San Raffaele Hospital, including Centro San Luigi and the Infectious Disease Unit, is strongly dedicated to improving its Electronic Medical Record (EMR) system for enhanced patient monitoring and to aid healthcare providers in their work. This interest encompasses the detailed documentation of vaccinations, including those for HPV, Hepatitis A and B, Meningococcus, Pneumococcus, and Shingrix, as well as better documenting the use of Doxycycline Post-Exposure Prophylaxis (DoxyPEP) for preventing sexually transmitted infections (STIs). The goal is to improve patient outcomes through efficient data management and support for clinical decision-making. The thesis revolves around three primary goals: improving vaccination records, streamlining medication management, and creating user personas using statistical analysis. Developing a "Patient Vaccination Status" table was done to improve vaccination records, collecting detailed immunization backgrounds to assist clinical decisions and prompt interventions. This table provides clear documentation of vaccinations, including vaccination dates and sources. Potential enhancements involve merging national vaccination records with sophisticated data analysis to detect vaccination trends, supporting public health decisions. Developing a user-friendly interface for recording medications like DoxyPEP has made the medication recording process simpler, leading to fewer errors and better patient outcomes. This interface guarantees precise and punctual medication data updates. Future work will involve broadening the variety of medications included and improving the user interface by adding functions such as predictive text input and linking with clinical decision support systems. Building on the known effectiveness of DoxyPEP, proven by many researches (Luetkemeyer et al. (2023)) included also the ones from San Raffaele Hospital on antimicrobial resistance (Raccagni et al. (2023)), the next phase of this thesis focuses on a detailed statistical analysis. This analysis uses data from a dataset specifically created for this study. The interest of this thesis lies in identifying individual traits that result in a higher likelihood of taking the treatment after it is prescribed. This involves analyzing factors such as whether the medication was taken, demographic information, past infections, vaccination history, and the utilization of other preventative measures such as Pre-exposure Prophylaxis (PrEP) for HIV. The objective is to create individual profiles or “personas” based on these characteristics to assist healthcare providers in recognizing which individuals may be more prone to DoxyPEP adherence and, conversely, which ones may be less likely to take the medication. This method will enhance prevention tactics for STIs and improve healthcare services for individuals with increased STI vulnerability. This analytical journey aims to confirm and possibly expand upon the discoveries from the New England Journal of Medicine within the patient cohort at San Raffaele Hospital, focusing on patient willingness to take the medication rather than solely on the medication itself. In summary, the upgrades to the EMR system not just enhance its effectiveness and precision but also bolster improved clinical decision-making and patient care. The methods and knowledge acquired from this project can be utilized in different healthcare environments, leading to progress in health informatics and patient care.
L’Ospedale San Raffaele, compresi il Centro San Luigi e l’Unità di Malattie Infettive, è fortemente impegnato nel migliorare il sistema di Cartella Clinica Elettronica (EMR) per un monitoraggio avanzato dei pazienti e per aiutare gli operatori sanitari nel loro lavoro. Questo interesse include la documentazione dettagliata delle vaccinazioni, tra cui quelle per HPV, Epatite A e B, Meningococco, Pneumococco e Shingrix, nonché una migliore documentazione dell’uso della Doxiciclina come Profilassi Post-Esposizione (DoxyPEP) per prevenire le infezioni sessualmente trasmissibili (STI). L’obiettivo è migliorare i risultati clinici attraverso una gestione efficiente dei dati e il supporto alle decisioni cliniche. La tesi ruota attorno a tre obiettivi principali: migliorare la registrazione delle vac- cinazioni, semplificare la gestione dei farmaci e creare profili o "personas" utilizzando l’analisi statistica. Prima fase è stata la creazione di una tabella “Stato di Vaccinazione del Paziente” per migliorare la registrazione delle vaccinazioni, raccogliendo dettagliate informazioni sull’immunizzazione per assistere nelle decisioni cliniche e negli interventi tempestivi. Questa tabella fornisce una documentazione chiara delle vaccinazioni, comprese le date e le fonti delle vaccinazioni. I potenziali miglioramenti includono l’integrazione dei registri vaccinali nazionali con un’analisi dati avanzata per rilevare tendenze vaccinali, supportando le decisioni di salute pubblica. Lo sviluppo di un’interfaccia user-friendly per la registrazione dei farmaci come DoxyPEP ha reso il processo di registrazione dei farmaci più semplice, portando a meno errori e migliori risultati clinici. Questa interfaccia garantisce aggiornamenti precisi e puntuali dei dati su DoxyPEP. I lavori futuri includeranno l’ampliamento della gamma di farmaci inclusi e il miglioramento dell’interfaccia utente con funzioni come l’input di testo predittivo e il collegamento con i sistemi di supporto alle decisioni cliniche. Basandosi sull’efficacia nota della DoxyPEP e sulla ricerca dell’Ospedale San Raffaele sulla resistenza antimicrobica, la fase successiva di questa tesi si concentra su un’analisi statistica dettagliata. Questa analisi utilizza i dati di un dataset creato specificamente per questo studio. L’interesse di questa tesi risiede nell’identificare le caratteristiche individuali che determinano una maggiore probabilità di assumere il trattamento dopo che è stato prescritto. Ciò comporta l’analisi di fattori come se il farmaco sia stato assunto, informazioni demografiche, infezioni passate, storia delle vaccinazioni e l’utilizzo di altre misure preventive come la Profilassi Pre-Esposizione (PrEP) per l’HIV. L’obiettivo è creare profili individuali o “personas” basati su queste caratteristiche per assistere gli operatori sanitari nel riconoscere quali individui potrebbero essere più propensi ad aderire alla DoxyPEP e, al contrario, quali potrebbero essere meno inclini a prendere il farmaco. Questo metodo migliorerà le tattiche di prevenzione per le STI e i servizi sanitari per gli individui con maggiore vulnerabilità alle STI. Questo percorso analitico mira a confermare e possibilmente espandere le scoperte del New England Journal of Medicine all’interno della coorte di pazienti dell’Ospedale San Raffaele, concentrandosi sulla volontà dei pazienti di prendere il farmaco piuttosto che studiare solo la sua efficacia. In sintesi, gli aggiornamenti al sistema EMR non solo ne migliorano l’efficacia e la preci- sione, ma supportano anche un miglior processo decisionale clinico e la cura del paziente. I metodi e le conoscenze acquisite da questo progetto possono essere utilizzati in diversi ambienti sanitari, portando a progressi nell’informatica sanitaria e nella cura del paziente.
Enhancing electronic medical record for infectious disease management and clustering analysis at San Raffaele Hospital
Masserini, Michele
2023/2024
Abstract
San Raffaele Hospital, including Centro San Luigi and the Infectious Disease Unit, is strongly dedicated to improving its Electronic Medical Record (EMR) system for enhanced patient monitoring and to aid healthcare providers in their work. This interest encompasses the detailed documentation of vaccinations, including those for HPV, Hepatitis A and B, Meningococcus, Pneumococcus, and Shingrix, as well as better documenting the use of Doxycycline Post-Exposure Prophylaxis (DoxyPEP) for preventing sexually transmitted infections (STIs). The goal is to improve patient outcomes through efficient data management and support for clinical decision-making. The thesis revolves around three primary goals: improving vaccination records, streamlining medication management, and creating user personas using statistical analysis. Developing a "Patient Vaccination Status" table was done to improve vaccination records, collecting detailed immunization backgrounds to assist clinical decisions and prompt interventions. This table provides clear documentation of vaccinations, including vaccination dates and sources. Potential enhancements involve merging national vaccination records with sophisticated data analysis to detect vaccination trends, supporting public health decisions. Developing a user-friendly interface for recording medications like DoxyPEP has made the medication recording process simpler, leading to fewer errors and better patient outcomes. This interface guarantees precise and punctual medication data updates. Future work will involve broadening the variety of medications included and improving the user interface by adding functions such as predictive text input and linking with clinical decision support systems. Building on the known effectiveness of DoxyPEP, proven by many researches (Luetkemeyer et al. (2023)) included also the ones from San Raffaele Hospital on antimicrobial resistance (Raccagni et al. (2023)), the next phase of this thesis focuses on a detailed statistical analysis. This analysis uses data from a dataset specifically created for this study. The interest of this thesis lies in identifying individual traits that result in a higher likelihood of taking the treatment after it is prescribed. This involves analyzing factors such as whether the medication was taken, demographic information, past infections, vaccination history, and the utilization of other preventative measures such as Pre-exposure Prophylaxis (PrEP) for HIV. The objective is to create individual profiles or “personas” based on these characteristics to assist healthcare providers in recognizing which individuals may be more prone to DoxyPEP adherence and, conversely, which ones may be less likely to take the medication. This method will enhance prevention tactics for STIs and improve healthcare services for individuals with increased STI vulnerability. This analytical journey aims to confirm and possibly expand upon the discoveries from the New England Journal of Medicine within the patient cohort at San Raffaele Hospital, focusing on patient willingness to take the medication rather than solely on the medication itself. In summary, the upgrades to the EMR system not just enhance its effectiveness and precision but also bolster improved clinical decision-making and patient care. The methods and knowledge acquired from this project can be utilized in different healthcare environments, leading to progress in health informatics and patient care.File | Dimensione | Formato | |
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MasseriniMicheleAndrea_ExecSummaryOSR.pdf
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Descrizione: Executive summary of the Master’s thesis in Biomedical Engineering - Information Bioengineering, written by Michele Andrea Masserini. The thesis was developed in collaboration with I.R.C.C.S. Ospedale San Raffaele - Gruppo San Donato and focuses on optimizing the Electronic Medical Record (EMR) system for infectious disease management and clustering analysis, from which three personas were derived.
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3.3 MB
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MasseriniMicheleAndrea_TesiOSR.pdf
accessibile in internet solo dagli utenti autorizzati
Descrizione: Master’s thesis in Biomedical Engineering - Information Bioengineering, written by Michele Andrea Masserini. The thesis was developed in collaboration with I.R.C.C.S. Ospedale San Raffaele - Gruppo San Donato and focuses on optimizing the Electronic Medical Record (EMR) system for infectious disease management and clustering analysis, from which three personas were derived.
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19.91 MB
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Adobe PDF
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19.91 MB | Adobe PDF | Visualizza/Apri |
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https://hdl.handle.net/10589/226420