iPhone Medical Dictation App
Budget / Salary$250–750
TypeFreelance project
LocationRemote
Posted2 hours ago
I dictate operative notes on the go and need an iPhone app that can turn those spoken details into a completed Word (.docm) template and a matching PDF, all while meeting medical-grade confidentiality standards.
Core workflow
• I open the app, authenticate with Face ID, and tap “Record.”
• While I dictate the patient’s name, date of service, MRN, laterality, devices used, and any other details, the app transcribes in real time.
• Using the existing .docm form I supply, it must recognise each field and insert the correct value. If I skip a field, the template’s original text should remain untouched.
• Once I stop recording, the app presents a summary screen showing every field it filled and the values it placed so I can edit or approve before saving.
• On approval, it stores both the updated .docm and an automatically generated PDF inside the app’s secure file area.
Essential requirements
• Accurate speech-to-text.
• Field-matching logic that is flexible when items are dictated out of order.
• Local, encrypted storage; nothing should ever leave the device.
• Face ID gate on every launch and when returning from background.
• Simple interface so I can finish a note in under a minute.
Acceptance criteria
1. Dictation populates all mapped fields in the supplied template with ≥95 % accuracy.
2. Skipped fields remain as original placeholder text.
3. Review screen lists each populated field and its value for confirmation or manual edit.
4. One-tap export saves both the Word (.docm) file and the generated PDF to a protected in-app folder.
5. All data stay on-device and are accessible only after Face ID unlock.
Let me know which speech recognition framework and document automation library you plan to use so we can be sure they run smoothly on current iOS versions.
Core workflow
• I open the app, authenticate with Face ID, and tap “Record.”
• While I dictate the patient’s name, date of service, MRN, laterality, devices used, and any other details, the app transcribes in real time.
• Using the existing .docm form I supply, it must recognise each field and insert the correct value. If I skip a field, the template’s original text should remain untouched.
• Once I stop recording, the app presents a summary screen showing every field it filled and the values it placed so I can edit or approve before saving.
• On approval, it stores both the updated .docm and an automatically generated PDF inside the app’s secure file area.
Essential requirements
• Accurate speech-to-text.
• Field-matching logic that is flexible when items are dictated out of order.
• Local, encrypted storage; nothing should ever leave the device.
• Face ID gate on every launch and when returning from background.
• Simple interface so I can finish a note in under a minute.
Acceptance criteria
1. Dictation populates all mapped fields in the supplied template with ≥95 % accuracy.
2. Skipped fields remain as original placeholder text.
3. Review screen lists each populated field and its value for confirmation or manual edit.
4. One-tap export saves both the Word (.docm) file and the generated PDF to a protected in-app folder.
5. All data stay on-device and are accessible only after Face ID unlock.
Let me know which speech recognition framework and document automation library you plan to use so we can be sure they run smoothly on current iOS versions.
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