Publicação
Process mining and lean six sigma: a blended approach to improve the purchasing process of a hospital
| Resumo: | With the rising budget and resource contingencies in the healthcare system, the need to improve processes to ensure the quality of care for the patients is paramount. More than ever, the right strategies and management practices are urgently needed to optimize scarce resources and alleviate shortages. In light of these challenges, the purchasing process plays a strategic role in successful healthcare operations. Its fluidity is critical for the best clinical activity to happen, by assuring the right product is purchased, at the best price, in the most efficient way. Achieving the best outcomes for patients relies strongly on non-clinical processes running smoothly in the background. Acknowledging the importance of achieving a frictionless purchasing process, a healthcare provider, along with one of its key suppliers, started an improvement initiative keen on evaluating their purchasing behavior. The assessment focused on two main dimensions: the quality of the orders issued, and the ordering time of new products. Firstly, because each purchase has an underlying processing cost, and secondly because the higher the ordering time the higher the potential disruption in the end-to-end supply chain. With such a complex inter-departmental process, the standard Lean Six Sigma approach would fall short in terms of process coverage. For this reason, it was combined with Process Mining methodologies, by using event-driven data stored to speed some phases of the DMAIC. If on one hand Process Mining presented itself as an effective way of discovering the end-to-end process, Lean Six Sigma, with the DMAIC cycle, provided a logical structure to analyze it. By combining the speed of analysis of the first, and the quality tools of the second, a blended methodology was deployed, translating logged information into valuable business insights. Despite the importance of obtaining full visibility over operations and the operational excellence that derives from it, few cases of transformational improvement initiatives, resulting from the analysis of logged information are documented and made available, especially from the healthcare sector. Usually, they focus entirely on one of the approaches individually. The goal of this thesis is to depict how process mining can instigate evidence-based quality improvements in healthcare, contributing to the scientific literature. Finally, a reflection is provided regarding the managerial and theoretical implications of the dissertation. Also, the obstacles of deploying such an approach in a highly-conservative healthcare procurement context are depicted. |
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| Autores principais: | Ramires, Francisco da Silva |
| Assunto: | DMAIC Hospital purchasing process Lean six sigma Process mining Compras hospitalares Lean seis sigma Melhoria de processos |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | With the rising budget and resource contingencies in the healthcare system, the need to improve processes to ensure the quality of care for the patients is paramount. More than ever, the right strategies and management practices are urgently needed to optimize scarce resources and alleviate shortages. In light of these challenges, the purchasing process plays a strategic role in successful healthcare operations. Its fluidity is critical for the best clinical activity to happen, by assuring the right product is purchased, at the best price, in the most efficient way. Achieving the best outcomes for patients relies strongly on non-clinical processes running smoothly in the background. Acknowledging the importance of achieving a frictionless purchasing process, a healthcare provider, along with one of its key suppliers, started an improvement initiative keen on evaluating their purchasing behavior. The assessment focused on two main dimensions: the quality of the orders issued, and the ordering time of new products. Firstly, because each purchase has an underlying processing cost, and secondly because the higher the ordering time the higher the potential disruption in the end-to-end supply chain. With such a complex inter-departmental process, the standard Lean Six Sigma approach would fall short in terms of process coverage. For this reason, it was combined with Process Mining methodologies, by using event-driven data stored to speed some phases of the DMAIC. If on one hand Process Mining presented itself as an effective way of discovering the end-to-end process, Lean Six Sigma, with the DMAIC cycle, provided a logical structure to analyze it. By combining the speed of analysis of the first, and the quality tools of the second, a blended methodology was deployed, translating logged information into valuable business insights. Despite the importance of obtaining full visibility over operations and the operational excellence that derives from it, few cases of transformational improvement initiatives, resulting from the analysis of logged information are documented and made available, especially from the healthcare sector. Usually, they focus entirely on one of the approaches individually. The goal of this thesis is to depict how process mining can instigate evidence-based quality improvements in healthcare, contributing to the scientific literature. Finally, a reflection is provided regarding the managerial and theoretical implications of the dissertation. Also, the obstacles of deploying such an approach in a highly-conservative healthcare procurement context are depicted. |
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