Encounter

Encounter¶

encounter_dto ¶

VitalSign ¶

Bases: BaseModel

Represents a single vital sign measurement.

Attributes:

Name	Type	Description
`value`	`str`	The value of the vital sign.
`unit`	`str`	The unit of the vital sign.

MedicalHistoryItem ¶

Bases: BaseModel

Represents a single item in the patient's medical history.

Attributes:

Name	Type	Description
`condition`	`Optional[str]`	A medical condition in the patient's history.
`procedure`	`Optional[str]`	A medical procedure in the patient's history.

FamilyHistoryItem ¶

Bases: BaseModel

Represents a single item in the patient's family history.

Attributes:

Name	Type	Description
`relation`	`str`	The relation to the patient.
`condition`	`str`	The medical condition of the relative.

ProcedureItem ¶

Bases: BaseModel

Represents a single procedure performed on the patient.

Attributes:

Name	Type	Description
`description`	`str`	Description of the procedure.
`complications`	`Optional[str]`	Any complications during the procedure.

InvestigationItem ¶

Bases: BaseModel

Represents a single investigation record.

Attributes:

Name	Type	Description
`observations`	`list[str]`	Observed vital signs.
`status`	`str`	Status of the investigation.
`recordedDate`	`str`	Date when the investigation was recorded.

LabReportItem ¶

Bases: BaseModel

Represents a single lab report.

Attributes:

Name	Type	Description
`observations`	`list[str]`	Observed vital signs.
`status`	`str`	Status of the lab report.
`recordedDate`	`str`	Date when the lab report was recorded.
`category`	`str`	Category of the lab report.
`conclusion`	`str`	Conclusion of the lab report.

PatientDetails ¶

Bases: BaseModel

Represents patient demographic and admission details.

Attributes:

Name	Type	Description
`first_name`	`str`	Patient's first name.
`middle_name`	`Optional[str]`	Patient's middle name.
`last_name`	`str`	Patient's last name.
`birth_date`	`str`	Patient's date of birth in ISO format (YYYY-MM-DD).
`gender`	`Gender`	Patient's gender, represented as an enum.
`mobile_number`	`str`	Patient's mobile number.
`email_id`	`Optional[str]`	Patient's email address.
`address`	`str`	Patient's residential address.
`pincode`	`str`	Patient's postal code.
`state`	`str`	Patient's state of residence.
`wants_to_link_whatsapp`	`Optional[bool]`	Indicates if the patient wants to link their WhatsApp number.
`photo`	`Optional[str]`	Base64 encoded string of the patient's photo.
`id_number`	`str`	Unique identifier for the patient (e.g., Aadhar number).
`id_type`	`str`	Type of the ID number (e.g., "Aadhar", "PAN").
`abha_address`	`Optional[str]`	ABHA address for the patient, if available.
`resource_id`	`Optional[str]`	Resource ID for the patient in the system.

DoctorDetails ¶

Bases: BaseModel

Represents doctor information.

Attributes:

Name	Type	Description
`first_name`	`str`	Doctor's first name.
`middle_name`	`Optional[str]`	Doctor's middle name.
`last_name`	`str`	Doctor's last name.
`birth_date`	`str`	Doctor's date of birth in ISO format (YYYY-MM-DD).
`gender`	`str`	Doctor's gender, represented as an enum.
`mobile_number`	`str`	Doctor's mobile number.
`email_id`	`Optional[str]`	Doctor's email address.
`address`	`str`	Doctor's residential address.
`pincode`	`str`	Doctor's postal code.
`state`	`str`	Doctor's state of residence.
`wants_to_link_whatsapp`	`Optional[bool]`	Indicates if the doctor wants to link their WhatsApp number.
`photo`	`Optional[str]`	Base64 encoded string of the doctor's photo.
`designation`	`str`	Doctor's designation (e.g., "Cardiologist").
`joining_date`	`Optional[str]`	Date when the doctor joined the organization in ISO format (YYYY-MM-DD).
`department`	`str`	Department of the doctor (e.g., "Cardiology").
`registration_id`	`str`	Doctor's registration ID.
`hpr_id`	`Optional[str]`	HPR ID of the doctor, if available.
`resource_id`	`Optional[str]`	Resource ID for the doctor in the system.

CommonHealthInformationDTO ¶

Bases: BaseModel

Base DTO for common health information sections.

Attributes:

Name	Type	Description
`chief_complaints`	`str`	The patient's chief complaints.
`physical_examination`	`str`	Patient's physical examination.
`medical_history`	`Optional[list[MedicalHistoryItem]]`	Patient's medical history.
`family_history`	`Optional[list[FamilyHistoryItem]]`	Patient's family history.
`condtions`	`Optional[list[str]]`	Patient's conditions.
`current_procedures`	`Optional[list[ProcedureItem]]`	Patient's procedures.
`current_medications`	`Optional[list[str]]`	Patient's medications.
`prescribed_medications`	`Optional[list[str]]`	Patient's prescribed medications.
`allergies`	`Optional[list[str]]`	Patient's allergies.
`immunizations`	`Optional[list[str]]`	Patient's immunizations.
`advisory_notes`	`Optional[list[str]]`	Patient's advisory notes.
`care_plan`	`Optional[list[str]]`	Patient's care plan.
`follow_up`	`Optional[list[str]]`	Patient's follow-up plan.

OPConsultationSections ¶

Bases: CommonHealthInformationDTO

Represents the OP consultation section, inheriting common health information from CommonHealthInformationDTO.

DischargeSummarySections ¶

Bases: CommonHealthInformationDTO

Represents the discharge summary section, inheriting common health information.

Attributes:

Name	Type	Description
`investigations`	`InvestigationItem`	Patient's investigations.

PrescriptionSections ¶

Bases: BaseModel

Represents the prescription section.

Attributes:

Name	Type	Description
`prescribed_medications`	`list[str]`	Patient's prescribed medications.

WellnessRecordSections ¶

Bases: BaseModel

Represents the wellness record section.

Attributes:

Name	Type	Description
`vital_signs`	`Optional[list[str]]]`	Patient's vital signs.
`body_measurements`	`Optional[list[str]]]`	Patient's body measurements.
`physical_activities`	`Optional[list[str]]]`	Patient's physical activities.
`women_health`	`Optional[list[str]]]`	Women's health data.
`life_style`	`Optional[list[str]]]`	Lifestyle data.
`others`	`Optional[list[str]]]`	Other health data.

ImmunizationRecordSections ¶

Bases: BaseModel

Represents the immunization record section.

Attributes:

Name	Type	Description
`immunizations`	`list[str]`	Patient's immunizations.

DiagnosticReportSections ¶

Bases: BaseModel

Represents the diagnostic report section.

Attributes:

Name	Type	Description
`lab_reports`	`LabReportItem`	Patient's lab reports.

OPConsultationDTO ¶

Bases: BaseModel

Data Transfer Object for OP Consultation. Attributes: case_sheets (Optional[list[str]]): List of case sheets associated with the patient. payload (Optional[OPConsultationSections]): The raw data for the OP consultation.

DischargeSummaryDTO ¶

Bases: BaseModel

Data Transfer Object for Discharge Summary. Attributes: case_sheets (Optional[list[str]]): List of case sheets associated with the patient. payload (Optional[DischargeSummarySections]): The raw data for the discharge summary.

PrescriptionRecordDTO ¶

Bases: BaseModel

Data Transfer Object for Prescription Record. Attributes: case_sheets (Optional[list[str]]): List of case sheets associated with the patient. payload (Optional[PrescriptionSections]): The raw data for the prescription record.

WellnessRecordDTO ¶

Bases: BaseModel

Data Transfer Object for Wellness Record. Attributes: case_sheets (Optional[list[str]]): List of case sheets associated with the patient. payload (Optional[WellnessRecordSections]): The raw data for the wellness record.

ImmunizationRecordDTO ¶

Bases: BaseModel

Data Transfer Object for Immunization Record.

Attributes:

Name	Type	Description
`case_sheets`	`Optional[list[str]]`	List of case sheets associated with the patient.
`payload`	`Optional[ImmunizationRecordSections]`	The raw data for the immunization record.

DiagnosticReportDTO ¶

Bases: BaseModel

Data Transfer Object for Diagnostic Report. Attributes: case_sheets (Optional[list[str]]): List of case sheets associated with the patient. payload (Optional[DiagnosticReportSections]): The raw data for the diagnostic report.

GenerateFhirFromExtractedDataDto ¶

Bases: BaseModel

Data Transfer Object for generating a FHIR bundle from extracted data. Attributes: case_type (str): The type of case (e.g., OPConsultation, DischargeSummary). Serialized as caseType. record_id (Optional[str]): Identifier for the record, if available. Serialized as recordId. extracted_data (dict[str, Any]): Extracted clinical data for the bundle. document_references (Optional[list[str]]): List of document references to be included in the bundle.

HealthDocumentRecordDTO ¶

Bases: BaseModel

Data Transfer Object for Health Document Record. Attributes: case_sheets (Optional[list[str]]): List of case sheets associated with the patient.

EncounterRequestDTO ¶

Bases: BaseModel

Data Transfer Object for Encounter Request.

Attributes:

Name	Type	Description
`case_type`	`str`	The type of health information case (e.g., `OPConsultation`, `DischargeSummary`).
`enable_extraction`	`bool`	Flag to enable data extraction from the provided documents.
`patient_details`	`PatientDetails`	Patient's information.
`doctor_details`	`list[DoctorDetails]`	List of doctors involved in the case.
`dto`	`HealthInformationDTOUnion`	The health information data, which can be one of the specific DTOs.
`document_references`	`Optional[list[str]]`	List of document references to be included in the request.

Encounter ¶

Encounter(config: ClientConfig)

Bases: BaseService

Service for orchestrating healthcare encounter workflows, FHIR bundle and discharge summary generation.

This service provides a unified interface to create FHIR bundles or discharge summaries based on provided encounter data. It handles validation, encryption, and orchestrates AI-powered healthcare processing endpoints.

Key Features

Validates incoming encounter request data thoroughly.
Supports both file-based and payload-based FHIR bundle generation workflows.
Handles discharge summary generation from encrypted data.
Encrypts sensitive patient data and associated files before transmission.
Robust error handling with clear logging for diagnosis.

Methods:

Name	Description
`create`	Creates a FHIR bundle or discharge summary based on encounter data.
`generate_fhir_from_sections`	Generates FHIR bundle from provided clinical sections (payload).
`generate_fhir_from_files`	Generates FHIR bundle from case sheet files and optional lab reports.
`generate_discharge_summary`	Calls AI endpoint to generate discharge summary.
`generate_fhir_bundle`	Calls AI endpoint to generate FHIR bundle from extracted data and files.

Parameters:

Name	Type	Description	Default
`config`	`ClientConfig`	API credentials and settings for service initialization.	required

Example

config = ClientConfig(
    api_key="your_api_key",
)
encounter_service = Encounter(config)
request = EncounterRequestDTO(
    case_type=CaseType.OP_CONSULTATION,
    dto=OPConsultationDTO(payload=OPConsultationSections(...))
)
bundle = await encounter_service.create(request)
print(bundle["resourceType"])

create `async` ¶

create(request_body: EncounterRequestDTO) -> dict[str, Any]

Main entrypoint: creates a FHIR bundle or discharge summary for the given encounter data.

Determines workflow: file-based (case sheets), section-based (payload), and manages FHIR bundle and summary extraction/encryption as required.

Parameters:

Name	Type	Description	Default
`request_body`	`EncounterRequestDTO`	All data for FHIR/document generation, including case type, files, payload, patient/practitioner info, etc.	required

Returns:

Type	Description
`dict[str, Any]`	dict[str, Any]: Serialized FHIR-compliant bundle or discharge summary document.

Raises:

Type	Description
`EhrApiError`	On validation or any underlying process failure.

Example

encounter_request = EncounterRequestDTO(
    case_type=CaseType.OP_CONSULTATION,
    enable_extraction=True,
    record_id="12345",
    patient_details=PatientDetails(name="John Doe", ...),
    doctor_details=[DoctorDetails(name="Dr. Smith", ...)],
    document_references=["lab_report_1.pdf"],
    dto=OPConsultationDTO(
        caseSheets=None,
        payload=OPConsultationSections(
            chief_complaints="Fever and cough",
            physical_examination=PhysicalExamination(...),
            ...
        )
    ),
)

or

encounter_request = EncounterRequestDTO(
    case_type=CaseType.OP_CONSULTATION,
    enable_extraction=False,
    record_id="12345",
    patient_details=PatientDetails(name="John Doe", ...),
    doctor_details=[DoctorDetails(name="Dr. Smith", ...)],
    document_references=["lab_report_1.pdf"],
    dto=OPCONSULTATIONDTO(
        caseSheets=["case_sheet_1.pdf", "case_sheet_2.pdf"],
    ),
)

response = await encounter_service.create(encounter_request)
print(response)

Response:¶

Sample Output for the given example:
{
    "resourceType": "Bundle",
    "type": "document",
    "entry": [ ...FHIR resources... ]
}

generate_discharge_summary `async` ¶

generate_discharge_summary(case_type: str, encrypted_data: str) -> DischargeSummaryResponse

Generates a discharge summary from encrypted case sheet data.

Parameters:

Name	Type	Description	Default
`case_type`	`str`	The caseType for AI endpoint (e.g., 'inpatient').	required
`encrypted_data`	`str`	Encryption result for case sheets.	required

Returns:

Name	Type	Description
`DischargeSummaryResponse`	`DischargeSummaryResponse`	Extracted summary with meta data.

Raises:

Type	Description
`EhrApiError`	On API or process failures.

Example

summary = await encounter_service._generate_discharge_summary("inpatient", encrypted_files) print(summary.dischargeSummary)

generate_fhir_from_files `async` ¶

generate_fhir_from_files(case_type: str, enable_extraction: bool, case_sheets: list[str], document_references: list[str], record_id: Optional[str] = None, patient_details: Optional[PatientDetails] = None, doctor_details: Optional[list[DoctorDetails]] = None) -> dict[str, Any]

Generates a FHIR bundle from provided case sheet files and any document references.

Workflow: 1. Optionally encrypts document references (lab reports, scans, etc) 2. If extraction enabled: a. Encrypts case sheets. b. Extracts discharge summary & data. c. Encrypts extracted summary data for FHIR. 3. If extraction disabled: requires patient and practitioner details.

Parameters:

Name	Type	Description	Default
`case_type`	`str`	Case type code.	required
`enable_extraction`	`bool`	Whether to extract summary from the files.	required
`case_sheets`	`list[str]`	Source case files (URLs, filenames, etc).	required
`document_references`	`list[str]`	Any supporting doc refs (base64-encoded files).	required
`patient_details`	`Optional[PatientDetails]`	Demographic data, if used.	`None`
`doctor_details`	`Optional[list[DoctorDetails]]`	Provider/practitioner data, if used.	`None`

Returns:

Type	Description
`dict[str, Any]`	dict[str, Any]: The parsed FHIR-compliant document.

Raises:

Type	Description
`EhrApiError`	On API/encryption/validation failure.

Example

``` bundle = await encounter_service._generate_fhir_from_files( case_type="SURGERY", enable_extraction=True, case_sheets=["cs1.pdf", "cs2.pdf"], document_references=["lab1.pdf"], patient_details=details, doctor_details=[doctor], ) print(bundle["resourceType"])

Response:¶

{
    "resourceType": "Bundle",
    "type": "document",
    "entry": [ ...FHIR resources... ]
}
```

generate_fhir_from_sections `async` ¶

generate_fhir_from_sections(case_type: str, enabled_extraction: bool, sections: dict[str, Any], document_references: list[str] = [], record_id: Optional[str] = None, patient_details: Optional[PatientDetails] = None, doctor_details: Optional[list[DoctorDetails]] = None) -> dict[str, Any]

Generates a FHIR-compliant bundle using provided section (payload) data and optional supporting docs.

When extraction is enabled, the entire sections/payload dict is encrypted and included in the FHIR call. When disabled, requires explicit patient and practitioner metadata.

Parameters:

Name	Type	Description	Default
`case_type`	`str`	Encounter/case type.	required
`enabled_extraction`	`bool`	Whether to encrypt/process sections for extraction.	required
`sections`	`dict`	Clinical sections, e.g. consultation notes, as dict.	required
`document_references`	`list[str]`	Doc references (e.g. lab reports).	`[]`
`patient_details`	`Optional[PatientDetails]`	Patient metadata, required if extraction is off.	`None`
`doctor_details`	`Optional[list[DoctorDetails]]`	Provider metadata, required if extraction is off.	`None`

Returns:

Name	Type	Description
`dict`	`dict[str, Any]`	FHIR-compliant bundle resource.

Raises:

Type	Description
`EhrApiError`	On validation or API failure.

Example

``` bundle = await encounter_service._generate_fhir_from_sections( case_type="OP_CONSULTATION", enabled_extraction=True, sections=payload, document_references=[], patient_details=details, doctor_details=[doctor], )

Response:¶

{
    "resourceType": "Bundle",
    "type": "document",
    "entry": [ ...FHIR resources... ]
}
```

Encounter

Encounter¶

encounter_dto ¶

VitalSign ¶

MedicalHistoryItem ¶

FamilyHistoryItem ¶

ProcedureItem ¶

InvestigationItem ¶

LabReportItem ¶

PatientDetails ¶

DoctorDetails ¶

CommonHealthInformationDTO ¶

OPConsultationSections ¶

DischargeSummarySections ¶

PrescriptionSections ¶

WellnessRecordSections ¶

ImmunizationRecordSections ¶

DiagnosticReportSections ¶

OPConsultationDTO ¶

DischargeSummaryDTO ¶

PrescriptionRecordDTO ¶

WellnessRecordDTO ¶

ImmunizationRecordDTO ¶

DiagnosticReportDTO ¶

GenerateFhirFromExtractedDataDto ¶

HealthDocumentRecordDTO ¶

EncounterRequestDTO ¶

Encounter ¶

create async ¶

Response:¶

generate_discharge_summary async ¶

generate_fhir_from_files async ¶

Response:¶

generate_fhir_from_sections async ¶

Response:¶

create `async` ¶

generate_discharge_summary `async` ¶

generate_fhir_from_files `async` ¶

generate_fhir_from_sections `async` ¶