diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 6765c1bea40524..fa888c5967e7da 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -1,6 +1,6 @@
 # pylint: disable=E1101,E1103
 # pylint: disable=W0703,W0622,W0613,W0201
-from pandas.compat import range, text_type, zip, u
+from pandas.compat import range, text_type, zip, u, PY2
 from pandas import compat
 from functools import partial
 import itertools
@@ -923,19 +923,21 @@ def get_empty_Frame(data, sparse):
 
     number_of_cols = len(levels)
 
-    py2_prefix_sep_is_unicode = isinstance(prefix_sep, text_type)
-    if prefix is not None:
-        py2_prefix_is_unicode = isinstance(prefix, text_type)
-        dummy_cols = []
-        for level in levels:
-            fstr = '{prefix}{sep}{level}'
-            if py2_prefix_sep_is_unicode or py2_prefix_is_unicode or \
-               isinstance(level, text_type):
-                fstr = u(fstr)
-            dummy_cols.append(fstr.format(
-                prefix=prefix, sep=prefix_sep, level=level))
-    else:
+    if prefix is None:
         dummy_cols = levels
+    else:
+        def _make_col_name(prefix, prefix_sep, level):
+            fstr = '{prefix}{prefix_sep}{level}'
+            if PY2 and (isinstance(prefix, text_type) or
+                        isinstance(prefix_sep, text_type) or
+                        isinstance(level, text_type)):
+                fstr = u(fstr)
+            return fstr.format(prefix=prefix,
+                               prefix_sep=prefix_sep,
+                               level=level)
+
+        dummy_cols = [_make_col_name(prefix, prefix_sep, level)
+                      for level in levels]
 
     if isinstance(data, Series):
         index = data.index
diff --git a/pandas/tests/reshape/test_reshape.py b/pandas/tests/reshape/test_reshape.py
index 1dbe8f2ef7440a..3f4ccd7693a8f6 100644
--- a/pandas/tests/reshape/test_reshape.py
+++ b/pandas/tests/reshape/test_reshape.py
@@ -302,24 +302,22 @@ def test_dataframe_dummies_with_categorical(self, df, sparse, dtype):
         expected.sort_index(axis=1)
         assert_frame_equal(result, expected)
 
-    def test_dataframe_dummies_unicode(self):
-        df = pd.DataFrame(({u'ä': ['a']}))
-        result = get_dummies(df)
-        expected = pd.DataFrame({u'ä_a': [1]}, dtype=np.uint8)
-        assert_frame_equal(result, expected)
-
-        df = pd.DataFrame({'x': [u'ä']})
-        result = pd.get_dummies(df)
-        expected = pd.DataFrame({u'x_ä': [1]}, dtype=np.uint8)
-        assert_frame_equal(result, expected)
-
-        df = pd.DataFrame({'x': ['a']})
-        result = pd.get_dummies(df, prefix=u'ä')
-        expected = pd.DataFrame({u'ä_a': [1]}, dtype=np.uint8)
-        assert_frame_equal(result, expected)
-
-        result = pd.get_dummies(df, prefix_sep=u'ä')
-        expected = pd.DataFrame({u'xäa': [1]}, dtype=np.uint8)
+    @pytest.mark.parametrize('get_dummies_kwargs,expected', [
+        ({'data': pd.DataFrame(({u'ä': ['a']}))},
+         pd.DataFrame({u'ä_a': [1]}, dtype=np.uint8)),
+
+        ({'data': pd.DataFrame({'x': [u'ä']})},
+         pd.DataFrame({u'x_ä': [1]}, dtype=np.uint8)),
+
+        ({'data': pd.DataFrame({'x': [u'a']}), 'prefix':u'ä'},
+         pd.DataFrame({u'ä_a': [1]}, dtype=np.uint8)),
+
+        ({'data': pd.DataFrame({'x': [u'a']}), 'prefix_sep':u'ä'},
+         pd.DataFrame({u'xäa': [1]}, dtype=np.uint8))])
+    def test_dataframe_dummies_unicode(self, get_dummies_kwargs, expected):
+        # GH22084 pd.get_dummies incorrectly encodes unicode characters
+        # in dataframe column names
+        result = get_dummies(**get_dummies_kwargs)
         assert_frame_equal(result, expected)
 
     def test_basic_drop_first(self, sparse):