Hierachical Condition Categories Python Package.
This module implements the Hierachical Condition Categories that are used for adjusting risks for the Medicare population. The original SAS implementation can be found here. Currently, hccpy supports CMS-HCC V22, V23, and V24 and HHS-HCC Year 2019.
NOTE: This package does not support for ICD-9. NOTE: The latest version is 0.1.1 - updated on 2021/10/17
Installing from the source:
$ git clone [email protected]:yubin-park/hccpy.git
$ cd hccpy
$ python setup.py develop
Or, simply using pip:
$ pip install hccpy
hccpy/: The package source code is located here.data/: The raw data files directly downloaded from the National Burequ of Economics Research- Here, you see the original SAS scripts and data files for the CMS HCC models.
_AGESEXV2.py: a Python re-write of theAGESEXV2.TXTSAS script._V2218O1M.py: a Python re-write of theV2218O1M.TXTSAS script._V2218O1P.py: a Python re-write of theV2219O1P.TXTSAS script._V22I0ED2.py: a Python re-write of theV22I0ED2.TXTSAS script._V2318P1M.py: a Python re-write of theV2318P1M.TXTSAS script._V2419P1M.py: a Python re-write of theV2419P1M.TXTSAS script.hcc.py: the main module that combines the various logical components for CMS-HCChhshcc.py: the main module for HHS-HCCutils.py: utility functions for reading data files
tests/: test scripts to check the validity of the outputs.LICENSE.txt: Apache 2.0.README.md: This README file.setup.py: a set-up script.
hccpy is really simple to use.
Please see some examples below:
To import the HCCEngine class from hccpy:
>>> import json
>>> from hccpy.hcc import HCCEngine
>>> he = HCCEngine()
>>> print(he.profile.__doc__)
Returns the HCC risk profile of a given patient information.
Parameters
----------
dx_lst : list of str
A list of ICD10 codes for the measurement year.
age : int or float
The age of the patient.
sex : str
The sex of the patient; {"M", "F"}
elig : str
The eligibility segment of the patient.
Allowed values are as follows:
- "CFA": Community Full Benefit Dual Aged
- "CFD": Community Full Benefit Dual Disabled
- "CNA": Community NonDual Aged
- "CND": Community NonDual Disabled
- "CPA": Community Partial Benefit Dual Aged
- "CPD": Community Partial Benefit Dual Disabled
- "INS": Long Term Institutional
- "NE": New Enrollee
- "SNPNE": SNP NE
orec: str
Original reason for entitlement code.
- "0": Old age and survivor's insurance
- "1": Disability insurance benefits
- "2": End-stage renal disease
- "3": Both DIB and ESRD
medicaid: bool
If the patient is in Medicaid or not.
>>>To get a HCC profile from a list of diagnosis codes (in ICD-10):
>>> rp = he.profile(["E1169", "I5030", "I509", "I211", "I209", "R05"])
>>> print(json.dumps(rp, indent=2))
{
"risk_score": 1.3139999999999998,
"details": {
"CNA_M70_74": 0.379,
"CNA_HCC85": 0.323,
"CNA_HCC88": 0.14,
"CNA_HCC18": 0.318,
"CNA_HCC85_gDiabetesMellit": 0.154,
"CNA_DIABETES_CHF": 0.0
},
"hcc_lst": [
"HCC85",
"HCC88",
"HCC18"
],
"hcc_map": {
"I5030": "HCC85",
"I209": "HCC88",
"E1169": "HCC18",
"I509": "HCC85"
},
"parameters": {
"age": 70,
"sex": "M",
"elig": "CNA",
"medicaid": false,
"disabled": 0,
"origds": 0
}
}
>>>If a member is new, then provide the elig="NE" in the input:
>>> rp = he.profile([], elig="NE", age=65)
>>> print(json.dumps(rp, indent=2))
{
"risk_score": 0.514,
"details": {
"NE_NMCAID_NORIGDIS_NEM65": 0.514
},
"hcc_lst": [],
"hcc_map": {},
"parameters": {
"age": 65,
"sex": "M",
"elig": "NE_NMCAID_NORIGDIS_NE",
"medicaid": false,
"disabled": 0,
"origds": 0
}
}
>>>If a member has a different eligibility status, change the eligibility as follows (e.g. institutionalized member):
>>> rp = he.profile(["E1169", "I5030", "I509", "I209"], elig="INS")
>>> print(json.dumps(rp, indent=2))
{
"risk_score": 2.6059999999999994,
"details": {
"INS_M70_74": 1.323,
"INS_HCC88": 0.497,
"INS_HCC18": 0.441,
"INS_HCC85": 0.191,
"INS_HCC85_gDiabetesMellit": 0.0,
"INS_DIABETES_CHF": 0.154
},
"hcc_lst": [
"HCC88",
"HCC18",
"HCC85"
],
"hcc_map": {
"I209": "HCC88",
"E1169": "HCC18",
"I509": "HCC85",
"I5030": "HCC85"
},
"parameters": {
"age": 70,
"sex": "M",
"elig": "INS",
"medicaid": false,
"disabled": 0,
"origds": 0
}
}To get the description, hierarchy parents and children of a HCC:
>>> hcc_doc = he.describe_hcc("HCC19") # either "HCC19", "hcc19" or "19"
>>> print(json.dumps(hcc_doc, indent=2))
{
"description": "Diabetes without Complication",
"children": [],
"parents": [
"HCC17",
"HCC18"
]
}Not all claims are eligible for risk adjustment. For professional claims, a certain set of CPT codes is required to be eligible, while for institutional claims, a certain set of bill types is needed. This module provides an easy interface for determining if a certain claim is eligible for risk adjustment or not.
NOTE: This function uses CPT codes, and this requires AMA CPT license. Once you carefully review the license, you need to download a data file.
>>> from hccpy.raeligible import RAEligible
>>> rae = RAEligible()
>>> rae.load(fn="CY2019Q2_CPTHCPCS_CMS_20190425.csv")
>>> rae.is_eligible(pr_lst=["C5271"])
True
>>> rae.is_eligible(pr_lst=["C5270"])
False
>>>NOTE: The data file (CY2019Q2_CPTHCPCS_CMS_20190425.csv) should be located in the same folder.
python -m build
twine upload dist/*
Apache 2.0
- Yubin Park @yubin-park
- Thomas Chen @t-kychen
- Matt Walker @mwalker14
- David Roberts @dr00b
- Kevin Buchan Jr. @kevinbuchanjr
- https://www.nber.org/data/cms-risk-adjustment.html
- https://www.cms.gov/medicare/health-plans/medicareadvtgspecratestats/risk-adjustors.html
- https://github.com/calyxhealth/pyriskadjust
- https://github.com/AlgorexHealth/hcc-python
- https://github.com/galtay/hcc_risk_models
- https://www.cms.gov/cciio/resources/forms-reports-and-other-resources/downloads/ra-march-31-white-paper-032416.pdf
- https://www.cms.gov/cciio/resources/regulations-and-guidance/index.html
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent