feat: Improve positive had injury description

src/ctk_functions/microservices/redcap.py

@@ -429,15 +429,6 @@ def intake_name(self) -> str:
         return self.name.replace("_", " ")
 
 
-class PriorDisease(pydantic.BaseModel):
-    """Class used for prior diseases in the Primary Care Information."""
-
-    name: str
-    was_positive: bool
-    age: str | None
-    treatment: str | None
-
-
 class Intervention(pydantic.BaseModel):
     """Information about Early Intervention and CPSE services."""
 

src/ctk_functions/routers/intake/intake_processing/parser.py

@@ -646,23 +646,16 @@ def __init__(self, patient_data: redcap.RedCapData) -> None:
             """)
 
         diseases = [
-            redcap.PriorDisease(
+            parser_models.PriorDisease(
                 name=disease,
                 was_positive=getattr(patient_data, disease),
                 age=getattr(patient_data, f"{disease}_age"),
                 treatment=getattr(patient_data, f"{disease}_treatment"),
             )
             for disease in ("seizures", "migraines", "meningitis", "encephalitis")
         ]
-        diseases.append(
-            redcap.PriorDisease(
-                name="head injury",
-                was_positive=patient_data.head_injuries,
-                age=None,
-                treatment=None,
-            ),
-        )
-        self.prior_diseases = transformers.PriorDiseases(diseases).transform()
+        self.head_injury = patient_data.head_injury_yes
+        self.prior_diseases = transformers.PriorDiseases(diseases)
 
 
 class SocialFunctioning:

src/ctk_functions/routers/intake/intake_processing/parser_models.py

@@ -121,3 +121,12 @@ def split_comma_separated_values(cls, value: str | list[str] | None) -> list[str
         if value is None:
             return []
         return value.lower().split(",")
+
+
+class PriorDisease(pydantic.BaseModel):
+    """Class used for prior diseases in the Primary Care Information."""
+
+    name: str
+    was_positive: bool
+    age: str | None = None
+    treatment: str | None = None

src/ctk_functions/routers/intake/intake_processing/transformers.py

@@ -382,8 +382,10 @@ def transform(self) -> str:
         raise exceptions.TransformerError(msg)
 
 
-class PriorDiseases(MultiTransformer[redcap.PriorDisease]):
-    """Transformer for the prior diseases information."""
+class PriorDiseases(
+    MultiTransformer[parser_models.PriorDisease],
+):
+    """Transformer for the prior diseases' information."""
 
     def transform(self) -> str:
         """Transforms the prior diseases information to a string.

src/ctk_functions/routers/intake/intake_processing/writer.py

@@ -1,6 +1,7 @@
 """Contains report writing functionality for intake information."""
 
 import asyncio
+import copy
 import enum
 import itertools
 import re
@@ -17,6 +18,7 @@
 from ctk_functions.microservices import redcap
 from ctk_functions.routers.intake.intake_processing import (
     parser,
+    parser_models,
     transformers,
     writer_llm,
 )
@@ -1067,9 +1069,30 @@
             currently taking any medications for chronic medical conditions.""",
             f"""
             {primary_care.glasses_hearing_device}.
-            {primary_care.prior_diseases}.
             """,
         ]
+
+        prior_diseases = copy.deepcopy(primary_care.prior_diseases)
+        if primary_care.head_injury is None:
+            prior_diseases.base.append(
+                parser_models.PriorDisease(
+                    name="head injury",
+                    was_positive=False,
+                ),
+            )
+            head_injury_text = ""
+        else:
+            head_injury_text = self.llm.run_edit(
+                primary_care.head_injury,
+                additional_instruction=(
+                    "The response should be a single sentence that rephrases this "
+                    "parent's statement on their child's head injury"
+                ),
+                context=" ".join(texts),
+                comment=primary_care.head_injury,
+            )
+        texts.append(head_injury_text)
+        texts.append(prior_diseases.transform())
         texts = [string_utils.remove_excess_whitespace(text) for text in texts]
 
         self._insert("MEDICAL HISTORY", _StyleName.HEADING_1)