app.py

import pandas as pd
import plotly.express as px
import streamlit as st
import jsonlines

st.markdown("""
| 📝 #Definition | 📋 Data Fields |
| --- | --- |
| 🤝 asking for more help or #treatment | 📄 Patient info, Referral details |
| 💼 about a patient's health #problem or #limits | 📄 Patient info, Health #problem details |
| 💊 allowing medicine | 📄 Patient info, #Medicine #details |
| 🔎 explaining a #patient's health #problem | 📄 Patient info, Health #problem details |
| 🚑 plan for getting better | 📄 Patient info, #Treatment details |
| 🏥 patient needs surgery | 📄 Patient info, #Surgery details |
| 🏃 patient can do activities | 📄 Patient info, #Activity details |
| 📅 reminding about appointments | 📄 Patient info, #Appointment details |
| ♿ patient's disability | 📄 Patient info, #Disability details |
| 🍎 teaching about health | 📄 Patient info, #Education topic |
""")
# Create a DataFrame with CPT codes, procedures, and expected costs
import pandas as pd
import plotly.graph_objects as go
import streamlit as st
import jsonlines
import base64
from datetime import datetime

# Create a DataFrame with Code types, values, descriptions, and expected costs
data = {
    'Code Type': ['CPT', 'SNOMED', 'RXNORM', 'DEA', 'LOINC', 'ORI', 'ORU', 'CCD'],
    'Code Value': ['99201', 'A-12345', 'R-12345', 'D-12345', 'L-12345', 'O-12345', 'U-12345', 'C-12345'],
    'Code Description': ['Office/Outpatient Visit', 'Inpatient Consultation', 'Initial Hospital Care', 'Subsequent Hospital Care', 'Critical Care Services', 'Procedure 6', 'Procedure 7', 'Procedure 8'],
    'Expected Cost': [100, 200, 150, 250, 300, 350, 400, 450]
}
df = pd.DataFrame(data)

# Create a sunburst plot with Plotly
fig = go.Figure(go.Sunburst(
    labels=df['Code Type'],
    parents=['']*len(df),
    values=df['Expected Cost'],
    text=df['Code Description'],
    hoverinfo="label+value+text",
    branchvalues="total",
))

fig.update_layout(margin=dict(t=0, l=0, r=0, b=0))

# Display the sunburst plot in Streamlit
st.plotly_chart(fig)

# Save DataFrame to JSONL file
timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
filename = f"output_{timestamp}.jsonl"
with jsonlines.open(filename, mode='w') as writer:
    writer.write(df.to_dict(orient='records'))

# Function to create a download link
def create_download_link(filename):
    with open(filename, 'r') as file:
        data = file.read()
    b64 = base64.b64encode(data.encode()).decode()
    return f'<a href="data:file/txt;base64,{b64}" download="{filename}">Download data as JSONL</a>'

# Display a link to download the JSONL file
st.markdown(create_download_link(filename), unsafe_allow_html=True)