Create backupapp.py

backupapp.py

@@ -0,0 +1,71 @@
+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)