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import streamlit as st
import plotly.graph_objects as go
# List of top six prior auth conditions
conditions = [
{
"diagnosis": "Diagnosis 1",
"observations": "Observations 1",
"CCD": "CCD 1",
"CCD_procedures": "CCD Procedures 1"
},
# Add more conditions here
]
# MSK hip and knee surgery list dictionary
surgery_data = [
{
"CPTCode": "CPT Code 1",
"CPTDescription": "MSK Hip Surgery",
"ICD10Code": "ICD10 Code 1",
"ICD10Description": "ICD10 Description 1",
"Emoji": "💉",
"Description": "Hip Surgery",
"Cost": 10
},
{
"CPTCode": "CPT Code 2",
"CPTDescription": "MSK Knee Surgery",
"ICD10Code": "ICD10 Code 2",
"ICD10Description": "ICD10 Description 2",
"Emoji": "💊",
"Description": "Knee Surgery",
"Cost": 15
}
]
# Sort the surgery data by descending cost
surgery_data.sort(key=lambda x: x["Cost"], reverse=True)
# Function to create heatmap circle plot
def create_heatmap_circle_plot(surgery_data):
fig = go.Figure()
for surgery in surgery_data:
fig.add_trace(go.Scatter(
x=[surgery["CPTCode"]],
y=[surgery["Cost"]],
mode='markers',
marker=dict(
size=20,
color=[surgery["Cost"]],
colorscale='Viridis',
showscale=True
),
text=surgery["CPTDescription"],
hovertemplate='<b>%{text}</b><br><i>CPT Code</i>: %{x}<br><i>Cost</i>: %{y}'))
fig.update_layout(title='Heatmap Circle Plot of Surgery Types',
xaxis_title='CPT Codes',
yaxis_title='Cost (in billions)')
return fig
# Streamlit app
st.title("Top Prior Auth Conditions")
st.header("MSK Hip and Knee Surgery")
st.write(surgery_data)
st.header("Heatmap Circle Plot")
fig = create_heatmap_circle_plot(surgery_data)
st.plotly_chart(fig)
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