Healthcare runs on paperwork. AI can change that — if it can be trusted.
Generic AI tools cannot operate in healthcare. They are probabilistic, opaque, and architecturally incompatible with HIPAA, CMS requirements, and the audit demands of payers and regulators. Prescott Data's platform is built from the ground up for regulated care environments — where every automated decision must be traceable, explainable, and reproducible.
Automation across the full care operations stack.
Claims Processing Automation
Automate the end-to-end claims adjudication workflow — from intake and eligibility to coding, review, and payment — with deterministic AI that produces auditable outcomes.
Pre-Authorization & Prior Auth
Reduce prior authorization turnaround from days to minutes. Autonomous agents validate clinical criteria, check policy rules, and escalate edge cases with full documentation.
Clinical Documentation Intelligence
Extract structured intelligence from unstructured clinical notes, discharge summaries, and imaging reports. Eliminate manual chart review without sacrificing accuracy.
Regulatory Compliance Monitoring
Continuously monitor operations against CMS, HIPAA, and payer-specific requirements. Generate audit-ready evidence chains for every AI-assisted decision.
Patient Entity Resolution
Resolve patient identity across fragmented EHR systems, payer records, and care networks. Build a longitudinal, unified patient view without consolidating raw data.
Healthcare Fraud Detection
Detect upcoding, phantom billing, and provider fraud networks using graph intelligence across claims histories — before they become write-offs.
Claims Processing Automation
Healthcare claims adjudication is one of the most complex document processing workflows in any industry. Each claim requires eligibility verification, clinical necessity validation, coding accuracy review, and payer policy enforcement — across thousands of claim types and payer-specific rules. Dromos automates this workflow deterministically, ensuring the same input always produces the same adjudication outcome, with a complete audit trail satisfying CMS and payer examination requirements.
Regulatory Compliance
HIPAA, CMS Conditions of Participation, and state insurance regulations impose strict requirements on how healthcare AI systems must behave. Every AI-driven decision must be explainable, reproducible, and supported by an evidence trail. Dromos generates this evidence automatically — logging the input data, clinical criteria evaluated, policy rules applied, and final determination for every automated decision made in your environment.
Frequently Asked Questions
How is AI used in healthcare claims processing?
AI in healthcare claims processing automates the adjudication workflow — validating eligibility, applying clinical and billing rules, detecting anomalies, and routing edge cases for human review. Prescott Data's Dromos platform enforces deterministic execution, meaning every claims decision is traceable and auditable, which is essential for CMS and payer compliance.
What is AI for clinical documentation?
AI for clinical documentation extracts structured medical data from unstructured sources — physician notes, discharge summaries, lab results, and imaging reports. This eliminates manual chart review and coding backlogs while maintaining the accuracy and traceability standards that healthcare compliance demands.
How can AI improve prior authorization in healthcare?
AI automates prior authorization by evaluating clinical criteria, checking payer policy rules, and verifying patient eligibility in real time — reducing turnaround from days to minutes. Autonomous agents handle routine approvals and escalate complex cases to clinical reviewers with full documentation.
Is AI in healthcare compliant with HIPAA?
Prescott Data's platform is designed for data-sovereign deployments. It operates within your data perimeter — no raw patient data leaves your environment. All AI-driven decisions generate audit trails meeting HIPAA and CMS documentation requirements.
How does AI detect fraud in healthcare?
AI detects healthcare fraud using graph intelligence to connect claimants, providers, and billing entities across claims histories. Graph analysis reveals upcoding patterns, phantom billing networks, and provider fraud rings that appear unrelated when evaluated on a per-claim basis.