Automate clinical documentation and decision-making with the AI Physician Assistant—built for high-acuity specialty practices. From SOAP notes to surgical risk scores, we help physicians practice at the top of their license.
The AI scribe captures and structures clinical notes—without manual typing.
Clinical decision support tools surface conflicts, red flags, and scoring tools instantly.
The agent pulls in critical data in real-time—no need to dig through the EMR.
Whether anesthesia clearance or cardiology risk scores, the agent supports domain-specific logic.
The assistant integrates across EMR, labs, and imaging—responding to prompts or voice commands.
- Reduce documentation by 80%
- Let doctors focus on patients—not typing
- Surface key insights from labs, meds, and notes
- Reduce risk of missed alerts or drug conflicts
- CDS tools based on specialty-specific scoring models
- More accurate, defensible decisions across providers
- One assistant across voice, chat, EMR, and history
- Integrated context = faster, safer care
BitLab specializes in helping medical professionals convert medical insights into compliant, investor-ready healthtech platforms.
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A high-volume orthopedic surgeon was spending over 2 hours every evening transcribing patient encounters into SOAP notes. This after-hours workload led to delayed charting, burnout, and occasional documentation gaps that impacted care continuity.
Manual charting caused significant time strain. Important surgical details were occasionally forgotten or misrecorded due to delayed note entry. The EMR offered little support beyond a basic template.
- 2+ hours/day of after-clinic charting
- 3 delayed surgeries due to missing documentation
- Declining job satisfaction and rising staff attrition risk
The AI would have:
- Transcribed the encounter in real time and structured it into SOAP format
- Inserted relevant patient history, labs, and imaging into the note
- Flagged missing or conflicting inputs during the visit
→ Notes completed during or immediately after the visit
→ Fewer delays in care and handoffs
→ Physician time reclaimed and documentation quality improved
A patient with a recent cardiac event came in for follow-up. The cardiologist was about to prescribe a new medication, unaware that it conflicted with a blood thinner already on file in the EMR. There was no alert from the system before submission.
The EMR’s default CDS wasn’t configured to flag the specific contraindication. The pharmacist caught the error post-discharge, but the delay risked patient safety and required additional follow-up.
- 1 near-miss adverse drug event
- Emergency pharmacy callback and last-minute prescription change
- Patient concern and trust erosion
The AI would have:
- Cross-checked the proposed medication against current prescriptions
- Surfaced the conflict in real time
- Suggested safe alternatives and dosage adjustments
→ Prevented medication error
→ Protected patient safety and reduced liability risk
→ Increased provider confidence in prescribing
In a surgical center, anesthesiologists were calculating preoperative risk manually, with each provider using different tools or heuristics. This led to inconsistent patient clearances, redundant testing, and disagreements during surgical prep.
Lack of standardization created friction between departments. Patient risk levels were evaluated differently depending on who was on call, leading to confusion and delays in surgical scheduling.
- 4 surgeries delayed due to conflicting clearance decisions
- Unnecessary tests ordered “just in case”
- Surgeon and anesthesiologist misalignment
The AI would have:
- Prompted the anesthesiologist to complete a structured pre-op scoring module
- Used clinical data to generate a consistent ASA and cardiac risk score
- Documented the logic in the EMR to reduce second-guessing
→ Reduced surgery delays due to unified risk assessments
→ Improved provider alignment across teams
→ Decreased unnecessary pre-op testing
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