diff --git a/Changelog.md b/Changelog.md
index 24ff8ff..0fb0676 100644
--- a/Changelog.md
+++ b/Changelog.md
@@ -4,6 +4,16 @@ Changes in this log refer only to changes that make it to the 'main' branch. and
 
 For changes in deployment, please see the [deployment changelog](deploy/cttso-ica-to-pieriandx-cdk/Changelog.md) 
 
+## 2023-11-17
+
+> Author: Alexis Lucattini
+> Email: [Alexis.Lucattini@umccr.org](mailto:alexis.lucattini@umccr.org)
+
+
+### Hotfixes
+
+* Update how is_identified column is processed as it can both be a string and a boolean value (https://github.com/umccr/cttso-ica-to-pieriandx/pull/163)
+  * Resolves https://github.com/umccr/cttso-ica-to-pieriandx/issues/162
 
 ## 2023-10-18
 
diff --git a/utils/accession.py b/utils/accession.py
index 21759c7..6223631 100644
--- a/utils/accession.py
+++ b/utils/accession.py
@@ -345,6 +345,28 @@ def datetime_obj_to_utc(datetime_obj: datetime) -> datetime:
     return datetime_obj.replace(microsecond=0)
 
 
+def is_identified_sample(is_identified: Union[str, bool]) -> bool:
+    """
+    Is either True / False or "identified" / "deidentified"
+    :param is_identified:
+    :return:
+    """
+
+    if isinstance(is_identified, bool):
+        return is_identified
+
+    if isinstance(is_identified, str):
+        if is_identified not in ["identified", "deidentified"]:
+            logger.error(f"Got '{is_identified}', expected one of 'identified' or 'deidentified'")
+            raise ValueError
+        if is_identified == "identified":
+            return True
+        return False
+
+    logger.error(f"Did not expect type {type(is_identified)} for is_identified input")
+    raise TypeError
+
+
 def sanitise_data_frame(input_df: pd.DataFrame) -> pd.DataFrame:
     # Copy dataframe and convert blanks to nas
     input_df = input_df.copy().replace("", pd.NA)
@@ -461,7 +483,7 @@ def sanitise_data_frame(input_df: pd.DataFrame) -> pd.DataFrame:
     input_df["gender"] = input_df["gender"].apply(lambda x: Gender(x.lower()))
 
     # Check if identified column set, if not set, set to false
-    input_df["is_identified"] = input_df.apply(lambda x: x.is_identified
+    input_df["is_identified"] = input_df.apply(lambda x: is_identified_sample(x.is_identified)
                                                          if hasattr(x, "is_identified")
                                                          else False,
                                                axis="columns")