Scribeberry used Anvil's PDF Fill API to automatically generate structured PDFs from AI-scribed medical data, speeding up clinical workflows and reducing administrative overhead.
The Company
Scribeberry provides an AI-based medical scribe service to streamline clinical documentation for healthcare providers. The platform uses artificial intelligence to listen to patient-provider conversations and automatically generate clinical notes, encounter documentation, and other medical records. By automating the documentation that traditionally requires physicians to spend hours typing or dictating notes after patient visits, Scribeberry allows providers to focus on patient care rather than paperwork.
The Problem
Clinical documentation is one of the most time-consuming aspects of medical practice. After each patient encounter, physicians must document the visit in the electronic health record (EHR)—recording the chief complaint, history of present illness, physical examination findings, assessment, and treatment plan. This documentation serves multiple critical purposes: continuity of care, billing justification, legal protection, and quality measurement.
The documentation burden has become so severe that physician burnout is often directly attributed to "pajama time"—the hours physicians spend after clinic completing notes. Many physicians spend 1-2 hours on documentation for every hour of patient care. This administrative burden reduces the time available for patients, contributes to provider burnout, and ultimately limits how many patients a physician can see.
AI medical scribes like Scribeberry solve part of this problem by automatically generating structured clinical notes from patient conversations. However, that's only half the solution. The scribed data needs to be formatted into the specific documents required for medical billing, EHR upload, and patient records. Creating these PDFs from the scribed data—encounter notes, billing forms, patient summaries—requires another layer of automation to truly eliminate the documentation burden.
Manually formatting scribed data into PDFs would negate much of the time savings from AI scription. Scribeberry needed a way to automatically generate professional, properly formatted medical documents directly from the AI-generated clinical data.
The Solution
Scribeberry implemented Anvil's PDF Fill API to automatically convert AI-scribed clinical data into structured PDF documents.
When Scribeberry's AI processes a patient-physician conversation, it extracts structured clinical information—patient symptoms, examination findings, diagnoses, treatment plans, medication prescriptions. This structured data is precisely what needs to appear in clinical documentation, but in specific formats required by EHRs, billing systems, and patient records.
Scribeberry uses Anvil's PDF Fill API to transform this structured data into professional medical documents. The API takes the scribed data and populates templates for encounter notes, billing documents, and patient summaries. Each document type has specific formatting requirements and field placements, which the API handles automatically.
For encounter notes, the patient's chief complaint, history, physical exam findings, assessment, and plan all flow into the correct sections of standard medical note templates. Billing forms like superbills or CMS-1500 forms are populated with diagnosis codes, procedure codes, and visit information extracted from the scribed conversation. Patient summaries showing key visit information can be generated for patient portals or after-visit instructions.
The generated PDFs are immediately available for review by the physician. Rather than spending 15-30 minutes typing notes after each patient visit, physicians can quickly review the AI-generated, properly formatted documents, make any necessary adjustments, and move on. The documents can be electronically signed and uploaded directly to the EHR or sent to billing systems.
This automation means that clinical documentation becomes a byproduct of the patient visit rather than a separate administrative task. As Scribeberry listens to and processes the clinical conversation, the required documentation is automatically generated in parallel.
By implementing Anvil's PDF Fill API, Scribeberry completed the clinical documentation automation loop—not just transcribing conversations into structured data, but automatically generating the final, formatted documents that physicians need, truly eliminating the documentation burden that contributes to provider burnout.
