AI that decides instead of assists
Scores generated without clinician review are a clinical and liability risk.
AI Clinical Assessment Software Development
AI-Assisted Clinical Assessment & Scoring
AI listens to the assessment interview, extracts the evidence and suggests a value for each field. A clinician reviews and approves every field, and scores are calculated only after that approval.
What Is This Service?
Decision support for assessments, with the clinician deciding
Structured clinical assessments take time because every field needs the clinician's attention: listening, recalling what was said, choosing a value and documenting why. AI can remove the typing and searching without taking over the judgment.
In the systems we build, the AI works from the recorded interview. For each assessment field it suggests a value and shows the exact transcript passages that support it. The clinician accepts, changes or rejects each suggestion. Only when the clinician has approved the fields does the software calculate any dimension or composite score, using the scoring rules of the assessment tool your organization is licensed to use.
The AI never issues a score or a level-of-care determination on its own. It prepares the evidence; the clinician decides.
Business Challenges
Where assessment tools go wrong
Suggestions without evidence
A suggested value is only useful if the clinician can see what in the conversation supports it.
Proprietary criteria and licensing
Many assessment instruments and criteria are copyrighted or licensed, with rules about how software may use them.
No audit trail
Programs need to show who approved each value, when, and what the AI originally suggested.
Features & Capabilities
What the system does
Evidence extraction
Finds the passages in the interview that relate to each assessment field and links them to it.
Suggested field values
Proposes a value for each field as a draft, marked clearly as an AI suggestion.
Clinician review and approval
Each field is accepted, edited or rejected by the clinician, with the evidence beside it.
Scoring after approval
Dimension and composite scores are calculated by deterministic rules from clinician-approved values, never from raw AI output.
Audit history
Records the AI suggestion, the clinician's final value, who approved it and when.
Fits your existing form
Works inside your current assessment application and saves to your existing system.
Business Benefits
Business value designed into the system
Shorter assessments
Clinicians confirm and correct instead of recalling and typing every field.
Better-supported decisions
Each value is linked to what the patient actually said.
Consistency
The same evidence standard is applied to every assessment, with the clinician's judgment on top.
Defensible records
A clear trail shows that a licensed clinician reviewed and approved every scored value.
How It Works
From interview to approved score
Confirm tools and licensing
We identify the assessment instruments and criteria you use and confirm, with you, what your licenses permit before any design work.
Record the interview
The assessment conversation is captured and transcribed inside your existing application.
Extract evidence
The AI links relevant passages to each field of your assessment form.
Suggest values
A draft value is proposed for each field, shown with its evidence.
Clinician approves
The clinician reviews every field and approves, edits or rejects each suggestion.
Calculate and save
Scores are computed from approved values using your tool's rules and saved with a full audit trail.
Technologies We Use
A production stack selected for your requirements
Language models handle evidence extraction and suggestions; scoring is deterministic code, so results are reproducible and testable.
- AssemblyAI
- AWS Transcribe
- Whisper
- OpenAI
- Anthropic
- LangChain
- RAG
- Python
- FastAPI
- React
- React Native
- PostgreSQL
- AWS
- FHIR
Who It's For
Teams that complete structured assessments
Addiction treatment programs
Intake and placement assessments completed by counselors and clinicians.
Behavioral health providers
Structured clinical interviews and periodic reassessments.
Home health and care organizations
Recurring structured assessments completed in the field.
Health-tech products
Vendors adding AI assistance to assessment modules in their software.
Why Torch Solutions
Why build it with Torch Solutions
Human approval is the architecture
Suggest, review, approve, then score. The order is enforced in the software, not left to policy.
We respect licensed criteria
We do not embed proprietary criteria in AI. We work with your licensed tools and confirm licensing during discovery.
Proven clinical AI engineering
The capture, drafting and clinician-approval patterns come from our SureScribe build.
Added to your existing app
No new platform; the assistance appears inside the assessment your team already uses.
Related Case Studies
Clinician-in-the-loop AI we have built
SureScribe AI Clinical Documentation Platform
HIPAA-aware AI scribe: clinical speech recognition, multi-stage LLM notes, clinician approval and Athenahealth / CharmHealth integration. Documentation cut from 60+ to about 20 minutes per patient.
Read Case Study →Engagement & Timelines
How to start
Assessment projects begin with tools, licensing and one form.
Discovery
About 1–2 weeks
Assessment tools, licensing, current application and review workflow.
- Licensing and tool confirmation
- Field-by-field design
- Estimate
Proof of concept
About 4 weeks
One assessment form: evidence, suggestions and clinician approval.
- Working prototype
- Evaluation with clinicians
- Production plan
Integration
Phased
Built into your application with scoring, audit trail and write-back.
- Review and approval in your app
- Post-approval scoring
- Audit history
We do not put the ASAM Criteria or other proprietary criteria into AI systems, and we do not automate level-of-care decisions. This page is general information, not legal or clinical advice.
Related Services
Combine this capability with the application, cloud, data, integration, and product engineering required to operate it reliably.
Frequently Asked Questions
Questions about AI-Assisted Clinical Assessment & Scoring
Does the AI assign the score or level of care?
No. The AI suggests field values with supporting evidence. A licensed clinician reviews and approves each field, and scores are calculated only from approved values. The clinician makes the determination.
Do you build the ASAM Criteria into AI?
No. We do not put the ASAM Criteria or other proprietary criteria into AI systems or automate ASAM level-of-care decisions. We work with the criteria and assessment tools your organization is licensed to use, and we confirm licensing for any proprietary criteria during discovery.
How does a clinician check a suggestion?
Each suggested value appears next to the transcript passages that support it. The clinician can accept it, change it or reject it, and the system records the outcome.
How are scores calculated?
By deterministic rules implemented in code from the scoring method of your licensed tool, applied only to clinician-approved values. The language model is not used to compute scores.
Can this be added to our current assessment application?
Yes. This is designed as an addition to an existing app, including older web applications, with results saved to your current system.
Is the audit trail kept?
Yes. The system stores the AI suggestion, the clinician's final value, the approver and the time, so reviews and audits can see how each value was reached.
Want AI assistance in your assessments, with clinicians in control? Contact Torch Solutions.
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