only created inpatient tokens for inpatient and er visits

src/cehrbert/data_generators/hf_data_generator/hf_dataset_mapping.py

@@ -30,6 +30,7 @@
     "Visit/61",
     "NUCC/315D00000X",
 ]
+ED_VISIT_TYPE_CODES = ["VISIT/ER"]
 DISCHARGE_FACILITY_TYPES = [
     "8536",
     "8863",
@@ -238,7 +239,11 @@ def transform(self, record: Dict[str, Any]) -> Dict[str, Any]:
 
             # We assume the first measurement to be the visit type of the current visit
             visit_type = visit["visit_type"]
-            is_inpatient = visit_type in INPATIENT_VISIT_TYPES or visit_type in INPATIENT_VISIT_TYPE_CODES
+            is_er_or_inpatient = (
+                visit_type in INPATIENT_VISIT_TYPES
+                or visit_type in INPATIENT_VISIT_TYPE_CODES
+                or visit_type in ED_VISIT_TYPE_CODES
+            )
 
             # Add artificial time tokens to the patient timeline if timedelta exists
             if time_delta:
@@ -283,32 +288,31 @@ def transform(self, record: Dict[str, Any]) -> Dict[str, Any]:
                 # Add a medical token to the patient timeline
                 # If this is an inpatient visit, we use the event time stamps to calculate age and date
                 # because the patient can stay in the hospital for a period of time.
-                if is_inpatient:
+                if is_er_or_inpatient:
                     # Calculate age using the event time stamp
                     age = relativedelta(e["time"], birth_datetime).years
                     # Calculate the week number since the epoch time
                     date = (e["time"] - datetime.datetime(year=1970, month=1, day=1)).days // 7
+                    # Calculate the time diff in days w.r.t the previous measurement
+                    meas_time_diff = (e["time"] - date_cursor).days
+                    # Update the date_cursor if the time diff between two neighboring measurements is greater than and
+                    # equal to 1 day
+                    if meas_time_diff > 0:
+                        date_cursor = e["time"]
+                        if self._inpatient_time_token_function:
+                            # This generates an artificial time token depending on the choice of the time token functions
+                            self._update_cehrbert_record(
+                                cehrbert_record,
+                                code=f"i-{self._inpatient_time_token_function(meas_time_diff)}",
+                                visit_concept_order=i + 1,
+                                visit_segment=visit_segment,
+                                visit_concept_id=visit_type,
+                            )
                 else:
                     # For outpatient visits, we use the visit time stamp to calculate age and time because we assume
                     # the outpatient visits start and end on the same day
                     pass
 
-                # Calculate the time diff in days w.r.t the previous measurement
-                meas_time_diff = (e["time"] - date_cursor).days
-                # Update the date_cursor if the time diff between two neighboring measurements is greater than and
-                # equal to 1 day
-                if meas_time_diff > 0:
-                    date_cursor = e["time"]
-                    if self._inpatient_time_token_function:
-                        # This generates an artificial time token depending on the choice of the time token functions
-                        self._update_cehrbert_record(
-                            cehrbert_record,
-                            code=f"i-{self._inpatient_time_token_function(meas_time_diff)}",
-                            visit_concept_order=i + 1,
-                            visit_segment=visit_segment,
-                            visit_concept_id=visit_type,
-                        )
-
                 # If numeric_value exists, this is a concept/value tuple, we indicate this using a concept_value_mask
                 numeric_value = e.get("numeric_value", None)
                 # The unit might be populated with a None value
@@ -338,7 +342,7 @@ def transform(self, record: Dict[str, Any]) -> Dict[str, Any]:
                     mlm_skip_value=concept_value_mask,
                 )
 
-            if is_inpatient:
+            if is_er_or_inpatient:
                 # If visit_end_datetime is populated for the inpatient visit, we update the date_cursor
                 visit_end_datetime = visit.get("visit_end_datetime", None)
                 if visit_end_datetime: