diff --git a/fhirflat/flat2fhir.py b/fhirflat/flat2fhir.py
index 977317e..a821199 100644
--- a/fhirflat/flat2fhir.py
+++ b/fhirflat/flat2fhir.py
@@ -251,6 +251,9 @@ def create_single_extension(k: str, v: dict | str | float | bool) -> dict:
             else:
                 raise e  # pragma: no cover
 
+        except KeyError:
+            continue
+
     raise RuntimeError(f"extension not created from {k, v}")  # pragma: no cover
 
 
diff --git a/fhirflat/ingest.py b/fhirflat/ingest.py
index 8969a67..3a911b3 100644
--- a/fhirflat/ingest.py
+++ b/fhirflat/ingest.py
@@ -5,6 +5,7 @@
 
 import argparse
 import hashlib
+import logging
 import os
 import shutil
 import timeit
@@ -25,6 +26,8 @@
 import fhirflat
 from fhirflat.util import get_local_resource, group_keys
 
+logger = logging.getLogger(__name__)
+
 # 1:1 (single row, single resource) mapping: Patient, Encounter
 # 1:M (single row, multiple resources) mapping: Observation, Condition, Procedure, ...
 
@@ -95,12 +98,12 @@ def find_field_value(
     return return_val
 
 
-def format_dates(date_str: str, date_format: str, timezone: str) -> str:
+def format_dates(date_str: str | float, date_format: str, timezone: str) -> str:
     """
     Converts dates into ISO8601 format with timezone information.
     """
 
-    if date_str is None:
+    if date_str is None or date_str is np.nan:
         return date_str
 
     new_tz = ZoneInfo(timezone)
@@ -124,7 +127,7 @@ def format_dates(date_str: str, date_format: str, timezone: str) -> str:
                 f"Date {date_str} could not be converted using date format"
                 f" {date_format}",
                 UserWarning,
-                stacklevel=2,
+                stacklevel=1,
             )
             return date_str
 
@@ -167,7 +170,7 @@ def create_dict_wide(
                     warnings.warn(
                         f"No mapping for column {column} response {response}",
                         UserWarning,
-                        stacklevel=2,
+                        stacklevel=1,
                     )
                     continue
             else:
@@ -261,11 +264,15 @@ def create_dict_long(
         except KeyError:
             # No mapping found for this column and response despite presence
             # in mapping file
-            warnings.warn(
-                f"No mapping for column {column} response {response}",
-                UserWarning,
-                stacklevel=2,
-            )
+            if response == 0.0:
+                # mostly this is ignoring unfilled responses
+                logger.info(f"No mapping for column {column} response {response}")
+            else:
+                warnings.warn(
+                    f"No mapping for column {column} response {response}",
+                    UserWarning,
+                    stacklevel=1,
+                )
             return None
     return None
 
@@ -329,7 +336,11 @@ def condense(x):
                 # If the column contains a single non-nan value, return it
                 non_nan_values = x.dropna()
                 if non_nan_values.nunique() == 1:
-                    return non_nan_values
+                    return (
+                        non_nan_values
+                        if len(non_nan_values) == 1
+                        else non_nan_values.unique()[0]
+                    )
                 elif non_nan_values.empty:
                     return np.nan
                 else:
@@ -337,6 +348,8 @@ def condense(x):
             else:
                 if len(x) == 1:
                     return x
+                elif x.nunique() == 1:
+                    return x.unique()[0]
                 else:
                     raise ValueError("Multiple values found in one-to-one mapping")
 
@@ -364,6 +377,13 @@ def condense(x):
 
     # Set multi-index for easier access
     map_df.set_index(["raw_variable", "raw_response"], inplace=True)
+    map_df.sort_index(inplace=True)  # for performance improvements
+
+    if not map_df.index.is_unique:
+        raise ValueError(
+            f"Mapping file for the {resource} resource has duplicate entries "
+            f"{map_df.index[map_df.index.duplicated()]}"
+        )
 
     # Generate the flat_like dictionary
     if one_to_one:
@@ -522,7 +542,7 @@ def convert_resource(
                 date_format=date_format,
                 timezone=timezone,
             )
-            if df is None:
+            if df is None or df.empty:
                 return None
         else:
             raise ValueError(f"Unknown mapping type {t}")
diff --git a/fhirflat/resources/diagnosticreport.py b/fhirflat/resources/diagnosticreport.py
index 8de5640..323326e 100644
--- a/fhirflat/resources/diagnosticreport.py
+++ b/fhirflat/resources/diagnosticreport.py
@@ -79,6 +79,7 @@ def cleanup(cls, data: dict) -> dict:
             {
                 "basedOn",
                 "subject",
+                "encounter",
                 "performer",
                 "resultsInterpreter",
                 "specimen",
diff --git a/fhirflat/resources/encounter.py b/fhirflat/resources/encounter.py
index 6270d75..65d4e65 100644
--- a/fhirflat/resources/encounter.py
+++ b/fhirflat/resources/encounter.py
@@ -14,8 +14,13 @@
 from pydantic.v1 import Field, validator
 
 from .base import FHIRFlatBase
-from .extension_types import relativePeriodType, timingPhaseDetailType, timingPhaseType
-from .extensions import relativePeriod, timingPhase, timingPhaseDetail
+from .extension_types import (
+    durationType,
+    relativePeriodType,
+    timingPhaseDetailType,
+    timingPhaseType,
+)
+from .extensions import Duration, relativePeriod, timingPhase, timingPhaseDetail
 
 JsonString: TypeAlias = str
 
@@ -26,6 +31,7 @@ class Encounter(_Encounter, FHIRFlatBase):
             relativePeriodType,
             timingPhaseType,
             timingPhaseDetailType,
+            durationType,
             fhirtypes.ExtensionType,
         ]
     ] = Field(
@@ -71,11 +77,10 @@ def validate_extension_contents(cls, extensions):
         rel_phase_count = sum(isinstance(item, relativePeriod) for item in extensions)
         timing_count = sum(isinstance(item, timingPhase) for item in extensions)
         detail_count = sum(isinstance(item, timingPhaseDetail) for item in extensions)
+        dur_count = sum(isinstance(item, Duration) for item in extensions)
 
-        if rel_phase_count > 1 or timing_count > 1 or detail_count > 1:
-            raise ValueError(
-                "relativePeriod, timingPhase and timingPhaseDetail can only appear once."  # noqa E501
-            )
+        if rel_phase_count > 1 or timing_count > 1 or detail_count > 1 or dur_count > 1:
+            raise ValueError("Each extension can only appear once.")
 
         if timing_count > 0 and detail_count > 0:
             raise ValueError(