Context and objective The San Raffaele Hospital in Milan is a clinic of diagnostic and therapeutic excellence in medical, surgical and interventional medicine. Founded in 1971, already in 1972 it received the recognition of IRCCS for diabetology, until 2001, when the extension of the qualification reached the whole field of molecular medicine. The Transformation Office (TO) was founded in 2020 and constitutes the Operational Management of the Hospital. The objective of the Office is to use the data obtained from the departments and outpatient clinics through innovative and efficient methods of constant monitoring of operations to develop projects and strategic plans. In addition, the TO aims to reconfigure outdated hospital processes, seeking to improve the quality of services provided by the hospital and optimizing administrative management. Pursuing the objectives of the Office, the following thesis work was born. This work proposes the reconstruction of the current clinical-administrative-informatics process of the dialysis department, the analysis of its critical points and provides ideas for the total reconfiguration and optimization of the process. Materials and Methods The work was structured according to the following logic: to define priorities for intervention through the analysis of hospital data, thus identifying which departments or outpatient clinics had a non-optimal process management and in contrast with the innovative principles of TO. To decide on priorities, the services offered by departments and their importance in terms of hospital turnover were also taken into consideration. The path was therefore dictated by an initial analysis of the turnover, going into detail as we went along and discovering anomalies in the system. The sources of data were the central hospital databases, managed by IT. The central databases are made up of the information collected by the numerous software programs used in the management of wards, outpatient clinics, admissions and every other area of the hospital. The software referred to for data analysis, were: - QlikSense and QlikView, for the collection and visualization of historical and real-time data; - SAP, for acceptances and performance billing; - TSS and TM, for IT management of the dialysis department. Process Mining methods were then used to reconstruct the current process, i.e. a series of interviews and strategic planning to go into total detail about the process configuration. The logic of the PDCA (Plan-Do-Check-Act) theory, advocated by engineer W. Edward Deming, was then followed, a modular operational strategy that can be applied globally to the organization. Finally, the Signavio software was used as a Business Process Modeling tool, for the reconstruction of the process and for its reconfiguration in an optimized version. Results, conclusions and future developments The analyses performed allowed for the development of graphs on turnover trends, which led to a focus on the dialysis department. Next, detailed graphs of the dialysis department itself were constructed in order to extract as much information as possible and translate it into strategic decisions and operations. From there, interviews were conducted to build the process and a graph of what was obtained was reported, using the chosen Business Process Modeling tool. Considering the needs of each actor involved in the process, a new optimized process has been built. The project is in the phase of evaluating the development costs, which will be provided by the companies supplying the software used in the process; this task is currently managed by the Information Systems in collaboration with the Transformation Office. The objective of this internship and thesis work has been largely achieved, having defined the project and implemented it at the company level. The future goal will be to extend the process to the Control Room, i.e. the real-time monitoring of the department's operations with the possibility of implementing Machine Learning predictive techniques.
Contesto e obiettivo L’Ospedale San Raffaele di Milano è una clinica di eccellenza diagnostica e terapeutica medica, chirurgica ed interventistica. Fondato nel 1971, già nel 1972 ricevette il riconoscimento di IRCCS per diabetologia, fino al 2001, anno in cui l’estensione della qualifica raggiunse tutto l’ambito della medicina molecolare. Il Transformation Office (TO) viene fondato nel 2020 andando a costituire la Direzione Operativa dell’Ospedale. Obiettivo dell’Ufficio è utilizzare i dati ottenuti dai reparti e dagli ambulatori attraverso metodi innovativi ed efficienti di monitoraggio costante dell’operatività per elaborare progetti e piani strategici. Inoltre, il TO ha lo scopo di riconfigurare i processi ospedalieri obsoleti, cercando di migliorare la qualità dei servizi offerti dall’ospedale e ottimizzando la gestione amministrativa. Perseguendo gli obiettivi dell’Ufficio nasce il seguente lavoro di tesi. Tale lavoro propone la ricostruzione dell’attuale processo clinico-amministrativo-informatico del reparto di dialisi, l’analisi dei suoi punti critici e fornisce spunti per la totale riconfigurazione ed ottimizzazione del processo. Materiali e metodi Il lavoro è stato strutturato secondo la seguente logica: definire delle priorità di intervento attraverso l’analisi dei dati ospedalieri, andando quindi a identificare quali reparti o ambulatori avessero una gestione dei processi non ottimale ed in contrasto con i principi innovativi del TO. Per decidere le priorità sono stati presi in considerazione anche i servizi offerti dai reparti e la loro importanza a livello di fatturato ospedaliero. Il percorso è stato dunque dettato da un’analisi iniziale sui fatturati, addentrandosi, man mano nei dettagli e scoprendo anomalie nel sistema. Le fonti di dati sono stati i database centrali ospedalieri, gestiti dai Sistemi Informativi. I database centrali sono costituiti dalle informazioni raccolte dai numerosi software impiegati nella gestione di reparti, ambulatori, accettazioni e ogni altro settore ospedaliero. I software a cui si è fatto riferimento per le analisi di dati, sono stati: • QlikSense e QlikView, per la raccolta e la visualizzazione degli storici e dei dati in tempo reale; • SAP, per le accettazioni e per la fatturazione delle prestazioni; • TSS e TM, per la gestione informatica del reparto di dialisi. Sono stati utilizzati, in seguito, i metodi di Process Mining per la ricostruzione del processo attuale, ovvero una serie di interviste e di pianificazioni strategiche per scendere nel dettaglio totale della configurazione del processo. È stata seguita, dunque, la logica della teoria PDCA (Plan-Do-Check-Act), sostenuta dall’ingegnere W. Edward Deming, una strategia operativa modulare che può essere applicata globalmente all’Organizzazione. Infine, è stato utilizzato il software Signavio come strumento di Business Process Modeling, per la ricostruzione del processo e per la riconfigurazione dello stesso in versione ottimizzata. Risultati, conclusioni e sviluppi futuri Le analisi effettuate hanno permesso di elaborare grafici sull’andamento dei fatturati che hanno portato ad incentrare il lavoro sul reparto di dialisi. In seguito, sono stati costruiti grafici dettagliati del reparto dialisi stesso, in modo da estrapolare quanta più informazione possibile e tradurla in decisioni e operazioni strategiche. Da qui sono state condotte interviste volte alla costruzione del processo ed è stato riportato il grafo di quanto ottenuto, tramite lo strumento scelto di Business Process Modeling. Considerando le esigenze di ogni attore coinvolto nel processo è stato costruito un nuovo processo ottimizzato. Il progetto si trova nella fase di valutazione dei costi di sviluppo, che verranno forniti dalle aziende fornitrici dei software utilizzati nel processo; tale compito è attualmente gestito dai Sistemi Informativi in collaborazione con il Transformation Office. L’obiettivo del presente lavoro di tirocinio e di tesi è stato ampiamente raggiunto, avendo definito il progetto ed essendo stato attuato a livello aziendale. L’obiettivo futuro sarà quello di estendere il processo alla Control Room, ovvero il monitoraggio in tempo reale dell’operatività del reparto con la possibilità di attuare tecniche predittive di Machine Learning.
Identificazione e ottimizzazione delle attività nel processo di gestione del paziente dializzato
Lannutti, Giuseppe
2020/2021
Abstract
Context and objective The San Raffaele Hospital in Milan is a clinic of diagnostic and therapeutic excellence in medical, surgical and interventional medicine. Founded in 1971, already in 1972 it received the recognition of IRCCS for diabetology, until 2001, when the extension of the qualification reached the whole field of molecular medicine. The Transformation Office (TO) was founded in 2020 and constitutes the Operational Management of the Hospital. The objective of the Office is to use the data obtained from the departments and outpatient clinics through innovative and efficient methods of constant monitoring of operations to develop projects and strategic plans. In addition, the TO aims to reconfigure outdated hospital processes, seeking to improve the quality of services provided by the hospital and optimizing administrative management. Pursuing the objectives of the Office, the following thesis work was born. This work proposes the reconstruction of the current clinical-administrative-informatics process of the dialysis department, the analysis of its critical points and provides ideas for the total reconfiguration and optimization of the process. Materials and Methods The work was structured according to the following logic: to define priorities for intervention through the analysis of hospital data, thus identifying which departments or outpatient clinics had a non-optimal process management and in contrast with the innovative principles of TO. To decide on priorities, the services offered by departments and their importance in terms of hospital turnover were also taken into consideration. The path was therefore dictated by an initial analysis of the turnover, going into detail as we went along and discovering anomalies in the system. The sources of data were the central hospital databases, managed by IT. The central databases are made up of the information collected by the numerous software programs used in the management of wards, outpatient clinics, admissions and every other area of the hospital. The software referred to for data analysis, were: - QlikSense and QlikView, for the collection and visualization of historical and real-time data; - SAP, for acceptances and performance billing; - TSS and TM, for IT management of the dialysis department. Process Mining methods were then used to reconstruct the current process, i.e. a series of interviews and strategic planning to go into total detail about the process configuration. The logic of the PDCA (Plan-Do-Check-Act) theory, advocated by engineer W. Edward Deming, was then followed, a modular operational strategy that can be applied globally to the organization. Finally, the Signavio software was used as a Business Process Modeling tool, for the reconstruction of the process and for its reconfiguration in an optimized version. Results, conclusions and future developments The analyses performed allowed for the development of graphs on turnover trends, which led to a focus on the dialysis department. Next, detailed graphs of the dialysis department itself were constructed in order to extract as much information as possible and translate it into strategic decisions and operations. From there, interviews were conducted to build the process and a graph of what was obtained was reported, using the chosen Business Process Modeling tool. Considering the needs of each actor involved in the process, a new optimized process has been built. The project is in the phase of evaluating the development costs, which will be provided by the companies supplying the software used in the process; this task is currently managed by the Information Systems in collaboration with the Transformation Office. The objective of this internship and thesis work has been largely achieved, having defined the project and implemented it at the company level. The future goal will be to extend the process to the Control Room, i.e. the real-time monitoring of the department's operations with the possibility of implementing Machine Learning predictive techniques.| File | Dimensione | Formato | |
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2021_10_Lannutti.pdf
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Descrizione: Tesi magistrale Lannutti Giuseppe
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https://hdl.handle.net/10589/179762