Impact of COVID-19 on Timing of Hip-Fracture Surgeries: An Interrupted Time-Series Analysis of the Pre/Post-Quarantine Period in Northern Italy

To assess whether the imposition of the coronavirus disease 2019 (COVID-19) national quarantine (March 10, 2020) resulted in a shift in the proportion of patients operated for hip fracture on the day of admission, the following day and two days after admission in the region of Piedmont, northern Italy

Determinants of cesarean delivery: a classification tree analysis.

open4noBackground Cesarean delivery (CD) rates are rising in many parts of the world. To define strategies to reduce them, it is important to identify their clinical and organizational determinants. The objective of this cross-sectional study is to identify sub-types of women at higher risk of CD using demographic, clinical and organizational variables. Methods All hospital discharge records of women who delivered between 2005 and mid-2010 in the Emilia-Romagna Region of Italy were retrieved and linked with birth certificates. Sociodemographic and clinical information was retrieved from the two data sources. Organizational variables included activity volume (number of births per year), hospital type, and hour and day of delivery. A classification tree analysis was used to identify the variables and the combinations of variables that best discriminated cesarean from vaginal delivery. Results The classification tree analysis indicated that the most important variables discriminating the sub-groups of women at different risk of cesarean section were: previous cesarean, mal-position/mal-presentation, fetal distress, and abruptio placentae or placenta previa or ante-partum hemorrhage. These variables account for more than 60% of all cesarean deliveries. A sensitivity analysis identified multiparity and fetal weight as additional discriminatory variables. Conclusions Clinical variables are important predictors of CD. To reduce the CD rate, audit activities should examine in more detail the clinical conditions for which the need of CD is questionable or inappropriate.openStivanello E;Rucci P;Lenzi J;Fantini MPStivanello E;Rucci P;Lenzi J;Fantini M

Burden of multimorbidity in relation to age, gender and immigrant status: A cross-sectional study based on administrative data

Objectives Many studies have investigated multimorbidity, whose prevalence varies according to settings and data sources. However, few studies on this topic have been conducted in Italy, a country with universal healthcare and one of the most aged populations in the world. The aim of this study was to estimate the prevalence of multimorbidity in a Northern Italian region, to investigate its distribution by age, gender and citizenship and to analyse the correlations of diseases. Design Cross-sectional study based on administrative data. Setting Emilia-Romagna, an Italian region with-1/44.4 million inhabitants, of which almost one-fourth are aged 6565 years. Participants All adults residing in Emilia-Romagna on 31 December 2012. Hospitalisations, drug prescriptions and contacts with community mental health services from 2003 to 2012 were traced to identify the presence of 17 physical and 9 mental health disorders. Primary and secondary outcome measures Descriptive analysis of differences in the prevalence of multimorbidity in relation to age, gender and citizenship. The correlations of diseases were analysed using exploratory factor analysis. Results The study population included 622 026 men and 751 011women, with a mean age of 66.4 years. Patients with multimorbidity were 33.5% in 75 years and >60% among patients aged 6590 years; among patients aged 6565 years, the proportion of multimorbidity was 39.9%. After standardisation by age and gender, multimorbidity was significantly more frequent among Italian citizens than among immigrants. Factor analysis identified 5 multimorbidity patterns: (1) psychiatric disorders, (2) cardiovascular, renal, pulmonary and cerebrovascular diseases, (3) neurological diseases, (4) liver diseases, AIDS/HIV and substance abuse and (5) tumours. Conclusions Multimorbidity was highly prevalent in Emilia-Romagna and strongly associated with age. This finding highlights the need for healthcare providers to adopt individualised care plans and ensure continuity of care

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 (approximate to 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

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

Medical Costs of Patients with Type 2 Diabetes in a Single Payer System: A Classification and Regression Tree Analysis

Background and objectives Many studies and systematic reviews have estimated the healthcare costs of diabetes using a cost-of-illness approach. However, in the studies based on this approach patients\u2019 heterogeneity is rarely taken into account. The aim of this study is to stratify patients with type-2 diabetes into homogeneous cost groups based on demographic and clinical characteristics. Methods We conducted a retrospective cost of illness study by linking individual data on health services utilization retrieved from the administrative databases of Emilia-Romagna Region (Italy). Direct medical costs (either all-cause or diabetes-related) were calculated from the perspective of regional health service, using tariffs for hospitalizations and outpatient services and the unit costs of prescriptions for drugs. The determinants of costs identified in a generalized linear regression model were used to characterize subgroups of patients with homogeneous costs in a classification and regression tree analysis. Results The study population consists of a cohort of 101,334 patients with type 2 diabetes, followed up for 1 year, with a mean age of 70.9 years. Age, gender, complications, comorbidities and living area accounted significantly for cost variability. The classification tree identified 10 patient subgroups with different costs, ranging from a median of \u20ac 483 to \u20ac 39,578. The 2 subgroups with highest costs comprised dialysis patients and the largest subgroup (57.9%) comprised patients aged 6565 years without renal, cardiovascular and cerebrovascular complications. Conclusions Patients\u2019 classification into homogeneous cost subgroups can be used to improve the management and budget allocation for patients with type 2 diabetes

Health equity during COVID-19: A qualitative study on the consequences of the syndemic on refugees’ and asylum seekers’ health in reception centres in Bologna (Italy)

Background As coronavirus infection spread across the world, the dramatic consequences of Sars-CoV-2 and confinement measures highlighted the disparities within our society, impacting more severely on the wellbeing of the most disadvantaged groups of people, such as migrants. The structural characteristics of reception centres create many challenges in the implementation of measures to contrast the diffusion of the virus, putting refugees and asylum seekers (RAS) even more at risk. For these reasons, we carried out a qualitative study to analyze the impact of the syndemic on the health of RAS who reside in reception facilities in Bologna (one of the cities with the highest number of migrants in Italy) and the measures that were introduced to contrast the diffusion of Sars-CoV-2. Methods Between April and September 2020, we interviewed 25 professionals and volunteers who were critical in the management of the COVID-19 epidemic in reception centres. Key-informants were selected through a snowball sampling process and covered various professions (i.e. doctors, nurses, social workers, psychologists, cultural mediators, anthropologists, lawyers). The semi-structured interviews explored the consequences of COVID-19 on the health of RAS living in reception centres, the measures implemented to contrast the diffusion of the epidemic and the challenges that interviewees had in handling the emergency. After transcription, the interviews were analyzed using deductive and inductive approaches. Results All key-informants agreed to participate in the study. Even though various measures were implemented in reception centres (i.e. mass quarantine, supply of personal protective equipment, risk communication campaigns and specific governance tools) they often had a discriminatory approach towards migrants and only considered the biomedical aspects of COVID-19, excluding its social roots and repercussions. This factor, together with the lack of an effective governance system at both the local and the national level, was the most relevant issue associated with the management of the syndemic in reception facilities and affected all the social determinants that shape the health profile of RAS. Conclusions The study revealed the importance of social factors in the management of the syndemic in reception centres. It also highlighted how the underlying causes of the impact of COVID-19 are tightly correlated to the political and social approaches of local and national institutions to migration. In order to guarantee the well-being of society as a whole and successfully control the epidemic, it is necessary to consider migration as a human reality rather than an emergency, and demolish all the policies and bureaucratic systems that act as structural violence on RAS. This process brings into play different levels of responsibility and many action plans. We need to develop intersectoral collaborations for more holistic and interconnected practices, while investing the resources to build a worthy reception system and effective social protection programs. This way it will be possible to develop more inclusive approaches to public health and guarantee the conditions for RAS' empowerment

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