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8bb9bd4
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Parent(s):
5e53513
Upload 3 files
Browse files- app.py +29 -0
- backupapp.py +71 -0
- requirements.txt +1 -0
app.py
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import streamlit as st
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import plotly.graph_objects as go
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import plotly.graph_objects as go
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def create_sunburst_plot(labels, parents, values, ids, text):
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fig = go.Figure(go.Sunburst(
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labels=labels,
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parents=parents,
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values=values,
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ids=ids,
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text=text,
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hoverinfo="label+value",
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branchvalues="total",
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))
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fig.update_layout(margin=dict(t=0, l=0, r=0, b=0))
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return fig
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# Replace these lists with your own data
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labels = ["Root", "Hip Surgery", "Knee Surgery", "CPT1", "CPT2", "CPT3", "CPT4"]
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parents = ["", "Root", "Root", "Hip Surgery", "Hip Surgery", "Knee Surgery", "Knee Surgery"]
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values = [None, 30, 40, 20, 10, 25, 15]
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ids = ["Root", "Hip Surgery", "Knee Surgery", "CPT1", "CPT2", "CPT3", "CPT4"]
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text = ["Root", "Hip Surgery", "Knee Surgery", "CPT1", "CPT2", "CPT3", "CPT4"]
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fig = create_sunburst_plot(labels, parents, values, ids, text)
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st.plotly_chart(fig)
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backupapp.py
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import streamlit as st
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import plotly.graph_objects as go
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# List of top six prior auth conditions
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conditions = [
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{
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"diagnosis": "Diagnosis 1",
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"observations": "Observations 1",
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"CCD": "CCD 1",
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"CCD_procedures": "CCD Procedures 1"
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},
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# Add more conditions here
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]
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# MSK hip and knee surgery list dictionary
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surgery_data = [
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{
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"CPTCode": "CPT Code 1",
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"CPTDescription": "MSK Hip Surgery",
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"ICD10Code": "ICD10 Code 1",
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"ICD10Description": "ICD10 Description 1",
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"Emoji": "💉",
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"Description": "Hip Surgery",
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"Cost": 10
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},
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{
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"CPTCode": "CPT Code 2",
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"CPTDescription": "MSK Knee Surgery",
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"ICD10Code": "ICD10 Code 2",
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"ICD10Description": "ICD10 Description 2",
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"Emoji": "💊",
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"Description": "Knee Surgery",
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"Cost": 15
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}
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]
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# Sort the surgery data by descending cost
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surgery_data.sort(key=lambda x: x["Cost"], reverse=True)
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# Function to create heatmap circle plot
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def create_heatmap_circle_plot(surgery_data):
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fig = go.Figure()
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for surgery in surgery_data:
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fig.add_trace(go.Scatter(
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x=[surgery["CPTCode"]],
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y=[surgery["Cost"]],
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mode='markers',
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marker=dict(
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size=20,
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color=[surgery["Cost"]],
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colorscale='Viridis',
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showscale=True
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),
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text=surgery["CPTDescription"],
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hovertemplate='<b>%{text}</b><br><i>CPT Code</i>: %{x}<br><i>Cost</i>: %{y}'))
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fig.update_layout(title='Heatmap Circle Plot of Surgery Types',
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xaxis_title='CPT Codes',
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yaxis_title='Cost (in billions)')
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return fig
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# Streamlit app
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st.title("Top Prior Auth Conditions")
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st.header("MSK Hip and Knee Surgery")
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st.write(surgery_data)
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st.header("Heatmap Circle Plot")
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fig = create_heatmap_circle_plot(surgery_data)
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st.plotly_chart(fig)
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requirements.txt
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plotly
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