Application of DMAIC Cycle and Modeling as Tools for Health Technology Assessment in a University Hospital

Author:

Ponsiglione Alfonso Maria1ORCID,Ricciardi Carlo2ORCID,Scala Arianna3ORCID,Fiorillo Antonella2ORCID,Sorrentino Alfonso4ORCID,Triassi Maria3ORCID,Dell’Aversana Orabona Giovanni4ORCID,Improta Giovanni3ORCID

Affiliation:

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 Hospital of Naples “Federico II”, Naples, Italy

4. Maxillofacial Surgery Unit, Department of Neurosciences, Reproductive and Odontostomatological Sciences, University Hospital of Naples “Federico II”, Naples, Italy

Abstract

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.

Publisher

Hindawi Limited

Subject

Health Informatics,Biomedical Engineering,Surgery,Biotechnology

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