Patients with cancer and hospital admissions: disease trajectory and strategic choices.

OBJECTIVES: Hospital admission (HA) in cancer history is a common, repeated and frequently unplanned event. The emergency departments (EDs) and the oncological outpatient service (OOS) are the ordinary way of entry. We studied the reasons of admission, pathways of access and discharge and prognostic factors in a population of admitted patients with cancer. METHODS: The health records of the admitted patients in the oncological ward of a referral hospital in a 6-month period were retrieved and analysed. The characteristics of those admitted in the last 3 months of life were compared with the other group. RESULTS: Among the 147 HA, 79.5% were unplanned, 48.9% passing through the ED and 30.6% through the OOS; 56.5% were due to cancer-related symptoms; 50.3% occurred in the last 3 months of life. Median overall survival was 90 days (95% IC 53.1-126.9). Independent prognostic factors for survival were: being admitted for symptoms, referral through the ED and not being discharged at home. CONCLUSIONS: Hospital is a turning point in the cancer care pathway. Patients needing HA have a dismal prognosis, half of them being in the last 3 months of life. This group can be identified using universally available variables.

Short-term effect of colorectal cancer on income: analysis of an Italian cohort.

INTRODUCTION: The ability to return to work after a cancer diagnosis is a key aspect of cancer survivorship and quality of life. Studies have reported a significant risk of income loss for cancer survivors; however, there is limited evidence of the Italian context. METHODS: The Work Histories Italian Panel (WHIP)-Salute database was used to select a cohort of incident cases of colorectal cancer (CRC) among workers in the private sector, based on hospital discharges. A propensity score matching was used to find a balanced control group for several confounders. Ordinary least square and logistic regressions were used to estimate the effect of a CRC diagnosis on annual income and the probability of switching from a full-time contract to a part-time one considering 3 years after the diagnosis. RESULTS: Overall, we identified 925 CRC incident cases from 2006 until 2012. Our results confirm a statistically significant reduction in survivors' income compared with controls. This reduction was greater in the first year and then tend to decrease, with an average income loss over 3 years of about €12 000. Stratified analyses by sex and position confirmed the overall trend while indicating a strong effect modification. Regarding the switching from full-time to part-time employment, the results were never significant. CONCLUSION: Income loss does not seem to be related to an increase in part-time contracts, but rather to survivors' reduced work capacity following the invasive treatments. Further research is needed to investigate the complex dynamics behind this association.

Neural networks and hospital length of stay: an application to support healthcare management with national benchmarks and thresholds.

BACKGROUND: The problem of correct inpatient scheduling is extremely significant for healthcare management. Extended length of stay can have negative effects on the supply of healthcare treatments, reducing patient accessibility and creating missed opportunities to increase hospital revenues by means of other treatments and additional hospitalizations. METHODS: Adopting available national reference values and focusing on a Department of Internal and Emergency Medicine located in the North-West of Italy, this work assesses prediction models of hospitalizations with length of stay longer than the selected benchmarks and thresholds. The prediction models investigated in this case study are based on Artificial Neural Networks and examine risk factors for prolonged hospitalizations in 2018. With respect current alternative approaches (e.g., logistic models), Artificial Neural Networks give the opportunity to identify whether the model will maximize specificity or sensitivity. RESULTS: Our sample includes administrative data extracted from the hospital database, collecting information on more than 16,000 hospitalizations between January 2018 and December 2019. Considering the overall department in 2018, 40% of the hospitalizations lasted more than the national average, and almost 3.74% were outliers (i.e., they lasted more than the threshold). According to our results, the adoption of the prediction models in 2019 could reduce the average length of stay by up to 2 days, guaranteeing more than 2000 additional hospitalizations in a year. CONCLUSIONS: The proposed models might represent an effective tool for administrators and medical professionals to predict the outcome of hospital admission and design interventions to improve hospital efficiency and effectiveness.

The hospital care of patients with cancer: a retrospective analysis of the characteristics of their hospital stay in comparison with other medical conditions.

PURPOSE: Hospital admission is a frequent occurrence among patients with cancer, and a significant proportion of patients admitted to medical units have cancer. Their hospital stay has features that may be different compared with patients without cancer. We performed a retrospective analysis of the characteristics of patients with cancer admitted for medical conditions. PATIENTS AND METHODS: We studied the administrative data of patients with solid cancer admitted to the medical department of a large referral hospital over a 12-month period and compared them with those of patients without cancer. RESULTS: Seven thousand eight hundred two consecutive admissions were analysed, of which 1099 (14.1%) had a principal or associated diagnosis of cancer. Admissions were distributed across 12 units, with 44% concentrated in the medical oncology unit and 56% in other units. Patients with cancer were more frequently men and were younger than patients without cancer. Admission less frequently involved the emergency department (ED), while discharge was more frequently assisted. The in-hospital death rate was higher, as was the readmission rate. Length of stay was longer (11.3 days vs. 9.8 days; p < 0.0001). Patients with cancer admitted to the medical oncology unit used the ED even less, and their length of stay was shorter than that of patients with cancer admitted in other units. CONCLUSIONS: The in-hospital pathway of patients with cancer displays specific issues and adds complexity to hospital stay of patients with medical conditions. The medical oncology unit plays a role in reducing ED use and in providing efficient care. The evidence gathered should help in shaping new models of care and in improving adequate clinical competencies.

Organizational determinants of hospital stay: establishing the basis of a widespread action on more efficient pathways in medical units.

Given the high hospital costs, the increasing clinical complexity and the overcrowding of emergency departments, it is crucial to improve the efficiency of medical admissions. We aimed at isolating organizational drivers potentially targetable through a widespread improvement action. We studied all medical admissions in a large tertiary referral hospital from January 1st to December 31st, 2018. Data were retrieved from the administrative database. Available information included age, sex, type (urgent or elective) and Unit of admission, number of internal transfers, main ICD-9 diagnosis, presence of cancer among diagnoses, surgical or medical code, type of discharge, month, day and hour of admission and discharge. National Ministry of Health database was used for comparisons. 8099 admissions were analyzed. Urgent admissions (80.5% of the total) were responsible for longer stays and were the object of the multivariate analysis. The variables most influencing length-of-stay (LOS) were internal transfers and assisted discharge: they contributed, respectively, to 62% and 40% prolongation of LOS. Also, the daily and weekly kinetics of admission accounted for a significant amount of variation in LOS. Long admissions (≥ 30 days) accounted for the 15.5% of total bed availability. Type of discharge and internal transfers were again among the major determinants. A few factors involved in LOS strictly depend on the organizational environment and are potentially modifiable. Re-engineering should be focused on making more efficient internal and external transitions and at ensuring continuity of the clinical process throughout the day and the week.

UF-5000 flow cytometer: A new technology to support microbiologists' interpretation of suspected urinary tract infections.

This case study aims to describe the adoption of an innovative flow cytometer (i.e., UF-5000), which can support the microbiologists' process of diagnosing suspected urinary tract infections (UTIs). The new clinical information provided can be used to improve the identification of both contamination and colonization, thus reducing inappropriate antibiotic prescriptions. In July and August 2017, the Microbiology Laboratory of Alessandria (Italy) conducted a retrospective monocentric study analyzing data about 1,295 urine specimens from inpatients and outpatients with symptoms of UTIs. The results of this study show that the innovative technology can successfully support the diagnostic process in microbiology laboratories and, consequently, the supply of sustainable treatments by hospitals.

Toward uniform and controlled clinical pathways in cancer care: a qualitative description.

QUALITY ISSUE: The definition of clinical pathways (CPs) and their application are heterogeneous. Each center is used to choose whether to adopt this instrument or not and to variably conceive its features We consider CPs as the necessary description of the cancer patient journey and we emphasize their role as the user view of clinical processes rather than a local translation of guidelines. CHOICE OF SOLUTION: We proposed a unique CPs model for all the centers of our regional network, with the aim of making CPs accountable and comparable. We also established a central quality evaluation. IMPLEMENTATION: Through a multi-step process, the model was proposed to the 22 Regional centers. Landmark characteristics of the project were: the involvement of hospital administrations; reference to a unique set of guidelines; a peer-review and open evaluation. EVALUATION: Of the 374 expected CPs, 253 (68%) were received and evaluated. A median number of 131 items were the object of evaluation in each hub center and 77 in each spoke center. About 79.5% items were considered well described, 15.5% were absent and 5.0% partially described. The median percentage of fulfilled indicators was 85.6% in hub CPs and 82.2% in spoke CPs. Although, not all diseases were equally covered through the territory a high degree of homogeneity and a good quality of compilation were achieved. LESSONS LEARNED: The project was shown to be feasible and achieved its goal. We suggest this process as a functional way for building uniform cancer CPs.

Artificial neural networks and risk stratification in emergency departments.

Emergency departments are characterized by the need for quick diagnosis under pressure. To select the most appropriate treatment, a series of rules to support decision-making has been offered by scientific societies. The effectiveness of these rules affects the appropriateness of treatment and the hospitalization of patients. Analyzing a sample of 1844 patients and focusing on the decision to hospitalize a patient after a syncope event to prevent severe short-term outcomes, this work proposes a new algorithm based on neural networks. Artificial neural networks are a non-parametric technique with the well-known ability to generalize behaviors, and they can thus predict severe short-term outcomes with pre-selected levels of sensitivity and specificity. This innovative technique can outperform the traditional models, since it does not require a specific functional form, i.e., the data are not supposed to be distributed following a specific design. Based on our results, the innovative model can predict hospitalization with a sensitivity of 100% and a specificity of 79%, significantly increasing the appropriateness of medical treatment and, as a result, hospital efficiency. According to Garson's Indexes, the most significant variables are exertion, the absence of symptoms, and the patient's gender. On the contrary, cardio-vascular history, hypertension, and age have the lowest impact on the determination of the subject's health status. The main application of this new technology is the adoption of smart solutions (e.g., a mobile app) to customize the stratification of patients admitted to emergency departments (ED)s after a syncope event. Indeed, the adoption of these smart solutions gives the opportunity to customize risk stratification according to the specific clinical case (i.e., the patient's health status) and the physician's decision-making process (i.e., the desired levels of sensitivity and specificity). Moreover, a decision-making process based on these smart solutions might ensure a more effective use of available resources, improving the management of syncope patients and reducing the cost of inappropriate treatment and hospitalization.

Correction to: The private healthcare market and the sustainability of an innovative community nurses programme based on social entrepreneurship - CoNSENSo project.

Following publication of the original article [1], the author reported that their first names and last names were swapped. The original article has been corrected.

The private healthcare market and the sustainability of an innovative community nurses programme based on social entrepreneurship - CoNSENSo project.

BACKGROUND: CoNSENSo is a project funded by the European Union, which is aimed at developing an innovative care model based on community nurses to support active ageing in mountain areas. The planned sustainability of this innovative approach relies on social entrepreneurship on the healthcare market, and this work highlights the necessary conditions for the successful implementation of these entrepreneurial initiatives. METHODS: Considering municipalities in the Piedmont Region and those aged 65 or older as target population, the authors propose several negative binomial regression models to estimate the effectiveness of current private healthcare services in supporting the active aging process. Such effectiveness may represent the ex-ante (positive) reputation of these new social entrepreneurial initiatives on the market. RESULTS: According to our results, the private supply of healthcare services can effectively support the aging process. Indeed, given that the other predictor variables in the model are held constant, there are statistically significant negative relations between the number of hip fractures and the private supply of healthcare services by dental practitioners and psychologists (p-value < 0.05), as well as the private supply of opportunities for social interaction by coffee bars (p-value < 0.05). CONCLUSIONS: The authors expect a favourable environment for the entrepreneurial initiatives of community nurses in mountain areas. Accordingly, policy makers cannot reject the hypothesis that the goals reached by the CoNSENSo project may be maintained for the sake of the future generations, avoiding its collapse as soon as public funding shifts to new programmes.

The Economic Impact of Clinical Research in an Italian Public Hospital: The Malignant Pleural Mesothelioma Case Study.

BACKGROUND: The current economic constraints cause hospital management to use the available public resources as rationally as possible. At the same time, there is the necessity to improve current scientific knowledge. This is even more relevant in the case of patients with malignant pleural mesothelioma (MPM), given the severity of the disease, its dismal prognosis, and the cost of chemotherapy drugs. This work aims to evaluate the standard cost of patients with MPM, supporting physicians in their decision-making process in relation to budget constraints, as well as policy-makers with respect research policy. METHODS: The authors conducted a retrospective cost analysis on all the patients with MPM who were first admitted to a reference hospital specialized in MPM care between 2014 and 2015, collecting data on their diagnostic pathways and active treatments, as well as on the related official fees for each procedure. Then, using a multiple regression model, we estimated the overall expected cost of a patient with MPM treated in our hospital, to be born by the Regional Healthcare System based on the chosen clinical pathway. RESULTS: According to results, the economic impact of caring for a patient with MPM is mostly related to the selected active treatments, with drug and hospitalization costs as main drivers. Our analysis suggests that the expected reimbursed fee to care for a patient with MPM is equal to € 18 214.99, with chemotherapy and monitoring costs equal to € 12 861.43 and hospitalization cost equal to € 5353.55. This cost decreases to € 320.18 in the case of enrollment in an experimental trial of first-line treatment. In the other cases (second-line or third-line trials), the expected cost borne by the healthcare system for treating patients grows exponentially (€ 40,124.18 and € 59 839.94, respectively). CONCLUSION: Experimental trials might be a solution to decrease the economic burden for the public healthcare system only in the case of first-line treatments, where the cost of chemotherapy is relevant. Nevertheless, policy-makers have to accept the sharing of this economic burden between society and the pharmaceutical industry to broaden the current scientific knowledge.

The sustainability of a community nurses programme aimed at supporting active ageing in mountain areas.

BACKGROUND: Community Nurse Supporting Elderly iN a changing SOciety is a project funded by the European Union, which is aimed at developing an innovative care model based on community nurses to support active ageing in mountain areas. The planned sustainability of this innovative approach relies on social entrepreneurship, and this work highlights the necessary conditions for the existence of these entrepreneurial initiatives on the market, with community nurses' services purchased by the public health care system. METHODS: The authors propose a sustainability framework for this project based on three relevant dimensions (ie, health, organisation, and context), highlighting the necessary conditions for continued provision of health services beyond project conclusion. Then, considering the Piedmont Region and those aged 65 or older as target population, health outcomes are analysed, proposing a break-even analysis to calculate expected levels. RESULTS: According to our results, in order to care for 191 977 elderly people for 3 years, a successful pro-active approach is needed to prevent 1657 falls with hip fracture, reducing the prevalence of this adverse outcome by 36%. These are the expected health outcome levels for the existence of a social market, which can be achieved through the successful involvement of local public health organisations and stakeholders. CONCLUSIONS: Policy makers need clear information on the economic impact of extending this new intervention to the whole target population and on the required preconditions for its financial sustainability in terms of health outcomes. However, a participatory process involving all relevant local stakeholders and organisations is crucial to extend current achievements beyond project conclusion.

Human Mating Theory, Migration, and Marital Dissolution.

Marriage dissolution has been extensively analyzed in the last few decades, looking for the determinants of this well-known phenomenon, but so far the relationship between female migration and marriage dissolution does not seem to have been thoroughly investigated. This work aimed to analyze the correlation between marriage dissolution and migration, which might bias the sex ratio within a given society, introducing new social and cultural values. Considering the Regions of Italy between 2002 and 2007 (i.e., 120 observations), several multiple regression models (OLS) were presented to test the proposed hypothesis, applying the robust option. The dependent variable of our empirical investigation was a marriage dissolution index, while the key explanatory variables were a sex ratio and several female rates. Based on the results, the hypothesis of a statistically significant positive relation between the influx of female immigrants and household dissolution could be supported (i.e., p < .01). However, not all migrating women are the same and a different impact is foreseeable according to the nature of this influx. Indeed, given a 1% influx of unmarried foreign females, increasing the sex ratio within society, marital dissolutions grow by 5381 for every 100,000 marriages. In the case of a 1% influx of Italian unmarried females, marital dissolutions grew by 3173 for every 100,000 marriages. Therefore, females could have specific sexual, social and cultural characteristics, which might be able to increase (or decrease) the probability of men being driven to sexual infidelity, thus leading to a higher frequency of marriage dissolutions.

Neural networks as a tool to predict syncope risk in the Emergency Department.

AIMS: There is no universally accepted tool for the risk stratification of syncope patients in the Emergency Department. The aim of this study was to investigate the short-term predictive accuracy of an artificial neural network (ANN) in stratifying the risk in this patient group. METHODS AND RESULTS: We analysed individual level data from three prospective studies, with a cumulative sample size of 1844 subjects. Each dataset was reanalysed to reduce the heterogeneity among studies defining abnormal electrocardiogram (ECG) and serious outcomes according to a previous consensus. Ten variables from patient history, ECG, and the circumstances of syncope were used to train and test the neural network. Given the exploratory nature of this work, we adopted two approaches to train and validate the tool. One approach used 4/5 of the data for the training set and 1/5 for the validation set, and the other approach used 9/10 for the training set and 1/10 for the validation set. The sensitivity, specificity, and area under the receiver operating characteristic curve of ANNs in identifying short-term adverse events after syncope were 95% [95% confidence interval (CI) 80-98%], 67% (95% CI 62-72%), 0.69 with the 1/5 approach and 100% (95% CI 84-100%), 79% (95% CI 72-85%), 0.78 with the 1/10 approach. CONCLUSION: The results of our study suggest that ANNs are effective in predicting the short-term risk of patients with syncope. Prospective studies are needed in order to compare ANNs' predictive capability with existing rules and clinical judgment.

Artificial Neural Networks and risk stratification models in Emergency Departments: The policy maker's perspective.

The primary goal of Emergency Department (ED) physicians is to discriminate between individuals at low risk, who can be safely discharged, and patients at high risk, who require prompt hospitalization. The problem of correctly classifying patients is an issue involving not only clinical but also managerial aspects, since reducing the rate of admission of patients to EDs could dramatically cut costs. Nevertheless, a trade-off might arise due to the need to find a balance between economic interests and the health conditions of patients. This work considers patients in EDs after a syncope event and presents a comparative analysis between two models: a multivariate logistic regression model, as proposed by the scientific community to stratify the expected risk of severe outcomes in the short and long run, and Artificial Neural Networks (ANNs), an innovative model. The analysis highlights differences in correct classification of severe outcomes at 10 days (98.30% vs. 94.07%) and 1 year (97.67% vs. 96.40%), pointing to the superiority of Neural Networks. According to the results, there is also a significant superiority of ANNs in terms of false negatives both at 10 days (3.70% vs. 5.93%) and at 1 year (2.33% vs. 10.07%). However, considering the false positives, the adoption of ANNs would cause an increase in hospital costs, highlighting the potential trade-off which policy makers might face.

Priorities for emergency department syncope research.

STUDY OBJECTIVES: There is limited evidence to guide the emergency department (ED) evaluation and management of syncope. The First International Workshop on Syncope Risk Stratification in the Emergency Department identified key research questions and methodological standards essential to advancing the science of ED-based syncope research. METHODS: We recruited a multinational panel of syncope experts. A preconference survey identified research priorities, which were refined during and after the conference through an iterative review process. RESULTS: There were 31 participants from 7 countries who represented 10 clinical and methodological specialties. High-priority research recommendations were organized around a conceptual model of ED decisionmaking for syncope, and they address definition, cohort selection, risk stratification, and management. CONCLUSION: We convened a multispecialty group of syncope experts to identify the most pressing knowledge gaps and defined a high-priority research agenda to improve the care of patients with syncope in the ED.

Economic efficiency of countries' clinical review processes and competitiveness on the market of human experimentation.

Clinical research is a specific phase of pharmaceutical industry's production process in which companies test candidate drugs on patients to collect clinical evidence about safety and effectiveness. Information is essential to obtain manufacturing authorization from the national drug agency and, in this way, make profits on the market. Considering this activity, however, the public stakeholder has to face a conflict of interests. On the one side, there is society's necessity to make advances in medicine and, of course, to promote pharmaceutical companies' investments in this specific phase (new generation). On the other side, there is the duty to protect patients involved in these experimental treatments (old generation). To abide by this moral duty, a protection system was developed through the years, based on two legal institutions: informed consent and institutional review board. How should an efficient protection system that would take human experimentation into account be shaped? Would it be possible for the national protection system of patients' rights to affect the choice of whether to develop a clinical trial in a given country or not? Looking at Europe and considering a protection system that is shaped around institutional review boards, this article is an empirical work that tries to give answers to these open questions. It shows how a protection system that can minimize the time necessary to start a trial can positively affect pharmaceutical clinical research, that is, the choice of pharmaceutical companies to start innovative medical treatments in a given country.

Hospital organization and performance: a directional distance function approach.

The present study considers the Italian healthcare system, investigating the aspects that might affect the efficiency of Italian hospitals. The authors analyze what influences a specific definition of efficiency, which is calculated maximizing healthcare production but minimizing potential financial losses. In other words, this work considers efficient each hospital which is able to maximize the production of medical treatments while complying, at the same time, with budget constraints. Hence, the results of this paper are twofold: from the organizational point of view, they underline the need for rebalancing the various administrative levels of hospitals; from the technical point of view, a more coherent model is proposed in order to account for all the aspects of the healthcare industry.