patientChat: 'patientChat()' generates synthetic patients in the OMOP-CDM...

In PatientGenerator: Generator of Synthetic Patient Data for the OMOP Common Data Model

patientChat() generates synthetic patients in the OMOP-CDM using an LLM API.

Description

Requires an OPEN_AI_KEY in ~/.Renviron. After that just sent a prompt and save() the results. The JSON file can be used as an OMOP-CDM patient test set.

Details

Accepts a prompt as input. Produces a test set using a structured JSON schema. Utilizes tools such as CodelistGenerator or Hecate to look up concept IDs. Accepts subsequent prompts to modify existing test sets that the LLM uses as context.

This class allows testing patient sets created by the LLM, prompt engineering, integration of search tools and functionality, and creating a set of patients to test analytical packages.

Value

A JSON response that includes: the natural language answer from the LLM and a JSON with test set patients in accordance to the provided schema.

Public fields

chat

An ellmer chat instance

json_schema_path

JSON schema to output structured results

response

Ouput from the LLM

codelist

A codelist with details to search for concepts ids

Methods

Public methods

• patientChat$new()

• patientChat$prompt()

• patientChat$json_response()

• patientChat$output()

• patientChat$retrieveCodelist()

• patientChat$save()

• patientChat$availableModels()

• patientChat$clone()

---

patientChat$new()

Create a new chat to create JSON test sets for OMOP-CDM.

Usage

patientChat$new(
  system_prompt = NULL,
  model = "gpt-5.4",
  jsonSchemaPath = NULL,
  echo = c("none", "output", "all"),
  codelist_data = NULL
)

Arguments

system_prompt

Initial system prompt to impose behaviour to the LLM

model

Such as "gpt-5.3". For a complete list, call patientChat$availableModels()

jsonSchemaPath

The JSON schema to structure output from LLM

echo

How the output will be displayed in the console

codelist_data

A codelist with details to search for concepts ids

Returns

A new patientChat object.

---

patientChat$prompt()

Prompt to request data from LLM API

Usage

patientChat$prompt(prompt)

Arguments

prompt

A query in character.

---

patientChat$json_response()

Output in JSON format

Usage

patientChat$json_response()

---

patientChat$output()

Returns the chat object

Usage

patientChat$output()

---

patientChat$retrieveCodelist()

Retrieves and filters data from codelist_data

Usage

patientChat$retrieveCodelist(concept_label = "Stage 1", domain = "Measurement")

Arguments

concept_label

Filters the concept_name in the codelist with details

domain

Filters the domain in the codelist with details.

---

patientChat$save()

Saves the JSON test set to disk.

Usage

patientChat$save(name = "patient-chat-test", path = NULL)

Arguments

name

Name of the file

path

To save the file. If NULL, the package first tries testthat::test_path("testCases"), then checks options(PatientGenerator.testSetDir = "..."), and finally falls back to the package user data directory.

---

patientChat$availableModels()

Retrieves available models from the LLM API.

Usage

patientChat$availableModels()

---

patientChat$clone()

The objects of this class are cloneable with this method.

Usage

patientChat$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

## Not run: 
generator <- patientChat$new()
generator$prompt("Give me 5 patients")
generator$save("my_test")

## End(Not run)

PatientGenerator documentation built on Sept. 16, 2026, 1:06 a.m.