EQ-5D-5L Population Norms for Italy.

OBJECTIVES: This study aimed to provide normative data obtained in response to the EQ-5D-5L questionnaire in Italy and compare this with data from other countries. METHODS: A sample of the Italian adult population (aged ≥ 18 years) was recruited and interviewed online using videoconferencing software (Zoom) between November 2020 and February 2021. The distribution of answers was estimated as per the descriptive system of the EQ-5D-5L, and descriptive statistics were calculated for the EQ VAS score and EQ-5D-5L index value in the whole sample and relevant subgroups. An ordinary least square (OLS) regression was performed to evaluate the impact of sociodemographic variables on EQ-5D-5L results. Lastly, a comparison was made with EQ-5D-5L population norms of other countries. Data analysis was performed using Microsoft Excel and Stata 13. RESULTS: Overall, 1182 people representative of the Italian population (2020) in terms of sex and geographical area responded to the survey. Of the 3125 potential EQ-5D-5L health states, only 106 (3.4%) were selected, and the '11111' and '11112' states were chosen by half of the participants. In terms of EQ-5D-5L dimensions, the frequency of any problems (from slight to extreme) associated with anxiety and depression was high among the very young (18-24 years, 56.0%) and in women of all ages (49.7%). The mean index value (± standard deviation [SD]) was 0.93 (± 0.11) for the entire sample and gradually decreased with age, moving from 0.95 (± 0.06) in the youngest group (18-24 years) to 0.91 (± 0.13) in the oldest age group (≥ 75 years). Similarly, the mean EQ VAS score (± SD) was 81.8 (± 13.5), and decreased from 87.0 (± 8.9) in the 18-24 years age group to 75.1 (± 16.4) among participants > 75 years of age. The existence of self-reported chronic conditions (e.g., cardiovascular disease), female sex, and social assistance recipiency were negatively associated with the EQ-5D index value, while the EQ VAS score was significantly lower in people with chronic conditions and aged > 55 years. Conversely, higher income levels had a positive impact on both the EQ-5D index value and the EQ VAS score. Lastly, both the EQ-5D index value and EQ VAS score in Italy were, on average, higher than in most European countries. CONCLUSIONS: EQ-5D-5L population norms provide useful insights into the health status of the Italian population and can be used as a reference for other surveys using the same instrument.

Recommendations for developing a lifecycle, multidimensional assessment framework for mobile medical apps.

Digital health and mobile medical apps (MMAs) have shown great promise in transforming health care, but their adoption in clinical care has been unsatisfactory, and regulatory guidance and coverage decisions have been lacking or incomplete. A multidimensional assessment framework for regulatory, policymaking, health technology assessment, and coverage purposes based on the MMA lifecycle is needed. A targeted review of relevant policy documents from international sources was conducted to map current MMA assessment frameworks, to formulate 10 recommendations, subsequently shared amongst an expert panel of key stakeholders. Recommendations go beyond economic dimensions such as cost and economic evaluation and also include MMA development and update, classification and evidentiary requirements, performance and maintenance monitoring, usability testing, clinical evidence requirements, safety and security, equity considerations, organizational assessment, and additional outcome domains (patient empowerment and environmental impact). The COVID-19 pandemic greatly expanded the use of MMAs, but temporary policies governing their use and oversight need consolidation through well-developed frameworks to support decision-makers, producers and introduction into clinical care processes, especially in light of the strong international, cross-border character of MMAs, the new EU medical device and health technology assessment regulations, and the Next Generation EU funding earmarked for health digitalization.

Response to COVID-19: was Italy (un)prepared?

On 31st January 2020, the Italian cabinet declared a 6-month national emergency after the detection of the first two COVID-19 positive cases in Rome, two Chinese tourists travelling from Wuhan. Between then and the total lockdown introduced on 22nd March 2020 Italy was hit by an unprecedented crisis. In addition to being the first European country to be heavily swept by the COVID-19 pandemic, Italy was the first to introduce stringent lockdown measures. The SARS-CoV-2 outbreak and related COVID-19 pandemic have been the worst public health challenge endured in recent history by Italy. Two months since the beginning of the first wave, the estimated excess deaths in Lombardy, the hardest hit region in the country, reached a peak of more than 23,000 deaths. The extraordinary pressures exerted on the Italian Servizio Sanitario Nazionale (SSN) inevitably leads to questions about its preparedness and the appropriateness and effectiveness of responses implemented at both national and regional levels. The aim of the paper is to critically review the Italian response to the COVID-19 crisis spanning from the first early acute phases of the emergency (March-May 2020) to the relative stability of the epidemiological situation just before the second outbreak in October 2020.

An EQ-5D-5L value set for Italy using videoconferencing interviews and feasibility of a new mode of administration.

OBJECTIVES: To test the feasibility of using videoconferencing (VC) administered interviews and to derive an EQ-5D-5L value set for Italy. METHODS: Preferences were collected using the EuroQol standardized valuation protocol (EQ-VT) administered via VC. Two valuation methods were employed, composite time trade-off (cTTO) and discrete choice experiment (DCE). Technical, organizational and protocol feasibility were tested in a pilot of 198 interviews. Upon positive assessment, data collection continued with a target sample of 1000-1200 participants including the pilot. Quality control (QC) procedures were employed to monitor interviewers' performance during the pilot and the data collection. Data were modelled using GLS, Tobit, Logit and Hybrid models with different error specifications. Monotonicity of coefficients, statistical significance, and theoretical considerations informed the model choice. RESULTS: Dropouts and technical problems occurred in less than 5% of the 198 pilot interviews. Protocol compliance was demonstrated with significant improvements in QC parameters and limited interviewers' effects, for all interviewers. Overall, interviewers were satisfied with this mode of administration, highlighting it allows flexibility and efficient scheduling. Based on these results, VC was deemed as a feasible mode of administration. The study collected preferences for 1182 responders, including the pilot interviews. The demographic characteristics of the sample were representative of the Italian general population for age, gender and geographical macro-areas. The hybrid Tobit heteroscedastic model without constant estimated on the full sample (including pilot) was selected for the derivation of the value set. Values ranged from -0.571 for the worst health state (55555) to 1 for the best health state (11111). Pain/discomfort registered the largest decrement, followed by mobility, anxiety/depression, self-care, and usual activities. 523 health states were worse than dead. CONCLUSIONS: VC is viable for the conduct of valuation interviews. The Italian value set for the EQ-5D-5L can be used for value determinations of health technologies.

Development features and study characteristics of mobile health apps in the management of chronic conditions: a systematic review of randomised trials.

COVID-19 pandemic challenges have accelerated the reliance on digital health fuelling the expanded incorporation of mobile apps into healthcare services, particularly for the management of long-term conditions such as chronic diseases (CDs). However, the impact of health apps on outcomes for CD remains unclear, potentially owing to both the poor adoption of formal development standards in the design process and the methodological quality of studies. A systematic search of randomised trials was performed on Medline, ScienceDirect, the Cochrane Library and Scopus to provide a comprehensive outlook and review the impact of health apps on CD. We identified 69 studies on diabetes (n = 29), cardiovascular diseases (n = 13), chronic respiratory diseases (n = 13), cancer (n = 10) or their combinations (n = 4). The apps rarely adopted developmental factors in the design stage, with only around one-third of studies reporting user or healthcare professional engagement. Apps differed significantly in content, with a median of eight behaviour change techniques adopted, most frequently pertaining to the 'Feedback and monitoring' (91%) and 'Shaping knowledge' (72%) categories. As for the study methodologies, all studies adopted a traditional randomised control trial (RCT) design, with relatively short follow-ups and limited sample sizes. Findings were not significant for the majority of studies across all CD, with most RCTs revealing a high risk of bias. To support the adoption of apps for CD management, this review reinforces the need for more robust development and appropriate study characteristics to sustain evidence generation and elucidate whether study results reflect the true benefits of apps or a biased estimate due to unsuitable designs.

Distinguishing features in the assessment of mHealth apps.

Introduction: The unparalleled surge in digital health adoption during the COVID-19 pandemic has emphasized the potential of mHealth apps. However, the quality of available evidence is generally low, and regulatory frameworks have focused on apps with medical purposes only, overlooking apps with significant interactions with patients that may require stronger oversight.Areas covered: To support this expanded evidence generation process, we identified the reasons that distinguish mHealth apps compared to medical devices at large and that should differentially feature their assessment. mHealth apps are characterized by the iterative nature of the corresponding interventions, frequent user interactions with a non-linear relationship between technology usage, engagement and outcomes, significant organizational implications, as well as challenges associated with genericization, their broad diagnostic potential, and price setting.Expert Opinion: The renewed reliance experienced during the pandemic and the unprecedented injection of resources through recovery instruments can further boost the development of apps. Only robust evidence of the benefits of mHealth apps will persuade health-care professionals and beneficiaries to systematically deploy them. Regulatory bodies will need to question their current approaches by adopting comprehensive evaluation processes that adequately consider the specific features of mHealth apps.

Harnessing Digital Health Technologies During and After the COVID-19 Pandemic: Context Matters.

A common development observed during the COVID-19 pandemic is the renewed reliance on digital health technologies. Prior to the pandemic, the uptake of digital health technologies to directly strengthen public health systems had been unsatisfactory; however, a relentless acceleration took place within health care systems during the COVID-19 pandemic. Therefore, digital health technologies could not be prescinded from the organizational and institutional merits of the systems in which they were introduced. The Italian National Health Service is strongly decentralized, with the national government exercising general stewardship and regions responsible for the delivery of health care services. Together with the substantial lack of digital efforts previously, these institutional characteristics resulted in delays in the uptake of appropriate solutions, territorial differences, and issues in engaging the appropriate health care professionals during the pandemic. An in-depth analysis of the organizational context is instrumental in fully interpreting the contribution of digital health during the pandemic and providing the foundation for the digital reconstruction of what is to come after.