diff --git a/biasanalyzer/api.py b/biasanalyzer/api.py
index 57d947c..c7a59aa 100644
--- a/biasanalyzer/api.py
+++ b/biasanalyzer/api.py
@@ -40,7 +40,7 @@ def set_config(self, config_file_path: str):
             except ValidationError as ex:
                 notify_users(f"configuration yaml file is not valid with validation error: {ex}", level="error")
 
-    def set_root_omop(self):
+    def set_root_omop(self, read_only=True):
         if not self.config:
             notify_users(
                 "no valid configuration to set root OMOP CDM data. "
@@ -62,7 +62,7 @@ def set_root_omop(self):
             self.bias_db = BiasDatabase(":memory:", omop_db_url=db_url)
         elif db_type == "duckdb":
             db_path = self.config["root_omop_cdm_database"].get("database", ":memory:")
-            self.omop_cdm_db = OMOPCDMDatabase(db_path)
+            self.omop_cdm_db = OMOPCDMDatabase(db_path, read_only=read_only)
             self.bias_db = BiasDatabase(":memory:", omop_db_url=db_path)
         else:
             notify_users(f"Unsupported database type: {db_type}")
diff --git a/biasanalyzer/cohort.py b/biasanalyzer/cohort.py
index 979eac5..bd0968a 100644
--- a/biasanalyzer/cohort.py
+++ b/biasanalyzer/cohort.py
@@ -10,7 +10,7 @@
 from biasanalyzer.concept import ConceptHierarchy
 from biasanalyzer.config import load_cohort_creation_config
 from biasanalyzer.database import BiasDatabase, OMOPCDMDatabase
-from biasanalyzer.models import CohortDefinition, DOMAIN_MAPPING
+from biasanalyzer.models import DOMAIN_MAPPING, CohortDefinition
 from biasanalyzer.utils import clean_string, hellinger_distance, notify_users
 
 
@@ -60,7 +60,7 @@ def get_concept_stats(
         Get cohort concept statistics such as concept prevalence
         """
         if concept_type not in DOMAIN_MAPPING:
-            raise ValueError(f'input concept_type {concept_type} is not a valid concept type to get concept stats')
+            raise ValueError(f"input concept_type {concept_type} is not a valid concept type to get concept stats")
 
         cohort_stats = self.bias_db.get_cohort_concept_stats(
             self.cohort_id,
diff --git a/biasanalyzer/database.py b/biasanalyzer/database.py
index 44e75d1..5f18b3d 100644
--- a/biasanalyzer/database.py
+++ b/biasanalyzer/database.py
@@ -1,6 +1,5 @@
 # ruff: noqa: S608
 import gc
-import platform
 from datetime import datetime
 from typing import Optional
 
@@ -322,13 +321,13 @@ class OMOPCDMDatabase:
     _instance = None  # indicating a singleton with only one instance of the class ever created
     _database_type = None
 
-    def __new__(cls, *args, **kwargs):
+    def __new__(cls, db_url, read_only=True):
         if cls._instance is None:
             cls._instance = super().__new__(cls)
-            cls._instance._initialize(*args, **kwargs)  # Initialize only once
+            cls._instance._initialize(db_url, read_only=read_only)  # Initialize only once
         return cls._instance
 
-    def _initialize(self, db_url):
+    def _initialize(self, db_url, read_only=True):
         if db_url.endswith(".duckdb"):
             # close any potential global connections if any
             for obj in gc.get_objects():  # pragma: no cover
@@ -340,11 +339,8 @@ def _initialize(self, db_url):
 
             # Handle DuckDB connection
             try:
-                if platform.system().lower() == "windows":  # pragma: no cover
-                    # it is critical to set duckdb connection to be read-only on windows platform
-                    self.engine = duckdb.connect(db_url, read_only=True)
-                else:
-                    self.engine = duckdb.connect(db_url)
+                # it is critical to set duckdb connection to be read-only on windows and Mac platforms
+                self.engine = duckdb.connect(db_url, read_only=read_only)
                 notify_users(f"Connected to the DuckDB database: {db_url}.")
             except duckdb.Error as e:  # pragma: no cover
                 notify_users(f"Failed to connect to DuckDB: {e}", level="error")
@@ -573,4 +569,4 @@ def close(self):
         else:
             self.engine.dispose()  # pragma: no cover
         OMOPCDMDatabase._instance = None
-        notify_users("Connection to the OMOP CDM database closed.")
\ No newline at end of file
+        notify_users("Connection to the OMOP CDM database closed.")
diff --git a/poetry.lock b/poetry.lock
index 28cf8c9..1fa9bb1 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -12,9 +12,6 @@ files = [
     {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
 ]
 
-[package.dependencies]
-typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
-
 [[package]]
 name = "appnope"
 version = "0.1.4"
@@ -273,7 +270,7 @@ description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
-markers = "python_version <= \"3.10\""
+markers = "python_version < \"3.11\""
 files = [
     {file = "exceptiongroup-1.2.2-py3-none-any.whl", hash = "sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b"},
     {file = "exceptiongroup-1.2.2.tar.gz", hash = "sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc"},
@@ -635,7 +632,7 @@ description = "Fundamental package for array computing in Python"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "python_version < \"3.12\""
+markers = "python_version <= \"3.11\""
 files = [
     {file = "numpy-1.24.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c0bfb52d2169d58c1cdb8cc1f16989101639b34c7d3ce60ed70b19c63eba0b64"},
     {file = "numpy-1.24.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:ed094d4f0c177b1b8e7aa9cba7d6ceed51c0e569a5318ac0ca9a090680a6a1b1"},
@@ -728,71 +725,103 @@ files = [
 
 [[package]]
 name = "pandas"
-version = "2.0.3"
+version = "2.3.3"
 description = "Powerful data structures for data analysis, time series, and statistics"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "pandas-2.3.3-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2e3ebdb170b5ef78f19bfb71b0dc5dc58775032361fa188e814959b74d726dd5"},
+    {file = "pandas-2.3.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:d051c0e065b94b7a3cea50eb1ec32e912cd96dba41647eb24104b6c6c14c5788"},
+    {file = "pandas-2.3.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:3869faf4bd07b3b66a9f462417d0ca3a9df29a9f6abd5d0d0dbab15dac7abe87"},
+    {file = "pandas-2.3.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c503ba5216814e295f40711470446bc3fd00f0faea8a086cbc688808e26f92a2"},
+    {file = "pandas-2.3.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a637c5cdfa04b6d6e2ecedcb81fc52ffb0fd78ce2ebccc9ea964df9f658de8c8"},
+    {file = "pandas-2.3.3-cp39-cp39-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:854d00d556406bffe66a4c0802f334c9ad5a96b4f1f868adf036a21b11ef13ff"},
+    {file = "pandas-2.3.3-cp39-cp39-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bf1f8a81d04ca90e32a0aceb819d34dbd378a98bf923b6398b9a3ec0bf44de29"},
+    {file = "pandas-2.3.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:23ebd657a4d38268c7dfbdf089fbc31ea709d82e4923c5ffd4fbd5747133ce73"},
+    {file = "pandas-2.3.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:5554c929ccc317d41a5e3d1234f3be588248e61f08a74dd17c9eabb535777dc9"},
+    {file = "pandas-2.3.3-cp39-cp39-win_amd64.whl", hash = "sha256:d3e28b3e83862ccf4d85ff19cf8c20b2ae7e503881711ff2d534dc8f761131aa"},
+    {file = "pandas-2.3.3.tar.gz", hash = "sha256:e05e1af93b977f7eafa636d043f9f94c7ee3ac81af99c13508215942e64c993b"},
 ]
 
 [package.dependencies]
 numpy = [
-    {version = ">=1.20.3", markers = "python_version < \"3.10\""},
-    {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
-    {version = ">=1.21.0", markers = "python_version == \"3.10\""},
+    {version = ">=1.22.4", markers = "python_version < \"3.11\""},
+    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
+    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
-tzdata = ">=2022.1"
+tzdata = ">=2022.7"
 
 [package.extras]
-all = ["PyQt5 (>=5.15.1)", "SQLAlchemy (>=1.4.16)", "beautifulsoup4 (>=4.9.3)", "bottleneck (>=1.3.2)", "brotlipy (>=0.7.0)", "fastparquet (>=0.6.3)", "fsspec (>=2021.07.0)", "gcsfs (>=2021.07.0)", "html5lib (>=1.1)", "hypothesis (>=6.34.2)", "jinja2 (>=3.0.0)", "lxml (>=4.6.3)", "matplotlib (>=3.6.1)", "numba (>=0.53.1)", "numexpr (>=2.7.3)", "odfpy (>=1.4.1)", "openpyxl (>=3.0.7)", "pandas-gbq (>=0.15.0)", "psycopg2 (>=2.8.6)", "pyarrow (>=7.0.0)", "pymysql (>=1.0.2)", "pyreadstat (>=1.1.2)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)", "python-snappy (>=0.6.0)", "pyxlsb (>=1.0.8)", "qtpy (>=2.2.0)", "s3fs (>=2021.08.0)", "scipy (>=1.7.1)", "tables (>=3.6.1)", "tabulate (>=0.8.9)", "xarray (>=0.21.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=1.4.3)", "zstandard (>=0.15.2)"]
-aws = ["s3fs (>=2021.08.0)"]
-clipboard = ["PyQt5 (>=5.15.1)", "qtpy (>=2.2.0)"]
-compression = ["brotlipy (>=0.7.0)", "python-snappy (>=0.6.0)", "zstandard (>=0.15.2)"]
-computation = ["scipy (>=1.7.1)", "xarray (>=0.21.0)"]
-excel = ["odfpy (>=1.4.1)", "openpyxl (>=3.0.7)", "pyxlsb (>=1.0.8)", "xlrd (>=2.0.1)", "xlsxwriter (>=1.4.3)"]
-feather = ["pyarrow (>=7.0.0)"]
-fss = ["fsspec (>=2021.07.0)"]
-gcp = ["gcsfs (>=2021.07.0)", "pandas-gbq (>=0.15.0)"]
-hdf5 = ["tables (>=3.6.1)"]
-html = ["beautifulsoup4 (>=4.9.3)", "html5lib (>=1.1)", "lxml (>=4.6.3)"]
-mysql = ["SQLAlchemy (>=1.4.16)", "pymysql (>=1.0.2)"]
-output-formatting = ["jinja2 (>=3.0.0)", "tabulate (>=0.8.9)"]
-parquet = ["pyarrow (>=7.0.0)"]
-performance = ["bottleneck (>=1.3.2)", "numba (>=0.53.1)", "numexpr (>=2.7.1)"]
-plot = ["matplotlib (>=3.6.1)"]
-postgresql = ["SQLAlchemy (>=1.4.16)", "psycopg2 (>=2.8.6)"]
-spss = ["pyreadstat (>=1.1.2)"]
-sql-other = ["SQLAlchemy (>=1.4.16)"]
-test = ["hypothesis (>=6.34.2)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)"]
-xml = ["lxml (>=4.6.3)"]
+all = ["PyQt5 (>=5.15.9)", "SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)", "beautifulsoup4 (>=4.11.2)", "bottleneck (>=1.3.6)", "dataframe-api-compat (>=0.1.7)", "fastparquet (>=2022.12.0)", "fsspec (>=2022.11.0)", "gcsfs (>=2022.11.0)", "html5lib (>=1.1)", "hypothesis (>=6.46.1)", "jinja2 (>=3.1.2)", "lxml (>=4.9.2)", "matplotlib (>=3.6.3)", "numba (>=0.56.4)", "numexpr (>=2.8.4)", "odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "pandas-gbq (>=0.19.0)", "psycopg2 (>=2.9.6)", "pyarrow (>=10.0.1)", "pymysql (>=1.0.2)", "pyreadstat (>=1.2.0)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "qtpy (>=2.3.0)", "s3fs (>=2022.11.0)", "scipy (>=1.10.0)", "tables (>=3.8.0)", "tabulate (>=0.9.0)", "xarray (>=2022.12.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)", "zstandard (>=0.19.0)"]
+aws = ["s3fs (>=2022.11.0)"]
+clipboard = ["PyQt5 (>=5.15.9)", "qtpy (>=2.3.0)"]
+compression = ["zstandard (>=0.19.0)"]
+computation = ["scipy (>=1.10.0)", "xarray (>=2022.12.0)"]
+consortium-standard = ["dataframe-api-compat (>=0.1.7)"]
+excel = ["odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)"]
+feather = ["pyarrow (>=10.0.1)"]
+fss = ["fsspec (>=2022.11.0)"]
+gcp = ["gcsfs (>=2022.11.0)", "pandas-gbq (>=0.19.0)"]
+hdf5 = ["tables (>=3.8.0)"]
+html = ["beautifulsoup4 (>=4.11.2)", "html5lib (>=1.1)", "lxml (>=4.9.2)"]
+mysql = ["SQLAlchemy (>=2.0.0)", "pymysql (>=1.0.2)"]
+output-formatting = ["jinja2 (>=3.1.2)", "tabulate (>=0.9.0)"]
+parquet = ["pyarrow (>=10.0.1)"]
+performance = ["bottleneck (>=1.3.6)", "numba (>=0.56.4)", "numexpr (>=2.8.4)"]
+plot = ["matplotlib (>=3.6.3)"]
+postgresql = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "psycopg2 (>=2.9.6)"]
+pyarrow = ["pyarrow (>=10.0.1)"]
+spss = ["pyreadstat (>=1.2.0)"]
+sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)"]
+test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
+xml = ["lxml (>=4.9.2)"]
 
 [[package]]
 name = "parso"
@@ -883,6 +912,7 @@ files = [
     {file = "psycopg2-2.9.10-cp311-cp311-win_amd64.whl", hash = "sha256:0435034157049f6846e95103bd8f5a668788dd913a7c30162ca9503fdf542cb4"},
     {file = "psycopg2-2.9.10-cp312-cp312-win32.whl", hash = "sha256:65a63d7ab0e067e2cdb3cf266de39663203d38d6a8ed97f5ca0cb315c73fe067"},
     {file = "psycopg2-2.9.10-cp312-cp312-win_amd64.whl", hash = "sha256:4a579d6243da40a7b3182e0430493dbd55950c493d8c68f4eec0b302f6bbf20e"},
+    {file = "psycopg2-2.9.10-cp313-cp313-win_amd64.whl", hash = "sha256:91fd603a2155da8d0cfcdbf8ab24a2d54bca72795b90d2a3ed2b6da8d979dee2"},
     {file = "psycopg2-2.9.10-cp39-cp39-win32.whl", hash = "sha256:9d5b3b94b79a844a986d029eee38998232451119ad653aea42bb9220a8c5066b"},
     {file = "psycopg2-2.9.10-cp39-cp39-win_amd64.whl", hash = "sha256:88138c8dedcbfa96408023ea2b0c369eda40fe5d75002c0964c78f46f11fa442"},
     {file = "psycopg2-2.9.10.tar.gz", hash = "sha256:12ec0b40b0273f95296233e8750441339298e6a572f7039da5b260e3c8b60e11"},
@@ -1233,7 +1263,7 @@ description = "Fundamental algorithms for scientific computing in Python"
 optional = false
 python-versions = "<3.12,>=3.8"
 groups = ["main"]
-markers = "python_version < \"3.12\""
+markers = "python_version <= \"3.11\""
 files = [
     {file = "scipy-1.10.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e7354fd7527a4b0377ce55f286805b34e8c54b91be865bac273f527e1b839019"},
     {file = "scipy-1.10.1-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:4b3f429188c66603a1a5c549fb414e4d3bdc2a24792e061ffbd607d3d75fd84e"},
@@ -1453,7 +1483,7 @@ description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
-markers = "python_version <= \"3.10\""
+markers = "python_version < \"3.11\""
 files = [
     {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
     {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"},
@@ -1577,5 +1607,5 @@ files = [
 
 [metadata]
 lock-version = "2.1"
-python-versions = ">=3.8.10,<3.13"
-content-hash = "a588906e6e90991a51af15f24a95ed2841c834dc72b79872e843b54e889f56c5"
+python-versions = ">=3.9,<3.13"
+content-hash = "31223cf102fa64b291d8ddbff67377aa0e1c9a03368c30fa6d949b4486cee7a5"
diff --git a/pyproject.toml b/pyproject.toml
index 34f0901..7037a2b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,9 +10,9 @@ include = [
     {path = "biasanalyzer/sql_templates/*.sql", format=["sdist", "wheel"]}
 ]
 [tool.poetry.dependencies]
-python = ">=3.8.10,<3.13"
+python = ">=3.9,<3.13"
 duckdb = "^1.1.1"
-pandas = "2.0.3"
+pandas = "^2.1.4"
 
 scipy = [
     {version = ">=1.10.1,<1.11", markers = "python_version<'3.12'"},
diff --git a/scripts/ingest_csvs_to_omop_duckdb.py b/scripts/ingest_csvs_to_omop_duckdb.py
index 633ecc6..c77f4b8 100644
--- a/scripts/ingest_csvs_to_omop_duckdb.py
+++ b/scripts/ingest_csvs_to_omop_duckdb.py
@@ -11,45 +11,30 @@
 """
 
 import argparse
-import sys
 import csv
+import sys
 import time
 from pathlib import Path
 
 import duckdb
 
-
 FILENAME_STEM_TO_TABLE_NAME_MAPPING = {
     # 'demographics': 'person'
     # 'conditions': 'condition_occurrence'
     # 'drugs': 'drug_exposure'
     # 'procedures': 'procedure_occurrence'
     # 'visits': 'visit_occurrence'
-    'observations': 'observation'
+    "observations": "observation"
 }
 
 COLUMN_MAPPINGS = {
-    "person": {
-        "deid_pat_id": "person_id"
-    },
-    "condition_occurrence": {
-        "deid_pat_id": "person_id"
-    },
-    "drug_exposure": {
-        "deid_pat_id": "person_id"
-    },
-    "procedure_occurrence": {
-        "deid_pat_id": "person_id"
-    },
-    "visit_occurrence": {
-        "deid_pat_id": "person_id"
-    },
-    "observation": {
-        "deid_pat_id": "person_id"
-    },
-    "measurement": {
-        "deid_pat_id": "person_id"
-    },
+    "person": {"deid_pat_id": "person_id"},
+    "condition_occurrence": {"deid_pat_id": "person_id"},
+    "drug_exposure": {"deid_pat_id": "person_id"},
+    "procedure_occurrence": {"deid_pat_id": "person_id"},
+    "visit_occurrence": {"deid_pat_id": "person_id"},
+    "observation": {"deid_pat_id": "person_id"},
+    "measurement": {"deid_pat_id": "person_id"},
 }
 
 OMOP_TABLE_SCHEMAS = {
@@ -71,7 +56,7 @@
         "race_source_value",
         "race_source_concept_id",
         "ethnicity_source_value",
-        "ethnicity_source_concept_id"
+        "ethnicity_source_concept_id",
     ],
     "condition_occurrence": [
         "condition_occurrence_id",
@@ -89,9 +74,9 @@
         "visit_detail_id",
         "condition_source_value",
         "condition_source_concept_id",
-        "condition_status_source_value"
+        "condition_status_source_value",
     ],
-    'drug_exposure': [
+    "drug_exposure": [
         "drug_exposure_id",
         "person_id",
         "drug_concept_id",
@@ -114,9 +99,9 @@
         "drug_source_value",
         "drug_source_concept_id",
         "route_source_value",
-        "dose_unit_source_value"
+        "dose_unit_source_value",
     ],
-    'procedure_occurrence': [
+    "procedure_occurrence": [
         "procedure_occurrence_id",
         "person_id",
         "procedure_concept_id",
@@ -132,9 +117,9 @@
         "visit_detail_id",
         "procedure_source_value",
         "procedure_source_concept_id",
-        "modifier_source_value"
+        "modifier_source_value",
     ],
-    'visit_occurrence': [
+    "visit_occurrence": [
         "visit_occurrence_id",
         "person_id",
         "visit_concept_id",
@@ -151,9 +136,9 @@
         "admitted_from_source_value",
         "discharged_to_concept_id",
         "discharged_to_source_value",
-        "preceding_visit_occurrence_id"
+        "preceding_visit_occurrence_id",
     ],
-    'observation': [
+    "observation": [
         "observation_id",
         "person_id",
         "observation_concept_id",
@@ -174,28 +159,29 @@
         "qualifier_source_value",
         "value_source_value",
         "observation_event_id",
-        "obs_event_field_concept_id"
-    ]
+        "obs_event_field_concept_id",
+    ],
 }
 
+
 def load_csv_to_duckdb(con, csv_path: Path, table_name: str):
     """Load a single CSV file into DuckDB."""
     t0 = time.time()
     print(f"loading {table_name} from {csv_path}")
 
     # read and normalize header
-    with open(csv_path, "r", newline="") as f:
+    with open(csv_path, newline="") as f:
         reader = csv.reader(f)
         raw_header = next(reader)
 
     # normalize: lower case + strip quotes/spaces
-    raw_header = [h.strip().replace('"', '') for h in raw_header]
+    raw_header = [h.strip().replace('"', "") for h in raw_header]
     header = [h.lower() for h in raw_header]
-    print(f'normalized header: {header}')
+    print(f"normalized header: {header}")
 
     mapping = COLUMN_MAPPINGS.get(table_name, {})
     final_cols = [mapping.get(col, col) for col in header]
-    print(f'mapped header: {final_cols}')
+    print(f"mapped header: {final_cols}")
 
     expected = OMOP_TABLE_SCHEMAS.get(table_name, [])
     final_set = set(final_cols)
@@ -209,7 +195,7 @@ def load_csv_to_duckdb(con, csv_path: Path, table_name: str):
     extra = final_set - set(expected)
     if extra:
         print(f"WARNING: Extra columns in CSV for {table_name}: {sorted(extra)}")
-        print(f"Extra columns will NOT be ingested.")
+        print("Extra columns will NOT be ingested.")
 
     select_clauses = []
     for orig, new in zip(raw_header, final_cols):
@@ -217,7 +203,7 @@ def load_csv_to_duckdb(con, csv_path: Path, table_name: str):
             # skip extra columns entirely
             continue
         if orig != new:
-            select_clauses.append(f'{orig} AS {new}')
+            select_clauses.append(f"{orig} AS {new}")
         else:
             select_clauses.append(orig)
 
@@ -268,9 +254,13 @@ def main():
         required=False,
         help="Directory containing OMOP vocabulary CSVs (concept, concept_relationship, etc.)",
     )
-    parser.add_argument("--output", type=Path,
-                        default=Path("Y:/OMOP_duckdb/omop.duckdb"),
-                        required=False, help="Output DuckDB file path")
+    parser.add_argument(
+        "--output",
+        type=Path,
+        default=Path("Y:/OMOP_duckdb/omop.duckdb"),
+        required=False,
+        help="Output DuckDB file path",
+    )
 
     args = parser.parse_args()
 
diff --git a/tests/conftest.py b/tests/conftest.py
index e71d1ed..c377057 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -273,7 +273,7 @@ def test_db():
 
     # mock configuration file
     bias = BIAS(config_file_path=config_file)
-    bias.set_root_omop()
+    bias.set_root_omop(read_only=False)
 
     yield bias  # Provide the connection to the test
 
diff --git a/tests/query_based/test_cohort_creation.py b/tests/query_based/test_cohort_creation.py
index 45c349c..e2fa59a 100644
--- a/tests/query_based/test_cohort_creation.py
+++ b/tests/query_based/test_cohort_creation.py
@@ -86,10 +86,10 @@ def test_cohort_creation_baseline(caplog, test_db):
 
     patient_ids = set([item["subject_id"] for item in cohort.data])
     assert_equal(len(patient_ids), 5)
-    assert_equal(patient_ids, {'106', '108', '110', '111', '112'})
+    assert_equal(patient_ids, {"106", "108", "110", "111", "112"})
     # select two patients to check for cohort_start_date and cohort_end_date automatically computed
-    patient_106 = next(item for item in cohort.data if item["subject_id"] == '106')
-    patient_108 = next(item for item in cohort.data if item["subject_id"] == '108')
+    patient_106 = next(item for item in cohort.data if item["subject_id"] == "106")
+    patient_108 = next(item for item in cohort.data if item["subject_id"] == "108")
 
     # Replace dates with actual values from your test data
     assert_equal(
@@ -127,7 +127,7 @@ def test_cohort_creation_study(test_db):
     assert cohort.data is not None, "Cohort creation wrongly returned None data"
     patient_ids = set([item["subject_id"] for item in cohort.data])
     assert_equal(len(patient_ids), 4)
-    assert_equal(patient_ids, {'108', '110', '111', '112'})
+    assert_equal(patient_ids, {"108", "110", "111", "112"})
 
 
 def test_cohort_creation_study2(caplog, test_db):
@@ -155,7 +155,7 @@ def test_cohort_creation_study2(caplog, test_db):
     assert cohort.data is not None, "Cohort creation wrongly returned None data"
     patient_ids = set([item["subject_id"] for item in cohort.data])
     assert_equal(len(patient_ids), 1)
-    assert_equal(patient_ids, {'106'})
+    assert_equal(patient_ids, {"106"})
 
 
 def test_cohort_creation_all(caplog, test_db):
@@ -191,7 +191,7 @@ def test_cohort_creation_all(caplog, test_db):
     patient_ids = set([item["subject_id"] for item in cohort.data])
     print(f"patient_ids: {patient_ids}", flush=True)
     assert_equal(len(patient_ids), 2)
-    assert_equal(patient_ids, {'108', '110'})
+    assert_equal(patient_ids, {"108", "110"})
 
 
 def test_cohort_creation_multiple_temporary_groups_with_no_operator(test_db):
@@ -214,7 +214,7 @@ def test_cohort_creation_multiple_temporary_groups_with_no_operator(test_db):
     patient_ids = set([item["subject_id"] for item in cohort.data])
     print(f"patient_ids: {patient_ids}", flush=True)
     assert_equal(len(patient_ids), 2)
-    assert_equal(patient_ids, {'108', '110'})
+    assert_equal(patient_ids, {"108", "110"})
 
 
 def test_cohort_creation_mixed_domains(test_db):
@@ -242,7 +242,7 @@ def test_cohort_creation_mixed_domains(test_db):
     patient_ids = set([item["subject_id"] for item in cohort.data])
     print(f"patient_ids: {patient_ids}", flush=True)
     assert_equal(len(patient_ids), 3)
-    assert_equal(patient_ids, {'1', '2', '6'})
+    assert_equal(patient_ids, {"1", "2", "6"})
     start_dates = [item["cohort_start_date"] for item in cohort.data]
     assert_equal(len(start_dates), 3)
     assert_equal(start_dates, [datetime.date(2020, 6, 1), datetime.date(2020, 6, 1), datetime.date(2018, 1, 1)])
@@ -356,10 +356,10 @@ def test_cohort_creation_negative_instance(test_db):
 
     patient_ids = set([item["subject_id"] for item in cohort.data])
     assert_equal(len(patient_ids), 6)  # Female patients 1, 2, 3, 5
-    assert_equal(patient_ids, {'1', '2', '3', '5', '6', '7'})
+    assert_equal(patient_ids, {"1", "2", "3", "5", "6", "7"})
 
     # Verify dates for a specific patient (e.g., patient 1 with last diabetes diagnosis)
-    patient_1 = next(item for item in cohort.data if item["subject_id"] == '1')
+    patient_1 = next(item for item in cohort.data if item["subject_id"] == "1")
     assert_equal(
         patient_1["cohort_start_date"],
         datetime.date(2020, 6, 1),
@@ -392,10 +392,10 @@ def test_cohort_creation_offset(test_db):
 
     patient_ids = set([item["subject_id"] for item in cohort.data])
     assert_equal(len(patient_ids), 6)  # Female patients 1, 2, 3, 5
-    assert_equal(patient_ids, {'1', '2', '3', '5', '6', '7'})
+    assert_equal(patient_ids, {"1", "2", "3", "5", "6", "7"})
 
     # Verify dates for a specific patient (e.g., patient 1 with offset)
-    patient_1 = next(item for item in cohort.data if item["subject_id"] == '1')
+    patient_1 = next(item for item in cohort.data if item["subject_id"] == "1")
     # Diabetes on 2020-06-01: -730 days = 2018-06-02, +180 days = 2020-11-28
     assert_equal(
         patient_1["cohort_start_date"],
@@ -435,10 +435,10 @@ def test_cohort_creation_negative_instance_offset(test_db):
 
     patient_ids = set([item["subject_id"] for item in cohort.data])
     assert_equal(len(patient_ids), 6)
-    assert_equal(patient_ids, {'1', '2', '3', '5', '6', '7'})
+    assert_equal(patient_ids, {"1", "2", "3", "5", "6", "7"})
 
     # Verify dates for a specific patient (e.g., patient 1 with last diabetes and offset)
-    patient_1 = next(item for item in cohort.data if item["subject_id"] == '1')
+    patient_1 = next(item for item in cohort.data if item["subject_id"] == "1")
     # Last diabetes on 2020-06-01: +180 days = 2020-11-28
     assert_equal(
         patient_1["cohort_start_date"],
diff --git a/tests/query_based/test_hierarchical_prevalence.py b/tests/query_based/test_hierarchical_prevalence.py
index 4541883..e9a4099 100644
--- a/tests/query_based/test_hierarchical_prevalence.py
+++ b/tests/query_based/test_hierarchical_prevalence.py
@@ -1,7 +1,6 @@
 import pytest
-from numpy.ma.testutils import assert_equal
-
 from biasanalyzer.concept import ConceptHierarchy
+from numpy.ma.testutils import assert_equal
 
 
 def test_cohort_concept_hierarchical_prevalence(test_db, caplog):
@@ -28,7 +27,7 @@ def test_cohort_concept_hierarchical_prevalence(test_db, caplog):
 
     # test the cohort does not have procedure_occurrence related concepts
     cohort_stat, _ = cohort.get_concept_stats(concept_type="procedure_occurrence")
-    assert_equal(cohort_stat, {'procedure_occurrence': []})
+    assert_equal(cohort_stat, {"procedure_occurrence": []})
 
     concept_stats, _ = cohort.get_concept_stats(vocab="ICD10CM", print_concept_hierarchy=True)
     assert concept_stats is not None, "Failed to fetch concept stats"
diff --git a/tests/test_database.py b/tests/test_database.py
index 97ab8a8..9901331 100644
--- a/tests/test_database.py
+++ b/tests/test_database.py
@@ -168,8 +168,9 @@ def test_get_cohort_concept_stats_handles_exception(caplog):
     db = BiasDatabase(":memory:")
     db.omop_cdm_db_url = "duckdb"
     qry_builder = CohortQueryBuilder(cohort_creation=False)
+
     with pytest.raises(ValueError):
-        db.get_cohort_concept_stats(123, qry_builder)
+        db.get_cohort_concept_stats(123, qry_builder, concept_type="dummy")
 
 
 def test_get_cohort_attributes_handles_exception():