diff --git a/monai/transforms/utility/dictionary.py b/monai/transforms/utility/dictionary.py
index 3e8fecd691..dd4fd381d9 100644
--- a/monai/transforms/utility/dictionary.py
+++ b/monai/transforms/utility/dictionary.py
@@ -730,10 +730,11 @@ def __call__(self, data):
 
         """
         d = dict(data)
-        for new_key in self.names:
-            if new_key in d:
-                raise KeyError(f"Key {new_key} already exists in data.")
-            for key in self.key_iterator(d):
+        key_len = len(self.keys)
+        for i in range(self.times):
+            for key, new_key in self.key_iterator(d, self.names[i * key_len : (i + 1) * key_len]):
+                if new_key in d:
+                    raise KeyError(f"Key {new_key} already exists in data.")
                 if isinstance(d[key], torch.Tensor):
                     d[new_key] = d[key].detach().clone()
                 else:
diff --git a/tests/test_copy_itemsd.py b/tests/test_copy_itemsd.py
index e3133ae4f8..a0a1ad412b 100644
--- a/tests/test_copy_itemsd.py
+++ b/tests/test_copy_itemsd.py
@@ -31,12 +31,12 @@
 class TestCopyItemsd(unittest.TestCase):
     @parameterized.expand([TEST_CASE_1, TEST_CASE_2, TEST_CASE_3, TEST_CASE_4])
     def test_numpy_values(self, keys, times, names):
-        input_data = {"img": np.array([[0, 1], [1, 2]]), "seg": np.array([[0, 1], [1, 2]])}
+        input_data = {"img": np.array([[0, 1], [1, 2]]), "seg": np.array([[3, 4], [4, 5]])}
         result = CopyItemsd(keys=keys, times=times, names=names)(input_data)
         for name in ensure_tuple(names):
             self.assertTrue(name in result)
-            result[name] += 1
-            np.testing.assert_allclose(result[name], np.array([[1, 2], [2, 3]]))
+        result["img_1"] += 1
+        np.testing.assert_allclose(result["img_1"], np.array([[1, 2], [2, 3]]))
         np.testing.assert_allclose(result["img"], np.array([[0, 1], [1, 2]]))
 
     def test_tensor_values(self):