplish most of the quality checklist aspects and are therefore exhaustive. These FEEMD have been used in the framework of decision making for an efficient management of the NHS basic portfolio.