ccbhc-measurements 2025.2.15

An easy way to calculate CCBHC measurements.

CCBHC Measurements

Table of Contents

• Purpose
• Currently Supported Measurements
• Code Demonstration
• De-panda-cies
• License
• Installation
• Contributors
• Contributions and Discussions

Purpose

All CCBHCs are required to report Quality Measurements. The goal of this package is to simplify the process for calculating CCBHC measurements for all CCBHCs.

Our code is simple:

1. Import the Measurement you want to calculate.
2. Give it the required data (downloaded excel reports from your EHR, query data from SQL, or whatever)
3. Run get_all_submeasures(). Under the hood, get_all_submeasures() determines which data meets the Measurments criteria and which does not.
4. Export your data to your preferred tool for analysis. If you want to keep it in pandas, you already have it. If you want to use Excel, or Power BI, you can export it there as well!

Currently Supported Measurements

• DEP REM 6 - Depression Remission at Six Months - Dep Rem 6 Required Data Input and Output Diagram

The definition for these Measurements can be at https://www.samhsa.gov/sites/default/files/ccbhc-quality-measures-technical-specifications-manual.pdf
At the moment we only have these Measurements, but more will be added in the future. Check out the Contributions and Discussions section.

Code Demonstration

import pandas as pd
import ccbhc_measurements as ccbhc

- Step 1: Load in the data into Pandas Dataframes

all_inclusive_excel_file = r"../file/path/to/Dep Rem Data.xlsx"
phq_data = pd.read_xlsx(all_inclusive_excel_file, sheet_name = "phq9")
diagnosis_data = pd.read_xlsx(all_inclusive_excel_file, sheet_name = "diagnosis")
demographic_data = pd.read_xlsx(all_inclusive_excel_file, sheet_name = "demographic")
insurance_data = pd.read_xlsx(all_inclusive_excel_file, sheet_name = "insurance")

- Step 2: Ensure that the dataframes follows the correct schema

Dep Rem 6 Required Data Input and Output Diagram

phq_data = phq_data[["patient_id","patient_DOB","encounter_id","encounter_datetime","total_score"]].copy()
diagnosis_data = diagnosis_data[["patient_id","encounter_datetime","diagnosis"]].copy()
demographic_data = demographic_data[["patient_id","race","ethnicity"]].copy()
insurance_data = insurance_data[["patient_id","insurance","start_datetime","end_datetime"]].copy()

- Step 3: Calculate Dep-Rem

submeasure_data = [phq_data,diagnosis_data,demographic_data,insurance_data]
measure = ccbhc.Dep_Rem(submeasure_data)
results = measure.get_all_submeasures()s
for name, data in results.items():
    data.to_excel(name+".xlsx", index=False)

De-panda-cies

• pandas - Powerful data structures for data analysis, time series, and statistics
• python-dateutil - Extensions to the standard Python datetime module
• pytz - Brings the Olson tz database into Python which allows accurate and cross platform timezone calculations

License

CC BY-NC-SA 4.0

Installation

The source code is currently hosted on GitHub at: https://github.com/Pesach-Tikvah-Hope-Development-Inc/CCBHC_Measurements

Binary installers for the latest released version are available at the Python Package Index (PyPI)

# PyPI
pip install ccbhc-measurements

Contributors

• Alex Gursky
• Yisroel Len

Contributions and Discussions

Feel free to add and create you own Measurements. All Measurements should follow this uml.

Send us your recomendations, bugs, questions or feedback at [e-mail]

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