Tell me your portfolio and I will guess who you are: social incentives for more fitting pension funds

Taking as sample, data obtained directly by the pension fund of an Italian multinational containing more than 35 thousand members, it is assessed, through logistic regression models, how demographic characteristics might affect individual risk aversion. The test is useful to identify groups of workers that by nature are more risk averse and could be disadvantaged by the 2006 TFR (severance indemnity) Italian pension reform. For example women controlling for age, income, region and financial literacy prefer lower risky portfolio and they are more likely to switch toward safer sub-funds. This analysis could support the policymaker to calibrate a suitable appendix to the last TFR reform in order to cover gaps in opportunities among different kind of risk takers mitigating the so called \u201csocial security risk\u201d. In the meantime, it is taken the occasion of such a rich dataset to exploit this sizeable shock in order to test forced (or semi-forced) participation, confirming higher risk aversion for forced participants

Machine Learning and Lean Six Sigma to Assess How COVID-19 Has Changed the Patient Management of the Complex Operative Unit of Neurology and Stroke Unit: A Single Center Study

Background: In health, it is important to promote the effectiveness, efficiency and adequacy of the services provided; these concepts become even more important in the era of the COVID-19 pandemic, where efforts to manage the disease have absorbed all hospital resources. The COVID-19 emergency led to a profound restructuring-in a very short time-of the Italian hospital system. Some factors that impose higher costs on hospitals are inappropriate hospitalization and length of stay (LOS). The length of stay (LOS) is a very useful parameter for the management of services within the hospital and is an index evaluated for the management of costs. Methods: This study analyzed how COVID-19 changed the activity of the Complex Operative Unit (COU) of the Neurology and Stroke Unit of the San Giovanni di Dio e Ruggi d'Aragona University Hospital of Salerno (Italy). The methodology used in this study was Lean Six Sigma. Problem solving in Lean Six Sigma is the DMAIC roadmap, characterized by five operational phases. To add even more value to the processing, a single clinical case, represented by stroke patients, was investigated to verify the specific impact of the pandemic. Results: The results obtained show a reduction in LOS for stroke patients and an increase in the value of the diagnosis related group relative weight. Conclusions: This work has shown how, thanks to the implementation of protocols for the management of the COU of the Neurology and Stroke Unit, the work of doctors has improved, and this is evident from the values of the parameters taken into consideration

Health Technology Assessment: An Essential Approach to Guide Clinical Governance Choices on Risk Management

A large part of academic literature, business literature as well as practices in real life are resting on the assumption that uncertainty and risk does not exist. We all know that this is not true, yet, a whole variety of methods, tools and practices are not attuned to the fact that the future is uncertain and that risks are all around us. However, despite risk management entering the agenda some decades ago, it has introduced risks on its own as illustrated by the financial crisis. Here is a book that goes beyond risk management as it is today and tries to discuss what needs to be improved further. The book also offers some cases

Is It Possible to Predict the Length of Stay of Patients Undergoing Hip-Replacement Surgery?

The proximal fracture of the femur and hip is the most common reason for hospitalization in orthopedic departments. In Italy, 115,989 hip-replacement surgeries were performed in 2019, showing the economic relevance of studying this type of procedure. This study analyzed the data relating to patients who underwent hip-replacement surgery in the years 2010-2020 at the "San Giovanni di Dio e Ruggi d'Aragona" University Hospital of Salerno. The multiple linear regression (MLR) model and regression and classification algorithms were implemented in order to predict the total length of stay (LOS). Lastly, using a statistical analysis, the impact of COVID-19 was evaluated. The results obtained from the regression analysis showed that the best model was MLR, with an R2 value of 0.616, compared with XGBoost, Gradient-Boosted Tree, and Random Forest, with R2 values of 0.552, 0.543, and 0.448, respectively. The t-test showed that the variables that most influenced the LOS, with the exception of pre-operative LOS, were gender, age, anemia, fracture/dislocation, and urinary disorders. Among the classification algorithms, the best result was obtained with Random Forest, with a sensitivity of the longest LOS of over 89%. In terms of the overall accuracy, Random Forest and Gradient-Boosted Tree achieved a value of 71.76% and an error of 28.24%, followed by Decision Tree, with an accuracy of 71.13% and an error of 28.87%, and, finally, Support Vector Machine, with an accuracy of 65.06% and an error of 34.94%. A significant difference in cardiovascular disease, fracture/dislocation, and post-operative LOS variables was shown by the chi-squared test and Mann-Whitney test in the comparison between 2019 (before COVID-19) and 2020 (in full pandemic emergency conditions)

Tell me your portfolio and I will guess who you are: social incentives for more fitting pension funds

Taking as sample, data obtained directly by the pension fund of an Italian multinational containing more than 35 thousand members, it is assessed, through logistic regression models, how demographic characteristics might affect individual risk aversion. The test is useful to identify groups of workers that by nature are more risk averse and could be disadvantaged by the 2006 TFR (severance indemnity) Italian pension reform. For example women controlling for age, income, region and financial literacy prefer lower risky portfolio and they are more likely to switch toward safer sub-funds. This analysis could support the policymaker to calibrate a suitable appendix to the last TFR reform in order to cover gaps in opportunities among different kind of risk takers mitigating the so called “social security risk”. In the meantime, it is taken the occasion of such a rich dataset to exploit this sizeable shock in order to test forced (or semi-forced) participation, confirming higher risk aversion for forced participants.Taking as sample, data obtained directly by the pension fund of an Italian multinational containing more than 35 thousand members, it is assessed, through logistic regression models, how demographic characteristics might affect individual risk aversion. The test is useful to identify groups of workers that by nature are more risk averse and could be disadvantaged by the 2006 TFR (severance indemnity) Italian pension reform. For example women controlling for age, income, region and financial literacy prefer lower risky portfolio and they are more likely to switch toward safer sub-funds. This analysis could support the policymaker to calibrate a suitable appendix to the last TFR reform in order to cover gaps in opportunities among different kind of risk takers mitigating the so called “social security risk”. In the meantime, it is taken the occasion of such a rich dataset to exploit this sizeable shock in order to test forced (or semi-forced) participation, confirming higher risk aversion for forced participants.LUISS PhD Thesi

Symbolic Dynamics Analysis: a new methodology for foetal heart rate variability analysis

Cardiotocography (CTG) is a widespread foetal diagnostic methods. However, it lacks of objectivity and reproducibility since its dependence on observer's expertise. To overcome these limitations, more objective methods for CTG interpretation have been proposed. In particular, many developed techniques aim to assess the foetal heart rate variability (FHRV). Among them, some methodologies from nonlinear systems theory have been applied to the study of FHRV. All the techniques have proved to be helpful in specific cases. Nevertheless, none of them is more reliable than the others. Therefore, an in-depth study is necessary. The aim of this work is to deepen the FHRV analysis through the Symbolic Dynamics Analysis (SDA), a nonlinear technique already successfully employed for HRV analysis. Thanks to its simplicity of interpretation, it could be a useful tool for clinicians. We performed a literature study involving about 200 references on HRV and FHRV analysis; approximately 100 works were focused on non-linear techniques. Then, in order to compare linear and non-linear methods, we carried out a multiparametric study. 580 antepartum recordings of healthy fetuses were examined. Signals were processed using an updated software for CTG analysis and a new developed software for generating simulated CTG traces. Finally, statistical tests and regression analyses were carried out for estimating relationships among extracted indexes and other clinical information. Results confirm that none of the employed techniques is more reliable than the others. Moreover, in agreement with the literature, each analysis should take into account two relevant parameters, the foetal status and the week of gestation. Regarding the SDA, results show its promising capabilities in FHRV analysis. It allows recognizing foetal status, gestation week and global variability of FHR signals, even better than other methods. Nevertheless, further studies, which should involve even pathological cases, are necessary to establish its reliability.La Cardiotocografia (CTG) è una diffusa tecnica di diagnostica fetale. Nonostante ciò, la sua interpretazione soffre di forte variabilità intra- e inter- osservatore. Per superare tali limiti, sono stati proposti più oggettivi metodi di analisi. Particolare attenzione è stata rivolta alla variabilità della frequenza cardiaca fetale (FHRV). Nel presente lavoro abbiamo suddiviso le tecniche di analisi della FHRV in tradizionali, o lineari, e meno convenzionali, o non-lineari. Tutte si sono rivelate efficaci in casi specifici ma nessuna si è dimostrata più utile delle altre. Pertanto, abbiamo ritenuto necessario effettuare un’indagine più dettagliata. In particolare, scopo della tesi è stato approfondire una specifica metodologia non-lineare, la Symbolic Dynamics Analysis (SDA), data la sua notevole semplicità di interpretazione che la renderebbe un potenziale strumento di ausilio all’attività clinica. Sono stati esaminati all’incirca 200 riferimenti bibliografici sull’analisi di HRV e FHRV; di questi, circa 100 articoli specificamente incentrati sulle tecniche non-lineari. E’ stata condotta un’analisi multiparametrica su 580 tracciati CTG di feti sani per confrontare le metodologie adottate. Sono stati realizzati due software, uno per l’analisi dei segnali CTG reali e l’altro per la generazione di tracciati CTG simulati. Infine, sono state effettuate analisi statistiche e di regressione per esaminare le correlazioni tra indici calcolati e parametri di interesse clinico. I risultati dimostrano che nessuno degli indici calcolati risulta più vantaggioso rispetto agli altri. Inoltre, in accordo con la letteratura, lo stato del feto e le settimane di gestazione sono parametri di riferimento da tenere sempre in considerazione per ogni analisi effettuata. Riguardo la SDA, essa risulta utile all’analisi della FHRV, permettendo di distinguere – meglio o al pari di altre tecniche – lo stato del feto, la settimana di gestazione e la variabilità complessiva del segnale. Tuttavia, sono necessari ulteriori studi, che includano anche casi di feti patologici, per confermare queste evidenze

Application of Supply Chain Management at Drugs Flow in an Italian Hospital District

The globalization has pushed to change the organization of every companies, even the hospitals. The principal phenomenon in that period and fundamental today again, has been the Supply Chain Management (SCM), with which the company is no longer seen as an isolated entity but active part in an extremely complex supply network. In fact, the only way to guarantee the competitiveness of businesses in the new world economy is through the cooperation and the integration between customers and suppliers. The present work analyses the drugs flow of three Italian hospital: the Cardarelli Hospital in Campobasso, the Veneziale located in Isernia and the San Timoteo site in Termoli. The data was provided by MOLISE DATA SPA that collected the information from all ASREM with particular interest in the already mentioned hospitals. Particularly, will be highlight, using simulation model, the benefits deriving from the implementation of a new Supply Chain, creating a collaboration along the entire logistics production chain. Thanks to a more efficient management of drugs will get a reduction of business costs and an improvement of the health services offered

Fuzzy logic–based clinical decision support system for the evaluation of renal function in post‐Transplant Patients

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Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy

The rapid growth in the complexity of services and stringent quality requirements present a challenge to all healthcare facilities, especially from an economic perspective. The goal is to implement different strategies that allows to enhance and obtain health processes closer to standards. The Length Of Stay (LOS) is a very useful parameter for the management of services within the hospital and is an index evaluated for the management of costs. In fact, a patient's LOS can be affected by a number of factors, including their particular condition, medical history, or medical needs. To reduce and better manage the LOS it is necessary to be able to predict this value

A novel approach to estimate the upper limb reaching movement in three-dimensional space

Background: In spite of the complexity that the number of redundancy levels suggests, humans show amazingly regularities when generating movement. When moving the hand between pairs of targets, subjects tended to generate roughly straight hand trajectories with single-peaked, bell-shaped speed profiles. The original minimum-jerk model, in which limb displacement is represented by a fifth order polynomial, has been shown to predict qualitative features of experimental trajectories recorded in monkeys performing intermediate speed one-joint elbow movements to a target. However, it is difficult to compare a real (experimentally measured) movement to its equivalent minimum-jerk trajectory (MJT) because the exact start and end times and positions of real movements are usually not well defined: even discrete movements usually exhibit an extended period of low (but non-zero) velocity and acceleration before and after a movement, making estimation of the exact start and end times inaccurate. Aim: The purpose of this study was to describe a method used for correctly fitting the minimum jerk trajectory to real movement data assuming that the minimum-jerk trajectory satisfies the same threshold condition as the real movement (the same position and the same percentage of maximum velocity), rather than the movements start and end at full rest. Thus, the original minimum-jerk model was revised. Materials and methods: Starting from the original minimum-jerk model, in this work is proposed a method used for correctly fitting the minimum jerk trajectory to real movement data defined by a threshold condition. This method enables users to accurately compare a minimum-jerk trajectory to real movements. The latter were recorded using APDM inertial sensors. To estimate if the ideal model fits adequately the real reaching movements we consider three kinematic indexes. Results: and Discussion: A total of 100 upper arm straight line reaching movements executed by healthy subjects were acquired. MJTs follow closely to the reaching movements when they have been computed considering the revised model. On the contrary, the MJTs do not follow the real profiles when considering the original formulation. This behaviour is confirmed when we consider the three kinematic indexes. These findings help us better understand important characteristics of movements in health. Future works will focus on the investigation of the performance of the upper arm straight line reaching movements in a larger healthy subjects sample and then in pathological conditions. Keywords: Reaching movements, Minimum jerk model, Reaching movements, Rehabilitatio