Automations
This pillar addresses regulated healthcare workflows where model outputs must be interpretable, auditable, and defensible to practitioners, operators, and oversight bodies. The content should show how explainability layers, risk scoring, bias checks, and model audit logs can be built directly into clinical and diagnostic automation systems without breaking operational speed.
This foundational page outlines the architecture for building custom, auditable compliance workflows where AI decisions are paired with justification layers, bias checks, and risk scoring. It shows healthcare enterprises how to embed explainability into clinical and operational automation to meet regulatory scrutiny while improving throughput and reducing manual oversight burden.
This workflow automates the prioritization and routing of abnormal lab results by analyzing values against patient history and clinical guidelines, generating clear escalation rationales. It reduces clinician alert fatigue, accelerates critical result notification, and provides an auditable trail of triage decisions for compliance and quality review.
This automation extracts key diagnoses, procedures, and assessments from unstructured clinical notes to generate structured summaries and suggest accurate billing codes. It reduces coder administrative burden, improves documentation accuracy for reimbursement, and creates an explainable link between note content and coded output for audit defense.
This agentic workflow compares medication lists across admission, transfer, and discharge documents, flagging discrepancies and generating reconciliation notes with cited sources. It reduces medication errors, ensures Joint Commission compliance, and provides a transparent audit trail of reconciliation decisions for pharmacist and physician review.
This workflow continuously analyzes remote patient monitoring data, EHR trends, and guideline-based protocols to identify non-adherence or deterioration, triggering personalized patient outreach with clinical rationale. It improves population health outcomes, optimizes care team effort, and maintains a compliance-ready record of intervention logic.
This system automates post-discharge check-in scheduling, medication adherence verification, and readmission risk scoring based on discharge summaries and care plans. It reduces preventable readmissions, ensures CMS compliance, and documents follow-up attempts and clinical reasoning for quality reporting.
This workflow ingests clinical notes and imaging to draft prior authorization requests that map patient data to payer-specific medical necessity criteria, citing supporting evidence. It accelerates approval cycles, reduces administrative denials, and creates a defensible, transparent submission package for appeals and audits.
This system monitors patient records in real-time against the latest clinical guidelines (e.g., ACC/AHA, NCCN), generating gap reports and suggested order sets with explicit guideline references. It standardizes care, improves quality metric scores, and produces an explainable adherence dashboard for credentialing and accreditation.
This workflow aggregates and analyzes longitudinal PRO data, detecting significant changes, correlating them with clinical events, and generating summaries for care team review with trend visualizations. It operationalizes value-based care, supports shared decision-making, and creates auditable evidence for quality reporting and research.
This automation parses denial reasons from payer EOBs, retrieves relevant clinical documentation, and drafts structured appeal letters with targeted clinical and contractual arguments. It increases appeal win rates, reduces revenue cycle staff workload, and builds a searchable knowledge base of successful appeal rationales.
This workflow reviews clinical documentation, procedure notes, and supply logs to identify missed charges, suggest accurate CPT/ICD-10 codes, and flag documentation deficiencies before billing. It optimizes revenue integrity, reduces compliance risk from overcoding, and provides clear audit trails linking charges to source data.
This system automates the collection and verification of provider credentials from primary sources, tracks expiration dates, and assembles complete privileging packets with gap reports. It accelerates onboarding, ensures continuous compliance with TJC standards, and maintains a verifiable chain of custody for all credential data.
This workflow continuously monitors staff licenses, certifications, and mandatory training against organizational policy and regulatory requirements, triggering renewal alerts and access restrictions. It reduces compliance violations, automates HR and nursing administration tasks, and provides a real-time, auditable compliance dashboard.
This pre-emptive audit system uses NLP and rule engines to scan coded claims against clinical documentation, identifying potential errors, unbundling, or lack of medical necessity before submission. It minimizes audit risk and recoupments, educates coding staff, and generates detailed findings reports with supporting evidence for review.
This system analyzes historical attendance, socioeconomic factors, and communication patterns to predict no-show risk, triggering personalized reminder sequences and offering alternative scheduling. It improves clinic utilization and revenue, supports equitable access, and documents intervention attempts for performance and compliance tracking.
This workflow automates the initial triage of potential privacy breaches by correlating access logs, user roles, and patient context to assess incident severity and generate preliminary reports. It accelerates mandatory reporting timelines, reduces privacy officer workload, and creates a detailed, defensible investigation audit trail.
This system identifies cases requiring mandatory public health reporting from diagnostic codes and clinical notes, auto-populates jurisdiction-specific forms, and routes them for authorized sign-off. It ensures timely legal compliance, reduces manual data entry errors, and maintains a complete submission ledger for health department audits.
This real-time CDI workflow reviews physician notes concurrently, suggests clarifications to support higher-specificity coding and severity capture, and provides educational rationale. It increases case-mix index (CMI), improves documentation quality, and creates a transparent query trail that supports both education and audit defense.
This automation analyzes case complexity, outcome variances, and procedural volumes to objectively identify cases for peer review, ensuring a fair and comprehensive selection process. It reduces administrative bias, fulfills OPPE/FPPE requirements efficiently, and generates a documented rationale for each selected case.
This workflow assists RCA teams by aggregating timeline data from EHR, device logs, and staff interviews, identifying contributing factors, and drafting structured RCA reports per JC standards. It standardizes the RCA process, accelerates reporting, and creates a more rigorous, evidence-based analysis for corrective action planning.
This system analyzes prescribing patterns against PDMP data, patient risk scores, and guidelines to flag potential misuse, generating alerts with supporting evidence for pharmacist or committee review. It supports DEA compliance and stewardship programs, reduces diversion risk, and provides auditable oversight logs.
This workflow audits blood product orders against institutional criteria and clinical indications, flagging non-compliant orders for retrospective review and providing educational feedback. It optimizes blood bank resources, ensures compliance with AABB and TJC standards, and automates reporting for utilization committees.
This system monitors antibiotic orders for spectrum, duration, and culture results, sending automated, guideline-based recommendations to prescribers and tracking acceptance rates. It improves stewardship metrics, supports ASP reporting to CMS, and creates a transparent record of interventions and rationale.
This automation continuously reviews restraint/seclusion documentation for completeness, timeliness, and regulatory requirements (e.g., 1-hour face-to-face evaluation), generating deficiency reports for nursing leadership. It reduces compliance risks, automates a labor-intensive audit process, and ensures documentation supports safe patient care practices.
This workflow automates the extraction and calculation of complex quality measures from EHR and claims data, generating numerator/denominator reports with patient-level drill-down and data lineage. It eliminates manual chart reviews for HEDIS, improves measure accuracy, and creates an auditable data trail for health plan reporting.
This system aggregates provider performance data (e.g., outcomes, volumes, peer feedback) against specialty-specific benchmarks, generating standardized OPPE/FPPE reports for committee review. It streamlines credentialing maintenance, ensures objective, data-driven evaluations, and maintains a complete compliance archive for TJC surveys.
This workflow applies ML to analyze alert overrides, patient context, and historical harm to intelligently suppress low-value alerts and prioritize high-risk ones with clear rationale. It reduces clinician burnout from alert fatigue, improves response to critical warnings, and provides analytics on alert efficacy for CDS governance.
This system monitors EHR and research data against trial protocol criteria in near real-time, identifying potential deviations (e.g., missed visits, incorrect procedures) and routing them for PI review. It improves trial integrity, accelerates deviation reporting to sponsors and IRBs, and creates a searchable deviation log for audit readiness.
This workflow cross-references provider disclosures with external databases (e.g., Open Payments) and internal purchasing records, flagging unreported conflicts for compliance officer review. It automates a tedious monitoring process, strengthens institutional COI management, and generates audit-ready reconciliation reports.
This system analyzes unstructured patient complaint and survey data to categorize issues, detect sentiment trends, and route actionable items to appropriate departments with suggested responses. It improves patient experience response times, identifies systemic quality issues, and creates a documented loop for service recovery and compliance.
This automation orchestrates the collection, validation, and assembly of essential documents (1572, CVs, lab certs) from disparate sites and systems for study startup, flagging gaps. It dramatically shortens site activation timelines, ensures regulatory binder completeness, and provides a transparent dashboard of document status for sponsors and CROs.
This workflow manages the lifecycle of ICFs across multi-site trials, ensuring the correct version is used for each patient visit based on IRB approval dates and protocol amendments. It eliminates consenting with outdated forms, a critical compliance risk, and maintains an immutable audit log of form issuance and patient signature.
This system continuously audits the TMF for missing, misfiled, or expired documents against the DIA TMF Reference Model, generating QC reports and auto-requesting missing items from functional areas. It ensures inspection readiness, reduces manual QC labor for CROs and sponsors, and provides a clear accountability trail for document compliance.
This automation ingests adverse event data from various sources (CRFs, literature, calls), maps it to E2B (R3) standards, performs validity checks, and prepares submissions for pharmacovigilance review. It accelerates regulatory reporting timelines, reduces manual coding errors, and ensures a consistent, auditable transformation process.
This workflow continuously scans scientific literature and conference abstracts for potential safety signals related to a drug product, summarizing findings and triaging them to safety scientists. It improves signal detection sensitivity, fulfills regulatory literature monitoring requirements, and documents the review rationale for each article.
This system uses NLP to classify incoming product complaints from various channels (phone, web, email), assesses severity based on predefined rules, and routes them to appropriate quality and regulatory teams. It standardizes complaint handling, ensures timely MDR reporting decisions, and creates a unified, searchable complaint log.
This payer workflow automates the application of complex medical policies to incoming claims, comparing diagnosis codes, procedure details, and clinical notes to policy criteria to determine medical necessity. It increases auto-adjudication rates, ensures consistent policy application, and generates detailed denial explanations referencing specific policy rules.
This system uses anomaly detection and network analysis on claims data to identify patterns suggestive of FWA, generating prioritized cases for investigators with supporting evidence and risk scores. It improves investigator efficiency, strengthens payer compliance programs, and creates a defensible, data-driven case file for potential recovery actions.
This workflow audits provider-submitted diagnosis codes used for RAF scoring, verifying documentation support in clinical notes and suggesting additional codes that may be supported. It optimizes accurate risk capture for Medicare Advantage plans, reduces audit exposure, and provides educational feedback to providers with clear audit trails.
This payer-side automation evaluates prior auth requests against the plan's clinical criteria in real-time, requesting additional information if needed and providing instant determinations with cited criteria. It reduces manual review volume, speeds member access to care, and ensures consistent, transparent application of coverage policies.
This system ingests claims, EHR, and quality data to calculate provider performance against value-based contract metrics (cost, quality, outcomes), generating dashboards and reconciliation reports. It automates complex performance calculations, supports accurate incentive payments, and provides transparent data for provider discussions and audit defense.
This workflow automatically identifies claims where another payer may be primary (COB) or where a third party may be liable (subrogation), gathering evidence and initiating recovery processes. It maximizes payer recoveries, reduces manual investigation work, and maintains a compliant, documented chain of correspondence and decisions.
This public health workflow automates the extraction, normalization, and submission of syndromic data (e.g., chief complaints) from multiple EDs and clinics to health departments. It ensures timely reporting for outbreak detection, reduces manual data aggregation burden on hospitals, and provides data lineage for public health audits.
This system automatically extracts immunization administration data from the EHR, maps it to jurisdiction-specific standards (e.g., HL7), and submits it to Immunization Information Systems (IIS). It ensures compliance with mandatory reporting laws, improves registry data completeness, and reduces manual work for clinic staff.
This workflow administers, scores, and interprets standardized SDOH screenings within clinical workflows, flagging positive screens and suggesting community resource referrals based on patient location. It operationalizes SDOH integration into care, supports CMS requirements, and creates a documented screening and referral history.
This system tracks patient interactions, care plan updates, and time spent to automatically generate documentation supporting CCM billing codes (99490, 99491), ensuring all Medicare requirements are met. It optimizes legitimate CCM revenue, reduces audit risk from insufficient documentation, and automates a complex billing compliance process.
This SNF workflow pulls data from clinical charts, therapy notes, and observations to pre-populate MDS 3.0 sections, performs internal consistency checks, and prepares submissions to CMS. It reduces assessment coordinator burden, improves data accuracy for reimbursement (PDPM), and ensures timely regulatory submission.
This system reviews clinician-completed OASIS assessments for clinical consistency and coding accuracy against supporting documentation, flagging potential errors before submission. It improves outcome-based quality measure (OBQM) scores, ensures accurate reimbursement, and provides targeted education to clinicians, creating an audit trail of review.
This workflow automates the periodic assessment of resident functional status, behaviors, and care needs, updating care plans and generating alerts for significant changes. It ensures compliance with state licensing requirements, improves care coordination, and maintains a longitudinal, auditable record of resident status.
This system reviews DME orders (e.g., CPAP, wheelchairs) against Medicare documentation requirements, identifying missing elements in clinical notes and generating templated justification letters for physician signature. It reduces claim denials, accelerates patient access to equipment, and ensures orders are supportable for audits.
This workflow monitors progress notes and outcome assessments against individualized treatment plans, alerting clinicians to deviations or lack of progress and suggesting plan revisions. It supports compliance with accreditation standards (e.g., CARF), improves care quality, and automates the tedious process of plan-to-documentation alignment.
This system performs an automated pre-review of new IRB submissions, checking for completeness, consistency, and common regulatory pitfalls (e.g., consent language, risk description). It streamlines IRB office workflow, improves submission quality, and provides investigators with clear, actionable feedback to accelerate approval.
This workflow applies the HIPAA Safe Harbor method (and other techniques) to structured and unstructured patient data for research, generating a de-identified dataset with a report documenting all transformations. It enables compliant data sharing, reduces manual redaction effort, and creates a defensible audit log of the de-identification process.
This system tracks data usage against the specific terms of executed DUAs, monitoring approved users, purposes, and security controls, and flagging potential violations. It automates a critical but manual compliance task for research administrators, reduces institutional risk, and provides real-time dashboards of DUA adherence.
This workflow automates the complex charge routing for clinical trial visits, distinguishing routine care (bill to insurance) from research-only procedures (bill to sponsor) based on the protocol and coverage analysis. It prevents costly billing errors, ensures Medicare compliance, and creates a clear, auditable mapping of services to payers.
This system orchestrates the extraction, transformation, and quality checking of EHR and claims data for RWE studies, applying study-specific inclusion criteria and generating a curated dataset with a data dictionary and provenance log. It accelerates study setup, ensures data quality for regulatory submissions, and provides transparency into the curation pipeline.
This specialty workflow ingests stress test data (ECG, imaging, hemodynamics), applies guideline-based interpretation logic, and drafts a structured report with findings, impressions, and recommendations. It reduces cardiologist reporting time, standardizes report quality, and embeds the clinical reasoning behind interpretations for downstream care and audits.
This workflow analyzes retinal images for signs of diabetic retinopathy, grades severity according to standards, and generates a screening report for the PCP with clear follow-up recommendations. It expands screening access, ensures consistent grading, and creates a documented screening outcome for quality measurement and referral tracking.
This system triages incoming teledermatology consultation requests by analyzing patient-submitted images and history, prioritizing urgent cases (e.g., suspected melanoma) and routing routine ones appropriately. It optimizes dermatologist time, improves access for urgent cases, and documents triage decisions for quality and liability purposes.
This workflow guides clinicians through a structured suicide risk assessment based on patient responses, auto-populates risk stratification documentation, and suggests safety planning interventions per protocol. It standardizes a critical high-risk process, ensures compliance with Joint Commission standards, and creates a clear, defensible risk assessment record.
This system validates dialysis treatment orders (e.g., dialysate composition, ultrafiltration goals) against patient lab trends and clinical guidelines, flagging potentially unsafe or ineffective orders for review. It enhances patient safety in dialysis units, ensures compliance with CMS Conditions for Coverage, and provides an educational audit trail.
How We Work
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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We understand the task, the users, and where AI can actually help.
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We define what needs search, automation, or product integration.
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We implement the part that proves the value first.
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We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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