{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "clinical_codes.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOfVne59Pd6mKkj2ylQyFCz",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/lisatwyw/data-gym/blob/master/clinical_codes.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5yhDXmRSs1es",
        "colab_type": "text"
      },
      "source": [
        "# Overview # \n",
        "\n",
        "Below provides code snippets for using the H-CUP package [(Healthcare Cost and Utilization Project)](https://github.com/yubin-park/hcuppy) that allows you to...\n",
        "- interpretting clinical codes\n",
        "- calculating the Elixhauser Comorbidity Index \n",
        "- ..."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KuvZ7_iGoeBg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 109
        },
        "outputId": "31c7453b-b670-4dfe-8de0-da603840f9cf"
      },
      "source": [
        "! pip install hcuppy\n",
        "\n",
        "from hcuppy.prcls import PrClsEngine\n",
        "pce = PrClsEngine()\n"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting hcuppy\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/da/50/90a7a6b85202281ad4c63fbf03022dedbed8f45ceddfde7c2edb22e3d33d/hcuppy-0.0.7-py3-none-any.whl (2.4MB)\n",
            "\u001b[K     |████████████████████████████████| 2.4MB 2.4MB/s \n",
            "\u001b[?25hInstalling collected packages: hcuppy\n",
            "Successfully installed hcuppy-0.0.7\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ili1_E-cu47q",
        "colab_type": "text"
      },
      "source": [
        "##  A) Query CCS codes ##"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p_pe8ZeNorLt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from hcuppy.ccs import CCSEngine\n",
        "ce = CCSEngine(mode=\"dx\")\n",
        "\n",
        "out = ce.get_ccs([\"E119\", \"I10\"])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tG7kjI64otRv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "8898fab4-ab67-4091-9a24-4e9fc343c22b"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "df=pd.DataFrame( out )\n",
        "df.head(5).transpose()\n"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>ccs</th>\n",
              "      <td>49</td>\n",
              "      <td>98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ccs_desc</th>\n",
              "      <td>Diabetes mellitus without complication</td>\n",
              "      <td>Essential hypertension</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ccs_lv1</th>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ccs_lv1_desc</th>\n",
              "      <td>Endocrine; nutritional; and metabolic diseases...</td>\n",
              "      <td>Diseases of the circulatory system</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ccs_lv2</th>\n",
              "      <td>3.2</td>\n",
              "      <td>7.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ccs_lv2_desc</th>\n",
              "      <td>Diabetes mellitus without complication [49.]</td>\n",
              "      <td>Hypertension</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                              0                                   1\n",
              "ccs                                                          49                                  98\n",
              "ccs_desc                 Diabetes mellitus without complication              Essential hypertension\n",
              "ccs_lv1                                                       3                                   7\n",
              "ccs_lv1_desc  Endocrine; nutritional; and metabolic diseases...  Diseases of the circulatory system\n",
              "ccs_lv2                                                     3.2                                 7.1\n",
              "ccs_lv2_desc       Diabetes mellitus without complication [49.]                        Hypertension"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bHnCIQLyu-fb",
        "colab_type": "text"
      },
      "source": [
        "##  B) Query procedural codes ##"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mKQLtoh4oxwi",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "outputId": "44354acf-dbf6-4d0e-e1d4-bb791f03f46c"
      },
      "source": [
        "from hcuppy.prcls import PrClsEngine\n",
        "pce = PrClsEngine()\n",
        "out2 = pce.get_prcls([\"B231Y0Z\"])\n",
        "\n",
        "df2=pd.DataFrame( out2 )\n",
        "\n",
        "df2.head(5).transpose()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>class</th>\n",
              "      <td>1</td>\n",
              "      <td>na</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>desc</th>\n",
              "      <td>Minor Diagnostic</td>\n",
              "      <td>na</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      0   1\n",
              "class                 1  na\n",
              "desc   Minor Diagnostic  na"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RxxHSZupvGvU",
        "colab_type": "text"
      },
      "source": [
        "## C) Calculate scores given certain codes ##"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G00Y_GUUu3BK",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "outputId": "32d730ed-a1f2-449c-e2f6-255a9ceed08d"
      },
      "source": [
        "from hcuppy.elixhauser import ElixhauserEngine\n",
        "ee = ElixhauserEngine()\n",
        "out = ee.get_elixhauser([\"E119\", \"E108\", \"I10\", \"I110\", \"Z944\"])\n",
        "\n",
        "out"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'cmrbdt_lst': ['DMCX', 'LIVER', 'HTNCX', 'CHF'],\n",
              " 'mrtlt_scr': 9,\n",
              " 'rdmsn_scr': 31}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    }
  ]
}