# HACS Models
Clinical models for Healthcare Agent Communication Standard (HACS).
## Overview
`hacs-models` provides comprehensive clinical data models that are FHIR-compliant and designed for healthcare agent communication. These models represent core healthcare entities like patients, observations, encounters, and agent messages.
## Key Models
### Patient
Represents a healthcare patient with:
- Demographics and identification
- Contact information
- Medical record integration
- FHIR R5 compliance
### Observation
Clinical observations and measurements:
- Vital signs and lab results
- Coded values with standard terminologies
- Temporal data with timestamps
- Quality indicators and reliability
### Encounter
Healthcare encounters and visits:
- Encounter classification and status
- Participant information
- Location and timing
- Care team assignments
### AgentMessage
Messages exchanged between healthcare agents:
- Structured message content
- Agent identification and routing
- Message threading and correlation
- Priority and urgency indicators
## Installation
```bash
pip install hacs-models
```
## Quick Start
```python
from hacs_models import Patient, Observation, Encounter, AgentMessage
from hacs_core import Actor
# Create a patient
patient = Patient(
display_name="John Doe",
birth_date="1980-01-01",
gender="male"
)
# Create an observation
observation = Observation(
patient_id=patient.id,
observation_type="vital_signs",
value={"systolic": 120, "diastolic": 80},
unit="mmHg",
timestamp="2024-01-15T10:30:00Z"
)
# Create an encounter
encounter = Encounter(
patient_id=patient.id,
encounter_type="outpatient",
status="in_progress",
start_time="2024-01-15T10:00:00Z"
)
# Create an agent message
actor = Actor(actor_id="dr_smith", actor_type="clinician")
message = AgentMessage(
sender_id="dr_smith",
content="Patient shows elevated blood pressure",
message_type="clinical_note",
actor_context=actor
)
```
## FHIR Compliance
All models are designed to be FHIR R5 compliant:
- Standard resource structures
- Coded values using standard terminologies
- Proper resource relationships
- Validation against FHIR specifications
## Documentation
For complete documentation, see the [HACS Models Documentation](https://github.com/solanovisitor/hacs/blob/main/docs/modules/hacs-models.md).
## License
Licensed under the Apache License, Version 2.0. See [LICENSE](https://github.com/solanovisitor/hacs/blob/main/LICENSE) for details.
## Contributing
See [Contributing Guidelines](https://github.com/solanovisitor/hacs/blob/main/docs/contributing/guidelines.md) for information on how to contribute to HACS Models.
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"description": "# HACS Models\n\nClinical models for Healthcare Agent Communication Standard (HACS).\n\n## Overview\n\n`hacs-models` provides comprehensive clinical data models that are FHIR-compliant and designed for healthcare agent communication. These models represent core healthcare entities like patients, observations, encounters, and agent messages.\n\n## Key Models\n\n### Patient\nRepresents a healthcare patient with:\n- Demographics and identification\n- Contact information\n- Medical record integration\n- FHIR R5 compliance\n\n### Observation\nClinical observations and measurements:\n- Vital signs and lab results\n- Coded values with standard terminologies\n- Temporal data with timestamps\n- Quality indicators and reliability\n\n### Encounter\nHealthcare encounters and visits:\n- Encounter classification and status\n- Participant information\n- Location and timing\n- Care team assignments\n\n### AgentMessage\nMessages exchanged between healthcare agents:\n- Structured message content\n- Agent identification and routing\n- Message threading and correlation\n- Priority and urgency indicators\n\n## Installation\n\n```bash\npip install hacs-models\n```\n\n## Quick Start\n\n```python\nfrom hacs_models import Patient, Observation, Encounter, AgentMessage\nfrom hacs_core import Actor\n\n# Create a patient\npatient = Patient(\n display_name=\"John Doe\",\n birth_date=\"1980-01-01\",\n gender=\"male\"\n)\n\n# Create an observation\nobservation = Observation(\n patient_id=patient.id,\n observation_type=\"vital_signs\",\n value={\"systolic\": 120, \"diastolic\": 80},\n unit=\"mmHg\",\n timestamp=\"2024-01-15T10:30:00Z\"\n)\n\n# Create an encounter\nencounter = Encounter(\n patient_id=patient.id,\n encounter_type=\"outpatient\",\n status=\"in_progress\",\n start_time=\"2024-01-15T10:00:00Z\"\n)\n\n# Create an agent message\nactor = Actor(actor_id=\"dr_smith\", actor_type=\"clinician\")\nmessage = AgentMessage(\n sender_id=\"dr_smith\",\n content=\"Patient shows elevated blood pressure\",\n message_type=\"clinical_note\",\n actor_context=actor\n)\n```\n\n## FHIR Compliance\n\nAll models are designed to be FHIR R5 compliant:\n- Standard resource structures\n- Coded values using standard terminologies\n- Proper resource relationships\n- Validation against FHIR specifications\n\n## Documentation\n\nFor complete documentation, see the [HACS Models Documentation](https://github.com/solanovisitor/hacs/blob/main/docs/modules/hacs-models.md).\n\n## License\n\nLicensed under the Apache License, Version 2.0. See [LICENSE](https://github.com/solanovisitor/hacs/blob/main/LICENSE) for details.\n\n## Contributing\n\nSee [Contributing Guidelines](https://github.com/solanovisitor/hacs/blob/main/docs/contributing/guidelines.md) for information on how to contribute to HACS Models.\n",
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