dxitemspy
This package is a Python implementation of DXI, "DXI Mappings V2021P1 from Ellis, Randall P, Heather E Hsu, Jeffrey J Siracuse, Allan Walkey, Karen E Lasser, Brian C Jacobson, Corinne Andriola, Alexander Hoagland, Ying Liu, Chenlu Song, Tzu-Chun Kuo, and Arlene S Ash. “Development and Assessment of a New Framework for Disease Surveillance, Prediction and Risk Adjustment: The Diagnostic Items Classification System.” JAMA Health Forum. 2022; 3(3): e220276. doi:10.1001/jamahealthforum.2022.0276"
Table of Contents
Installation
pip install dxitemspyExamples
Note that this package assumes that you have appropriately collected all valid ICD10-CM codes.
When you have the codes, prepare those into a list structure. That's the only parameter needed.
% python
>>> from pprint import pprint
>>> from dxitemspy.dxitems import DXIEngine
>>> de = DXIEngine()
>>> out = de.get_dxi(["E089", "I10"])
>>> pprint(out)
{'dx2dxi': {'E089': ['END',
'DXI1_END006',
'HIER_END001',
'HIER_END002',
'HIER_END003',
'HIER_END004',
'CCSR_END002',
'CCSR_END006'],
'I10': ['CIR', 'DXI1_CIR002', 'HIER_CIR001', 'CCSR_CIR007']},
'labels': ['CCSR_END006',
'HIER_END004',
'CCSR_CIR007',
'CCSR_END002',
'HIER_END003',
'DXI1_END006',
'CIR',
'HIER_END002',
'END',
'HIER_CIR001',
'HIER_END001',
'DXI1_CIR002'],
'labels_info': {'CCSR_CIR007': {'ch_abbrev': 'CCSR',
'has_default_coeff': True,
'label': 'Essential hypertension',
'level': 1,
'score': 298.36,
'system': 'CCSR'},
'CCSR_END002': {'ch_abbrev': 'CCSR',
'has_default_coeff': True,
'label': 'Diabetes mellitus without '
'complication',
'level': 1,
'score': 1992.61,
'system': 'CCSR'},
'CCSR_END006': {'ch_abbrev': 'CCSR',
'has_default_coeff': True,
'label': 'Diabetes mellitus, due to '
'underlying condition, drug or '
'chemical induced, or other '
'specified type',
'level': 1,
'score': -2351.11,
'system': 'CCSR'},
'DXI1_CIR002': {'ch_abbrev': 'CIR',
'label': 'Essential_hypertension',
'level': 1,
'system': 'DXI'},
'DXI1_END006': {'ch_abbrev': 'END',
'has_default_coeff': True,
'label': 'Diabetes_mellitus_secondary',
'level': 1,
'score': 4274.95,
'system': 'DXI'},
'HIER_CIR001': {'ch_abbrev': 'CIR',
'label': 'CIR_Hyperten',
'level': 0},
'HIER_END001': {'ch_abbrev': 'END',
'label': 'END_DM_Type_1',
'level': 0},
'HIER_END002': {'ch_abbrev': 'END',
'label': 'END_DM_Type_2',
'level': 0},
'HIER_END003': {'ch_abbrev': 'END',
'label': 'END_DM_Drug_Chem',
'level': 0},
'HIER_END004': {'ch_abbrev': 'END',
'label': 'END_DM_Other',
'level': 0}},
'score': 4274.95}You can use the labels to construct a new feature matrix for other risk models.
The score uses the default coefficients used in the original paper. The score should be indicative of a concurrent estimation of annual spend.
References
License
Please note that the original code sets are published under Creative Commons.
dxitemspy is distributed under the terms of the MIT license, but its contents are subject to CC as well.
