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Background: During 2020, COVID-19 had a diversified distribution in Italy, the first nation in Europe to experience the outbreak of the epidemic. This was linked to geographical differences in population density and distribution of healthcare facilities, including Emergency Departments (EDs). This study aims to assess the impact of the pandemic on ED utilization in 2020 across different subpopulations and geographical locations in Italy. Methods: We used anonymized data from a survey conducted by the Italian National Institute of Statistics on 25,000 families to analyze the yearly rate of people who used EDs from 2015 to 2020. The rate of persons who accessed ED services in 2020 per 1,000 population was compared with those of the previous non-pandemic years. Results: The number of people accessing EDs in 2020 was 32.3% lower, although this reduction was not uniform across the 21 regions / autonomous provinces. People aged 0-14 years experienced the highest reduction in ED visits. In 2020, low educational level people exhibited a steeper reduction in the use of EDs. Conclusions: This study shows a significant drop in EDs use especially by children; the population section mostly affected by the effects of the pandemic. This study also confirms that education and socio-economic status are important determinants of ED use. The heterogeneous reduction in ED use across the regions of Italy highlights the need to further investigate the impact of this pattern on the health of the population, as well as to define adequate preparedness strategies to face future emergencies.
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Background Plenty of literature reported the applicability and usefulness of telemedicine and teleassistance (TMTA) services in the management of diabetes and other chronic conditions. Specifically, TMTA proved to be effective for conditions that require radical lifestyle modifications, tailored pharmacological interventions, and periodic monitoring of clinical health status. The purpose of this study is to investigate the individual and contextual determinants of the perceived quality (PQ) of the telemedicine and teleassistance (TMTA) services and the willingness to continue (WC) with them among patients with diabetes using TMTA during the COVID-19 pandemic in one large region of Italy (Emilia-Romagna). Methods A structured survey was administered to patients with type 1 and 2 diabetes who used TMTA services during the first wave of the COVID-19 pandemic. The questionnaire was comprised of questions on TMTA service experience and participants’ socio-demographic characteristics. Multiple regression models investigated the independent factors associated with PQ (score 1-100) and WC (yes/no). Results The final analysis included 569 patients with diabetes (54.7% female), with an average age of 58.1 years. TMTA services’ PQ and WC were high. A higher education (OR = 1.83;95%CI 1.04, 3.31) and being unemployed (OR = 2.57;95%CI 1.17, 6.02) were factors associated with an increased WC. Older age was negatively related to PQ (b = −3.6;95%CI −6.8, −0.29). Perceived support from TMTA service was positively associated with PQ (b = 10.1;95%CI 5.1, 15) and WC (OR = 2.03;95%CI 1.07, 3.85). Perceived increase in disease self-management was positively associated with PQ (b = 5.3;95%CI 0.24, 10) and WC (OR = 7.11;95%CI 4.04, 12.8). Conclusions Our study identified several determinants of PQ and WC. These socio-demographic and patient-perception related factors should be considered in the implementation of care pathways integrating in-person visits with TMTA services. Key messages • Socio-demographic factors play a crucial role in TMTA acceptance and should be taken into due consideration when implementing health pathways integrating in-person visits with TMTA services. • Health workers should always try to improve patients’ self-management skills and should always make patients feel supported. This is also true in the digital health era.
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Background Although investigating the patterns of COVID-19 excess mortality (EM) is relevant, understanding the effects of the pandemic on cause-specific mortality is even crucial and should also be assessed, as this metric allows for a more detailed analysis of the true impact of the pandemic. The aim of this systematic literature review is to estimate the impact of the pandemic on different causes of death, providing a quantitative and qualitative analysis of the phenomenon. Methods We searched MEDLINE to identify studies that reported cause-specific mortality during the COVID-19 pandemic. We adopted several inclusion criteria: original article;assessed at least one cause-specific mortality during the pandemic;assessed causes of deaths using the ICD-10 classification;reporting of at least one of the following outcomes: cause-specific mortality estimates or cause-specific EM;full-length articles. Several relevant data were extracted (e.g. publication year, data stratification, territory, country income level, all-cause EM, and cause-specific mortality, etc.). Results The search identified 548 articles. After title, and full-text screening, we extracted relevant data from the final set of 14 articles. Cause-specific mortality was reported using different units of measurement. Only 9 studies reported the statistical significance and/or confidence intervals. The most frequently analyzed causes of death were cardiovascular diseases (n = 11), cancer (n = 7), diabetes (n = 6), and suicide (n = 5). We found very heterogeneous patterns of cause-specific mortality, for all the specific causes of deaths, except for suicide and road accident. Conclusions The impact of the pandemic on cause-specific deaths has been very heterogeneous and the analyses conducted so far are not exhaustive. We advocate for the urgent need to find a consensus to define uniform methodological approaches to establish the true burden of the COVID-19 pandemic on non-COVID-19 mortality. Key messages • We reviewed the body of literature to estimate the impact of the COVID-19 pandemic on different causes of death, and to provide a quantitative and qualitative analysis of the phenomenon. • We did not identify unique patterns of cause-specific mortality due to too varied approaches in terms of disease classification and coding, and methodologies used for estimating mortality.
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sentences were classified by 2 domain experts into 7 types: Aim (A), Participants (P), Intervention (I), Outcome (O), Method (M), Results (R), and Conclusion (C). The performance of the tool was compared with that of the experts in terms of precision, recall, and F1. Results The classifier proved to have a 76% overall accuracy. Precision, recall, and F1 were above 75% for all types of sentences except I, M, and P. Conclusions The results indicate a promising ability of the semi-automated classifier to predict expert-validated labels on s of different topics. Our proposed tool is expected to significantly reduce the effort for producing medical guidelines and therefore have a strong, positive impact, particularly in emergency scenarios. The COKE Project also represents a call-to-action for similar initiatives, aimed at enhancing the information extraction process in medicine. Key messages • A rapidly changing healthcare requires fast decisions supported by scientific evidence. This is not compatible with the human limits in cognitive skills that reduce the ability to extract information. • The COKE Project aims to speed up the creation of healthcare guidelines, semi-automating parts of the workflow, and supporting the human-performed process of extracting and analyzing contents.
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OBJECTIVES: The objective of the study is to compare excess mortality (EM) patterns and spatial correlation between the first and second wave of the pandemic in Lombardy, the Italian region that paid an extremely high COVID-19-related mortality toll in March and April 2020. STUDY DESIGN: We conducted a longitudinal study using municipality-level mortality data. METHODS: We investigated the patterns and spatial correlation of EM of men aged ≥75 years during the first two pandemic waves (March-April 2020 vs November 2020) of COVID-19, using the mortality data released by the Italian National Institute of Statistics. EM was estimated at the municipality level to accurately detect the critical areas within the region. RESULTS: The areas that were mostly hit during the first wave of COVID-19 were generally spared by the second wave: EM of men aged ≥75 years in the municipality of Bergamo plummeted from +472% in March and April to -13% in November, and in Cremona the variation was from +344% to -19%. Conversely, in November 2020 EM was higher in some areas that had been protected in the first wave of the pandemic. Spatial correlation widely corroborates these findings, as large sections of the hot spots of EM detected in the first wave of the pandemic changed into cold spots in the second wave, and vice versa. CONCLUSIONS: Our results reveal the specular distribution of EM between the first and second wave of the pandemic, which may entail the consequences of social distancing measures and individual behaviors, local management strategies, 'harvesting' of the frailer population and, possibly, acquired immune protection. In conclusion, our findings support the need for continuous monitoring and analysis of mortality data using detailed spatial resolution.