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data-slate-fragment=\"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\">\n\u003Col>\n\u003Cli>\n\u003Cp>Jungmann S. Ripensare i percorsi diagnostici nell’assistenza sanitaria moderna. Presentato in occasione della Conferenza MESI 2026; 18 maggio 2026; Bled, Slovenia.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli>\n\u003Cp>American Medical Association, Centro per la salute digitale e l’intelligenza artificiale. Indagine 2026 tra i medici sull’intelligenza aumentata. Marzo 2026.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli>\n\u003Cp>Goh E, Gallo R, Hom J, et al. L’influenza dei modelli linguistici di grandi dimensioni sul ragionamento diagnostico: uno studio clinico randomizzato. JAMA Netw Open. 2024;7(10):e2440969. doi:10.1001\u002Fjamanetworkopen.2024.40969\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli>\n\u003Cp>Wolters Kluwer Health \u002F CITE Research. Indagine condotta su 518 operatori sanitari in merito agli strumenti di IA non autorizzati (“ombra”). Realizzata nel dicembre 2025; pubblicata nel gennaio 2026.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Fol>\n\u003C\u002Fdiv>\n",[2245,2246],{"_modelApiKey":45,"__typename":44,"id":491,"title":493,"slug":492},{"_modelApiKey":45,"__typename":44,"id":57,"title":59,"slug":58},{"schema":2248,"document":2249},"dast",{"type":2250,"children":2251},"root",[2252,2300,2307,2316,2325,2327,2334,2342,2344,2345,2352,2356,2360,2364,2370,2374,2381,2385,2391,2405,2406,2414,2418,2422,2427,2431,2440,2456,2461,2465,2472,2476,2480,2484,2488,2493,2505,2510,2514,2515,2520,2524],{"type":2253,"children":2254},"paragraph",[2255,2258,2262,2264,2267,2269,2273,2275,2277,2279,2288,2290,2298],{"type":2256,"value":2257},"span","Healthcare has never had more diagnostic tools at its disposal. Yet for many clinicians, the working day still starts in a surprisingly familiar way.\n\nOne measurement appears on one screen. Another arrives as a PDF waiting to be uploaded. An ECG sits in a different system behind another login. The information is all there, but it rarely exists in one place. Before a clinical decision can be made, someone has to bring the pieces together. ",{"type":2256,"marks":2259,"value":2261},[2260],"strong","Ogni singola volta.",{"type":2256,"value":2263},"\nThe devices themselves are rarely the problem. Most are faster, smarter and more accurate than ever before. The challenge lies in everything between them: disconnected workflows, fragmented data and the time required to turn measurements into meaningful clinical information.\n\nThat challenge is becoming even more important as healthcare embraces artificial intelligence. According to the AMA Physician Survey 2026 [2], ",{"type":2256,"marks":2265,"value":2266},[2260],"L'81% dei medici statunitensi utilizza ormai l'intelligenza artificiale nella pratica clinica",{"type":2256,"value":2268},", up from 38% in 2023. Yet despite this rapid adoption, many clinical workflows remain fragmented, making it difficult to fully realise the potential of AI.\n\nThis was one of the central themes in the keynote ",{"type":2256,"marks":2270,"value":2272},[2271],"emphasis","Ripensare i percorsi diagnostici nell’assistenza sanitaria moderna",{"type":2256,"value":2274},", a cura di ",{"type":2256,"marks":2276,"value":2147},[2260],{"type":2256,"value":2278}," presso ",{"url":2280,"meta":2281,"type":12,"children":2285},"https:\u002F\u002Fwww.mesiconference.com\u002F",[2282],{"id":2283,"value":2284},"target","_blank",[2286],{"type":2256,"value":2287},"MESI Conference 2026",{"type":2256,"value":2289},". Medico di formazione, che in seguito si è dedicato all’imprenditoria nel settore della sanità digitale, Jungmann è ora a capo di ",{"url":2291,"meta":2292,"type":12,"children":2294},"https:\u002F\u002Fwww.aiomics.io\u002F",[2293],{"id":2283,"value":2284},[2295],{"type":2256,"marks":2296,"value":2297},[2260],"aiomics",{"type":2256,"value":2299},", un’azienda specializzata nell’applicazione dell’intelligenza artificiale e dei sistemi basati sui dati per migliorare i processi decisionali in ambito sanitario.\nOperando al crocevia tra medicina, tecnologia e flussi di lavoro clinici, Jungmann offre una prospettiva unica sui motivi per cui il settore sanitario fatica ancora a tradurre misurazioni di alta qualità in decisioni cliniche coerenti.",{"type":2253,"children":2301},[2302,2304],{"type":2256,"value":2303},"Il suo messaggio era semplice: ",{"type":2256,"marks":2305,"value":2306},[2260],"Il futuro dell’assistenza sanitaria non sarà determinato dal numero di strumenti che aggiungeremo al sistema, bensì dalla capacità di collegarli in modo intelligente.",{"type":2308,"children":2309,"attribution":2315},"blockquote",[2310],{"type":2253,"children":2311},[2312],{"type":2256,"marks":2313,"value":2314},[2260],"«Come potrei riorganizzare il mio flusso di lavoro se non fosse ancora stato definito?» ","Sven Jungmann, MESI Conference 2026",{"type":2253,"children":2317},[2318,2320,2323],{"type":2256,"value":2319},"Come ha ricordato Jungmann al pubblico all’inizio del suo discorso di apertura, ",{"type":2256,"marks":2321,"value":2322},[2271],"un sciocco con uno strumento rimane pur sempre uno sciocco",{"type":2256,"value":2324},". Il concetto era semplice: la tecnologia da sola non basta a risolvere i problemi dei sistemi malfunzionanti. Senza i flussi di lavoro adeguati, i dati interconnessi e la logica clinica alla base, anche gli strumenti diagnostici più avanzati possono aumentare la complessità anziché ridurla. ",{"type":2326},"thematicBreak",{"type":2328,"level":2329,"children":2330},"heading",4,[2331],{"type":2256,"marks":2332,"value":2333},[2260],"Ascoltate cosa ha da dire Sven Jungmann",{"type":2253,"children":2335},[2336,2338,2340],{"type":2256,"value":2337},"Il discorso di apertura ha approfondito solo una parte del dibattito.\nIn questa intervista esclusiva registrata presso ",{"type":2256,"marks":2339,"value":2287},[2260],{"type":2256,"value":2341},", Sven Jungmann approfondisce le sfide legate alla frammentazione della diagnostica, alla qualità dei dati, all’intelligenza artificiale e al futuro dell’assistenza sanitaria connessa.",{"item":2204,"type":2343},"block",{"type":2326},{"type":2328,"level":458,"children":2346},[2347,2350],{"type":2256,"marks":2348,"value":2349},[2260],"Dispositivi migliori, gli stessi vecchi flussi di lavoro",{"type":2256,"value":2351}," ",{"type":2253,"children":2353},[2354],{"type":2256,"value":2355},"Per anni, l’innovazione nel settore sanitario si è concentrata sul miglioramento dei singoli dispositivi diagnostici. Sistemi ECG più efficaci, spirometria più rapida, dispositivi indossabili più intelligenti e tecnologie di imaging sempre più avanzate hanno tutti contribuito a creare un ambiente clinico più preciso e ricco di dati. Tuttavia, mentre gli strumenti stessi si sono evoluti, i percorsi che li circondano spesso non hanno seguito lo stesso percorso. ",{"type":2253,"children":2357},[2358],{"type":2256,"value":2359},"È spesso proprio qui che inizia la vera complessità, non nella misurazione in sé, ma in tutto ciò che la circonda. ",{"type":2253,"children":2361},[2362],{"type":2256,"value":2363},"In many healthcare settings, diagnostics still happen in fragments. One device produces one result, another device stores data elsewhere, and clinicians are left switching between interfaces, manually transferring information and piecing together a patient’s story across disconnected systems. Each step may feel manageable on its own, but together they create a workflow that is far more complex than it needs to be. \nThis is what fragmented diagnostics often look like in practice: clinical workflows where measurements, patient data and diagnostic reports are generated across disconnected devices and systems, without a seamless path between them. \nAt the core of this challenge is interoperability, or the lack of it. Without interoperability, data loses context. And without context, decision-making slows down. ",{"type":2328,"level":458,"children":2365},[2366,2369],{"type":2256,"marks":2367,"value":2368},[2260],"Il costo della frammentazione è spesso invisibile",{"type":2256,"value":2351},{"type":2253,"children":2371},[2372],{"type":2256,"value":2373},"Il costo di questa frammentazione è raramente evidente, poiché si distribuisce sull’intera giornata clinica. Si tratta dei minuti in più impiegati per accedere a un altro sistema, del referto stampato in attesa di essere scansionato, della trascrizione manuale nella cartella clinica elettronica o della telefonata di follow-up per verificare se un risultato sia stato effettivamente caricato. Nessuno di questi momenti sembra significativo se considerato isolatamente, ma nel corso del tempo si sommano fino a rappresentare ore di capacità clinica persa. \nIl lavoro più ampio di Jungmann nel campo della sanità digitale torna spesso a un’idea importante: l’innovazione non consiste sempre nell’apprendimento di qualcosa di nuovo. A volte consiste nel disimparare sistemi e abitudini che non sono più al servizio della medicina moderna.  ",{"type":2253,"children":2375},[2376,2378],{"type":2256,"value":2377},"Come egli stesso ha affermato,",{"type":2256,"marks":2379,"value":2380},[2260]," A volte innovare significa eliminare gli ostacoli, non aggiungere funzionalità. ",{"type":2253,"children":2382},[2383],{"type":2256,"value":2384},"Ciò è particolarmente rilevante nel campo della diagnostica, dove molti flussi di lavoro riflettono ancora modelli obsoleti, concepiti per un’epoca caratterizzata da ritmi più lenti e da una minore connettività. ",{"type":2328,"level":458,"children":2386},[2387,2390],{"type":2256,"marks":2388,"value":2389},[2260],"Il problema non sono i dati, bensì la loro qualità.",{"type":2256,"value":2351},{"type":2253,"children":2392},[2393,2395,2398,2400,2403],{"type":2256,"value":2394},"La sfida odierna non consiste più nel raccogliere una maggiore quantità di dati. Il settore sanitario ne produce già quantità enormi. La vera sfida consiste nel rendere tali dati utilizzabili, accessibili e significativi proprio nel momento in cui sono necessari.\nCome ha sottolineato Jungmann, l’intelligenza artificiale è potente, ma solo se le fondamenta su cui poggia sono sufficientemente solide. È qui che diventa impossibile ignorare uno dei principi più importanti della medicina digitale: ",{"type":2256,"marks":2396,"value":2397},[2260],"se si inseriscono dati errati, si ottengono risultati errati",{"type":2256,"value":2399},".\n\nJungmann referenced recent findings published in ",{"type":2256,"marks":2401,"value":2402},[2271],"JAMA Network Open",{"type":2256,"value":2404},", dove i medici che operavano autonomamente hanno ottenuto punteggi relativi al ragionamento diagnostico pari al 73,7%, i medici supportati da GPT-4 hanno totalizzato il 76,3%, mentre GPT-4 da solo ha raggiunto il 92,0%.",{"item":2224,"type":2343},{"type":2308,"children":2407,"attribution":2413},[2408],{"type":2253,"children":2409},[2410],{"type":2256,"marks":2411,"value":2412},[2260],"Se gli oggetti sono sparsi ovunque, sta saltando un passaggio.","Sven Jungmann, MESI Conference 2026 ",{"type":2253,"children":2415},[2416],{"type":2256,"value":2417},"I dati sono impressionanti, ma sollevano anche un’importante questione: se l’intelligenza artificiale è in grado di superare le prestazioni dei medici in scenari isolati, cosa accade quando i dati che alimentano tale sistema sono incompleti, frammentati o incoerenti?",{"type":2253,"children":2419},[2420],{"type":2256,"value":2421},"Per quanto avanzati possano diventare un modello di intelligenza artificiale, una piattaforma di analisi o un sistema di supporto alle decisioni cliniche, la qualità dei risultati dipenderà sempre dalla qualità dei dati in ingresso. Se i dati diagnostici sono incompleti, incoerenti, inseriti manualmente o dispersi in più sistemi non interconnessi, le informazioni ricavate da essi presenteranno inevitabilmente le stesse carenze.\nNon si tratta solo di una questione tecnica. Sta diventando una delle sfide cliniche più importanti dell’assistenza sanitaria moderna.",{"type":2328,"level":458,"children":2423},[2424],{"type":2256,"marks":2425,"value":2426},[2260],"La qualità dei dati sta diventando parte integrante dell’infrastruttura clinica",{"type":2253,"children":2428},[2429],{"type":2256,"value":2430},"Man mano che il settore sanitario si orienta sempre più verso l’analisi predittiva, l’automazione e i processi decisionali supportati dall’intelligenza artificiale, i dati diagnostici strutturati e standardizzati assumono un’importanza fondamentale. In loro assenza, il settore sanitario rischia di costruire sistemi sempre più sofisticati su basi instabili. La qualità dei dati non può più essere considerata una questione amministrativa o informatica di secondo piano. Sta diventando parte integrante dell’infrastruttura clinica stessa.",{"type":2253,"children":2432},[2433,2435,2438],{"type":2256,"value":2434},"Allo stesso tempo, la rapida diffusione dell’intelligenza artificiale sta creando nuove sfide in materia di governance. Jungmann ha sottolineato che ",{"type":2256,"marks":2436,"value":2437},[2260],"Il 40% degli operatori sanitari si è già imbattuto in strumenti di intelligenza artificiale non autorizzati",{"type":2256,"value":2439}," all’interno delle loro organizzazioni, dimostrando quanto rapidamente la tecnologia possa superare i sistemi clinici strutturati.",{"type":2253,"children":2441},[2442,2444,2451,2453],{"type":2256,"value":2443},"Dati affidabili e strutturati trasformano il modo in cui vengono fornite le cure. Consentono ai medici di ",{"item":491,"meta":2445,"type":2447,"children":2448},[2446],{"id":2283,"value":2284},"itemLink",[2449],{"type":2256,"value":2450},"prendere decisioni più rapidamente",{"type":2256,"value":2452},", migliora la continuità dell’assistenza e facilita il confronto dei risultati nel tempo. Inoltre, rafforza la collaborazione tra i team, poiché tutti operano sulla base dello stesso quadro clinico aggiornato. ",{"type":2256,"marks":2454,"value":2455},[2260],"Soprattutto nell’ambito della medicina preventiva, ciò può fare una differenza significativa, consentendo di individuare i rischi in una fase più precoce e di intervenire tempestivamente.",{"type":2328,"level":458,"children":2457},[2458],{"type":2256,"marks":2459,"value":2460},[2260],"Non tutti i costi si misurano in termini di tempo",{"type":2253,"children":2462},[2463],{"type":2256,"value":2464},"Ma non tutto ciò si misura in minuti. Una parte si misura in termini di attenzione. Ogni accesso in più, ogni trasferimento manuale e ogni segnalazione di disconnessione comportano un sovraccarico cognitivo.",{"type":2308,"children":2466,"attribution":2413},[2467],{"type":2253,"children":2468},[2469],{"type":2256,"marks":2470,"value":2471},[2260],"Si tende sempre a pensare che il tempo sia la nostra risorsa più scarsa, ma in realtà è la nostra attenzione.",{"type":2253,"children":2473},[2474],{"type":2256,"value":2475},"Ogni flusso di lavoro non integrato richiede uno sforzo aggiuntivo da parte degli operatori sanitari. Essi devono ricordare dove sono archiviati i dati, se sono stati caricati correttamente, quale sia la versione più recente e se le informazioni che hanno davanti siano attendibili. Questi piccoli momenti di incertezza creano attrito e, nel tempo, tale attrito si trasforma in stress mentale.",{"type":2253,"children":2477},[2478],{"type":2256,"value":2479},"Nei sistemi sanitari già sottoposti a forte pressione, questo aspetto è più importante che mai.",{"type":2253,"children":2481},[2482],{"type":2256,"value":2483},"Il burnout non è determinato solo dal carico di lavoro. È determinato anche dalla complessità, dall’inefficienza e dallo sforzo mentale costante richiesto per districarsi tra sistemi che dovrebbero invece facilitare il lavoro.",{"type":2253,"children":2485},[2486],{"type":2256,"value":2487},"La tecnologia dovrebbe alleggerire tale onere, non aumentarlo.",{"type":2328,"level":458,"children":2489},[2490],{"type":2256,"marks":2491,"value":2492},[2260],"Il futuro della diagnostica è interconnesso",{"type":2253,"children":2494},[2495,2497,2503],{"type":2256,"value":2496},"Ecco perché il dibattito sulla diagnostica deve evolversi. L’obiettivo non dovrebbe essere semplicemente quello di introdurre un maggior numero di strumenti nella pratica clinica, ma di creare ",{"item":57,"meta":2498,"type":2447,"children":2500},[2499],{"id":2283,"value":2284},[2501],{"type":2256,"value":2502},"ecosistemi diagnostici interconnessi",{"type":2256,"value":2504}," in cui ogni misurazione contribuisce a delineare un quadro clinico unificato del paziente. La diagnostica non dovrebbe costituire un evento isolato, ma parte integrante di un’infrastruttura clinica più ampia, progettata per favorire decisioni più rapide, analisi più chiare e una collaborazione più efficace.\nQuesto è, in definitiva, il cambiamento che Jungmann ha invitato il pubblico a prendere in considerazione. La questione non è più se il settore sanitario sia in grado di raccogliere una maggiore quantità di dati. È evidente che ne sia in grado.",{"type":2253,"children":2506},[2507],{"type":2256,"marks":2508,"value":2509},[2260],"La questione più importante è se il settore sanitario sia in grado di ricavare un'unica fonte di verità dai dati di cui già dispone e se i sistemi ad esso collegati siano progettati per trasformare tali dati in azioni concrete.",{"type":2253,"children":2511},[2512],{"type":2256,"value":2513},"Infatti, i costi nascosti di una diagnostica frammentata raramente risiedono nei dispositivi stessi. Più spesso, essi si manifestano nel tempo perso tra un esame e l’altro, nei ritardi decisionali, nel sovraccarico amministrativo e nelle opportunità mancate di intervenire tempestivamente.\nE nell’assistenza sanitaria moderna, sono spesso proprio questi i costi che contano di più.",{"type":2326},{"type":2328,"level":2329,"children":2516},[2517],{"type":2256,"marks":2518,"value":2519},[2260],"Informazioni su Sven Jungmann:",{"type":2253,"children":2521},[2522],{"type":2256,"value":2523},"Il lavoro di Sven Jungmann si colloca al crocevia tra medicina, intelligenza artificiale e sistemi sanitari digitali. Attraverso il suo lavoro presso aiomics e nel più ampio panorama dell’innovazione sanitaria, continua a mettere in discussione il modo in cui il settore sanitario concepisce i dati, i flussi di lavoro e i processi decisionali. 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