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"""
Visualization module for nursing care plans and assessments.
Provides charts and visualizations for clinical data.
"""
import streamlit as st
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
def create_care_plan_timeline(care_plan_data):
"""
Create a timeline visualization for care plan interventions.
Args:
care_plan_data: List of interventions with dates
Returns:
Plotly figure
"""
if not care_plan_data:
return None
df = pd.DataFrame(care_plan_data)
fig = px.timeline(
df,
x_start="start_date",
x_end="end_date",
y="intervention",
color="status",
title="Care Plan Timeline",
labels={"intervention": "Intervention", "status": "Status"}
)
fig.update_xaxes(type="date")
return fig
def create_assessment_radar(assessment_scores):
"""
Create a radar chart for multiple assessment domains.
Args:
assessment_scores: Dict with domain names and scores (0-100)
Returns:
Plotly figure
"""
if not assessment_scores:
return None
categories = list(assessment_scores.keys())
values = list(assessment_scores.values())
fig = go.Figure(data=go.Scatterpolar(
r=values,
theta=categories,
fill='toself',
name='Assessment Score'
))
fig.update_layout(
polar=dict(radialaxis=dict(
visible=True,
range=[0, 100]
)),
title="Clinical Assessment Profile",
showlegend=True
)
return fig
def create_health_indicators_gauge(
indicator_name,
current_value,
target_value
):
"""
Create a gauge chart for health indicators.
Args:
indicator_name: Name of the health indicator
current_value: Current value
target_value: Target value
Returns:
Plotly figure
"""
fig = go.Figure(data=go.Indicator(
mode="gauge+number+delta",
value=current_value,
delta={'reference': target_value},
gauge={
'axis': {'range': [0, 100]},
'bar': {'color': "darkblue"},
'steps': [
{'range': [0, 33], 'color': "lightgray"},
{'range': [33, 66], 'color': "gray"}
],
'threshold': {
'line': {'color': "red", 'width': 4},
'thickness': 0.75,
'value': target_value
}
},
title={'text': indicator_name}
))
return fig
def create_problem_severity_chart(problems):
"""
Create a bar chart showing problem severity.
Args:
problems: List of dict with 'name' and 'severity' (0-10)
Returns:
Plotly figure
"""
if not problems:
return None
df = pd.DataFrame(problems)
fig = px.bar(
df,
x="severity",
y="name",
orientation="h",
color="severity",
color_continuous_scale="Reds",
title="Nursing Problem Severity Assessment",
labels={"severity": "Severity Score", "name": "Problem"}
)
return fig
def create_goal_progress_chart(goals):
"""
Create a progress bar chart for care goals.
Args:
goals: List of dict with 'goal_name' and 'progress' (0-100)
Returns:
Plotly figure
"""
if not goals:
return None
df = pd.DataFrame(goals)
fig = px.bar(
df,
x="progress",
y="goal_name",
orientation="h",
color="progress",
color_continuous_scale="Greens",
title="Care Goal Progress",
labels={"progress": "Progress (%)", "goal_name": "Goal"}
)
return fig
def create_intervention_effectiveness_chart(interventions):
"""
Create a chart showing intervention effectiveness.
Args:
interventions: List of dict with 'intervention' and 'effectiveness'
Returns:
Plotly figure
"""
if not interventions:
return None
df = pd.DataFrame(interventions)
fig = px.scatter(
df,
x="duration_days",
y="effectiveness",
size="patient_benefit",
color="category",
hover_name="intervention",
title="Intervention Effectiveness Analysis",
labels={
"duration_days": "Duration (Days)",
"effectiveness": "Effectiveness Score",
"category": "Category"
}
)
return fig
def create_risk_assessment_heatmap(risks):
"""
Create a heatmap for risk assessment.
Args:
risks: 2D list with risk scores
Returns:
Plotly figure
"""
fig = px.imshow(
risks,
labels=dict(
x="Risk Factor",
y="Patient ID",
color="Risk Level"
),
color_continuous_scale="YlOrRd",
title="Risk Assessment Heatmap"
)
return fig
def display_care_plan_dashboard():
"""Display a comprehensive care plan dashboard."""
st.subheader("📋 Care Plan Dashboard")
col1, col2 = st.columns(2)
with col1:
st.metric(
"Active Care Goals",
5,
delta="+2 this week",
delta_color="normal"
)
with col2:
st.metric(
"Goal Achievement Rate",
"78%",
delta="+5%",
delta_color="off"
)
st.divider()
# Sample care plan data
sample_goals = [
{"goal_name": "Pain Management", "progress": 85},
{"goal_name": "Mobility Improvement", "progress": 60},
{"goal_name": "Nutritional Intake", "progress": 92},
{"goal_name": "Wound Healing", "progress": 45},
{"goal_name": "Patient Education", "progress": 78}
]
fig_goals = create_goal_progress_chart(sample_goals)
if fig_goals:
st.plotly_chart(fig_goals, use_container_width=True)
st.divider()
# Assessment scores
sample_assessment = {
"Mobility": 65,
"Nutrition": 78,
"Continence": 45,
"Mental Health": 82,
"Pain": 35,
"Communication": 90
}
fig_assessment = create_assessment_radar(sample_assessment)
if fig_assessment:
st.plotly_chart(fig_assessment, use_container_width=True)
def display_problem_assessment():
"""Display problem assessment visualizations."""
st.subheader("🔍 Problem Assessment")
sample_problems = [
{"name": "Acute Pain", "severity": 8},
{"name": "Limited Mobility", "severity": 6},
{"name": "Risk of Falls", "severity": 7},
{"name": "Impaired Nutrition", "severity": 5},
{"name": "Sleep Disturbance", "severity": 6}
]
fig_severity = create_problem_severity_chart(sample_problems)
if fig_severity:
st.plotly_chart(fig_severity, use_container_width=True)
def display_intervention_analysis():
"""Display intervention effectiveness analysis."""
st.subheader("💊 Intervention Analysis")
sample_interventions = [
{
"intervention": "Pain Medication",
"duration_days": 7,
"effectiveness": 8.5,
"patient_benefit": 85,
"category": "Pharmacological"
},
{
"intervention": "Physical Therapy",
"duration_days": 14,
"effectiveness": 7.2,
"patient_benefit": 72,
"category": "Rehabilitation"
},
{
"intervention": "Nutritional Support",
"duration_days": 10,
"effectiveness": 6.8,
"patient_benefit": 68,
"category": "Supportive Care"
},
{
"intervention": "Patient Education",
"duration_days": 5,
"effectiveness": 7.9,
"patient_benefit": 79,
"category": "Educational"
}
]
fig_interventions = create_intervention_effectiveness_chart(
sample_interventions
)
if fig_interventions:
st.plotly_chart(fig_interventions, use_container_width=True)
def display_health_indicators():
"""Display health indicators with gauges."""
st.subheader("📊 Health Indicators")
col1, col2, col3 = st.columns(3)
indicators = [
("Blood Pressure", 78, 80),
("Oxygen Saturation", 96, 95),
("Pain Score", 35, 30)
]
for idx, (name, current, target) in enumerate(indicators):
with st.columns(3)[idx % 3]:
fig = create_health_indicators_gauge(name, current, target)
st.plotly_chart(fig, use_container_width=True)
if __name__ == "__main__":
st.set_page_config(page_title="Nursing Visualizations")
st.title("🏥 Nursing Care Plan Visualizations")
page = st.sidebar.radio(
"Select View",
["Care Plan Dashboard", "Problem Assessment", "Intervention Analysis",
"Health Indicators"]
)
if page == "Care Plan Dashboard":
display_care_plan_dashboard()
elif page == "Problem Assessment":
display_problem_assessment()
elif page == "Intervention Analysis":
display_intervention_analysis()
elif page == "Health Indicators":
display_health_indicators()
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