2024 mein 70 se zyada health AI companies ko FDA clearance mili. Duniya bhar mein clinical AI mein investment $15 billion paar kar gaya. Har bade health system ne apni AI strategy announce ki.
Aur US hospitals mein bina warning ke bigadne wale patients ki sankhya mein koi khaas fark nahi aaya. Chronic kidney disease pakadne mein aaj bhi saalon lagte hain. Outpatient settings mein diagnostic errors aaj bhi har saal andazan 12 million American adults ko affect karte hain. Aapka naya doctor aaj bhi aapse kehta hai ki apni medication list khud yaad rakhiye.
Approach mein hi kuch gadbad hai.
Zyadatar healthcare AI asal mein karta kya hai
Zyadatar clinical AI products notes summarize karte hain, images classify karte hain, ya koi number threshold paar kare toh alert bhejte hain. Sab useful. Sab wrappers. Wo clinical data ko usi form mein lete hain jismein wo pehle se hai, ek model se guzaarte hain, aur result dikha dete hain. Underlying data nahi badla. System patient ko jis tarah represent karta hai, wo nahi badla.
AI ki madad se chest X-ray padh rahi radiologist aaj bhi ek pal ki ek image padh rahi hai. Ho sakta hai AI ek aisa nodule pakad le jo usse chhoot jaata. Ye sach mein valuable hai. Lekin AI use ye nahi bata sakta ki is patient ka pulmonary function teen saal mein paanch tests mein lagataar gir raha hai, ki aath mahine pehle ek medication change ke baad ye girawat tez ho gayi, aur ki ye trajectory athaarah mahine mein COPD ki taraf ja rahi hai. Ye jaankari maujood hai. Bas alag-alag providers aur saalon mein bikhri hui hai. Koi wrapper wahan tak nahi pahunch sakta, kyunki wrapper sirf current encounter dekhta hai.
Lagbhag har clinical AI mein analysis ki unit ek visit hai. Ek note. Ek image. Insaani bimari mein ye unit saal hai. Jab tak ye dono match nahi karte, healthcare mein AI galat sawaalon ke tez jawaab deta rahega.
Insaani bimari mein analysis ki unit saal hai.
Speed ka jaal
Har koi speed ko hi fayda batata hai. Discharge note ka summary seconds mein. Physician ki baat khatam hote hote referral draft. Free text se diagnoses turant nikaal lo.
Physician burnout asli hai. Documentation ka bojh kuchal dene wala hai. Jo bhi cheez time wapas clinical care ko de, uski value hai. Lekin maujooda infrastructure pe speed sirf ek efficiency problem solve karti hai. Jis physician ko aaj ki visit ka perfect AI summary mil jaata hai, use phir bhi nahi pata ki uske patient ka creatinine pichhle do saal se teen providers ke beech badh raha hai. Summary tez hai. Clinical picture bilkul wahi hai.
Healthcare systems aisa AI apnaate hain jo workflows tez kare, productivity gains report karte hain, aur AI strategy ko success keh dete hain. Is beech, bimari shuru hone aur pakde jaane ke beech ka gap zara bhi nahi hila. System usi disha mein aur tezi se ja raha hai. Kisi ne poocha hi nahi ki disha sahi hai ya nahi.
Industry wrappers kyun banati hai
Wrappers banana samajh mein aata hai. Ek pre-trained model lo, clinical text pe fine-tune karo, aur mahino mein product ship kar do. Validation simple hai: note andar, summary bahar. Sales jaana-pehchaana hai: "Hum aapke EHR mein plug hokar use smarter bana dete hain." Data architecture pe koi mushkil baatcheet nahi. Workflow mein koi disruption nahi.
Time ke saath health ko padhne wala system banana bilkul alag kaam hai. Patient ko saalon aur providers ke paar represent karna padta hai, aisi clinical reasoning banani padti hai jo position ki jagah direction pe chale, saikdon sites pe validate karna padta hai, aur hospitals ko yakeen dilana padta hai ki bimari do saal pehle pakadna ek summarization plugin se gehre integration ke laayak hai.
Ismein zyada time lagta hai, zyada kharcha hota hai, aur aisi baatcheet karni padti hai jiske liye zyadatar teams taiyar nahi hain. Lekin asli clinical gap ko address karne wala yahi ek approach hai.
Black box ise aur bigaad deta hai
Zyadatar clinical AI wrapper hone ke upar se black box ki tarah bhi chalta hai. Model data leta hai aur output de deta hai. Physician reasoning nahi dekh sakti. Wo ye sawaal nahi kar sakti ki kin inputs ne conclusion tay kiya. Wo beech ke steps pe apna judgment nahi laga sakti, kyunki beech ke koi steps dikhte hi nahi.
Practice mein clinicians in outputs ke saath wahi karte hain jo saikdon doosre EHR alerts ke saath karte hain: shak ke saath dekhte hain aur aadatan dismiss kar dete hain. Opaque systems ka engagement lagataar 10 se 15 percent hi rehta hai. System alert deta hai. Clinician ignore kar deta hai. AI chal raha hai, lekin clinically uska koi asar nahi.
Jin systems ne 80 percent se zyada clinician engagement paaya hai, unmein ek baat common hai: reasoning dikhti hai. Clinician dekh sakta hai ki assessment kis wajah se aaya aur uske khaas hisson se disagree kar sakta hai. Iske bina adoption hota hi nahi. Building shuru karne se pehle maine saalon tak ise na hote dekha.
Alag asal mein kaisa dikhta hai
Ek patient jiska creatinine 18 mahine se do providers ke beech har quarter 0.1 badh raha hai. Kisi ek value ne alarm nahi bajaya. Har visit pe number "within range" tha. Trajectories padhne wala system ise pakad leta hai. Physician ko ek alert milta hai jo trend, aage ka projected raasta, aur flag ke peeche ki clinical reasoning dikhata hai. Wo review karti hai, agree karti hai, aur patient ke threshold paar karne se ek saal pehle nephrology ko refer kar deti hai.
Chroneme ko hum isi tarah ka badlaav pakadne ke liye bana rahe hain. Hum ise ek pre-registered protocol ke tahat validate kar rahe hain, aur jo bhi milega wo publish karenge, ye bhi ki kahan ye kam padta hai.
Jo intelligence ICU mein dheere dheere hone wala drift pakadti hai, wahi primary care office mein bhi dheere ka drift pakad sakti hai. Jo system hafton mein upar jaati heart rate ko flag karta hai, wahi saalon mein upar jaate A1c ko bhi flag kar sakta hai. Architecture nahi badalta. Time scale badalta hai.
Pandrah billion dollar. Sattar clearances. Aur patient ka experience nahi badla.
Wo tab badlega jab infrastructure badlega. Jab clinical AI snapshots ki jagah trajectories padhega. Jab systems apni reasoning chhupane ki jagah dikhayenge. Jab health aisi cheez banegi jise insaan time ke saath badalte hue dekh sake, na ki aisi cheez jo baad mein pakdi jaaye.
Chroneme mein hum yahi bana rahe hain.
