GATEKEEPER's Strategy for the Multinational Large-Scale Piloting of an eHealth Platform: Tutorial on How to Identify Relevant Settings and Use Cases.

BACKGROUND: The World Health Organization's strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. OBJECTIVE: We aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. METHODS: The selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. RESULTS: Seven European countries were selected, covering Europe's geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence-based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. CONCLUSIONS: This paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space.

Correlates and Predictors of PTSD Symptoms Among Healthcare Workers During the COVID-19 Pandemic: Results of the egePan-VOICE Study.

Background: The COVID-19 pandemic has led to ongoing challenges for healthcare systems across the world. Previous research has provided evidence for an increased prevalence of depression and anxiety as well as post-traumatic stress disorder (PTSD). In Germany, however, only scarce data on correlates and predictors for PTSD symptomatology in the context of the COVID-19 pandemic among healthcare workers (HCW) are available. Methods: This research is part of a large prospective web-based survey (egePan-VOICE study) among HCW in Germany. The current sample (N = 4,724) consisted of physicians (n = 1,575), nurses (n = 1,277), medical technical assistants (MTA, n = 1,662), and psychologists (n = 210). PTSD symptomatology was measured using the abbreviated version of the Impact of Event Scale (IES-6). In addition, sociodemographic, occupational, COVID-19-related, psychological (e.g., depressive symptoms and generalized anxiety), as well as work-related variables were assessed. Results: Our findings revealed significant higher PTSD symptoms with medium effect sizes among HCW reporting an increased self-report burden during the pandemic, increased fear of becoming infected or infecting relatives with the virus, sleep problems, feeling physically or mentally exhausted, as well as increased levels of depressiveness and generalized anxiety. According to multiple linear regression analysis, the most relevant predictors for higher IES-6 scores were increased level of generalized anxiety and depressiveness, increased fear of infecting relatives, as well as medical profession (MTA compared to physicians). Conclusion: Despite the cross-sectional design of our study, the here identified associations with PTSD symptomatology may provide a basis for future preventive interventions.

Cardiovascular recovery after workload in German shift workers in the hotel and catering industry: results of 24-hour-ambulatory monitoring of heart rate and blood pressure.

PURPOSE: Shift work is associated with an impairment of sleep-wake cycles that can affect cardiovascular recovery (CR) negatively. The aim of this study was to examine CR of shift and day workers in the hotel and catering industry (HCI) and identify predictors of CR. METHODS: The sample consisted of 64 alternating and 96 day workers in the HCI. Monitoring of blood pressure (BP) and heart rate (HR) was conducted for 24 hours per working day during work, leisure and sleep. The CR process was examined for differences between work and leisure, work and sleep regarding a reduction in BP and HR. Lifestyle (physical activity, smoking, drinking) was assessed through questionnaires, BP over a four-day, self-assessment period (38% hypertensives). Participants taking BP medication (n = 12) were excluded from analyses. RESULTS: Shift workers had significantly higher BP (Ø 146/87 vs. Ø 140/84 mmHg; p = 0.034-0.044) and HR (Ø 86 vs. 82 bpm; p = 0.032) during their work phase verses day workers. There were no differences found for the CR between work and leisure nor work and sleep. As predictors of the CR, classic cardiovascular indicators (blood pressure status, smoking, age, physical activity, sex) were found which explains between 14% (HR) and 30% (BP) of the variance. Shift work was not a predictor for CR. CONCLUSIONS: Employees in the HCI show that their CR is mainly determined by the known cardiovascular indicators and less by shift work. This effect needs to be discussed in relation to the job requirements and the cardiovascular health of the employees.

Early Detection of Undiagnosed Hypertension Based on Occupational Screening in the Hotel and Restaurant Industry.

Blood pressure is the most important, modifiable risk factor for cardiovascular diseases. Lifestyle factors and also workload are the main, potential risk factors for the development of hypertension. This study focused on the early detection of unknown hypertension by screening employees in the hotel and restaurant industry (HRI). 148 HRI employees without hypertension (mean age: 34 years, men: 45%) self-measured their blood pressure during rest and for 24 hours of a normal workday. Individuals with a resting blood pressure ≥ 135/85 mmHg were classified as hypertensive. A further analysis investigated whether the currently applicable thresholds for hypertension during work, leisure, and sleep were exceeded on a working day. At rest, 36% of the study participants suffered from hypertension, which increased to 70% under workload and 46% during leisure time and dropped to 8% during sleep. Normal nocturnal dipping (10-20%) occurred only in 18% of cases; 78% were extreme dippers (>20%). Occupational hypertension screening is a suitable component of preventive healthcare. Resting blood pressure measurement alone is insufficient for the early detection of risk individuals and should be supplemented by 24-hour ambulatory blood pressure monitoring under working conditions. The impact of workload on blood pressure needs to be given more attention in the guidelines.