Changes in private health service utilisation and access to the Italian National Health Service between 2006 and 2019: a cross-sectional comparative study.

OBJECTIVES: Previous research highlighted that in the early 2000s a significant share of the Italian population used and paid out of pocket for private healthcare services even when they could potentially have received the same treatments from the National Health Service (NHS). The decrease in public investments in healthcare and the increase in health needs due to the population ageing may have modified the use of private health services and equity of access to the Italian NHS. This study aims to investigate the change in the prevalence of individuals who have fully paid out of pocket for accessing healthcare services in Italy between 2006 and 2019 and the main reasons behind this choice. DESIGN: Cross-sectional comparative study. PARTICIPANTS AND COMPARISON: Two representative samples of the Italian population were collected in 2006 and 2019. OUTCOME MEASURES: Prevalence of access to fully paid out-of-pocket private health services; type of service of the last fully paid out-of-pocket access; main reasons for the last fully paid out-of-pocket access. RESULTS: We found an increase in the prevalence of people who declared having fully paid out of pocket at least one access to health services during their lifetime from 79.0% in 2006 to 91.9% in 2019 (adjusted OR 2.66; 95% CI 1.98 to 3.58). 'To avoid waiting times' was the main reason and it was significantly more frequent in 2019 compared with 2006 (adjusted OR 1.75; 95% CI 1.45 to 2.11). CONCLUSIONS: This comparative study, conducted the year before the outbreak of the COVID-19 pandemic, highlighted an increase in the prevalence of Italian residents who have fully paid out of pocket for access to health services to overcome long waiting times. Our findings may indicate a reduced access and possible worsening of the equity of access to the public and universalistic Italian NHS between 2006 and 2019.

The impact of the SARS-CoV-2 pandemic on cause-specific mortality patterns: a systematic literature review.

Background: Understanding the effects of the COVID-19 pandemic on cause-specific mortality should be a priority, as this metric allows for a detailed analysis of the true burden 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, Scopus, and ProQuest for studies that reported cause-specific mortality during the COVID-19 pandemic, extracting relevant data. Results: A total of 2413 articles were retrieved, and after screening 22 were selected for data extraction. Cause-specific mortality results were reported using different units of measurement. The most frequently analyzed cause of death was cardiovascular diseases (n = 16), followed by cancer (n = 14) and diabetes (n = 11). We reported heterogeneous patterns of cause-specific mortality, except for suicide and road accident. Conclusions: Evidence on non-COVID-19 cause-specific deaths is not exhaustive. Reliable scientific evidence is needed by policymakers to make the best decisions in an unprecedented and extremely uncertain historical period. We advocate for the urgent need to find an international consensus to define reliable methodological approaches to establish the true burden of the COVID-19 pandemic on non-COVID-19 mortality. Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-022-01755-7.

Biased, wrong and counterfeited evidences published during the COVID-19 pandemic, a systematic review of retracted COVID-19 papers

In 2020 COVID-19 led to an unprecedented stream of papers being submitted to journals. Scientists and physicians all around the globe were in need for information about this new disease. In this climate, many articles were accepted after extremely fast peer-reviews to provide the scientific community with the latest discoveries and knowledge. Unfortunately, this also led to articles retraction due to authors’ misconduct or errors in methodology and/or conclusions. The aim of this study is to investigate the number and characteristics of retracted papers, and to explore the main causes that led to retraction. We conducted a systematic review on retracted articles, using PubMed as data source. Our inclusion criteria were the following: English-language retracted articles that reported original data, results, opinions or hypotheses on COVID-19 and Sars-CoV-2. Twenty-seven retracted articles were identified, mainly reporting observational studies and opinion pieces. Many articles published during the first year of the pandemic have been retracted, mainly due to the authors' scientific misconduct. Duplications, plagiarism, frauds and absence of consent, were the main reasons for retractions. In modern medicine, researchers are required to publish frequently, and, especially during situations like the COVID-19 pandemic, when articles were rapidly published, gaps in peer-reviews system and in the path to scientific publication arose.

Trust in science, medicine and medical providers and its relations to vaccine beliefs: A latent class analysis.

AIM: People may differ in their vaccine-related beliefs (i.e. efficacy, safety, purpose), with a host of factors influencing these differences. This can produce homogeneous groups of individuals who share certain beliefs, attitudes and opinions not only towards vaccines but science and medicine in general. This study aims to characterise distinct subgroups and identify ideal targets for tailored public health interventions to reinforce favourable vaccine beliefs. METHODS: Latent class analysis was used to derive unique profiles using the 2019 Gallup survey of 140 countries. We modelled a composite of vaccine beliefs and regressed this on class membership and relevant covariates. RESULTS: Patterns of item endorsement indicated a well-fitting five-class model, with classes distinguished based on whether individuals sought personal knowledge about science, medicine and health; trusted science and scientists; and reported confidence in the health care system. The lowest levels of vaccine beliefs were reported by a class lacking trust and confidence and the highest levels were reported by a class endorsing trust, confidence and desiring medical and scientific knowledge. Country-level income was moderately related to class membership, and vaccine beliefs were higher in lower-income countries. CONCLUSIONS: Findings suggest that public health campaigns can focus on improving trust in science and medical providers. Efforts to improve vaccination rates can only be achieved when individuals trust science, view the work of scientists as beneficial and hold favourable views towards health care providers. Individuals will then accrue the necessary wisdom to make good health care decisions that affect not only themselves but also their fellow citizens.

Variations of the quality of care during the COVID-19 pandemic affected the mortality rate of non-COVID-19 patients with hip fracture.

INTRODUCTION: As COVID-19 roared through the world, governments worldwide enforced containment measures that affected various treatment pathways, including those for hip fractures (HFs). This study aimed to measure process and outcome indicators related to the quality of care provided to non-COVID-19 elderly patients affected by HF in Emilia-Romagna, a region of Italy severely hit by the pandemic. METHODS: We collected the hospital discharge records of all patients admitted to the hospitals of Emilia-Romagna with a diagnosis of HF from January to May in the years 2019 (pre-pandemic period) and 2020 (pandemic period). We analyzed surgery rate, surgery delays, length of hospital stay, timely rehabilitation, and 30-day mortality for each HF patient. We evaluated monthly data (2020 vs. 2019) with the chi-square and t-test, where appropriate. Logistic regression was used to investigate the differences in 30-day mortality. RESULTS: Our study included 5379 patients with HF. In April and May 2020, there was a significant increase in the proportion of HF patients that did not undergo timely surgery. In March 2020, we found a significant increase in mortality (OR = 2.22). Male sex (OR = 1.92), age ≥90 years (OR = 4.33), surgery after 48 hours (OR = 3.08) and not receiving surgery (OR = 6.19) were significantly associated with increased mortality. After adjusting for the aforementioned factors, patients hospitalized in March 2020 still suffered higher mortality (OR = 2.21). CONCLUSIONS: There was a reduction in the overall quality of care provided to non-COVID-19 elderly patients affected by HF, whose mortality increased in March 2020. Patients' characteristics and variations in processes of care partially explained this increase. Policymakers and professionals involved in the management of COVID-19 patients should be aware of the needs of patients with other health needs, which should be carefully investigated and included in future emergency preparedness and response plans.

Semi-Automatic Systematic Literature Reviews and Information Extraction of COVID-19 Scientific Evidence: Description and Preliminary Results of the COKE Project

The COVID-19 pandemic highlighted the importance of validated and updated scientific information to help policy makers, healthcare professionals, and the public. The speed in disseminating reliable information and the subsequent guidelines and policy implementation are also essential to save as many lives as possible. Trustworthy guidelines should be based on a systematic evidence review which uses reproducible analytical methods to collect secondary data and analyse them. However, the guidelines' drafting process is time consuming and requires a great deal of resources. This paper aims to highlight the importance of accelerating and streamlining the extraction and synthesis of scientific evidence, specifically within the systematic review process. To do so, this paper describes the COKE (COVID-19 Knowledge Extraction framework for next generation discovery science) Project, which involves the use of machine reading and deep learning to design and implement a semi-automated system that supports and enhances the systematic literature review and guideline drafting processes. Specifically, we propose a framework for aiding in the literature selection and navigation process that employs natural language processing and clustering techniques for selecting and organizing the literature for human consultation, according to PICO (Population/Problem, Intervention, Comparison, and Outcome) elements. We show some preliminary results of the automatic classification of sentences on a dataset of s related to COVID-19.

The impact of health policies and vaccine rollout on the COVID-19 pandemic waves in Italy.

Background: Over the course of the COVID-19 pandemic in Italy, different response measures were taken to contain the spread of the virus. These include a variety of non-pharmaceutical interventions and a mass vaccination campaign. While not definitive, epidemiological measures provide some indication of the impact of such measures on the dynamics of the pandemic and lessons to better prepare for future emergencies. Objective: To describe the impact of vaccine rollout and health policies on the evolution of the COVID-19 pandemic in Italy from March 2020 to October 2021 using a set of epidemiological indicators. Methods: We performed a time-trend analysis of new confirmed COVID-19 cases, patients in hospital, and deaths. Using line charts, we informally assessed the relationship of these indicators with the immunization campaign and other health policies. Daily aggregate data were gathered from GitHub repositories of certified data from Italy's Government and Civil Protection. Results: The immunization coverage increased starting in March 2021, with a parallel decrease in COVID-19 infections, hospitalizations, and deaths. Despite different implementation approaches, the vaccine coverage growth rate had a similar pattern across regions. A comprehensive approach including measures such as requiring face masks and a "Green Pass" to enter indoor places also helped contain the pandemic. Conclusions: The vaccine rollout had a major effect on COVID-19 in Italy, especially on hospitalizations and deaths. Before the vaccine was available, however, other non-pharmaceutical interventions also helped to contain the spread of the virus and mitigate its effect on the population.

Non-COVID-19 patients in times of pandemic: Emergency department visits, hospitalizations and cause-specific mortality in Northern Italy.

The COVID-19 pandemic forced healthcare services organization to adjust to mutating healthcare needs. Not exhaustive data are available on the consequences of this on non-COVID-19 patients. The aim of this study was to assess the impact of the pandemic on non-COVID-19 patients living in a one-million inhabitants' area in Northern Italy (Bologna Metropolitan Area-BMA), analyzing time trends of Emergency Department (ED) visits, hospitalizations and mortality. We conducted a retrospective observational study using data extracted from BMA healthcare informative systems. Weekly trends of ED visits, hospitalizations, in- and out-of-hospital, all-cause and cause-specific mortality between December 1st, 2019 to May 31st, 2020, were compared with those of the same period of the previous year. Non-COVID-19 ED visits and hospitalizations showed a stable trend until the first Italian case of COVID-19 has been recorded, on February 19th, 2020, when they dropped simultaneously. The reduction of ED visits was observed in all age groups and across all severity and diagnosis groups. In the lockdown period a significant increase was found in overall out-of-hospital mortality (43.2%) and cause-specific out-of-hospital mortality related to neoplasms (76.7%), endocrine, nutritional and metabolic (79.5%) as well as cardiovascular (32.7%) diseases. The pandemic caused a sudden drop of ED visits and hospitalizations of non-COVID-19 patients during the lockdown period, and a concurrent increase in out-of-hospital mortality mainly driven by deaths for neoplasms, cardiovascular and endocrine diseases. As recurrencies of the COVID-19 pandemic are underway, the scenario described in this study might be useful to understand both the population reaction and the healthcare system response at the early phases of the pandemic in terms of reduced demand of care and systems capability in intercepting it.

The experience of patients with diabetes with the use of telemedicine and teleassistance services during the COVID-19 pandemic in Italy: Factors associated with perceived quality and willingness to continue.

AIM: 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 services during the COVID-19 pandemic in one large region of Italy. METHODS: A structured survey was administered to patients with type 1 and 2 diabetes who used TMTA during the first wave of the COVID-19 pandemic. The questionnaire contained questions on TMTA service experience and participants' socio-demographic characteristics. Multiple regression models investigated the independent factors associated with PQ and WC. 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 and being unemployed were factors associated with an increased WC. Older age was negatively related to PQ. Perceived support from TMTA service was positively associated with PQ and WC. Perceived increase in disease self-management was positively associated with PQ and WC. CONCLUSIONS: Our study identified several determinants of PQ and WC. These socio-demographic and TMTA-related factors should be considered in the implementation of care pathways integrating in-person visits with TMTA.

COVID-19 and regional differences in the timeliness of hip-fracture surgery: an interrupted time-series analysis.

BACKGROUND: It is of great importance to examine the impact of the healthcare reorganization adopted to confront the COVID-19 pandemic on the quality of care provided to non-COVID-19 patients. The aim of this study is to assess the impact of the COVID-19 national lockdown (March 9, 2020) on the quality of care provided to patients with hip fracture (HF) in Piedmont and Emilia-Romagna, two large regions of northern Italy severely hit by the pandemic. METHODS: We calculated the percentage of HF patients undergoing surgery within 2 days of hospital admission. An interrupted time-series analysis was performed on weekly data from December 11, 2019 to June 9, 2020 (≈6 months), interrupting the series in the 2nd week of March. The same data observed the year before were included as a control time series with no "intervention" (lockdown) in the middle of the observation period. RESULTS: Before the lockdown, 2-day surgery was 69.9% in Piedmont and 79.2% in Emilia-Romagna; after the lockdown, these proportions were equal to 69.8% (-0.1%) and 69.3% (-9.9%), respectively. While Piedmont did not experience any drop in the amount of surgery, Emilia-Romagna exhibited a significant decline at a weekly rate of -1.29% (95% CI [-1.71 to -0.88]). Divergent trend patterns in the two study regions reflect local differences in pandemic timing as well as in healthcare services capacity, management, and emergency preparedness.

Patterns of Emergency Department visits for acute and chronic diseases during the two pandemic waves in Italy.

BACKGROUND: Evidence is lacking about the impact of subsequent COVID-19 pandemic waves on Emergency Departments (ED). We analyzed the differences in patterns of ED visits in Italy during the two pandemic waves, focusing on changes in accesses for acute and chronic diseases. METHODS: We conducted a retrospective study using data from a metropolitan area in northern Italy that includes twelve ED. We analyzed weekly trends in non-COVID-19 ED visits during the first (FW) and second wave (SW) of the pandemic. Incidence rate ratios (IRRs) of triage codes, patient destination, and cause-specific ED visits in the FW and SW of the year 2020 vs. 2019 were estimated using Poisson regression models. MAIN FINDINGS: We found a significant decrease of ED visits by triage code, which was more marked for low priority codes and during the FW. We found an increased share of hospitalizations compared to home discharges both in the FW and in the SW. ED visits for acute and chronic conditions decreased during the FW, ranging, from -70% for injuries (IRR = 0.2862, p < 0.001) to -50% and - 60% for ischemic heart disease and heart failure. CONCLUSIONS: The two pandemic waves led to a selection of patients with higher and more urgent needs of acute hospital care. These findings should lead to investigate how to improve systems' capacity to manage changes in population needs.

Higher 90-Day Mortality after Surgery for Hip Fractures in Patients with COVID-19: A Case-Control Study from a Single Center in Italy.

The mortality of hip fracture (HF) patients is increased by concomitant COVID-19; however, evidence is limited to only short follow-up. A retrospective matched case-control study was designed with the aim to report the 90-day mortality and determine the hazard ratio (HR) of concomitant HF and COVID-19 infection. Cases were patients hospitalized for HF and diagnosed with COVID-19. Controls were patients hospitalized for HF not meeting the criteria for COVID-19 diagnosis and were individually matched with each case through a case-control (1:3) matching algorithm. A total of 89 HF patients were treated during the study period, and 14 of them were diagnosed as COVID-19 positive (overall 15.7%). Patients' demographic, clinical, and surgical characteristics were similar between case and control groups. At 90 days after surgery, 5 deaths were registered among the 14 COVID-19 cases (35.7%) and 4 among the 42 HF controls (9.5%). COVID-19-positive cases had a higher risk of mortality at 30 days (HR = 4.51; p = 0.0490) and 90 days (HR = 4.50; p = 0.025) with respect to controls. Patients with concomitant HF and COVID-19 exhibit high perioperative mortality, which reaches a plateau of nearly 30-35% after 30 to 45 days and is stable up to 90 days. The mortality risk is more than four-fold higher in patients with COVID-19.

Small-scale spatial distribution of COVID-19-related excess mortality.

Mortality due to massive events like the COVID-19 pandemic is underestimated because of several reasons, among which the impossibility to track all positive cases and the inadequacy of coding systems are presumably the most relevant. Therefore, the most affordable method to estimate COVID-19-related mortality is excess mortality (EM). Very often, though, EM is calculated on large spatial units that may entail different EM patterns and without stratifying deaths by age or sex, while, especially in the case of epidemics, it is important to identify the areas that suffered a higher death toll or that were spared. We developed the Stata COVID19_EM.ado procedure that estimates EM within municipalities in six subgroups defined by sex and age class using official data provided by ISTAT (Italian National Statistics Bureau) on deaths occurred from 2015 to 2020. Using simple linear regression models, we estimated the mortality trend in each age-and-sex subgroup and obtained the expected deaths of 2020 by extrapolating the linear trend. The results are then displayed using choropleth maps. Subsequently, local autocorrelation maps, which allow to appreciate the presence of local clusters of high or low EM, may be obtained using an R procedure that we developed.•We focused on estimating excess mortality in small-scale spatial units (municipalities) and in population strata defined by age and sex.•This method gives a deeper insight on excess mortality than summary figures at regional or national level, enabling to identify the local areas that suffered the most and the high-risk population subgroups within them.•This type of analysis could be replicated on different time frames, which might correspond to successive epidemic waves, as well as to periods in which containment measures were enforced and for different age classes; moreover, it could be applied in every instance of mortality crisis within a region or a country.

SARS-CoV-2/COVID-19 Testing: The Tower of Babel.

BACKGROUND AND AIM: Testing represents one of the main pillars of public health response to SARS-CoV-2/COVID-19 pandemic. This paper shows how accuracy and utility of testing programs depend not just on the type of tests, but on the context as well. METHODS: We describe the testing methods that have been developed and the possible testing strategies; then, we focus on two possible methods of population-wide testing, i.e., pooled testing and testing with rapid antigen tests. We show the accuracy of split-pooling method and how, in different pre-test probability scenarios, the positive and negative predictive values vary using rapid antigen tests. RESULTS: Split-pooling, followed by retesting of negative results, shows a higher sensitivity than individual testing and requires fewer tests. In case of low pre-test probability, a negative result with antigen test could allow to rule out the infection, while, in case of a positive result, a confirmatory molecular test would be necessary. CONCLUSIONS: Test performance alone is not enough to properly choose which test to use; goals and context of the testing program are essential. We advocate the use of pooled strategies when planning population-wide screening, and the weekly use of rapid tests for close periodic monitoring in low-prevalence populations.

Patterns of COVID-19 related excess mortality in the municipalities of Northern Italy during the first wave of the pandemic.

The impact of Coronavirus Disease 2019 (COVID-19) on mortality in Italy has been described at the regional level, while less is known about mortality in municipalities, although the spatial distribution of COVID-19 in its first wave has been uneven. We aimed to describe the excess mortality due to COVID-19 from February 23rd to April 30th, 2020 in the three most affected Italian regions, in age and gender subgroups within each municipality. Excess mortality varied widely among municipalities even within the same region; it was higher among the elderly and higher in males except in the ≥75 age group. Thus, nearby municipalities may show a different mortality burden despite being under common regional health policies, possibly as a result of local reinforcements of regional policies. Identifying the municipalities where mortality was higher and the pathways used by the virus to spread may help to concentrate efforts in understanding the reasons why this happened and to identify the frailest areas in light of recurrences of the epidemic.

Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19.

On December 31st 2019, the World Health Organization China Country Office was informed of cases of pneumonia of unknown etiology detected in Wuhan City. The cause of the syndrome was a new type of coronavirus isolated on January 7th 2020 and named Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2). SARS-CoV-2 is the cause of the coronavirus disease 2019 (COVID-19). Since January 2020 an ever increasing number of scientific works related to the new pathogen have appeared in literature. Identifying relevant research outcomes at very early stages is challenging. In this work we use COVID-19 as a use-case for investigating: (1) which tools and frameworks are mostly used for early scholarly communication; (2) to what extent altmetrics can be used to identify potential impactful research in tight (i.e. quasi-zero-day) time-windows. A literature review with rigorous eligibility criteria is performed for gathering a sample composed of scientific papers about SARS-CoV-2/COVID-19 appeared in literature in the tight time-window ranging from January 15th 2020 to February 24th 2020. This sample is used for building a knowledge graph that represents the knowledge about papers and indicators formally. This knowledge graph feeds a data analysis process which is applied for experimenting with altmetrics as impact indicators. We find moderate correlation among traditional citation count, citations on social media, and mentions on news and blogs. Additionally, correlation coefficients are not inflated by indicators associated with zero values, which are quite common at very early stages after an article has been published. This suggests there is a common intended meaning of the citational acts associated with aforementioned indicators. Then, we define a method, i.e. the Comprehensive Impact Score (CIS), that harmonises different indicators for providing a multi-dimensional impact indicator. CIS shows promising results as a tool for selecting relevant papers even in a tight time-window. Our results foster the development of automated frameworks aimed at helping the scientific community in identifying relevant work even in case of limited literature and observation time.

Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature.

BACKGROUND: The COVID-19 pandemic is favoring digital transitions in many industries and in society as a whole. Health care organizations have responded to the first phase of the pandemic by rapidly adopting digital solutions and advanced technology tools. OBJECTIVE: The aim of this review is to describe the digital solutions that have been reported in the early scientific literature to mitigate the impact of COVID-19 on individuals and health systems. METHODS: We conducted a systematic review of early COVID-19-related literature (from January 1 to April 30, 2020) by searching MEDLINE and medRxiv with appropriate terms to find relevant literature on the use of digital technologies in response to the pandemic. We extracted study characteristics such as the paper title, journal, and publication date, and we categorized the retrieved papers by the type of technology and patient needs addressed. We built a scoring rubric by cross-classifying the patient needs with the type of technology. We also extracted information and classified each technology reported by the selected articles according to health care system target, grade of innovation, and scalability to other geographical areas. RESULTS: The search identified 269 articles, of which 124 full-text articles were assessed and included in the review after screening. Most of the selected articles addressed the use of digital technologies for diagnosis, surveillance, and prevention. We report that most of these digital solutions and innovative technologies have been proposed for the diagnosis of COVID-19. In particular, within the reviewed articles, we identified numerous suggestions on the use of artificial intelligence (AI)-powered tools for the diagnosis and screening of COVID-19. Digital technologies are also useful for prevention and surveillance measures, such as contact-tracing apps and monitoring of internet searches and social media usage. Fewer scientific contributions address the use of digital technologies for lifestyle empowerment or patient engagement. CONCLUSIONS: In the field of diagnosis, digital solutions that integrate with traditional methods, such as AI-based diagnostic algorithms based both on imaging and clinical data, appear to be promising. For surveillance, digital apps have already proven their effectiveness; however, problems related to privacy and usability remain. For other patient needs, several solutions have been proposed, such as telemedicine or telehealth tools. These tools have long been available, but this historical moment may actually be favoring their definitive large-scale adoption. It is worth taking advantage of the impetus provided by the crisis; it is also important to keep track of the digital solutions currently being proposed to implement best practices and models of care in future and to adopt at least some of the solutions proposed in the scientific literature, especially in national health systems, which have proved to be particularly resistant to the digital transition in recent years.