Maniesh Srivastva

I’m happy to share that I’m starting a new position as a freelance linguist at Cactus Communications! #Freelance #Linguist #Transcription

A doctor recently showed me an AI-generated clinical note and asked a simple question: "Does this document look correct to you?" At first glance, the note looked fine. The consultation was captured. The structure was clean. The sentences were readable. But one small line caught my attention. The note documented, "Patient denies chest pain history.” What the doctor had actually dictated was, "Patient denies current chest pain.” Those two phrases are clinically very different. One suggests no historical occurrence. The other refers only to the present symptoms. This is the subtle challenge many clinics are now facing with AI-generated medical notes, as they must ensure that the notes accurately reflect both historical patient data and current symptoms to provide comprehensive care. AI is excellent at producing fast documentation drafts. But clinical documentation is not only about words. It requires understanding: • medical terminology • clinical context • diagnostic nuance After working with healthcare documentation for 23+ years supporting doctors across the US, UK, and Canada, I’ve seen how small documentation differences can create confusion later in: • patient records • coding interpretation • clinical clarity The workflow many clinics are beginning to adopt now is simple: Doctor Dictation ➡️ AI Draft ➡️ Clinical Documentation QA AI provides speed. Human expertise protects accuracy. I’ve been quietly helping a few doctors review and clean up their AI-generated notes before EMR upload. It often takes just a few minutes per note to ensure clinical precision. Curious to hear from doctors here: Are AI scribes saving time in your clinic—or creating extra corrections afterward? #AIinHealthcare #MedicalDocumentation #ClinicalAccuracy #HealthTech #HealthcareWorkflow #ManieshSrivastva #JheelTranscription #Jheel

A doctor once chose a poor child over a king. Why? “For the king, I am one of many. For this child, I am the only one.” That’s not just compassion; that’s responsibility. Now look at healthcare today. We reward: 1. Speed 2. Volume 3. Quick consults But ignore: 1. Patient trust 2. Real outcomes 👉 The problem: Systems are designed for efficiency, not impact. So doctors are pushed toward faster, higher-paying decisions, not necessarily the right ones. 👉 The solution: Repair the system, not the people. Build healthcare where: 1. Doing the right thing is easy 2. Time with complex patients is valued 3. Trust is rewarded, not sacrificed Because when trust erodes, everything else follows. The real question: Are we optimizing for growth… or for trust? #Healthcare #MedicalEthics #DoctorsOnLinkedIn #DigitalHealth #HealthcareLeadership #PatientCare #Trust #AIinHealthcare #HealthcareSystems #ManieshSrivastva