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        "description": "# hcuppy \n\nA Python package for [H-CUP Tools and Software](https://www.hcup-us.ahrq.gov/tools_software.jsp).\nThe modules implemented in this package are as follows:\n- \"[CCS (Clinical Classification Software)](https://www.hcup-us.ahrq.gov/toolssoftware/ccs10/ccs10.jsp)\" converts ICD-10 diagnosis and procedure codes to clinically meaningful groups\n- \"[CCI (Chronic Condition Indicator)](https://www.hcup-us.ahrq.gov/toolssoftware/chronic_icd10/chronic_icd10.jsp)\" identifies chronic conditions from ICD-10 diagnosis codes\n- \"[Elixhauser Comordibity Index](https://www.hcup-us.ahrq.gov/toolssoftware/comorbidityicd10/comorbidity_icd10.jsp)\" calculates both readmission and mortality risks using a set of ICD-10 diagnosis codes\n- \"[Procedure Classes](https://www.hcup-us.ahrq.gov/toolssoftware/procedureicd10/procedure_icd10.jsp)\" identify if a given ICD-10 procedure code is Minor/Major Diagnosis/Therapeutic\n- \"[Utilization Flags](https://www.hcup-us.ahrq.gov/toolssoftware/utilflagsicd10/utilflag_icd10.jsp)\" identify if a combination of UB40 revenue codes and ICD-10 procedure codes indicates (or implies) a certain resource utilization e.g. Intensive Care Unit, Ultrasound, X-Ray, etc.\n- \"[Surgery Flags](https://www.hcup-us.ahrq.gov/toolssoftware/surgflags/surgeryflags.jsp)\" identify if a CPT code is a surgery related or not. *NOTE that, to use this module, users must agree to an additional license agreement with the AMA for using CPT codes [here](https://www.hcup-us.ahrq.gov/toolssoftware/surgflags/surgeryflags_license.jsp)*.\n\nNOTE that this package does not support for ICD-9.\n\n## Installing\n\nInstalling from the source:\n```\n$ git clone git@github.com:yubin-park/hcuppy.git\n$ cd hcuppy\n$ python setup.py develop\n```\n\nOr, simply using `pip`:\n```\n$ pip install hcuppy\n```\n\n## File Structure\n- `hcuppy/`: The package source code is located here.\n  - `data/`: The raw data files downloaded from the H-CUP website.\n  - `ccs.py`: a module for CCS\n  - `cci.py`: a module for CCI\n  - `elixhauser.py`: a module for Elixhauser Comorbidity Index\n  - `prcls.py`: a module for Procedure Class\n  - `uflag.py`: a module for Utilization Flags\n  - `sflag.py`: a module for Surgery Flags\n  - `utils.py`: utility functions for reading data files.\n- `tests/`: test scripts to check the validity of the outputs.\n- `LICENSE.txt`: Apache 2.0.\n- `README.md`: This README file.\n- `setup.py`: a set-up script.\n\n## Code Examples\n`hcuppy` is really simple to use. \nPlease see some examples below.\nNOTE that all functions used below have docstrings. \nIf you want to see the input parameter specifications,\nplease type `print(<instance>.<function>.__doc__)`.\n\n### Using CCS\n```python\n>>> import json\n>>> from hcuppy.ccs import CCSEngine\n>>> ce = CCSEngine(mode=\"dx\")\n>>> out = ce.get_ccs([\"E119\", \"I10\"])\n>>> print(json.dumps(out, indent=2))\n[\n  {\n    \"ccs\": \"49\",\n    \"ccs_desc\": \"Diabetes mellitus without complication\",\n    \"ccs_lv1\": \"3\",\n    \"ccs_lv1_desc\": \"Endocrine; nutritional; and metabolic diseases and immunity disorders\",\n    \"ccs_lv2\": \"3.2\",\n    \"ccs_lv2_desc\": \"Diabetes mellitus without complication [49.]\"\n  },\n  {\n    \"ccs\": \"98\",\n    \"ccs_desc\": \"Essential hypertension\",\n    \"ccs_lv1\": \"7\",\n    \"ccs_lv1_desc\": \"Diseases of the circulatory system\",\n    \"ccs_lv2\": \"7.1\",\n    \"ccs_lv2_desc\": \"Hypertension\"\n  }\n]\n>>>\n```\n\n### Using CCI\n```python\n>>> from hcuppy.cci import CCIEngine\n>>> ce = CCIEngine()\n>>> out = ce.get_cci([\"E119\"])\n>>> print(json.dumps(out, indent=2))\n[\n  {\n    \"is_chronic\": true,\n    \"body_system\": \"3\",\n    \"body_system_desc\": \"Endocrine, nutritional, and metabolic diseases and immunity disorders\"\n  }\n]\n```\n\n### Using Elixhauser Comorbidity Index\n```python\n>>> from hcuppy.elixhauser import ElixhauserEngine\n>>> ee = ElixhauserEngine()\n>>> out = ee.get_elixhauser([\"E119\", \"E108\", \"I10\", \"I110\", \"Z944\"])\n>>> print(json.dumps(out, indent=2))\n{\n  \"cmrbdt_lst\": [\n    \"LIVER\",\n    \"DMCX\",\n    \"HTNCX\",\n    \"CHF\"\n  ],\n  \"rdmsn_scr\": 31,\n  \"mrtlt_scr\": 9\n}\n>>>\n```\n\n### Using Procedure Class\n```python\n>>> from hcuppy.prcls import PrClsEngine\n>>> pce = PrClsEngine()\n>>> out = pce.get_prcls([\"B231Y0Z\"])\n>>> print(json.dumps(out, indent=2))\n[\n  {\n    \"class\": \"1\",\n    \"desc\": \"Minor Diagnostic\"\n  }\n]\n>>>\n```\n\n### Using Utilization Flag\n```python\n>>> from hcuppy.uflag import UFlagEngine\n>>> ufe = UFlagEngine()\n>>> out = ufe.get_uflag(rev_lst=[\"0380\"], pr_lst=[\"BB0DZZZ\"])\n>>> print(json.dumps(out, indent=2))\n[\n  \"Blood\",\n  \"Chest X-Ray\"\n]\n>>>\n```\n\nPlease refer to the test scripts under the `tests/` folder if you want to see other example use cases.\n\n## License\nApache 2.0\n\n## Authors\nYubin Park, PhD\n\n## References\n- https://www.hcup-us.ahrq.gov/\n- https://www.hcup-us.ahrq.gov/tools_software.jsp\n- https://cran.r-project.org/web/packages/comorbidity/vignettes/comorbidityscores.html\n- https://github.com/modusdatascience/ccs\n\n\n\n\n\n\n\n\n",
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