Tesi etd-11262024-175820
Link copiato negli appunti
Tipo di tesi
Dottorato
Autore
PERUZZO, ELISA
URN
etd-11262024-175820
Titolo
Listening, Learning and Driving change: from data collection to data use
Settore scientifico disciplinare
SECS-P/08
Corso di studi
Istituto di Management - PhD in Health Science, Technology and Management - PON
Commissione
Relatore Prof.ssa VAINIERI, MILENA
Membro Dott.ssa BERTARELLI, GAIA
Presidente Prof. TAGLIABUE, MARCO
Membro Prof.ssa CANTARELLI, PAOLA
Membro Dott.ssa BERTARELLI, GAIA
Presidente Prof. TAGLIABUE, MARCO
Membro Prof.ssa CANTARELLI, PAOLA
Parole chiave
- Constructive research approach
- Continuous Quality Improvement
- Customer focus
- Data Use
- Data-driven Decision Making
- Patient-Reported data
- Service Quality
- Total Quality Management
Data inizio appello
30/11/2025;
Disponibilità
parziale
Riassunto analitico
Total Quality Management (TQM) is a management approach aimed at improving organizational performance through continuous improvement, data-driven decision-making and customer focus. Within this framework, Continuous Quality Improvement (CQI) represents an operational approach that support organizations in identifying areas for improvement, implementing changes and converting input into output to provide services that meets and satisfy customer expectations. This is particularly relevant in healthcare, given the complexity of the system and the attention required for both clinical and organizational aspects.
This PhD dissertation explores how patient-reported data can be effectively used for quality improvement and decision-making. Patient-reported data are a key input for continuous improvement, but their mere collection is not, in itself, a quality improvement tool. Therefore, this dissertation focuses on the transition from the collection of patient-reported data to their active use. To explore this transition, the thesis is structured around three interconnected studies. While each study has a specific objective and method, they are complementary in reflecting a cycle: from listening to learning, to driving change.
The first study addresses the listening phase, by identifying which aspects of patients’ experience should be prioritized to improve the overall patient satisfaction in different departmental areas (i.e., medical and surgical wards). More specifically, this study uses an optimization model to identify these priority aspects. The results highlight specific experiential factors that should be prioritized in quality improvement efforts. Additionally, these aspects vary according to the specific departmental area. By identifying priority areas, healthcare professionals can better allocate their time, activities and resources and develop targeted quality improvement initiatives.
In relation to this, a key challenge lies in converting patient-reported experience data into actionable knowledge for quality improvement.
Accordingly, the second study focused on learning, by mapping the actions derived from the use of patient-experience data within a real-world context. The findings underline a widespread use of patient-reported data as a knowledge base for action. Four key themes were identified, namely internal actions addressed to hospital staff, external actions addressed to users, comfort and hospitality aspects and review of processes and procedures. This research advocates for fostering a culture of continuous learning and improvement within and across healthcare organizations.
Finally, the third research of the thesis explores the driving change phase through three cases study. Each case study aimed to investigate how patient-reported data are used by professionals and the potential impact of the implemented quality improvement initiatives with particular attention on impact on patients’ experience. These cases demonstrate how feedback, when acted upon, can lead to visible and measurable change.
These three studies offer a comprehensive understanding of how patient-reported data can inform decision-making and drive targeted interventions and improvements at multiple levels of healthcare delivery.
The thesis contributes to the academic debate, by offering empirical insights and evidence into the role of patient-reported data, addressing a gap that is often explored from a theoretical perspective. From a practical point of view, the thesis shows strategies and tools that healthcare managers and practitioners can adopt to translate patients’ input into quality improvement initiatives.
Finally, this dissertation was made possible through collaboration and open dialogue between academic and healthcare worlds, according to a constructive approach. This partnership allows to create, validate and share knowledge and insights within the sphere of healthcare services and to generate practical evidence and real word impact.
This PhD dissertation explores how patient-reported data can be effectively used for quality improvement and decision-making. Patient-reported data are a key input for continuous improvement, but their mere collection is not, in itself, a quality improvement tool. Therefore, this dissertation focuses on the transition from the collection of patient-reported data to their active use. To explore this transition, the thesis is structured around three interconnected studies. While each study has a specific objective and method, they are complementary in reflecting a cycle: from listening to learning, to driving change.
The first study addresses the listening phase, by identifying which aspects of patients’ experience should be prioritized to improve the overall patient satisfaction in different departmental areas (i.e., medical and surgical wards). More specifically, this study uses an optimization model to identify these priority aspects. The results highlight specific experiential factors that should be prioritized in quality improvement efforts. Additionally, these aspects vary according to the specific departmental area. By identifying priority areas, healthcare professionals can better allocate their time, activities and resources and develop targeted quality improvement initiatives.
In relation to this, a key challenge lies in converting patient-reported experience data into actionable knowledge for quality improvement.
Accordingly, the second study focused on learning, by mapping the actions derived from the use of patient-experience data within a real-world context. The findings underline a widespread use of patient-reported data as a knowledge base for action. Four key themes were identified, namely internal actions addressed to hospital staff, external actions addressed to users, comfort and hospitality aspects and review of processes and procedures. This research advocates for fostering a culture of continuous learning and improvement within and across healthcare organizations.
Finally, the third research of the thesis explores the driving change phase through three cases study. Each case study aimed to investigate how patient-reported data are used by professionals and the potential impact of the implemented quality improvement initiatives with particular attention on impact on patients’ experience. These cases demonstrate how feedback, when acted upon, can lead to visible and measurable change.
These three studies offer a comprehensive understanding of how patient-reported data can inform decision-making and drive targeted interventions and improvements at multiple levels of healthcare delivery.
The thesis contributes to the academic debate, by offering empirical insights and evidence into the role of patient-reported data, addressing a gap that is often explored from a theoretical perspective. From a practical point of view, the thesis shows strategies and tools that healthcare managers and practitioners can adopt to translate patients’ input into quality improvement initiatives.
Finally, this dissertation was made possible through collaboration and open dialogue between academic and healthcare worlds, according to a constructive approach. This partnership allows to create, validate and share knowledge and insights within the sphere of healthcare services and to generate practical evidence and real word impact.
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