Hospital and economic burden of influenza-like illness and lower respiratory tract infection in adults ≥50 years-old.

BACKGROUND: Influenza-like illnesses (ILIs) and lower respiratory tract infections (LRTIs) cause substantial morbidity and mortality worldwide. The study assessed the health and economic burden of ILI and LRTI according to age and comorbidities, since available evidence is limited and heterogeneous. METHOD: The prevalence of comorbidities, the seasonal incidence rates and the mean and per capita direct costs of ED accesses for ILI/LRTI, whether followed by hospitalization or not, recorded in adults aged ≥50 years over the last 6 years, in the referral hospitals located in the Genoese metropolitan area (Liguria, Italy) where the syndromic surveillance system is active, were evaluated through a retrospective observational study. Comorbidities were estimated through the Chronic Condition Data Warehouse that integrates multiple Medicare data sources. A comparison with the administrative healthcare International Classification of Diseases-9th revision-Clinical Modification (ICD-9-CM)-based data was also conducted. RESULTS: The prevalence of subjects with ≥1 comorbidity ranged from 23.49 to 59.92%. The most prevalent all-age comorbidities were cardiovascular diseases and cancer. The overall ILI/LRTI incidence rate was 6.73/1000 person-years, almost double the value derived from routine data, and increased with age. The highest rates were observed in patients with renal failure and bronchopneumopathies. The mean cost of ED accesses/hospitalization for ILI/LRTI was €3353 and was almost twice as high in the ≥85 years as in the youngest age-group. The highest mean costs were observed in patients with renal failure and cancer. The per capita costs increased from €4 to €71 with age, and were highest in patients with renal failure and bronchopneumopathy. CONCLUSION: The burden of ILIs/LRTIs in terms of ED accesses and hospitalizations in adults aged ≥50 years is heavy, and is related to increasing age and, especially, to specific comorbidities. These results could contribute to revising age- and risk-based anti-influenza and -pneumococcus immunization strategies.

Weight of risk factors for mortality and short-term mortality displacement during the COVID-19 pandemic.

Background: We conducted a population-based cohort study to estimate mortality before, during and after the COVID-19 peak and to compare mortality in 2020 with rates reported in previous years, with a view to helping decision makers to apply containment measures for high-risk groups. Methods: All deaths were collected between 2015 and 2020 from municipal registry database. In 2020, weeks 1-26 were stratified in three periods: before, during and after the COVID mortality peak. The Poisson Generalized Linear regression Model showed the "harvesting effect". Three logistic regressions for 8 dependent variables (age and comorbidities) and a t-test of differences described all-cause mortality risk factors in 2019 and 2020 and differences between COVID and non-COVID patients. Results: A total of 47,876 deaths were collected. All-cause deaths increased by 38.5% during the COVID peak and decreased by 18% during the post-peak period in comparison with the average registered during the control period (2015-19), with significant mortality displacement in 2020. Except for chronic renal injuries in subjects aged 45-64 years, diabetes and chronic cardiovascular diseases in those aged 65-84 years, and neuropathies in those aged > 84 years, the weight of comorbidities in deaths was similar or lower in COVID subjects than in non-COVID subjects. Discussions: Surprisingly, the weight of comorbidities in death, compared to weight in non-COVID subjects allows you to highlight some surprising results such as COPD, IBD and Cancer. The excess mortality that we observed in the entire period were modest in comparison with initial estimates during the peak, owing to the mild influenza season and the harvesting effect starting from the second half of May.

Has Clinical and Epidemiological Varicella Burden Changed over Time in Children? Overview on Hospitalizations, Comorbidities and Costs from 2010 to 2017 in Italy.

According to WHO estimates, varicella disease is responsible of a worldwide significant burden in terms of hospitalizations, complications, and deaths, with more than 90% of cases under 12 years old. This study aims at evaluating the clinical, epidemiological, and economic burden of varicella in Ligurian children, about comorbidities, organizational variables, and vaccination coverages from 2010 to 2017, in terms of Emergency Department accesses and hospitalizations. The overall hospitalization rate was 179.76 (per 100,000 inhab.), with a gradual but significant decline since 2015, when universal varicella vaccination was introduced in Liguria (p < 0.0001). The risk of being hospitalized for complicated varicella in subjects with at least one comorbidity was significantly higher than in subjects without comorbidities (p = 0.0016). The economic analysis showed higher costs in subjects with complicated varicella who were 0-3 years old. This age group showed higher costs also considering extra-hospital costs for both outpatient procedures and pharmaceutical costs (p < 0.0001). The results confirm the relevant burden of varicella, especially in the 0-3 age group and in children with comorbidities. Thus, vaccination with the achievement of adequate vaccination coverages is confirmed to be a necessary control strategy to reduce hospitalizations and associated complications with important economic benefits.

The Unknown Health Burden of Herpes Zoster Hospitalizations: The Effect on Chronic Disease Course in Adult Patients ≥50 Years.

The effect of severe Herpes Zoster (HZ) on chronic diseases is a component of the real burden of this vaccine-preventable disease that is not commonly considered. A retrospective cohort study was conducted to assess the health burden of severe HZ in adults ≥50 years residing in Liguria Region from 2015 to 2017. Subjects hospitalized with and without HZ were matched (1:6 ratio). 437 subjects in the HZ cohort and 2622 subjects in the non-HZ cohort were enrolled. Previous immunodeficiency, autoimmune, and rare diseases are identified as main chronic conditions related to HZ hospitalization. Higher incidences of autoimmune (1.4% vs. 0.22%, p = 0.002) and gastrointestinal (7.04% vs. 3.62%, p = 0.015) diseases after hospitalization were observed in the HZ cohort compared to the non-HZ cohort. Significantly higher incidences were found after hospitalization versus the previous period for cardiovascular diseases (11.17% vs. 2.09%, p < 0.001), cerebral vasculopathy (6.13% vs. 0.60%, p < 0.001), non-arrhythmic myocardiopathy (4.31% vs. 0.59%, p = 0.002), and neuropathy (2.62% vs. 0.56%, p = 0.033). The HZ cohort showed a relative risk 10-fold higher for cerebral vasculopathy, 5-fold higher for cardiovascular diseases, and 7-fold higher for non-arrhythmic myocardiopathy. HZ causes a substantial impact on the chronic conditions. These data could suggest an implementation of HZ vaccination programs in the elderly and in high-risk groups.

A predictive model to allocate frequent service users of community-based mental health services to different packages of care.

AIM: To develop predictive models to allocate patients into frequent and low service users groups within the Italian Community-based Mental Health Services (CMHSs). To allocate frequent users to different packages of care, identifying the costs of these packages. METHODS: Socio-demographic and clinical data and GAF scores at baseline were collected for 1250 users attending five CMHSs. All psychiatric contacts made by these patients during six months were recorded. A logistic regression identified frequent service users predictive variables. Multinomial logistic regression identified variables able to predict the most appropriate package of care. A cost function was utilised to estimate costs. RESULTS: Frequent service users were 49%, using nearly 90% of all contacts. The model classified correctly 80% of users in the frequent and low users groups. Three packages of care were identified: Basic Community Treatment (4,133 Euro per six months); Intensive Community Treatment (6,180 Euro) and Rehabilitative Community Treatment (11,984 Euro) for 83%, 6% and 11% of frequent service users respectively. The model was found to be accurate for 85% of users. CONCLUSION: It is possible to develop predictive models to identify frequent service users and to assign them to pre-defined packages of care, and to use these models to inform the funding of psychiatric care.

[Proposal for a new funding system for mental health departments. Results from an evaluative multicentre Italian study (I-psycost)]. / Proposta per un nuovo sistema di finanziamento dei dipartimenti di salute mentale. Risultati di uno studio valutativo multicentrico nazionale (I-psycost study).

AIMS: To obtain a new, well-balanced mental health funding system, through the creation of (i) a list of psychiatric interventions provided by Italian Community-based Psychiatric Services (CPS), and associated costs; (ii) a new prospective funding system for patients with a high use of resources, based on packages of care. METHODS: Five Italian Community-based Psychiatric Services collected data from 1250 patients during October 2002. Socio-demographical and clinical characteristics and GAF scores were collected at baseline. All psychiatric contacts during the following six months were registered and categorised into 24 service contact types. Using elasticity equation and contact characteristics, we estimate the costs of care. Cluster analysis techniques identified packages of care. Logistic regression defined predictive variables of high use patients. Multinomial Logistic Model assigned each patient to a package of care. RESULTS: The sample's socio-demographic characteristics are similar, but variations exist between the different CPS. Patients were then divided into two groups, and the group with the highest use of resources was divided into three smaller groups, based on number and type of services provided. CONCLUSIONS: Our findings show how is possible to develop a cost predictive model to assign patients with a high use of resources to a group that can provide the right level of care. For these patients it might be possible to apply a prospective per-capita funding system based on packages of care.