๐Ÿฅ Care Placement Assessment System

AI-Powered Care Recommendations for Elderly Patients

๐Ÿ“‹ System Overview

The Care Placement Assessment System is an AI-powered tool designed to help healthcare professionals, families, and caregivers determine the most appropriate care setting for elderly individuals. Using machine learning algorithms trained on comprehensive geriatric assessment data, the system provides evidence-based recommendations for care placement decisions.

โš ๏ธ Important Disclaimer

This tool is designed to assist in care planning decisions and should not replace professional medical judgment. All recommendations should be reviewed with qualified healthcare providers, and individual circumstances should always be considered in final care placement decisions.

๐ŸŽฏ Assessment Types

๐Ÿฉบ

Medical Assessment

For Healthcare Professionals

  • Uses standardized medical assessment scales
  • MMSE, MoCA, ADL, IADL, GDS scores
  • Precise clinical measurements
  • Detailed feature importance analysis
  • Professional terminology and metrics

Ideal for doctors, nurses, social workers, and care coordinators

๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ

Family Assessment

For Families and Caregivers

  • Plain language questions
  • Likert scale responses (1-5)
  • Everyday scenarios and examples
  • Family-focused explanations
  • Cost and involvement guidance

Perfect for family members, friends, and non-medical caregivers

๐Ÿ  Care Placement Options

The system can recommend five different levels of care based on the individual's needs and functional status:

๐Ÿก Independent Living

Minimal assistance needed. Can live safely at home or in senior community with occasional support.

๐Ÿ  Home Care

Professional caregivers provide regular assistance while maintaining independence at home.

๐Ÿข Assisted Living

Residential community with 24/7 staff support, meals, activities, and assistance with daily tasks.

๐Ÿง  Memory Care

Specialized secure environment for individuals with dementia or Alzheimer's disease.

๐Ÿ“Š Assessment Comparison

Feature Medical Assessment Family Assessment
Target Users Healthcare professionals, clinicians Family members, caregivers, patients
Language Medical terminology, clinical scales Plain language, everyday terms
Input Method Numeric scores (MMSE: 0-30, ADL: 0-6) Likert scales (Excellent to Very Poor)
Cognitive Assessment MMSE and MoCA scores "How well can they remember recent events?"
Functional Assessment ADL and IADL scores "How well can they handle personal care?"
Results Format Clinical recommendation with feature importance Family-friendly explanation with next steps
Time to Complete 5-10 minutes (if scores available) 10-15 minutes (thoughtful consideration)

๐Ÿง  Feature Selection & Model Performance

Our assessment system is designed around evidence-based feature selection, focusing on the most clinically significant predictors of care placement needs.

๐Ÿ“Š Current Data Collection: 13 Core Features vs. 55-Feature Comprehensive Dataset

While comprehensive geriatric assessments can include 55+ features, our system strategically focuses on the 13 most impactful features that drive care placement decisions. This approach maintains clinical accuracy while ensuring user-friendly assessments.

๐ŸŽฏ High-Impact Features (Primary Predictors)

๐Ÿง  Cognitive Assessment

  • MMSE Score (0-30): Primary cognitive screening tool used globally
  • MoCA Score (0-30): More sensitive to mild cognitive impairment

Impact: Cognitive function is the strongest predictor of care needs and safety

๐Ÿƒ Functional Assessment

  • ADL Score (0-6): Basic self-care independence (bathing, dressing, toileting)
  • IADL Score (0-8): Complex daily tasks (cooking, finances, medication management)

Impact: Functional dependency directly determines level of care required

๐Ÿšถ Mobility & Safety

  • Mobility Level: Physical independence and assistive device needs
  • Fall Risk: Safety concerns and supervision requirements

Impact: Mobility limitations and fall risk drive safety-based placement decisions

๐Ÿ”ฌ Medium-High Impact Features

๐Ÿง‘โ€โš•๏ธ Clinical Factors

  • Primary Diagnosis: Main health condition affecting care needs
  • Comorbidities Count: Overall health complexity
  • GDS Score (0-15): Depression screening affecting engagement and safety

๐Ÿ‘ฅ Social & Environmental

  • Social Support Level: Available family/friend network
  • Living Situation: Current housing and support arrangement
  • Demographics: Age and gender for risk stratification

โœ… Why 13 Features Are Sufficient for Accurate Predictions

๐ŸŽฏ Pareto Principle (80/20 Rule)

Research shows that 80% of care placement decisions are driven by 20% of available features. Our 13 core features represent the most predictive variables in geriatric assessment.

๐Ÿ“Š Feature Importance Analysis

Machine learning feature importance analysis consistently ranks cognitive function, ADL/IADL scores, and mobility as the top predictors - all included in our assessment.

๐Ÿฅ Clinical Practice Standards

Our features align with standard geriatric assessment tools used in clinical practice (CGA - Comprehensive Geriatric Assessment core domains).

โšก Diminishing Returns

Additional features beyond the core 13 provide marginal improvement in prediction accuracy while significantly increasing assessment complexity and time.

๐Ÿ” What We're NOT Missing (And Why It's OK)

๐Ÿงช Laboratory Values & Vitals

Missing: Blood pressure, glucose, cholesterol, BMI

Why it's OK: These are captured indirectly through primary diagnosis and comorbidities count. Care placement decisions are rarely driven by specific lab values.

๐Ÿ’Š Detailed Medication Information

Missing: Specific medications, drug interactions, compliance

Why it's OK: Medication complexity is reflected in comorbidities count and cognitive/functional scores. Specific drugs don't typically change placement recommendations.

๐Ÿ  Detailed Environmental Assessment

Missing: Home safety scores, accessibility features, neighborhood resources

Why it's OK: These factors influence implementation but not the fundamental care level needed. Our social support and living situation capture the key elements.

๐Ÿ’ฐ Financial and Insurance Details

Missing: Income, insurance coverage, financial resources

Why it's OK: These affect care access and options but not clinical care needs. Our model predicts appropriate care level, not affordability.

๐Ÿฅ Care Placement Types & Recommendations

Our system predicts four main types of care placement based on comprehensive geriatric assessment:

๐Ÿ  Independent Living

For individuals who can manage all daily activities completely independently with no regular assistance needed.

Typical Criteria:
  • MMSE Score: 26-30 (Excellent cognition)
  • ADL Score: 6 (Fully independent)
  • IADL Score: 7-8 (Manages all complex tasks)
  • Low fall risk and excellent mobility

๐Ÿก Home Care

For individuals who can remain at home safely with professional support services for specific needs.

Typical Criteria:
  • MMSE Score: 20-26 (Mild to moderate impairment)
  • ADL Score: 4-5 (Some assistance needed)
  • IADL Score: 4-6 (Difficulty with complex tasks)
  • Medium fall risk, needs help with medications/meals

๐Ÿค Assisted Living

Provides support with daily activities while maintaining independence and dignity in a community setting.

Typical Criteria:
  • MMSE Score: 18-26 (Mild to moderate impairment)
  • ADL Score: 3-5 (Some assistance needed)
  • IADL Score: 3-6 (Difficulty with complex tasks)
  • Medium fall risk or mobility concerns

๐Ÿง  Memory Care

Specialized care for individuals with dementia, Alzheimer's, or significant cognitive impairment requiring secure environment.

Typical Criteria:
  • MMSE Score: 10-20 (Moderate to severe impairment)
  • Significant behavioral symptoms
  • Safety concerns due to wandering or confusion
  • Need for structured, secure environment

๐Ÿฅ Skilled Nursing

24/7 medical care and supervision for complex health conditions and high care needs.

Typical Criteria:
  • MMSE Score: Variable (focus on medical needs)
  • ADL Score: 0-3 (Significant assistance required)
  • Complex medical conditions
  • Need for continuous nursing care

๐Ÿ‘ฅ Sample Patient Profiles

Understanding how different patient characteristics lead to specific care recommendations:

๐Ÿ“‹ Profile A: Independent Living Candidate

Demographics: 72-year-old female

Cognitive Status: MMSE 29, MoCA 27 (Excellent)

Functional Status: ADL 6, IADL 8 (Fully independent)

Mobility: Independent, low fall risk, drives

Social: Active social life, lives with spouse

Recommendation: Continue independent living with annual checkups

๐Ÿ“‹ Profile B: Home Care Candidate

Demographics: 76-year-old male

Cognitive Status: MMSE 24, MoCA 21 (Mild impairment)

Functional Status: ADL 5, IADL 4 (Needs help with complex tasks)

Mobility: Uses cane, medication management issues

Social: Lives alone, family nearby

Recommendation: Home care services for medication and meal support

๐Ÿ“‹ Profile C: Assisted Living Candidate

Demographics: 78-year-old male

Cognitive Status: MMSE 22, MoCA 19 (Mild impairment)

Functional Status: ADL 4, IADL 5 (Some assistance needed)

Mobility: Uses walker, medium fall risk

Social: Limited family support, lives alone

Recommendation: Assisted living for safety and social engagement

๐Ÿ“‹ Profile D: Memory Care Candidate

Demographics: 81-year-old female

Cognitive Status: MMSE 15, MoCA 12 (Moderate dementia)

Functional Status: ADL 3, IADL 2 (Significant assistance)

Mobility: Wandering behavior, high fall risk

Social: Family caregiver burnout

Recommendation: Memory care for specialized dementia support

๐Ÿ“‹ Profile E: Skilled Nursing Candidate

Demographics: 85-year-old male

Cognitive Status: MMSE 18 (Variable due to medical issues)

Functional Status: ADL 1, IADL 0 (Dependent in most areas)

Mobility: Wheelchair bound, multiple medical devices

Medical: Multiple comorbidities requiring nursing care

Recommendation: Skilled nursing for medical complexity

๐Ÿš€ Future Enhancement Suggestions

While our current 13-feature model is clinically sound, here are potential enhancements for even greater accuracy:

๐Ÿ“ˆ Phase 1: High-Value Additions (5-7 features)

๐Ÿฅ Healthcare Utilization

  • Hospitalization frequency (last 12 months)
  • Emergency department visits
  • Length of stay patterns

Impact: Predicts care instability and need for higher supervision

๐Ÿง  Behavioral Symptoms

  • Agitation or aggression frequency
  • Wandering or exit-seeking behavior
  • Sleep disturbances

Impact: Critical for memory care vs. assisted living decisions

๐Ÿ‘จโ€โš•๏ธ Caregiver Factors

  • Caregiver burden score
  • Caregiver health status
  • Hours of care provided daily

Impact: Determines sustainability of home-based care

๐Ÿ“Š Phase 2: Specialized Assessments (8-12 features)

๐Ÿ” Detailed Functional Breakdown

  • Individual ADL components (bathing, dressing, toileting, etc.)
  • Individual IADL components (cooking, finances, medication management)
  • Assistive device usage and effectiveness

๐Ÿ  Environmental Assessment

  • Home safety score
  • Accessibility features present
  • Transportation availability

๐ŸŽฏ Implementation Strategy

๐Ÿ”„ Iterative Approach

Add features gradually based on real-world usage data and prediction accuracy improvements

๐Ÿ“ฑ Optional Modules

Implement advanced features as optional sections to maintain simplicity for basic assessments

๐Ÿค– Smart Forms

Use conditional logic to show additional questions only when they would significantly impact predictions

๐Ÿ“Š A/B Testing

Compare prediction accuracy between 13-feature and enhanced models using real assessment data

๐Ÿฉบ Medical Assessment Details

Assessment Scales Used

๐Ÿง  MMSE (Mini-Mental State Exam)

Range: 0-30 points

Purpose: Cognitive function screening

Interpretation:

  • 24-30: Normal cognition
  • 18-23: Mild cognitive impairment
  • 0-17: Severe cognitive impairment

๐ŸŽฏ MoCA (Montreal Cognitive Assessment)

Range: 0-30 points

Purpose: Detailed cognitive screening

Interpretation:

  • 26-30: Normal
  • 18-25: Mild cognitive impairment
  • 0-17: Moderate to severe impairment

๐Ÿƒ ADL (Activities of Daily Living)

Range: 0-6 points

Purpose: Basic self-care abilities

Includes: Bathing, dressing, toileting, transferring, continence, feeding

Interpretation: Higher scores = more independence

๐Ÿ  IADL (Instrumental ADL)

Range: 0-8 points

Purpose: Complex daily tasks

Includes: Shopping, cooking, housekeeping, managing finances, medications

Interpretation: Higher scores = more independence

๐Ÿ˜” GDS (Geriatric Depression Scale)

Range: 0-15 points

Purpose: Depression screening

Interpretation:

  • 0-4: Normal
  • 5-8: Mild depression
  • 9-15: Severe depression

โš–๏ธ Additional Factors

Mobility: Independent, Walker, Wheelchair, Bedbound

Fall Risk: Low, Medium, High

Social Support: None, Low, Moderate, High

Living Situation: Alone, With Family, With Spouse

๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Family Assessment Details

Question Categories

๐Ÿง  Memory and Thinking

What it measures: Cognitive function in everyday terms

Sample questions:

  • "How well can they remember recent events?"
  • "Can they follow conversations and instructions?"

Converts to: MMSE and MoCA scores

๐Ÿƒ Daily Activities

What it measures: Independence in self-care and household tasks

Sample questions:

  • "How well can they handle personal care?"
  • "Can they manage household tasks?"

Converts to: ADL and IADL scores

โš–๏ธ Safety and Mobility

What it measures: Physical safety and movement ability

Sample questions:

  • "How well can they move around safely?"
  • "Do they have falls or near-falls?"

Converts to: Mobility level and fall risk

๐Ÿ˜Š Mood and Social Connection

What it measures: Emotional well-being and support systems

Sample questions:

  • "How is their overall mood?"
  • "How much family support do they have?"

Converts to: GDS score and social support level

Likert Scale Conversion

The family assessment uses 5-point Likert scales that are automatically converted to medical scores:

Likert Response Numeric Value MMSE Equivalent ADL Equivalent
Excellent / Very Good 5 28-30 6
Good 4 24-27 5
Fair 3 20-23 4
Poor 2 12-19 2-3
Very Poor 1 0-11 0-1

๐Ÿค– Machine Learning Model

Model Architecture

Technology Stack

Algorithm
XGBoost Classifier
Features
55 input features
Backend
Python + Frappe
Frontend
HTML5 + JavaScript
Preprocessing
StandardScaler
Output
5 care categories

Key Features

๐ŸŽฏ High Accuracy

Trained on comprehensive geriatric assessment data with validated clinical outcomes

๐Ÿ” Feature Importance

Shows which factors most influenced the recommendation (MMSE, ADL, age, etc.)

๐Ÿ“Š Confidence Scores

Provides probability scores for each care type to indicate certainty

โšก Real-time Processing

Instant predictions with detailed explanations and recommendations

๐Ÿ“– Usage Guidelines

For Healthcare Professionals

๐Ÿฉบ Best Practices

  • Use standardized assessment tools to gather accurate scores
  • Consider the patient's medical history and current conditions
  • Review feature importance to understand key decision factors
  • Use recommendations as a starting point for care planning discussions
  • Always incorporate clinical judgment and patient preferences

For Families and Caregivers

๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Best Practices

  • Take time to thoughtfully consider each question
  • Think about typical days, not just good or bad days
  • Consider safety as well as independence
  • Discuss results with healthcare providers
  • Use recommendations to guide conversations about care options
  • Remember that needs can change over time

๐Ÿ”„ Regular Reassessment

Care needs can change over time due to health changes, medication adjustments, or life events. It's recommended to reassess every 6-12 months or when significant changes occur in the person's condition or circumstances.

๐Ÿ“ž Support and Resources

Getting Started

๐Ÿฉบ Healthcare Professionals

Start with the Medical Assessment if you have clinical assessment scores available.

๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Families

Begin with the Family Assessment for a user-friendly experience.

Next Steps After Assessment

  1. Review Results: Understand the recommended care level and contributing factors
  2. Consult Professionals: Discuss findings with healthcare providers or geriatricians
  3. Research Options: Explore specific facilities or services in your area
  4. Visit and Evaluate: Tour potential care facilities or interview home care agencies
  5. Financial Planning: Understand costs, insurance coverage, and payment options
  6. Create Transition Plan: Develop timeline and support for any care changes

๐Ÿ’ก Remember

This assessment tool provides guidance based on functional status and care needs. The best care plan should always be developed collaboratively with healthcare professionals, the individual receiving care, and their family members, taking into account personal preferences, values, and unique circumstances.