Evoluzione della spesa sanitaria in Puglia

Uno dei problemi più importanti che tiene sotto pressione le autorità non solo Regionali e nazionali ma internazionali, è quello della sostenibilità della spesa sanitaria, oggi meglio definita come “spesa per la salute” ovverosia ciò che è necessario per garantire ad ogni individuo, uno stato di completo benessere fisico, mentale e sociale e non semplice assenza di malattia (OMS). I cambiamenti demografici (meglio sarebbe dire la transizione demografica che si riferisce ad un processo attraverso il quale le popolazioni passano da una situazione di equilibrio caratterizzato da alti livelli di mortalità e fecondità, ad altro periodo caratterizzato da un livello di bassa mortalità e fecondità), l’invecchiamento della popolazione ma anche la recente e disastrosa esperienza della pandemia Covid-19, ne hanno completamente cambiato lo scenario. A tal proposito ricordiamo come la spesa per la salute è caratterizzata da tre tipi di spesa: quella propriamente detta spesa sanitaria, quella sociale di interesse sanitario e quella fiscale relativa alle agevolazioni fiscali per spese mediche e fondi sanitari. Fondamentale in questo settore fortemente collegato alla sostenibilità della spesa, è l’innovativo approccio della Value Based Heath Care (VBHC) ovvero un modello di sanità basato sul valore di un processo di miglioramento continuo che mette al centro del percorso di cura la figura fondamentale della dinamica sanitaria assistenziale: il paziente. I punti chiave della VBHC studiano l’intero ciclo di cura fino alle estreme complicazioni o complicanze, con un approccio multidimensionale e multidisciplinare, e anche l’aspetto della misura di esiti e costi di ciascun paziente, analizzando il finanziamento di ciclo di cura che sposti il modello verso sistemi di pagamento, tesi a sostenere spese più organizzate e oculate per rendere l’esito della prestazione o degenza, la migliore possibile. In ultima analisi un percorso virtuoso che mette a nudo il rapporto tra esiti di salute (i cosiddetti “patient outcomes”) e i costi reali sostenuti nell’intero ciclo di cura. Questi ultimi tendono a limitare o eliminare risorse erose e sacche di inefficienza che non si traducano in servizi (“no value expenditure”) o che siano utilizzati per servizi o prestazioni dal valore basso o negativo (“low- negative value expenditure”) e che spesso, rispetto ad un beneficio atteso ,presentino rischi maggiori degli stessi benefici. La spesa non deve essere solo oculata, deve essere anche organizzata bene, ed ecco perché l’altro aspetto che è sul tavolo delle autorità sanitarie e del comparto socio assistenziale, è quello della modifica dei setting assistenziali o dei luoghi di cura, con trasferimento di molti dei percorsi sanitari o socio assistenziali sul territorio, privilegiati per altro nella distribuzione dei finanziamenti del PNRR. L’esperienza di questi anni dimostra e ci insegna sempre più che il futuro si occuperà della protezione dei soggetti fragili, che sono quei soggetti sottoposti in maniera importante all’insidia di situazioni emergenziali o inaspettate come è stato per il Covid-19, soggetti fragili cioè soggetti gravati da malattie che non si esauriscono in maniera temporale sicura ma che sono portatrici di alterazioni ed evoluzioni che determinano situazioni di cronicità (dai tempi sempre più lunghi, considerato l ‘invecchiamento della popolazione). Si considerano anche quei soggetti sottoposti a trattamenti o a farmaci che abbiano effetti di immunodepressione e che rispetto al passato, usufruiscano di un prolungamento della loro sopravvivenza. La pandemia si è dimostrata particolarmente letale nella mortalità e anche nella gravità delle forme, nei soggetti che erano accompagnati da malattie croniche, da età avanzata, e da comorbidità importanti e numerose, quindi si rende sempre più necessaria la protezione dei soggetti fragili. Una delle sfide più complesse del XXI secolo è rappresentata dal modo con cui i sistemi socio sanitari ottimizzeranno l’uso delle risorse disponibili per rispondere alla domanda indotta dalla continua crescita delle patologie croniche. Un’ulteriore sfida consiste anche nel cercare percorsi, servizi e organizzazioni che possano massimizzare l’ “outcome” e che possano avere una sostenibilità economica più virtuosa possibile. Strettamente collegato a questi aspetti è l’avvento dell’era farmaco-economica, iniziata già negli anni ’90 del secolo scorso e corrisposta alla necessità, ormai improcrastinabile, di disporre di dati che consentano la valorizzazione e quindi la conoscenza di costi e strategie di intervento sanitario preventive, diagnostiche o terapeutiche. Lo scopo è di porre i “decision markers” nelle condizioni di allocare al meglio le risorse disponibili e progressivamente decrescenti. Oggetto di studio sono stati, l’analisi dei dati relativi a due esperienze, una italiana e l’altra pugliese, in cui si è valutata la possibilità di un risparmio di farmaci per l’asma bronchiale e la BPCO (Broncopatia Cronica Ostruttiva). Importanti sono state le conseguenze che il SSN ha subito a seguito della pandemia mondiale

The Hospital Emigration to Another Region in the Light of the Environmental, Social and Governance Model in Italy During the Period 2004-2021

The following article presents an analysis of the impact of the Environmental, Social and Governance-ESG determinants on Hospital Emigration to Another Region-HEAR in the Italian regions in the period 2004-2021. The data are analysed using Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS, Weighted Least Squares-WLS, and Dynamic Panel at 1 Stage. Results show that HEAR is negatively associated to E, positively to S and negatively associated to the G within the ESG model. The data were subjected to clustering with a k-Means algorithm optimized with the Silhouette coefficient. The optimal clustering with k=2 is compared to the sub-optimal cluster with k=3. The results suggest a negative relationship between the resident population and hospital emigration at regional level. Finally, a prediction is proposed with machine learning algorithms classified based on statistical performance. The results show that the Artificial Neural Network-ANN algorithm is the best predictor. The ANN predictions are critically analyzed in light of health economic policy directions

Investigating the Determinants of Beds for High-Care Specialties in the Italian Regions in the Environmental, Social and Governance Model

In the following article, it is presented an investigation of the determinants of Beds for High-Care Specialties-BHCS in the Italian regions in the context of Environmental, Social and Governance-ESG approach. Data from ISTAT-BES for 20 countries in the period 2004-2021 are been used. Different econometric techniques have been applied i.e.: Pooled Ordinary Least Squares, Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel at 1 stage. Furthermore, a cluster analysis performed with a k-Means algorithm optimized with the Silhouette Coefficient indicated the presence of three clusters. Finally, eight different machine-learning algorithms are analysed to predict the future value of BHCS. The results show that the Artificial Neural Network-ANN algorithm is the best algorithm. The future value of BHSC is expected to growth on average of 4.88% for the analysed regions

Elderly People Treated in Integrated Home Care in Italian Regions: A Metric Approach

In this article, we analyse the ESG determinants of the “Elderly People Treated in Integrated Home Care”-EPIHC in the Italian regions between 2004 and 2022. We used data from the ISTAT-BES database. We used different econometric techniques i.e.: Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS and Weighted Least Squares-WLS. The results show that the EPIHC is positively associated with “Nurses, midwives, and Soil sealing by artificial cover" and negatively associated with "Museum heritage density and relevance" and "Trust in law enforcement agencies and firefighters fire". Furthermore, we have applied a k-Means algorithm with the Silhouette Coefficient and we find the presence of two clusters. Finally, we propose a confrontation among eight different machine-learning algorithms and we find that Linear Regression is the best predictive algorithm

Voluntary lung function screening to reveal new COPD cases in southern Italy

Background: Underdiagnosis of COPD is a relevant issue, and most frequently involves patients at early stages of the disease. Physicians do not routinely recommend smokers to undergo spirometry, unless they are symptomatic. Aims: To investigate the effectiveness of voluntary lung function screening in bringing to light patients with previously unknown COPD and to evaluate the relationships among symptoms, smoking status, and airway obstruction. Methods: A voluntary screening study for COPD was conducted during two editions of the annual Fiera del Levante (2014 and 2015), an international trade fair in Bari. Subjects were eligible for the study if they fulfilled the following inclusion criteria: age â¥35 years, smoker/ex-smoker â¥5 pack-years (PYs), or at least one chronic respiratory symptom (cough, sputum production, shortness of breath, and wheezing). A free post-β2-agonist spirometry test was performed by trained physicians for each participant using portable spirometers. Post-β2-agonist forced expiratory volume in 1 second (FEV1):forced vital capacity ratio <0.7 was chosen to establish the diagnosis of COPD. Sensitivity, specificity, and negative and positive predictive values (NPVs and PPVs) of symptoms for the presence of obstruction were calculated. Results: A total of 1,920 individuals were eligible for the study; 188 subjects (9.8%) met COPD criteria. There was a 10.4% prevalence of COPD in subjects with one or more symptoms who had never smoked or smoked â¤5 PYs. Among COPD patients, prevalence of symptoms increased in the presence of FEV1<80%. COPD smokers were more symptomatic than smokers without COPD. Sensitivity and specificity in all subjects with one or more symptoms were 87% and 32%, respectively, whereas in smoker subgroups, sensitivity and specificity were 71% and 41% (â¥5 PYs) and 74% and 35% (â¥10 PYs), respectively. In all subjects, the presence of at least one symptom was associated with a low PPV for COPD of 11%, but a very high NPV (96%). These data did not change if the analysis was limited to smokers. Conclusion: Voluntary public lung function screening programs in Italy are effective, and may detect a large number of undiagnosed subjects with COPD in early stages. In our population, COPD symptoms had low specificity and PPV, even considering smokers only

Voluntary lung function screening to reveal new COPD cases in southern Italy

Background: Underdiagnosis of COPD is a relevant issue, and most frequently involves patients at early stages of the disease. Physicians do not routinely recommend smokers to undergo spirometry, unless they are symptomatic. Aims: To investigate the effectiveness of voluntary lung function screening in bringing to light patients with previously unknown COPD and to evaluate the relationships among symptoms, smoking status, and airway obstruction. Methods: A voluntary screening study for COPD was conducted during two editions of the annual Fiera del Levante (2014 and 2015), an international trade fair in Bari. Subjects were eligible for the study if they fulfilled the following inclusion criteria: age â¥35 years, smoker/ex-smoker â¥5 pack-years (PYs), or at least one chronic respiratory symptom (cough, sputum production, shortness of breath, and wheezing). A free post-Î22-agonist spirometry test was performed by trained physicians for each participant using portable spirometers. Post-Î22-agonist forced expiratory volume in 1 second (FEV1):forced vital capacity ratio <0.7 was chosen to establish the diagnosis of COPD. Sensitivity, specificity, and negative and positive predictive values (NPVs and PPVs) of symptoms for the presence of obstruction were calculated. Results: A total of 1,920 individuals were eligible for the study; 188 subjects (9.8%) met COPD criteria. There was a 10.4% prevalence of COPD in subjects with one or more symptoms who had never smoked or smoked â¤5 PYs. Among COPD patients, prevalence of symptoms increased in the presence of FEV1<80%. COPD smokers were more symptomatic than smokers without COPD. Sensitivity and specificity in all subjects with one or more symptoms were 87% and 32%, respectively, whereas in smoker subgroups, sensitivity and specificity were 71% and 41% (â¥5 PYs) and 74% and 35% (â¥10 PYs), respectively. In all subjects, the presence of at least one symptom was associated with a low PPV for COPD of 11%, but a very high NPV (96%). These data did not change if the analysis was limited to smokers. Conclusion: Voluntary public lung function screening programs in Italy are effective, and may detect a large number of undiagnosed subjects with COPD in early stages. In our population, COPD symptoms had low specificity and PPV, even considering smokers only

The Mental Health Index across the Italian Regions in the ESG Context

The following article analyses the relationship between the mental health index and the variables of the Environment, Social and Governance-ESG model in the Italian regions between 2004 and 2023. The econometric analysis is aimed at investigating in detail the relationships between the mental health index and the individual components of the ESG model. The results are critically discussed

The ESG Determinants of Mental Health Index Across Italian Regions: A Machine Learning Approach

The following article analyses the relationship between the mental health index and the variables of the Environment, Social and Governance-ESG model in the Italian regions between 2004 and 2023. First of all, a static analysis is proposed aimed at identifying trends relating to mental health in the Italian regions with indication of the regional gaps. Subsequently, a clustering with k-Means algorithm is proposed. Below is a comparison of 11 machine learning algorithms for predicting the performance of the mental health index. Finally, the article offers some economic policy suggestions. The results are critically discussed in light of the scientific literatur

Multi-photon in situ synthesis and patterning of polymer-embedded nanocrystals

The in situ synthesis and patterning of CdS nanocrystals in a polymer matrix is performed via multi-photon absorption. Quantum-sized CdS nanocrystals are obtained by irradiating a cadmium thiolate precursor dispersed in a transparent polymer matrix with a focused near infrared femtosecond laser beam. High resolution transmission electron microscopy evidences the formation of nanocrystals with wurtzite crystalline phase. Fluorescent, nanocomposite patterns with sub-micron spatial resolution are fabricated by scanning the laser beam on the polymer-precursor composite. Moreover, the emission energy of the CdS nanocrystals can be tuned in the range 2.5-2.7 eV, by changing the laser fluences in the range 0.10-0.45 J cm -2. This method enables therefore the synthesis of luminescent, CdS-based composites to be used within patterned nanophotonic and light-emitting devices

Expression profile of HERVs and inflammatory mediators detected in nasal mucosa as a predictive biomarker of COVID-19 severity

IntroductionOur research group and others demonstrated the implication of the human endogenous retroviruses (HERVs) in SARS-CoV-2 infection and their association with disease progression, suggesting HERVs as contributing factors in COVID-19 immunopathology. To identify early predictive biomarkers of the COVID-19 severity, we analyzed the expression of HERVs and inflammatory mediators in SARS-CoV-2-positive and -negative nasopharyngeal/oropharyngeal swabs with respect to biochemical parameters and clinical outcome.MethodsResiduals of swab samples (20 SARS-CoV-2-negative and 43 SARS-CoV-2-positive) were collected during the first wave of the pandemic and expression levels of HERVs and inflammatory mediators were analyzed by qRT-Real time PCR.ResultsThe results obtained show that infection with SARS-CoV-2 resulted in a general increase in the expression of HERVs and mediators of the immune response. In particular, SARS-CoV-2 infection is associated with increased expression of HERV-K and HERV-W, IL-1β, IL-6, IL-17, TNF-α, MCP-1, INF-γ, TLR-3, and TLR-7, while lower levels of IL-10, IFN-α, IFN-β, and TLR-4 were found in individuals who underwent hospitalization. Moreover, higher expression of HERV-W, IL-1β, IL-6, IFN-α, and IFN-β reflected the respiratory outcome of patients during hospitalization. Interestingly, a machine learning model was able to classify hospitalized vs not hospitalized patients with good accuracy based on the expression levels of HERV-K, HERV-W, IL-6, TNF-a, TLR-3, TLR-7, and the N gene of SARS-CoV-2. These latest biomarkers also correlated with parameters of coagulation and inflammation.DiscussionOverall, the present results suggest HERVs as contributing elements in COVID-19 and early genomic biomarkers to predict COVID-19 severity and disease outcome