Purpose The rise of the mean age incremented the occurrence of femur fractures with respect to the past, leading thus to serious consequences, as regards morbidity and socio-economic impact. The direction of the A.O.R.N. Cardarelli of Naples has introduced a DTAP whose aim was the reduction of LOS. The paper aims to discuss this issue. Design/methodology/approach The aim of this paper is to analyze the introduction of DTAP, employing Lean Thinking and Six Sigma methodology based on the DMAIC cycle. To evaluate the effectiveness of DTAP, two groups of patients have been observed for 14 months (before and after the implementation of DTAP). Findings Statistical tests were performed on the groups and graphics were provided to visualize the decrease of LOS (29.9 per cent). The overall population was also divided in subgroups according to six variables potentially influencing LOS. Research limitations/implications Authors considered six variables of influences; yet, others could be taken into account in the future. Practical implications The decrease of costs due to the management of elderly patients with femur fracture, the optimization of care processes in hospitals and a faster recovery for patients is the tangible contribute of DTAP. Originality/value The implementation of DTAP allowed the hospital to obtain a significant reduction of LOS with a consequently decrease of costs alleviating the hospital and the society from the socio-economic burden and the morbidity of this pathology.

Coronary artery disease is one of the most prevalent chronic pathologies in the modern world, leading to the deaths of thousands of people, both in the United States and in Europe. This article reports the use of data mining techniques to analyse a population of 10,265 people who were evaluated by the Department of Advanced Biomedical Sciences for myocardial ischaemia. Overall, 22 features are extracted, and linear discriminant analysis is implemented twice through both the Knime analytics platform and R statistical programming language to classify patients as either normal or pathological. The former of these analyses includes only classification, while the latter method includes principal component analysis before classification to create new features. The classification accuracies obtained for these methods were 84.5 and 86.0 per cent, respectively, with a specificity over 97 per cent and a sensitivity between 62 and 66 per cent. This article presents a practical implementation of traditional data mining techniques that can be used to help clinicians in decision-making; moreover, principal component analysis is used as an algorithm for feature reduction.

PurposeThe goal was to improve the quality of the hospitalization process and the management of patients, allowing the reduction of costs and the minimization of the preoperative Length of Hospital Stay (LOS).Design/methodology/approachThe methodology used to improve the quality of the hospitalization process and patient management was Lean Thinking. Therefore, the Lean tools (Value stream map and Ishikawa diagram) were used to identify waste and inefficiencies, improving the process with the implementation of corrective actions. The data was collected through personal observations, patient interviews, brainstorming and from printed medical records of 151 patients undergoing oral cancer surgery in the period from 2006 to 2018.FindingsThe authors identified, through Value Stream Map, waste and inefficiencies during preoperative activities, consequently influencing preoperative LOS, considered the best performance indicator. The main causes were identified through the Ishikawa diagram, allowing reflection on possible solutions. The main corrective action was the introduction of the pre-hospitalization service. A comparative statistical analysis showed the significance of the solutions implemented. The average preoperative LOS decreased from 4.90 to 3.80 days (−22.40%) with a p-value of 0.001.Originality/valueThe methodology allowed to highlight the improvement of the patient hospitalization process with the introduction of the pre-hospitalization service. Therefore, by adopting the culture of continuous improvement, the flow of hospitalization was redrawn. The benefits of the solutions implemented are addressed to the patient in terms of lower LOS and greater service satisfaction and to the hospital for lower patient management costs and improved process quality. This article will be useful for those who need examples on how to apply Lean tools in healthcare.

Background. The Health Technology Assessment (HTA) is used to evaluate health services, manage healthcare processes more efficiently, and compare medical technologies. The aim of this paper is to carry out an HTA study that compares two pharmacological therapies and provides the clinicians with two models to predict the length of hospital stay (LOS) of patients undergoing oral cavity cancer surgery on the bone tissue. Methods. The six Sigma method was used as a tool of HTA; it is a technique of quality management and process improvement that combines the use of statistics with a five-step procedure: “Define, Measure, Analyze, Improve, Control” referred to in the acronym DMAIC. Subsequently, multiple linear regression has been used to create two models. Two groups of patients were analyzed: 45 were treated with ceftriaxone while 48 were treated with the combination of cefazolin and clindamycin. Results. A reduction of the overall mean LOS of patients undergoing oral cavity cancer surgery on bone was observed of 40.9% in the group treated with ceftriaxone. Its reduction was observed in all the variables of the ceftriaxone group. The best results are obtained in younger patients (−54.1%) and in patients with low oral hygiene (−52.4%) treated. The regression results showed that the best LOS predictors for cefazolin/clindamycin are ASA score and flap while for ceftriaxone, in addition to these two, oral hygiene and lymphadenectomy are the best predictors. In addition, the adjusted R squared showed that the variables considered explain most of the variance of LOS. Conclusion. SS methodology, used as an HTA tool, allowed us to understand the performance of the antibiotics and provided variables that mostly influence postoperative LOS. The obtained models can improve the outcome of patients, reducing the postoperative LOS and the relative costs, consequently increasing patient safety, and improving the quality of care provided.

The seismic response of freestanding elements is typically extremely critical, and this is associated with a high seismic risk in the case of museum objects and artefacts. This paper reports the preliminary results of an experimental testing campaign aimed at assessing the dynamic properties and the seismic performance of museum objects and artefacts. Shake table tests of a typical museum display case containing a representative art object (vase) are performed. Both dynamic properties and seismic behavior of the specimens were assessed. Tentative damage assessment correlations are developed. The study sheds light on the critical behavior of the tested specimens, stressing the need for further studies towards a more comprehensive assessment of freestanding museum objects and artefacts.

PurposeOne of the biggest challenges in the health sector is that of costs compared to economic resources and the quality of services. Hospitals register a progressive increase in expenditure due to the aging of the population. In fact, hip and knee arthroplasty surgery are mainly due to primary osteoarthritis that affects the elderly population. This study was carried out with the aim of analysing the introduction of the fast track surgery protocol, through the lean Six Sigma, on patients undergoing knee and hip prosthetic replacement surgery. The goal was to improve the arthroplasty surgery process by reducing the average length of stay (LOA) and hospital costsDesign/methodology/approachLean Six Sigma was applied to evaluate the arthroplasty surgery process through the DMAIC cycle (define, measure, analyse, improve and control) and the lean tools (value stream map), adopted to analyse the new protocol and improve process performance. The dataset consisted of two samples of patients: 54 patients before the introduction of the protocol and 111 patients after the improvement. Clinical and demographic variables were collected for each patient (gender, age, allergies, diabetes, cardiovascular diseases and American Society of Anaesthesiologists (ASA) score).FindingsThe results showed a 12.70% statistically significant decrease in LOS from an overall average of 8.72 to 7.61 days. Women patients without allergies, with a low ASA score not suffering from diabetes and cardiovascular disease showed a significant a reduction in hospital days with the implementation of the FTS protocol. Only the age variable was not statistically significant.Originality/valueThe introduction of the FTS in the orthopaedic field, analysed through the LSS, demonstrated to reduce LOS and, consequently, costs. For each individual patient, there was an economic saving of € 445.85. Since our study takes into consideration a dataset of 111 patients post-FTS, the overall economic saving brought by this study amounts to €49,489.35.

Indoor air quality in hospital operating rooms is of great concern for the prevention of surgical site infections (SSI). A wide range of relevant medical and engineering literature has shown that the reduction in air contamination can be achieved by introducing a more efficient set of controls of HVAC systems and exploiting alarms and monitoring systems that allow having a clear report of the internal air status level. In this paper, an operating room air quality monitoring system based on a fuzzy decision support system has been proposed in order to help hospital staff responsible to guarantee a safe environment. The goal of the work is to reduce the airborne contamination in order to optimize the surgical environment, thus preventing the occurrence of SSI and reducing the related mortality rate. The advantage of FIS is that the evaluation of the air quality is based on easy-to-find input data established on the best combination of parameters and level of alert. Compared to other literature works, the proposed approach based on the FIS has been designed to take into account also the movement of clinicians in the operating room in order to monitor unauthorized paths. The test of the proposed strategy has been executed by exploiting data collected by ad-hoc sensors placed inside a real operating block during the experimental activities of the “Bacterial Infections Post Surgery” Project (BIPS). Results show that the system is capable to return risk values with extreme precision.

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