ABSTRACT
Health technology assessments (HTAs) are often difficult to conduct because of the decisive procedures of the HTA algorithm, which are often complex and not easy to apply. Thus, their use is not always convenient or possible for the assessment of technical requests requiring a multidisciplinary approach. This paper aims to address this issue through a multi-criteria analysis focusing on the analytic hierarchy process (AHP). This methodology allows the decision maker to analyse and evaluate different alternatives and monitor their impact on different actors during the decision-making process. However, the multi-criteria analysis is implemented through a simulation model to overcome the limitations of the AHP methodology. Simulations help decision-makers to make an appropriate decision and avoid unnecessary and costly attempts. Finally, a decision problem regarding the evaluation of two health technologies, namely, the evaluation of two biological prostheses for incisional infected hernias, will be analysed to assess the effectiveness of the model.
Subject(s)
Computer Simulation , Decision Support Techniques , Models, Theoretical , Technology Assessment, Biomedical/methods , HumansABSTRACT
RATIONALE, AIMS, AND OBJECTIVES: Lean Six Sigma (LSS) has been recognized as an effective management tool for improving healthcare performance. Here, LSS was adopted to reduce the risk of healthcare-associated infections (HAIs), a critical quality parameter in the healthcare sector. METHODS: Lean Six Sigma was applied to the areas of clinical medicine (including general medicine, pulmonology, oncology, nephrology, cardiology, neurology, gastroenterology, rheumatology, and diabetology), and data regarding HAIs were collected for 28,000 patients hospitalized between January 2011 and December 2016. Following the LSS define, measure, analyse, improve, and control cycle, the factors influencing the risk of HAI were identified by using typical LSS tools (statistical analyses, brainstorming sessions, and cause-effect diagrams). Finally, corrective measures to prevent HAIs were implemented and monitored for 1 year after implementation. RESULTS: Lean Six Sigma proved to be a useful tool for identifying variables affecting the risk of HAIs and implementing corrective actions to improve the performance of the care process. A reduction in the number of patients colonized by sentinel bacteria was achieved after the improvement phase. CONCLUSIONS: The implementation of an LSS approach could significantly decrease the percentage of patients with HAIs.
Subject(s)
Cross Infection/prevention & control , Hospitals, University/organization & administration , Quality Improvement/organization & administration , Total Quality Management/organization & administration , Data Collection , Efficiency, Organizational , Humans , Italy , Practice Guidelines as Topic , Root Cause AnalysisABSTRACT
RATIONALE, AIMS, AND OBJECTIVES: The work is a part of a project about the application of the Lean Six Sigma to improve health care processes. A previously published work regarding the hip replacement surgery has shown promising results. Here, we propose an application of the DMAIC (Define, Measure, Analyse, Improve, and Control) cycle to improve quality and reduce costs related to the prosthetic knee replacement surgery by decreasing patients' length of hospital stay (LOS) METHODS: The DMAIC cycle has been adopted to decrease the patients' LOS. The University Hospital "Federico II" of Naples, one of the most important university hospitals in Southern Italy, participated in this study. Data on 148 patients who underwent prosthetic knee replacement between 2010 and 2013 were used. Process mapping, statistical measures, brainstorming activities, and comparative analysis were performed to identify factors influencing LOS and improvement strategies. RESULTS: The study allowed the identification of variables influencing the prolongation of the LOS and the implementation of corrective actions to improve the process of care. The adopted actions reduced the LOS by 42%, from a mean value of 14.2 to 8.3 days (standard deviation also decreased from 5.2 to 2.3 days). CONCLUSIONS: The DMAIC approach has proven to be a helpful strategy ensuring a significant decreasing of the LOS. Furthermore, through its implementation, a significant reduction of the average costs of hospital stay can be achieved. Such a versatile approach could be applied to improve a wide range of health care processes.
