From 539077fbc6bae67efe8285891b88df94c39c9fa3 Mon Sep 17 00:00:00 2001
From: iabaako <iabaako@poverty-action.org>
Date: Sun, 4 Oct 2026 09:04:41 +0100
Subject: [PATCH 1/4] fix(backchecks): join backcheck dates on the backcheck
 KEY

_add_date_columns joined the backcheck date on the survey KEY, which differs
from the backcheck KEY in normal projects, so backcheck dates and the
"Avg Days" statistics were empty. Join on `{survey_key}__BCCL`, falling back
to survey_key when it is also the merge ID.

Closes #300

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 CHANGELOG.md                              |  4 ++
 src/datasure/checks/backchecks/compute.py | 15 ++--
 tests/checks/backchecks/test_compute.py   | 87 +++++++++++++++++++++++
 3 files changed, 102 insertions(+), 4 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index cce6456a..b602cedc 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -97,6 +97,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   and `backcheck_target_percent`, and the target is saved under
   `backcheck_target_percent` so it reloads in later sessions. Targets saved
   under the old `backcheck_goal` key were never applied and are ignored — #299
+- **Backcheck dates**: `_add_date_columns` joined backcheck dates on the survey
+  KEY, so when survey and backcheck KEYs differed the dates and the "Avg Days"
+  statistics were empty. Backcheck dates now join on the backcheck KEY
+  (`{survey_key}__BCCL`) — #300
 - **Correction log schema**: Removing the last correction entry now leaves an
   empty log with the full schema, including status columns — #296
 - **Constraint violations**: A value past a hard bound was reported as a soft
diff --git a/src/datasure/checks/backchecks/compute.py b/src/datasure/checks/backchecks/compute.py
index d63a094c..5590d590 100644
--- a/src/datasure/checks/backchecks/compute.py
+++ b/src/datasure/checks/backchecks/compute.py
@@ -743,12 +743,19 @@ def _add_date_columns(
         ).unique(subset=[survey_key])
         result = result.join(survey_dates, on=survey_key, how="left")
 
-    # Add backcheck date
+    # Add backcheck date, joining on the backcheck KEY. The analysis only lacks
+    # it when survey_key is the merge ID, which then matches both datasets.
     if backcheck_date and backcheck_date in backcheck_data.columns:
+        backcheck_key = f"{survey_key}__BCCL"
+        if backcheck_key not in result.columns:
+            backcheck_key = survey_key
         bc_dates = backcheck_data.select(
-            [survey_key, pl.col(backcheck_date).alias("backcheck_date_col")]
-        ).unique(subset=[survey_key])
-        result = result.join(bc_dates, on=survey_key, how="left")
+            [
+                pl.col(survey_key).alias(backcheck_key),
+                pl.col(backcheck_date).alias("backcheck_date_col"),
+            ]
+        ).unique(subset=[backcheck_key])
+        result = result.join(bc_dates, on=backcheck_key, how="left")
 
     return result
 
diff --git a/tests/checks/backchecks/test_compute.py b/tests/checks/backchecks/test_compute.py
index 0940f042..faf6cc29 100644
--- a/tests/checks/backchecks/test_compute.py
+++ b/tests/checks/backchecks/test_compute.py
@@ -2095,6 +2095,93 @@ def test_add_date_columns():
     assert "backcheck_date_col" in result.columns
 
 
+def test_add_date_columns_distinct_survey_and_backcheck_keys():
+    """Backcheck dates join on the backcheck KEY when it differs from the survey KEY."""
+    analysis = pl.DataFrame(
+        {
+            "key": ["s-1", "s-2"],
+            "key__BCCL": ["b-1", "b-2"],
+            "column_name": ["age", "age"],
+        }
+    )
+    survey_data = pl.DataFrame(
+        {
+            "key": ["s-1", "s-2"],
+            "survey_date": [date(2024, 1, 1), date(2024, 1, 2)],
+        }
+    )
+    backcheck_data = pl.DataFrame(
+        {
+            "key": ["b-1", "b-2"],
+            "backcheck_date": [date(2024, 1, 5), date(2024, 1, 9)],
+        }
+    )
+
+    result = _add_date_columns(
+        analysis, survey_data, backcheck_data, "key", "survey_date", "backcheck_date"
+    )
+
+    assert result["backcheck_date_col"].to_list() == [
+        date(2024, 1, 5),
+        date(2024, 1, 9),
+    ]
+    assert _calculate_average_days(result, "survey_date", "backcheck_date") == 5.5
+
+
+@pytest.mark.parametrize("staff_type", ["enumerator", "backchecker"])
+def test_stats_avg_days_with_distinct_survey_and_backcheck_keys(staff_type):
+    """Avg Days uses each backcheck's own date when the two datasets' KEYs differ."""
+    survey_data = pl.DataFrame(
+        {
+            "key": ["s-1", "s-2"],
+            "sid": ["A", "B"],
+            "enum": ["E1", "E1"],
+            "sdate": [date(2024, 1, 1), date(2024, 1, 1)],
+            "age": [25, 30],
+        }
+    )
+    backcheck_data = pl.DataFrame(
+        {
+            "key": ["b-1", "b-2"],
+            "sid": ["A", "B"],
+            "bcer": ["B1", "B1"],
+            "bdate": [date(2024, 1, 3), date(2024, 1, 5)],
+            "age": [25, 31],
+        }
+    )
+    settings = BackcheckSettings(
+        survey_key="key",
+        survey_id="sid",
+        survey_date="sdate",
+        backcheck_date="bdate",
+        enumerator="enum",
+        backchecker="bcer",
+    )
+    col_settings = pl.DataFrame(
+        {
+            "search_type": ["exact"],
+            "pattern": ["age"],
+            "column_name": [["age"]],
+            "category": [1],
+            "ok_range_type": [None],
+            "ok_range_values": [None],
+            "ttest": [False],
+            "prtest": [False],
+            "signrank": [False],
+            "reliability": [False],
+        }
+    )
+    analysis = compute_backcheck_analysis(
+        survey_data, backcheck_data, settings, col_settings
+    )
+
+    result = compute_enumerator_backchecker_stats(
+        survey_data, backcheck_data, analysis, settings, staff_type
+    )
+
+    assert result["Avg Days"].to_list() == [3.0]
+
+
 def test_calculate_average_days():
     """Test _calculate_average_days."""
     staff_data = pl.DataFrame(

From 258ffa2162d91fab12fa71bdc762e59155b6ad74 Mon Sep 17 00:00:00 2001
From: iabaako <iabaako@poverty-action.org>
Date: Sun, 4 Oct 2026 09:06:49 +0100
Subject: [PATCH 2/4] fix(backchecks): skip backcheck dates when backcheck data
 has no KEY

The fallback join selected survey_key from the backcheck data even when it
was missing there, raising ColumnNotFoundError. Skip the backcheck date in
that case, and correct the comment on when `{survey_key}__BCCL` is absent.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 src/datasure/checks/backchecks/compute.py | 11 ++++++++---
 tests/checks/backchecks/test_compute.py   | 14 ++++++++++++++
 2 files changed, 22 insertions(+), 3 deletions(-)

diff --git a/src/datasure/checks/backchecks/compute.py b/src/datasure/checks/backchecks/compute.py
index 5590d590..8f9c6c76 100644
--- a/src/datasure/checks/backchecks/compute.py
+++ b/src/datasure/checks/backchecks/compute.py
@@ -743,9 +743,14 @@ def _add_date_columns(
         ).unique(subset=[survey_key])
         result = result.join(survey_dates, on=survey_key, how="left")
 
-    # Add backcheck date, joining on the backcheck KEY. The analysis only lacks
-    # it when survey_key is the merge ID, which then matches both datasets.
-    if backcheck_date and backcheck_date in backcheck_data.columns:
+    # Add backcheck date, joining on the backcheck KEY ({survey_key}__BCCL).
+    # The merge only adds that column when both datasets have survey_key; if
+    # survey_key is also the merge ID, it is shared and the join uses it as is.
+    if (
+        backcheck_date
+        and backcheck_date in backcheck_data.columns
+        and survey_key in backcheck_data.columns
+    ):
         backcheck_key = f"{survey_key}__BCCL"
         if backcheck_key not in result.columns:
             backcheck_key = survey_key
diff --git a/tests/checks/backchecks/test_compute.py b/tests/checks/backchecks/test_compute.py
index faf6cc29..c42c9dbf 100644
--- a/tests/checks/backchecks/test_compute.py
+++ b/tests/checks/backchecks/test_compute.py
@@ -2128,6 +2128,20 @@ def test_add_date_columns_distinct_survey_and_backcheck_keys():
     assert _calculate_average_days(result, "survey_date", "backcheck_date") == 5.5
 
 
+def test_add_date_columns_backcheck_data_without_key():
+    """Backcheck dates are skipped, not a crash, when backcheck data has no KEY."""
+    analysis = pl.DataFrame({"key": ["s-1"], "column_name": ["age"]})
+    survey_data = pl.DataFrame({"key": ["s-1"], "survey_date": [date(2024, 1, 1)]})
+    backcheck_data = pl.DataFrame({"sid": ["A"], "backcheck_date": [date(2024, 1, 5)]})
+
+    result = _add_date_columns(
+        analysis, survey_data, backcheck_data, "key", "survey_date", "backcheck_date"
+    )
+
+    assert "survey_date_col" in result.columns
+    assert "backcheck_date_col" not in result.columns
+
+
 @pytest.mark.parametrize("staff_type", ["enumerator", "backchecker"])
 def test_stats_avg_days_with_distinct_survey_and_backcheck_keys(staff_type):
     """Avg Days uses each backcheck's own date when the two datasets' KEYs differ."""

From 5035a04d4d9c8ce52bdc0dab1929cc08045fc3e4 Mon Sep 17 00:00:00 2001
From: iabaako <iabaako@poverty-action.org>
Date: Sun, 4 Oct 2026 09:22:55 +0100
Subject: [PATCH 3/4] refactor(backchecks): share the backcheck-KEY join and
 suffix constant

Add BACKCHECK_SUFFIX and merged_backcheck_name() in models.py and use them
for every "__BCCL" in compute.py and report_ui.py. Extract
_join_backcheck_columns, which resolves the backcheck KEY (falling back to
survey_key when it is the merge ID) and skips missing columns, and use it for
both the backchecker staff join and the backcheck date join.
_join_staff_information no longer takes a join_key.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 src/datasure/checks/backchecks/compute.py   | 98 +++++++++++++--------
 src/datasure/checks/backchecks/models.py    | 10 +++
 src/datasure/checks/backchecks/report_ui.py |  3 +-
 tests/checks/backchecks/test_compute.py     | 23 +++--
 4 files changed, 92 insertions(+), 42 deletions(-)

diff --git a/src/datasure/checks/backchecks/compute.py b/src/datasure/checks/backchecks/compute.py
index 8f9c6c76..ddfd98d4 100644
--- a/src/datasure/checks/backchecks/compute.py
+++ b/src/datasure/checks/backchecks/compute.py
@@ -8,10 +8,12 @@
 from scipy import stats
 
 from datasure.checks.backchecks.models import (
+    BACKCHECK_SUFFIX,
     TAB_NAME,
     WEEKDAY_OFFSET_TO_NUMERIC,
     BackcheckSettings,
     SearchType,
+    merged_backcheck_name,
 )
 from datasure.utils.settings_utils import load_check_settings
 
@@ -317,7 +319,7 @@ def _process_backcheck_column(
     if col not in merged_data.columns:
         return None
 
-    backcheck_col = f"{col}__BCCL"
+    backcheck_col = merged_backcheck_name(col)
     if backcheck_col not in merged_data.columns:
         return None
 
@@ -453,7 +455,7 @@ def compute_backcheck_analysis(
         backcheck_for_merge,
         on=survey_id,
         how="inner",
-        suffix="__BCCL",
+        suffix=BACKCHECK_SUFFIX,
     )
 
     if merged_data.is_empty():
@@ -656,7 +658,7 @@ def _get_staff_configuration(
     else:  # backchecker
         staff_col = backcheck_settings.backchecker
         data_source = backcheck_data
-        join_key = f"{survey_key}__BCCL"
+        join_key = merged_backcheck_name(survey_key)
 
     if not staff_col or staff_col not in data_source.columns:
         return None
@@ -664,12 +666,54 @@ def _get_staff_configuration(
     return staff_col, data_source, join_key
 
 
+def _join_backcheck_columns(
+    analysis: pl.DataFrame,
+    backcheck_data: pl.DataFrame,
+    survey_key: str,
+    columns: dict[str, str],
+) -> pl.DataFrame:
+    """Left-join backcheck columns onto the analysis by backcheck KEY.
+
+    The analysis holds the backcheck KEY as `{survey_key}__BCCL`. The merge only
+    adds that column when both datasets have `survey_key`; if `survey_key` is
+    also the merge ID it is shared, and the join uses `survey_key` as is.
+
+    Parameters
+    ----------
+    analysis : pl.DataFrame
+        Backcheck analysis results.
+    backcheck_data : pl.DataFrame
+        Backcheck dataset.
+    survey_key : str
+        Survey key column name.
+    columns : dict[str, str]
+        Backcheck columns to add, mapped to their names in the result.
+
+    Returns
+    -------
+    pl.DataFrame
+        Analysis with the columns added, or unchanged if the backcheck data
+        lacks `survey_key` or any of the columns.
+    """
+    if any(col not in backcheck_data.columns for col in [survey_key, *columns]):
+        return analysis
+
+    backcheck_key = merged_backcheck_name(survey_key)
+    if backcheck_key not in analysis.columns:
+        backcheck_key = survey_key
+
+    backcheck_info = backcheck_data.select(
+        pl.col(survey_key).alias(backcheck_key),
+        *(pl.col(col).alias(alias) for col, alias in columns.items()),
+    ).unique(subset=[backcheck_key])
+    return analysis.join(backcheck_info, on=backcheck_key, how="left")
+
+
 def _join_staff_information(
     backcheck_analysis: pl.DataFrame,
     data_source: pl.DataFrame,
     staff_col: str,
     survey_key: str,
-    join_key: str,
     staff_type: str,
 ) -> pl.DataFrame:
     """Join backcheck analysis with staff information.
@@ -684,8 +728,6 @@ def _join_staff_information(
         Staff column name.
     survey_key : str
         Survey key column name.
-    join_key : str
-        Key to join on.
     staff_type : str
         Either "enumerator" or "backchecker".
 
@@ -694,14 +736,13 @@ def _join_staff_information(
     pl.DataFrame
         Analysis joined with staff information.
     """
-    staff_info = data_source.select([survey_key, staff_col]).unique(subset=[survey_key])
-
-    if staff_type == "enumerator":
-        return backcheck_analysis.join(staff_info, on=survey_key, how="left")
+    if staff_type == "backchecker":
+        return _join_backcheck_columns(
+            backcheck_analysis, data_source, survey_key, {staff_col: staff_col}
+        )
 
-    # For backcheckers, rename survey_key to match backcheck key
-    staff_info = staff_info.rename({survey_key: join_key})
-    return backcheck_analysis.join(staff_info, on=join_key, how="left")
+    staff_info = data_source.select([survey_key, staff_col]).unique(subset=[survey_key])
+    return backcheck_analysis.join(staff_info, on=survey_key, how="left")
 
 
 def _add_date_columns(
@@ -743,24 +784,11 @@ def _add_date_columns(
         ).unique(subset=[survey_key])
         result = result.join(survey_dates, on=survey_key, how="left")
 
-    # Add backcheck date, joining on the backcheck KEY ({survey_key}__BCCL).
-    # The merge only adds that column when both datasets have survey_key; if
-    # survey_key is also the merge ID, it is shared and the join uses it as is.
-    if (
-        backcheck_date
-        and backcheck_date in backcheck_data.columns
-        and survey_key in backcheck_data.columns
-    ):
-        backcheck_key = f"{survey_key}__BCCL"
-        if backcheck_key not in result.columns:
-            backcheck_key = survey_key
-        bc_dates = backcheck_data.select(
-            [
-                pl.col(survey_key).alias(backcheck_key),
-                pl.col(backcheck_date).alias("backcheck_date_col"),
-            ]
-        ).unique(subset=[backcheck_key])
-        result = result.join(bc_dates, on=backcheck_key, how="left")
+    # Add backcheck date
+    if backcheck_date:
+        result = _join_backcheck_columns(
+            result, backcheck_data, survey_key, {backcheck_date: "backcheck_date_col"}
+        )
 
     return result
 
@@ -995,7 +1023,7 @@ def compute_enumerator_backchecker_stats(
 
     # Join analysis with staff information
     analysis_with_staff = _join_staff_information(
-        backcheck_analysis, data_source, staff_col, survey_key, join_key, staff_type
+        backcheck_analysis, data_source, staff_col, survey_key, staff_type
     )
 
     # Add date columns
@@ -1337,7 +1365,7 @@ def _build_select_columns(
     ]
 
     # Include backcheck key if it exists in the data
-    backcheck_key = f"{survey_key}__BCCL"
+    backcheck_key = merged_backcheck_name(survey_key)
     if backcheck_key in data.columns:
         select_cols.insert(1, pl.col(backcheck_key))
 
@@ -1448,8 +1476,8 @@ def _are_columns_numeric(
     bool
         True if both columns are numeric.
     """
-    # Remove __BCCL suffix from backcheck column for schema lookup
-    backcheck_col_original = backcheck_col.replace("__BCCL", "")
+    # Remove the backcheck suffix from the column for schema lookup
+    backcheck_col_original = backcheck_col.removesuffix(BACKCHECK_SUFFIX)
     return (
         data.schema[survey_col].is_numeric()
         and data.schema[backcheck_col_original].is_numeric()
diff --git a/src/datasure/checks/backchecks/models.py b/src/datasure/checks/backchecks/models.py
index 59704427..dbc7e9de 100644
--- a/src/datasure/checks/backchecks/models.py
+++ b/src/datasure/checks/backchecks/models.py
@@ -6,6 +6,16 @@
 
 TAB_NAME: str = "backchecks"
 
+# Suffix the survey/backcheck merge adds to backcheck columns whose names
+# clash with survey columns, e.g. the backcheck KEY becomes "KEY__BCCL".
+BACKCHECK_SUFFIX: str = "__BCCL"
+
+
+def merged_backcheck_name(col: str) -> str:
+    """Return the merged-data name of backcheck column `col`."""
+    return f"{col}{BACKCHECK_SUFFIX}"
+
+
 # Weekday constants for productivity analysis
 WEEKDAY_NAMES = [
     "Monday",
diff --git a/src/datasure/checks/backchecks/report_ui.py b/src/datasure/checks/backchecks/report_ui.py
index 0e81dc44..a653fd69 100644
--- a/src/datasure/checks/backchecks/report_ui.py
+++ b/src/datasure/checks/backchecks/report_ui.py
@@ -22,6 +22,7 @@
     OkRangeType,
     OkRangeValues,
     SearchType,
+    merged_backcheck_name,
 )
 from datasure.checks.backchecks.settings_ui import backchecks_report_settings
 from datasure.utils.dataframe_utils import ColumnByType
@@ -1447,7 +1448,7 @@ def _render_backcheck_comparison_results(
     # Extract settings
     survey_key = backcheck_settings.survey_key
     survey_id = backcheck_settings.survey_id
-    backcheck_key = f"{survey_key}__BCCL"
+    backcheck_key = merged_backcheck_name(survey_key)
 
     # Get available columns from backcheck_analysis
     available_columns = sorted(
diff --git a/tests/checks/backchecks/test_compute.py b/tests/checks/backchecks/test_compute.py
index c42c9dbf..bdf97194 100644
--- a/tests/checks/backchecks/test_compute.py
+++ b/tests/checks/backchecks/test_compute.py
@@ -27,6 +27,7 @@
     _get_column_data_type,
     _get_staff_configuration,
     _get_test_value,
+    _join_backcheck_columns,
     _join_staff_information,
     _perform_statistical_tests,
     _prepare_data_for_merge,
@@ -2054,13 +2055,23 @@ def test_join_staff_information():
     )
 
     result = _join_staff_information(
-        analysis, survey_data, "staff", "survey_id", "survey_id", "enumerator"
+        analysis, survey_data, "staff", "survey_id", "enumerator"
     )
 
     assert "staff" in result.columns
     assert len(result) == 2
 
 
+def test_join_backcheck_columns_survey_key_is_merge_id():
+    """With no backcheck KEY column in the analysis, join on the shared survey_key."""
+    analysis = pl.DataFrame({"sid": ["A", "B"], "column_name": ["age", "age"]})
+    backcheck_data = pl.DataFrame({"sid": ["A", "B"], "bcer": ["B1", "B2"]})
+
+    result = _join_backcheck_columns(analysis, backcheck_data, "sid", {"bcer": "bcer"})
+
+    assert result["bcer"].to_list() == ["B1", "B2"]
+
+
 def test_add_date_columns():
     """Test _add_date_columns."""
     analysis = pl.DataFrame(
@@ -2756,15 +2767,15 @@ def test_process_backcheck_column_backcheck_col_missing():
 
 
 def test_join_staff_information_backchecker_path():
-    """_join_staff_information renames survey_key to join_key for backcheckers."""
-    analysis = pl.DataFrame({"key": [1, 2], "bc_key": [10, 20]})
-    data_source = pl.DataFrame({"key": [1, 2], "staff": ["a", "b"]})
+    """_join_staff_information joins backcheckers on the backcheck KEY."""
+    analysis = pl.DataFrame({"key": [1, 2], "key__BCCL": [10, 20]})
+    data_source = pl.DataFrame({"key": [20, 10], "staff": ["b", "a"]})
 
     result = _join_staff_information(
-        analysis, data_source, "staff", "key", "bc_key", "backchecker"
+        analysis, data_source, "staff", "key", "backchecker"
     )
 
-    assert "staff" in result.columns
+    assert result["staff"].to_list() == ["a", "b"]
 
 
 def test_add_date_columns_no_dates():

From 6914ec40aa9715dbd7af7af56062943df4fe8911 Mon Sep 17 00:00:00 2001
From: iabaako <iabaako@poverty-action.org>
Date: Sun, 4 Oct 2026 19:30:43 +0100
Subject: [PATCH 4/4] fix(backchecks): compute backchecker stats when
 survey_key is the merge ID

compute_enumerator_backchecker_stats required `{survey_key}__BCCL` in the
analysis before joining, but the merge adds no such column when survey_key
is also survey_id, so backchecker stats were always empty and the
_join_backcheck_columns fallback was unreachable. Drop the pre-join check
and return empty only when the join could not add the staff column.
_get_staff_configuration no longer returns or needs a join key.

Addresses Copilot review on #319.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 CHANGELOG.md                              |  3 +-
 src/datasure/checks/backchecks/compute.py | 24 +++---
 tests/checks/backchecks/test_compute.py   | 99 +++++++++++++++++++----
 3 files changed, 93 insertions(+), 33 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index b602cedc..c40b4a6b 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -100,7 +100,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - **Backcheck dates**: `_add_date_columns` joined backcheck dates on the survey
   KEY, so when survey and backcheck KEYs differed the dates and the "Avg Days"
   statistics were empty. Backcheck dates now join on the backcheck KEY
-  (`{survey_key}__BCCL`) — #300
+  (`{survey_key}__BCCL`). Backchecker statistics were also always empty when
+  the survey KEY was the merge ID; they are now computed — #300
 - **Correction log schema**: Removing the last correction entry now leaves an
   empty log with the full schema, including status columns — #296
 - **Constraint violations**: A value past a hard bound was reported as a soft
diff --git a/src/datasure/checks/backchecks/compute.py b/src/datasure/checks/backchecks/compute.py
index ddfd98d4..fcde2265 100644
--- a/src/datasure/checks/backchecks/compute.py
+++ b/src/datasure/checks/backchecks/compute.py
@@ -629,8 +629,7 @@ def _get_staff_configuration(
     survey_data: pl.DataFrame,
     backcheck_data: pl.DataFrame,
     backcheck_settings: BackcheckSettings,
-    survey_key: str,
-) -> tuple[str, pl.DataFrame, str] | None:
+) -> tuple[str, pl.DataFrame] | None:
     """Get staff column configuration based on staff type.
 
     Parameters
@@ -643,27 +642,23 @@ def _get_staff_configuration(
         Backcheck dataset.
     backcheck_settings : BackcheckSettings
         Backcheck settings.
-    survey_key : str
-        Survey key column name.
 
     Returns
     -------
-    tuple[str, pl.DataFrame, str] | None
-        Tuple of (staff_col, data_source, join_key) if valid, None otherwise.
+    tuple[str, pl.DataFrame] | None
+        Tuple of (staff_col, data_source) if valid, None otherwise.
     """
     if staff_type == "enumerator":
         staff_col = backcheck_settings.enumerator
         data_source = survey_data
-        join_key = survey_key
     else:  # backchecker
         staff_col = backcheck_settings.backchecker
         data_source = backcheck_data
-        join_key = merged_backcheck_name(survey_key)
 
     if not staff_col or staff_col not in data_source.columns:
         return None
 
-    return staff_col, data_source, join_key
+    return staff_col, data_source
 
 
 def _join_backcheck_columns(
@@ -1010,21 +1005,20 @@ def compute_enumerator_backchecker_stats(
 
     # Get staff configuration
     staff_config = _get_staff_configuration(
-        staff_type, survey_data, backcheck_data, backcheck_settings, survey_key
+        staff_type, survey_data, backcheck_data, backcheck_settings
     )
     if staff_config is None:
         return pl.DataFrame()
 
-    staff_col, data_source, join_key = staff_config
-
-    # Check if join key exists in analysis
-    if join_key not in backcheck_analysis.columns:
-        return pl.DataFrame()
+    staff_col, data_source = staff_config
 
     # Join analysis with staff information
     analysis_with_staff = _join_staff_information(
         backcheck_analysis, data_source, staff_col, survey_key, staff_type
     )
+    # The backchecker join is skipped when the backcheck data has no survey_key
+    if staff_col not in analysis_with_staff.columns:
+        return pl.DataFrame()
 
     # Add date columns
     analysis_with_staff = _add_date_columns(
diff --git a/tests/checks/backchecks/test_compute.py b/tests/checks/backchecks/test_compute.py
index bdf97194..ebf0fc51 100644
--- a/tests/checks/backchecks/test_compute.py
+++ b/tests/checks/backchecks/test_compute.py
@@ -652,9 +652,7 @@ def test_compute_enumerator_backchecker_stats_backchecker(
         col_settings,
     )
 
-    # Check that analysis has the backcheck key column
     assert not analysis.is_empty()
-    backcheck_key = f"{sample_backcheck_settings.survey_key}__BCCL"
 
     result = compute_enumerator_backchecker_stats(
         sample_survey_data_pl,
@@ -664,14 +662,8 @@ def test_compute_enumerator_backchecker_stats_backchecker(
         "backchecker",
     )
 
-    # The result might be empty if the backcheck key is not properly set up
-    # Check if backcheck key exists in analysis before asserting non-empty result
-    if backcheck_key in analysis.columns:
-        assert not result.is_empty()
-        assert "backchecker" in result.columns
-    else:
-        # If backcheck key is not in analysis, the result will be empty
-        assert result.is_empty()
+    assert not result.is_empty()
+    assert "backchecker" in result.columns
 
 
 def test_compute_enumerator_backchecker_stats_empty_analysis(
@@ -2012,13 +2004,12 @@ def test_get_staff_configuration_enumerator(
         sample_survey_data_pl,
         sample_backcheck_data_pl,
         sample_backcheck_settings,
-        "survey_id",
     )
 
     assert result is not None
-    staff_col, _, join_key = result
+    staff_col, data_source = result
     assert staff_col == "enumerator"
-    assert join_key == "survey_id"
+    assert data_source is sample_survey_data_pl
 
 
 def test_get_staff_configuration_backchecker(
@@ -2030,13 +2021,12 @@ def test_get_staff_configuration_backchecker(
         sample_survey_data_pl,
         sample_backcheck_data_pl,
         sample_backcheck_settings,
-        "survey_id",
     )
 
     assert result is not None
-    staff_col, _, join_key = result
+    staff_col, data_source = result
     assert staff_col == "backchecker"
-    assert join_key == "survey_id__BCCL"
+    assert data_source is sample_backcheck_data_pl
 
 
 def test_join_staff_information():
@@ -2207,6 +2197,82 @@ def test_stats_avg_days_with_distinct_survey_and_backcheck_keys(staff_type):
     assert result["Avg Days"].to_list() == [3.0]
 
 
+def _age_column_settings() -> pl.DataFrame:
+    return pl.DataFrame(
+        {
+            "search_type": ["exact"],
+            "pattern": ["age"],
+            "column_name": [["age"]],
+            "category": [1],
+            "ok_range_type": [None],
+            "ok_range_values": [None],
+            "ttest": [False],
+            "prtest": [False],
+            "signrank": [False],
+            "reliability": [False],
+        }
+    )
+
+
+def test_backchecker_stats_when_survey_key_is_merge_id():
+    """Backchecker stats are computed when survey_key is also the merge ID."""
+    survey_data = pl.DataFrame(
+        {
+            "sid": ["A", "B"],
+            "enum": ["E1", "E1"],
+            "sdate": [date(2024, 1, 1), date(2024, 1, 1)],
+            "age": [25, 30],
+        }
+    )
+    backcheck_data = pl.DataFrame(
+        {
+            "sid": ["A", "B"],
+            "bcer": ["B1", "B1"],
+            "bdate": [date(2024, 1, 3), date(2024, 1, 5)],
+            "age": [25, 31],
+        }
+    )
+    settings = BackcheckSettings(
+        survey_key="sid",
+        survey_id="sid",
+        survey_date="sdate",
+        backcheck_date="bdate",
+        enumerator="enum",
+        backchecker="bcer",
+    )
+    analysis = compute_backcheck_analysis(
+        survey_data, backcheck_data, settings, _age_column_settings()
+    )
+
+    result = compute_enumerator_backchecker_stats(
+        survey_data, backcheck_data, analysis, settings, "backchecker"
+    )
+
+    assert result["bcer"].to_list() == ["B1"]
+    assert result["Mismatches (Total)"].to_list() == [1]
+    assert result["Avg Days"].to_list() == [3.0]
+
+
+def test_backchecker_stats_empty_when_backcheck_data_has_no_survey_key():
+    """Backchecker stats are empty when the backcheck data lacks survey_key."""
+    survey_data = pl.DataFrame(
+        {"key": ["s-1", "s-2"], "sid": ["A", "B"], "age": [25, 30]}
+    )
+    backcheck_data = pl.DataFrame(
+        {"sid": ["A", "B"], "bcer": ["B1", "B1"], "age": [25, 31]}
+    )
+    settings = BackcheckSettings(survey_key="key", survey_id="sid", backchecker="bcer")
+    analysis = compute_backcheck_analysis(
+        survey_data, backcheck_data, settings, _age_column_settings()
+    )
+
+    result = compute_enumerator_backchecker_stats(
+        survey_data, backcheck_data, analysis, settings, "backchecker"
+    )
+
+    assert result.is_empty()
+
+
 def test_calculate_average_days():
     """Test _calculate_average_days."""
     staff_data = pl.DataFrame(
@@ -2629,7 +2695,6 @@ def test_get_staff_configuration_missing_staff_col(
         sample_survey_data_pl,
         sample_backcheck_data_pl,
         settings,
-        "survey_id",
     )
 
     assert result is None