Injury Case Management
Injury case management tooling tracks each case from report through closure, consolidating encounters, restrictions, and correspondence so case managers stop reconstructing status from scattered records.
Custom Software
AI Occupational Health Software Development
AI occupational health software applies machine learning to injury records, surveillance data, and case documentation to support occupational medicine teams with case management, compliance tracking, and return-to-work coordination. It functions as decision support only: the examining clinician makes every fitness, restriction, and treatment determination.
Occupational health carries a structural tension no other specialty shares: the clinician serves the worker while reporting to the employer. Taction Software builds AI occupational health tooling that automates case workflow and compliance tracking while keeping that boundary architecturally enforced rather than merely documented in policy.
Tell Us Your Requirements
Our experts are ready to understand your business goals.
Trusted Partners
Trusted by Industry Leaders Worldwide
Recognition
Awards & Recognitions
What Is AI Occupational Health Software
AI occupational health software refers to machine learning and workflow automation applied to occupational medicine: injury case management, workers compensation documentation, fitness-for-duty evaluation workflow, medical surveillance scheduling, drug and alcohol testing administration, and return-to-work coordination. Models organize case data, flag overdue surveillance, and prepare documentation. Every clinical determination, including work restrictions and fitness conclusions, stays with the examining clinician. This work sits inside our broader healthcare AI practice, where validation, access segmentation, and regulatory classification are treated as engineering deliverables.
Workers Compensation Workflow
Workers compensation automation prepares state-specific forms and carrier submissions from clinical documentation, with clinician verification required before anything is filed on their behalf.
Fitness-for-Duty Workflow
Fitness-for-duty tooling routes examinations, collects required components, and tracks completion. The examining clinician determines every fitness conclusion and restriction independently.
Medical Surveillance Programs
Medical surveillance scheduling tracks exposure-based testing obligations by job classification, flagging overdue examinations under respiratory, hearing, and hazardous exposure programs.
Drug and Alcohol Testing Administration
Testing workflow manages DOT compliance chains of custody, random selection pools, and result routing, keeping medical review officer determinations entirely with the qualified reviewer.
Decision Support Boundaries
Every output carries clinical decision support framing. The software does not determine fitness, set restrictions, clear workers for duty, or make return-to-work decisions autonomously.
Core AI Occupational Health Services
Our AI occupational health services span case management systems, employer reporting, surveillance automation, testing administration, and clinical documentation. This field runs on a distinctive integration set: employer HR systems, workers compensation carriers, state reporting portals, testing laboratories, and the clinical record itself. Each carries different access rules, and mixing them incorrectly creates real privacy exposure. Engagements typically open with a review of current data flows, employer reporting obligations, and where clinical and administrative information currently commingle. Deliverables are structured so occupational medicine clinicians, compliance, and employer account teams can each review their portion separately.
01
Case Management Platform Development
We build case management systems tracking injury cases, encounters, restrictions, and closure across employers, with role-based visibility separating clinical detail from employer-reportable status.
02
Employer Reporting and Portals
Employer-facing portals expose only reportable information, showing work status and restrictions without underlying clinical detail, which is the boundary most legacy systems handle poorly.
03
Clinical Documentation Integration
Integration connects occupational encounters with the clinical record. Our EHR and EMR integration practice covers the interface layer and segmentation logic.
04
Surveillance Scheduling Automation
Automated tracking of exposure monitoring obligations by job code and hazard flags overdue examinations, replacing spreadsheets that fail quietly as workforces change.
05
Incident and Safety Data Linkage
Linking clinical cases with safety reporting supports trend review, building on our incident reporting software work for injury trend visibility.
06
Telehealth and Remote Assessment
Remote injury triage and follow-up extend coverage across sites, drawing on our telehealth app development work for virtual occupational health delivery.
Benefits of AI Occupational Health Software
The benefits of AI occupational health software concentrate in case throughput, surveillance compliance, and cleaner separation between clinical and employer-facing information. Occupational medicine practices manage high case volume with heavy administrative load, much of it form preparation and status communication that software handles reliably. Surveillance compliance is another area where manual tracking fails as workforces change. We publish no figures on claim duration, cost, or return-to-work timing, because those depend entirely on employer population and case mix. What we deliver is instrumentation so your program measures against its own data.
Reduced Administrative Load
Automated form preparation and status communication reduce case administration time, which typically consumes more staff capacity than clinical work in occupational practices.
Stronger Surveillance Compliance
Systematic tracking of exposure-based testing obligations by job classification reduces missed examinations, supporting the compliance posture employers are contractually promised.
Cleaner Privacy Boundaries
Architectural separation of clinical and employer-visible data reduces inadvertent disclosure risk, which manual reporting processes create routinely and often invisibly.
Better Return-to-Work Coordination
Structured work restriction communication gives employers actionable accommodation information without clinical detail, supporting placement decisions made by the employer.
Improved Multi-Employer Operations
Multi-tenant design lets a practice serve many employers with distinct reporting rules, supporting account management without duplicating clinical infrastructure per client.
Measurable Program Performance
Structured case and surveillance data makes program metrics genuinely measurable, supporting employer reporting and internal quality review with real numbers.
Our AI Occupational Health Process
We deliver AI occupational health projects in gated phases so clinical, compliance, and commercial stakeholders approve direction before engineering cost accumulates. Discovery establishes intended use, data flows, and, unusually for a clinical build, the disclosure boundaries between clinician, worker, and employer. We treat that boundary as an architectural requirement defined before development rather than an access setting configured afterward. Development is iterative with clinician review inside each cycle, and deployment is staged by employer account so reporting rules are validated against real contracts before wider rollout.
Discovery and Boundary Definition
Discovery defines intended use and maps exactly what each party may see, producing a documented disclosure model alongside the fixed-scope estimate and architecture plan.
Data and Integration Assessment
We evaluate employer HR feeds, carrier interfaces, laboratory connections, and clinical records, since integration breadth drives occupational health effort more than model complexity.
Model Development and Validation
Where models are used, development runs to held-out validation with performance reported by employer, job classification, and demographic subgroup rather than a single aggregate.
Access Control Implementation
Role-based access is implemented and tested explicitly, including negative testing that confirms employer users cannot reach clinical detail through any interface path.
Pilot Account Deployment
Deployment begins with one employer account, validating reporting accuracy and boundary behavior against a real contract before extending to the wider book of business.
Rollout and Ongoing Support
Rollout expands account by account with performance dashboards, compliance review, and continuing support as state and federal requirements change.
Technology and Compliance
Occupational health software sits under an unusual compliance stack: HIPAA where the practice is a covered entity, ADA constraints on what employers may learn, GINA restrictions on genetic information, OSHA recordkeeping requirements, DOT rules for regulated testing, and state workers compensation statutes that vary considerably. Taction holds ISO 27001 certification and follows HIPAA-aligned engineering practice. The defining technical requirement is segmentation: employer-visible data and clinical data must be separated structurally, not by permission flags alone. We design that boundary during discovery.
HIPAA-Aligned Engineering
Builds apply encryption in transit and at rest, role-based access, and complete audit logging. Our HIPAA compliance software development practice defines these controls.
Employer Disclosure Segmentation
ADA constraints limit what employers may receive. We enforce this in the data model so employer views structurally cannot expose diagnosis or treatment detail.
OSHA and Regulatory Recordkeeping
OSHA recordkeeping requirements govern injury logs and retention. We build these as structured records with audit history rather than generated documents.
DOT and Regulated Testing Rules
DOT compliance governs chain of custody, random selection, and medical review officer workflow. We build to those procedural requirements without automating reviewer determinations.
Validation and Bias Monitoring
Where models inform case handling, bias monitoring across job classification and demographic subgroups is continuous, since employment consequences make disparate behavior especially serious.
Deployment Security
Deployments run on-premise, in your cloud tenancy, or hybrid, with network segmentation, signed container images, and documented penetration testing before production release.
Why Choose Taction Software
Taction Software was founded in 2013 and has spent over 12 years building healthcare software, delivering more than 200 healthcare projects from four US offices in Chicago, Cheyenne, Austin, and Sacramento, with ISO 27001 certification. Our relevant strength here is data segmentation under legal constraint: delivering CHIPSS for behavioral health required strict consent and disclosure controls, which is the same architectural problem occupational health presents in a different regulatory frame. Our leadership brings more than 20 years of personal experience in the field, shaping how we scope work where privacy boundaries carry legal weight.
01
Segmentation Under Legal Constraint
CHIPSS required consent segmentation where improper disclosure carried serious consequences, directly relevant to separating clinical detail from employer-visible information.
02
Established Healthcare Focus
Founded in 2013, we have concentrated on healthcare rather than treating it as one vertical among several, producing depth in clinical workflow and multi-party data governance.
03
Regulated Product Experience
We delivered the FDA-registered applications Revive Ease and PainKare, so design controls, validation documentation, and change management are established practice.
04
EHR and Clinical Systems Depth
Our Voyant Health EHR and EMR work means EHR integration is handled by engineers who have built systems on both sides of the interface.
05
Decision Support Engineering
We build clinical decision support with clinician authority preserved by design, detailed in our clinical decision support software development practice.
06
Certified Security Posture
ISO 27001 certification and HIPAA-aligned engineering mean security controls are documented and auditable, supporting employer and carrier vendor assessments.
Pricing
AI occupational health pricing depends on scope, integration breadth, jurisdictional coverage, and how many employer reporting variants are required. A surveillance tracking module costs considerably less than a multi-tenant case management platform with carrier interfaces across several states. We price after discovery, because integration surface and state form variation drive a large share of total effort in this field. Discovery produces an itemized, fixed-scope estimate with phase-level breakdown so components can be approved or deferred. Cloud infrastructure, laboratory interface fees, and testing network costs are separate from engineering and itemized clearly.
MVP or Single Module
An MVP covering one capability such as surveillance scheduling typically runs $40,000 to $80,000, validating operational value before broader commitment.
Full Platform Build
A full platform with case management, employer portals, surveillance, testing administration, and reporting typically falls between $80,000 and $200,000 depending on jurisdictional scope.
Enterprise Deployment
Enterprise engagements covering multi-state operations, carrier integrations, custom model development, and many employer variants start at $200,000 and scale with account count.
Discovery Phase Scoping
Discovery is a paid, time-boxed phase producing an itemized estimate, architecture plan, and documented disclosure model. It is deliberately separable so you can evaluate our work first.
Cost Drivers to Expect
State form variation, carrier interface count, employer reporting variants, and testing network integration are the largest variables, each identified during discovery for realistic budget planning.
Ongoing Support Costs
Post-launch regulatory updates, form revisions, new employer onboarding, and support are quoted separately as a retainer sized to your account footprint.
Get Started
If you are evaluating AI occupational health tooling for case management, surveillance tracking, employer reporting, or testing administration, the fastest next step is a discovery call with our team. We will review your integration landscape, jurisdictional scope, and disclosure requirements, then return an itemized, fixed-scope estimate with a documented boundary model. Contact us to schedule that conversation.
FAQs
Frequently Asked Questions
Occupational health buyers raise a different set of concerns than other specialties, centered on what employers can see, how multi-employer operations are handled, and how regulatory variation across states is managed. The answers below reflect how we scope and deliver these projects in practice. If your situation spans many jurisdictions, involves DOT-regulated testing, or includes onsite clinics embedded in employer facilities, the specifics matter more than any general answer.
Only what they are legally entitled to receive: work status, restrictions, and completion of required examinations. Diagnosis, treatment, and clinical notes are structurally unavailable to employer users, enforced in the data model rather than by permission settings alone. We include negative testing to confirm no interface path exposes clinical detail.
No. Every tool we build functions as clinical decision support. It routes examinations, collects required components, and tracks completion, but the examining clinician determines fitness and sets restrictions. The software does not clear workers, assign restrictions, or make return-to-work determinations in any configuration.
Yes, and this is usually the core requirement. We build multi-tenant architecture with per-employer reporting rules and per-state form variants. Jurisdictional coverage is a primary cost driver, so we scope which states and carriers are in scope during discovery rather than assuming national coverage from the start.
An MVP or single module runs $40,000 to $80,000. A full platform typically falls between $80,000 and $200,000. Enterprise deployments with multi-state operations and carrier integrations start at $200,000. Discovery produces an itemized, fixed-scope estimate, with infrastructure and laboratory fees quoted separately from engineering.
We build the procedural workflow, including chain of custody tracking, random selection pool management, and result routing to the medical review officer. The qualified reviewer makes every determination. We automate administration and documentation, never the review conclusion itself.
Both are treated as data model constraints rather than policy documents. Genetic information is excluded from collection paths where GINA applies, and employer-facing views are built so ADA-protected clinical detail cannot be surfaced. Compliance review with your counsel is part of the discovery deliverable.