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contract_manager_drilldown_hosp_rate.py
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contract_manager_drilldown_hosp_rate.py
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#!/usr/bin/env python3
import dash
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
import dash_table
import pandas as pd
import numpy as np
import pathlib
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from dash.dependencies import Input, Output, State
from utils import *
from figure import *
from modal_drilldown_tableview_crhr import *
from app import app
#callbacks for this section are in contract_manager_drilldown.py callback section ## drilldown_hosp_rate
df_drilldown=pd.read_csv("data/drilldown_sample_6.csv")
#dimensions=df_drilldown.columns[0:12]
df_drill_waterfall_crhr=pd.read_csv("data/drilldown waterfall graph ip.csv")
df_driver_crhr=pd.read_csv("data/Drilldown Odometer ip.csv")
df_driver_all_crhr=pd.read_csv("data/Drilldown All Drivers ip.csv")
data_lv2_crhr=drilldata_process_crhr(df_drilldown,'Sub Category')
all_dimension=[]
for i in list(df_drilldown.columns[0:14]):
all_dimension.append([i,'All'])
for j in list(df_drilldown[i].unique()):
all_dimension.append([i,j])
all_dimension=pd.DataFrame(all_dimension,columns=['dimension','value'])
#for modify criteria list
dimensions = ['Age Band' , 'Gender' , 'Patient Health Risk Level' , 'NYHA Class' , 'Medication Adherence' , 'Comorbidity Type', 'Weight Band' , 'Comorbidity Score' , 'Ejection Fraction' , 'Years Since HF Diagnosis' , 'Prior Use of ACE/ARB' ]
disable_list=['Comorbidity Type', 'Weight Band','Comorbidity Score','Ejection Fraction','Years Since HF Diagnosis','Prior Use of ACE/ARB']
#modebar display
button_to_rm=['zoom2d', 'pan2d', 'select2d', 'lasso2d', 'zoomIn2d', 'zoomOut2d', 'autoScale2d', 'hoverClosestCartesian','hoverCompareCartesian','hoverClosestGl2d', 'hoverClosestPie', 'toggleHover','toggleSpikelines']
def col_content_drilldown_crhr(app):
return html.Div(
[
dbc.Row(
[
dbc.Col(card_overview_drilldown_crhr(0.03),width=8),
dbc.Col(card_key_driver_drilldown_crhr(app),width=4),
]
),
card_confounding_factors_crhr(app),
html.Div(
[
dbc.Row(
[
dbc.Col(html.Div(
[
html.H2("Performance Drilldown", style={"font-size":"3rem"}),
html.H3("check table view for more details...", style={"font-size":"1rem"}),
],
style={"padding-left":"2rem"}
), width=8),
dbc.Col(modal_drilldown_tableview(), width=4)
]
)
],
style={"padding-bottom":"1rem", "padding-top":"2rem"}
),
html.Div(
dbc.Tabs(
[
dbc.Tab(tab_patient_analysis_crhr(app), label="Patient Analysis", style={"background-color":"#fff"}, tab_style={"font-family":"NotoSans-Condensed"}),
dbc.Tab(tab_physician_analysis_crhr(app), label="Physician Analysis", style={"background-color":"#fff"}, tab_style={"font-family":"NotoSans-Condensed"}),
],
# id = 'tab_container'
),
)
]
)
def card_overview_drilldown_crhr(percentage):
if percentage > 0:
color = "#dc3545"
condition = "worse than target"
elif percentage == 0:
color = "#1357DD"
condition = "same as target"
else:
color = "#28a745"
condition = "better than target"
return html.Div(
[
dbc.Row(
[
dbc.Col(html.H1("CHF Related Hospitalization Rate (per 1,000)", style={"font-size":"1.6rem"}), width="auto"),
dbc.Card(
dbc.CardBody(
[
html.H3("worse than target", style={"font-size":"0.8rem", "color":"#fff"}),
html.H2(str(percentage*100)+"%", style={"font-size":"1.2rem", "margin-top":"-9px", "color":"#fff"}),
],
style={"margin-top":"-20px"}
),
style={"height":"2.5rem", "border":"none", "background-color":color, "text-align":"center", "margin-top":"-6px"},
),
],
style={"padding-left":"1rem"}
),
html.P("As of June 30th.", style={"color":"#000", "font-size":"0.8rem","padding-left":"1rem"}),
dbc.Row(
[
dbc.Col(
[
html.Div(
[
dcc.Graph(figure=drill_bar(df_drill_waterfall_crhr),config={'modeBarButtonsToRemove': button_to_rm,'displaylogo': False,},style={"height":"28rem"}),
]
)
],
width=7,
style={"height":"10rem"}
),
dbc.Col(
[
html.Div(
[
html.H3("Risk Adjustment Details", style={"font-size":"0.8rem","margin-top":"-1.8rem","color":"#919191","background-color":"#f5f5f5","width":"9rem","padding-left":"1rem","padding-right":"1rem","text-align":"center"}),
html.Div([dcc.Graph(figure=drill_waterfall(df_drill_waterfall_crhr),style={"height":"24rem","padding-bottom":"1rem"},config={'modeBarButtonsToRemove': button_to_rm,'displaylogo': False,})]),
],
style={"border-radius":"0.5rem","border":"2px solid #d2d2d2","padding":"1rem","height":"25.5rem"}
)
],
width=4,
)
],
),
],
)
def card_key_driver_drilldown_crhr(app):
return dbc.Card(
dbc.CardBody(
[
dbc.Row(
[
dbc.Col(html.Img(src=app.get_asset_url("bullet-round-blue.png"), width="10px"), width="auto", align="start", style={"margin-top":"-4px"}),
dbc.Col(html.H4("Key Drivers", style={"font-size":"1rem", "margin-left":"10px"}), width=8),
dbc.Col([dbc.Button("See All Drivers", id = 'button-all-driver-crhr',
style={"background-color":"#38160f", "border":"none", "border-radius":"10rem", "font-family":"NotoSans-Regular", "font-size":"0.6rem"},
),
dbc.Modal([
dbc.ModalHeader("All Drivers"),
dbc.ModalBody(children = html.Div([table_driver_all(df_driver_all_crhr)], style={"padding":"1rem"})),
dbc.ModalFooter(
dbc.Button("Close", id = 'close-all-driver-crhr',
style={"background-color":"#38160f", "border":"none", "border-radius":"10rem", "font-family":"NotoSans-Regular", "font-size":"0.8rem"},
)
)
], id = 'modal-all-driver-crhr', size="lg")],
width=3,
),
],
no_gutters=True,
),
dbc.Row(
[
dbc.Col(
[
html.Div([gaugegraph(df_driver_crhr,0)], style={"padding-top":"1.5rem"}),
html.Div(html.H4("{:.1f} %".format(abs(df_driver_crhr['%'][0]*100)),style={"color":"#ff4d17"}), style={"margin-top":"-1.5rem","text-align":"center","font-size":"1rem","color":"#ffeb78"}),
],
width=6),
dbc.Col(
[
html.Div([gaugegraph(df_driver_crhr,1)], style={"padding-top":"1.5rem"}),
html.Div(html.H4("{:.1f} %".format(abs(df_driver_crhr['%'][1]*100)),style={"color":"#ff4d17"}), style={"margin-top":"-1.5rem","text-align":"center","font-size":"1rem","color":"#aeff78"}),
],
width=6),
dbc.Col(
[
html.Div([gaugegraph(df_driver_crhr,2)], style={"padding-top":"1.5rem"}),
html.Div(html.H4("{:.1f} %".format(abs(df_driver_crhr['%'][2]*100)),style={"color":"#ff4d17"}), style={"margin-top":"-1.5rem","text-align":"center","font-size":"1rem","color":"#39db44"}),
],
width=6),
dbc.Col(
[
html.Div([gaugegraph(df_driver_crhr,3)], style={"padding-top":"1.5rem"}),
html.Div(html.H4("{:.1f} %".format(abs(df_driver_crhr['%'][3]*100)),style={"color":"#18cc75"}), style={"margin-top":"-1.5rem","text-align":"center","font-size":"1rem","color":"#39db44"}),
],
width=6),
],
),
]
),
className="mb-3",
style={"box-shadow":"0 4px 8px 0 rgba(0, 0, 0, 0.05), 0 6px 20px 0 rgba(0, 0, 0, 0.05)", "border":"none", "border-radius":"0.5rem"}
)
def card_confounding_factors_crhr(app):
return dbc.Card(
dbc.CardBody(
[
dbc.Row(
[
dbc.Col(html.Img(src=app.get_asset_url("bullet-round-blue.png"), width="10px"), width="auto", align="start", style={"margin-top":"-4px"}),
dbc.Col(html.H4("Confounding Factors Unaccounted for in the Contract", style={"font-size":"1rem", "margin-left":"10px"}), width=8),
],
no_gutters=True,
),
dbc.Row(
[
dbc.Col(element_confounding_factors_crhr(0.003, "Benefit Change")),
dbc.Col(element_confounding_factors_crhr(-0.002, "Outlier Impact")),
],
),
]
),
className="mb-3",
style={"box-shadow":"0 4px 8px 0 rgba(0, 0, 0, 0.05), 0 6px 20px 0 rgba(0, 0, 0, 0.05)", "border":"none", "border-radius":"0.5rem"}
)
def element_confounding_factors_crhr(percentage, factor):
if percentage > 0:
color = "success"
elif percentage == 0:
color = "secondary"
else:
color = "danger"
return dbc.Row(
[
dbc.Col(dbc.Badge(str(abs(percentage*100))+"%", color=color, className="mr-1"), width="auto", style={"font-family":"NotoSans-SemiBold"}),
dbc.Col(html.H6(factor, style = {"font-size":"1rem", "padding-top":"0.1rem"})),
],
style={"padding":"1rem"}
)
def tab_patient_analysis_crhr(app):
return html.Div(
[
dbc.Card(
dbc.CardBody(
[
card_graph1_patient_performance_drilldown_crhr(app),
html.Hr(),
card_table1_patient_performance_drilldown_crhr(app),
]
),
className="mb-3",
style={"border":"none", "border-radius":"0.5rem"}
),
]
)
def tab_physician_analysis_crhr(app):
return html.Div(
[
dbc.Card(
dbc.CardBody(
[
card_graph2_physician_performance_drilldown_crhr(app),
html.Hr(),
card_table1_physician_performance_drilldown_crhr(app),
]
),
className="mb-3",
style={"border":"none", "border-radius":"0.5rem"}
),
]
)
def mod_criteria_button_crhr():
return [
dbc.Button(
"Click to modify criteria",
id="button-mod-dim-lv1-crhr",
className="mb-3",
style={"background-color":"#38160f", "border":"none", "border-radius":"10rem", "font-family":"NotoSans-Regular", "font-size":"0.8rem"},
),
dbc.Popover([
dbc.PopoverHeader("Modify criteria"),
dbc.PopoverBody([
html.Div(
[
dbc.RadioItems(
options = [{'label':c , 'value':c,'disabled' : False} if c not in disable_list else {'label':c , 'value':c,'disabled' : True} for c in dimensions
],
value = "Medication Adherence",
labelCheckedStyle={"color": "#057aff"},
id = "list-dim-lv1-crhr",
style={"font-family":"NotoSans-Condensed", "font-size":"0.8rem", "padding":"1rem"},
),
],
style={"padding-top":"0.5rem", "padding-bottom":"2rem"}
)
]
),
],
id = "popover-mod-dim-lv1-crhr",
is_open = False,
target = "button-mod-dim-lv1-crhr",
placement = "top",
),
]
def card_graph1_patient_performance_drilldown_crhr(app):
return dbc.Card(
dbc.CardBody(
[
dbc.Row(
[
dbc.Col(html.Img(src=app.get_asset_url("bullet-round-blue.png"), width="10px"), width="auto", align="start", style={"margin-top":"-4px"}),
dbc.Col(html.H4("Performance Drilldown by Patient Cohort", style={"font-size":"1rem", "margin-left":"10px"}), width=8),
],
no_gutters=True,
),
html.Div(
[
html.Div(
[
dbc.Row(
[
dbc.Col(html.H1("By Medication Adherence",id='dimname_on_patient_lv1_crhr', style={"color":"#f0a800", "font-size":"1.5rem","padding-top":"0.8rem"}), width=9),
dbc.Col(mod_criteria_button_crhr(), style={"padding-top":"0.8rem"}),
]
)
],
style={"padding-left":"2rem","padding-right":"1rem","border-radius":"5rem","background-color":"#f7f7f7","margin-top":"2rem"}
),
html.Div(drillgraph_lv1_crhr(drilldata_process_crhr(df_drilldown,'Medication Adherence'),'dashtable_patient_lv1_crhr','Medication Adherence'),id="drill_patient_lv1_crhr",style={"padding-top":"2rem","padding-bottom":"2rem"}),
],
style={"max-height":"80rem"}
),
]
),
className="mb-3",
style={"box-shadow":"0 4px 8px 0 rgba(0, 0, 0, 0.05), 0 6px 20px 0 rgba(0, 0, 0, 0.05)", "border":"none", "border-radius":"0.5rem"}
)
def filter_template_crhr(dim,idname,default_val='All'):
return(dcc.Dropdown(
id=idname,
options=[{'label': i, 'value': i} for i in all_dimension[all_dimension['dimension']==dim].loc[:,'value']],
value=default_val,
clearable=False,
))
def card_table1_patient_performance_drilldown_crhr(app):
return dbc.Card(
dbc.CardBody(
[
dbc.Row(
[
dbc.Col(html.Img(src=app.get_asset_url("bullet-round-blue.png"), width="10px"), width="auto", align="start", style={"margin-top":"-4px"}),
dbc.Col(html.H4("Hospitalization Rate by Medical Condition", style={"font-size":"1rem", "margin-left":"10px"}), width=8),
],
no_gutters=True,
),
html.Div(
[
html.Div(
[
dbc.Row(
[
dbc.Col(html.H1("By Medical Condition", style={"color":"#f0a800", "font-size":"1.5rem","padding-top":"1.2rem"}), width=5),
dbc.Col(
[
html.Div("Medication Adherence",id="filter_patient_1_2_name_crhr", style={"font-size":"0.6rem"}),
html.Div(filter_template_crhr("Medication Adherence","filter_patient_1_2_value_crhr",default_val='All'),id="filter_patient_1_2_contain_crhr"),
],
style={"padding":"0.8rem"},
width=2,
),
]
)
],
style={"padding-left":"2rem","padding-right":"1rem","border-radius":"5rem","background-color":"#f7f7f7","margin-top":"2rem"}
),
html.H4("* Default sorting: by Contribution to Overall Performance Difference", style={"font-size":"0.8rem","color":"#919191","padding-top":"1rem","margin-bottom":"-1rem"}),
html.Div([dashtable_lv3_crhr(data_lv2_crhr,'Sub Category','dashtable_patient_lv2_crhr',0)],id="drill_patient_lv2_crhr",style={"padding":"1rem"})
],
style={"max-height":"120rem"}
),
]
),
className="mb-3",
style={"box-shadow":"0 4px 8px 0 rgba(0, 0, 0, 0.05), 0 6px 20px 0 rgba(0, 0, 0, 0.05)", "border":"none", "border-radius":"0.5rem"}
)
def card_graph2_physician_performance_drilldown_crhr(app):
return dbc.Card(
dbc.CardBody(
[
dbc.Row(
[
dbc.Col(html.Img(src=app.get_asset_url("bullet-round-blue.png"), width="10px"), width="auto", align="start", style={"margin-top":"-4px"}),
dbc.Col(html.H4("Performance Drilldown by Managing Physician (Group)", style={"font-size":"1rem", "margin-left":"10px"}), width=8),
],
no_gutters=True,
),
html.Div(
[
html.Div(
[
dbc.Row(
[
dbc.Col(html.H1("By Managing Physician (Group)", style={"color":"#f0a800", "font-size":"1.5rem","padding-top":"1.2rem"}), width=6),
]
)
],
style={"padding-left":"2rem","padding-right":"1rem","border-radius":"5rem","background-color":"#f7f7f7","margin-top":"2rem"}
),
html.Div(drillgraph_lv1_crhr(drilldata_process_crhr(df_drilldown,'Managing Physician (Group)'),'dashtable_physician_lv1_crhr','Managing Physician (Group)'),id="drill_physician_lv1_crhr",style={"padding-top":"2rem","padding-bottom":"2rem"}),
],
style={"max-height":"80rem"}
),
]
),
className="mb-3",
style={"box-shadow":"0 4px 8px 0 rgba(0, 0, 0, 0.05), 0 6px 20px 0 rgba(0, 0, 0, 0.05)", "border":"none", "border-radius":"0.5rem"}
)
def card_table1_physician_performance_drilldown_crhr(app):
return dbc.Card(
dbc.CardBody(
[
dbc.Row(
[
dbc.Col(html.Img(src=app.get_asset_url("bullet-round-blue.png"), width="10px"), width="auto", align="start", style={"margin-top":"-4px"}),
dbc.Col(html.H4("Hospitalization Rate by Medical Condition", style={"font-size":"1rem", "margin-left":"10px"}), width=8),
],
no_gutters=True,
),
html.Div(
[
html.Div(
[
dbc.Row(
[
dbc.Col(html.H1("By Medical Condition", style={"color":"#f0a800", "font-size":"1.5rem","padding-top":"1.2rem"}), width=5),
dbc.Col(
[
html.Div("Managing Physician (Group)",id="filter_physician_1_2_name_crhr", style={"font-size":"0.6rem"}),
html.Div(filter_template_crhr("Managing Physician (Group)","filter_physician_1_2_value_crhr",default_val='All'),id='filter_physician_1_2_contain_crhr'),
],
style={"padding":"0.8rem"},
width=2,
),
]
)
],
style={"padding-left":"2rem","padding-right":"1rem","border-radius":"5rem","background-color":"#f7f7f7","margin-top":"2rem"}
),
html.H4("* Default sorting: by Contribution to Overall Performance Difference", style={"font-size":"0.8rem","color":"#919191","padding-top":"1rem","margin-bottom":"-1rem"}),
html.Div([dashtable_lv3_crhr(data_lv2_crhr,'Sub Category','dashtable_physician_lv2_crhr',0)],id="drill_physician_lv2_crhr",style={"padding":"1rem"})
],
style={"max-height":"120rem"}
),
]
),
className="mb-3",
style={"box-shadow":"0 4px 8px 0 rgba(0, 0, 0, 0.05), 0 6px 20px 0 rgba(0, 0, 0, 0.05)", "border":"none", "border-radius":"0.5rem"}
)
if __name__ == "__main__":
app.run_server(host="127.0.0.1",debug=True)