Literature DB >> 22755481

Application of Six Sigma methodology to a diagnostic imaging process.

Mehmet Tolga Taner1, Bulent Sezen, Kamal M Atwat.   

Abstract

PURPOSE: This paper aims to apply the Six Sigma methodology to improve workflow by eliminating the causes of failure in the medical imaging department of a private Turkish hospital. DESIGN/METHODOLOGY/APPROACH: Implementation of the design, measure, analyse, improve and control (DMAIC) improvement cycle, workflow chart, fishbone diagrams and Pareto charts were employed, together with rigorous data collection in the department. The identification of root causes of repeat sessions and delays was followed by failure, mode and effect analysis, hazard analysis and decision tree analysis.
FINDINGS: The most frequent causes of failure were malfunction of the RIS/PACS system and improper positioning of patients. Subsequent to extensive training of professionals, the sigma level was increased from 3.5 to 4.2. RESEARCH LIMITATIONS/IMPLICATIONS: The data were collected over only four months. PRACTICAL IMPLICATIONS: Six Sigma's data measurement and process improvement methodology is the impetus for health care organisations to rethink their workflow and reduce malpractice. It involves measuring, recording and reporting data on a regular basis. This enables the administration to monitor workflow continuously. SOCIAL IMPLICATIONS: The improvements in the workflow under study, made by determining the failures and potential risks associated with radiologic care, will have a positive impact on society in terms of patient safety. Having eliminated repeat examinations, the risk of being exposed to more radiation was also minimised. ORIGINALITY/VALUE: This paper supports the need to apply Six Sigma and present an evaluation of the process in an imaging department.

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Year:  2012        PMID: 22755481     DOI: 10.1108/09526861211221482

Source DB:  PubMed          Journal:  Int J Health Care Qual Assur        ISSN: 0952-6862


  1 in total

1.  Using Six Sigma DMAIC Methodology and Discrete Event Simulation to Reduce Patient Discharge Time in King Hussein Cancer Center.

Authors:  Mazen Arafeh; Mahmoud A Barghash; Nirmin Haddad; Nadeem Musharbash; Dana Nashawati; Adnan Al-Bashir; Fatina Assaf
Journal:  J Healthc Eng       Date:  2018-06-24       Impact factor: 2.682

  1 in total

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