Skip to main content

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"

PyPI - Version PyPI - Python Version


Table of Contents

Installation

pip install dxitemspy

Examples

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.

Metadata

Release files for dxitemspy 0.0.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for dxitemspy 0.0.5
File Size Uploaded Provenance
dxitemspy-0.0.5.tar.gz 520.6 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for dxitemspy 0.0.5
File Interpreter ABI Platform
dxitemspy-0.0.5-py3-none-any.whl Python 3 none any Details

Total release size: 11.5 MB

Release files / dxitemspy-0.0.5.tar.gz

Download URL dxitemspy-0.0.5.tar.gz
Size 520.6 kB
Tags Source
SHA-256 checksum
How to use checksums
b0a7e0ace87a9fdcdc5acb3361ae551f33144e96d0a953963d191595f30db7dd
BLAKE2b-256 checksum
How to use checksums
6700d0bfadf4620ea95802375ce924b46f817881baf4d9946be59ab8245bb1bf
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via python-httpx/0.24.1

Release files / dxitemspy-0.0.5-py3-none-any.whl

Download URL dxitemspy-0.0.5-py3-none-any.whl
Size 11.0 MB
Tags Python 3
SHA-256 checksum
How to use checksums
7e7e206421faeab806daeb4878381eab3532151ddefedf37f19b2f9711e14917
BLAKE2b-256 checksum
How to use checksums
46bd8cce23605632f03db8db05d5178c4a6e0945df51fa7a26fa4287222e1647
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via python-httpx/0.24.1

Security for dxitemspy 0.0.5

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page