A Six Sigma DMAIC methodology as a support tool for Health Technology Assessment of two antibiotics

Alfonso Maria Ponsiglione; Carlo Ricciardi; Giovanni Improta; Giovanni Dell'Aversana Orabona; Alfonso Sorrentino; Francesco Amato; Maria Romano; Alfonso Maria Ponsiglione; Carlo Ricciardi; Giovanni Improta; Giovanni Dell'Aversana Orabona; Alfonso Sorrentino; Francesco Amato; Maria Romano

doi:10.3934/mbe.2021174

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 4: 3469-3490. doi: 10.3934/mbe.2021174

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A Six Sigma DMAIC methodology as a support tool for Health Technology Assessment of two antibiotics

1.
Department of Electrical Engineering and Information Technology (DIETI), University of Naples "Federico II", Naples, Italy
2.
Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
3.
Department of Public Health, University of Naples "Federico II", Naples, Italy
4.
Interdepartmental Center for Research in Healthcare Management and Innovation in Healthcare (CIRMIS), University of Naples "Federico II", Naples, Italy
5.
Maxillofacial Surgery Unit, Department of Neurosciences, Reproductive and Odontostomatological Sciences, University Hospital of Naples "Federico II", Naples, Italy

Academic Editor: Ping Jiang

Received: 21 January 2021 Accepted: 01 April 2021 Published: 19 April 2021

Health Technology Assessment (HTA) and Six Sigma (SS) have largely proved their reliability in the healthcare context. The former focuses on the assessment of health technologies to be introduced in a healthcare system. The latter deals with the improvement of the quality of services, reducing errors and variability in the healthcare processes. Both the approaches demand a detailed analysis, evidence-based decisions, and efficient control plans. In this paper, the SS is applied as a support tool for HTA of two antibiotics with the final aim of assessing their clinical and organizational impact in terms of postoperative Length Of Stay (LOS) for patients undergoing tongue cancer surgery. More specifically, the SS has been implemented through its main tool, namely the DMAIC (Define, Measure, Analyse, Improve, Control) cycle. Moreover, within the DMAIC cycle, a modelling approach based on a multiple linear regression analysis technique is introduced, in the Control phase, to add complementary information and confirm the results obtained by the statistical analysis performed within the other phases of the SS DMAIC. The obtained results show that the proposed methodology is effective to determine the clinical and organizational impact of each of the examined antibiotics, when LOS is taken as a measure of performance, and guide the decision-making process. Furthermore, our study provides a systematic procedure which, properly combining different and well-assessed tools available in the literature, demonstrated to be a useful guidance for choosing the right treatment based on the available data in the specific circumstance.
- Health Technology Assessment,
- Six Sigma,
- DMAIC,
- modelling,
- public health
Citation: Alfonso Maria Ponsiglione, Carlo Ricciardi, Giovanni Improta, Giovanni Dell'Aversana Orabona, Alfonso Sorrentino, Francesco Amato, Maria Romano. A Six Sigma DMAIC methodology as a support tool for Health Technology Assessment of two antibiotics[J]. Mathematical Biosciences and Engineering, 2021, 18(4): 3469-3490. doi: 10.3934/mbe.2021174

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Abstract

Health Technology Assessment (HTA) and Six Sigma (SS) have largely proved their reliability in the healthcare context. The former focuses on the assessment of health technologies to be introduced in a healthcare system. The latter deals with the improvement of the quality of services, reducing errors and variability in the healthcare processes. Both the approaches demand a detailed analysis, evidence-based decisions, and efficient control plans. In this paper, the SS is applied as a support tool for HTA of two antibiotics with the final aim of assessing their clinical and organizational impact in terms of postoperative Length Of Stay (LOS) for patients undergoing tongue cancer surgery. More specifically, the SS has been implemented through its main tool, namely the DMAIC (Define, Measure, Analyse, Improve, Control) cycle. Moreover, within the DMAIC cycle, a modelling approach based on a multiple linear regression analysis technique is introduced, in the Control phase, to add complementary information and confirm the results obtained by the statistical analysis performed within the other phases of the SS DMAIC. The obtained results show that the proposed methodology is effective to determine the clinical and organizational impact of each of the examined antibiotics, when LOS is taken as a measure of performance, and guide the decision-making process. Furthermore, our study provides a systematic procedure which, properly combining different and well-assessed tools available in the literature, demonstrated to be a useful guidance for choosing the right treatment based on the available data in the specific circumstance.

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