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Zhongwei Li
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skills/treatment-plans/scripts/validate_treatment_plan.py
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367
skills/treatment-plans/scripts/validate_treatment_plan.py
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#!/usr/bin/env python3
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"""
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Validate Treatment Plan Quality
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Comprehensive validation of treatment plan content quality and compliance.
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"""
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import sys
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import re
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import argparse
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from pathlib import Path
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from typing import Dict, List, Tuple
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# Validation criteria and patterns
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VALIDATION_CHECKS = {
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'smart_goals': {
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'name': 'SMART Goals Criteria',
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'patterns': [
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(r'\bspecific\b', 'Specific criterion'),
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(r'\bmeasurable\b', 'Measurable criterion'),
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(r'\bachievable\b', 'Achievable criterion'),
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(r'\brelevant\b', 'Relevant criterion'),
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(r'\btime[- ]?bound\b', 'Time-bound criterion')
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]
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},
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'evidence_based': {
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'name': 'Evidence-Based Practice',
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'patterns': [
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(r'guideline|evidence|study|trial|research', 'Evidence/guideline references'),
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(r'\\cite\{|\\bibitem\{|\\bibliography\{', 'Citations present')
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]
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},
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'patient_centered': {
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'name': 'Patient-Centered Care',
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'patterns': [
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(r'patient.*preference|shared decision|patient.*value|patient.*priority', 'Patient preferences'),
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(r'quality of life|functional.*goal|patient.*goal', 'Functional/QoL goals')
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]
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},
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'safety': {
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'name': 'Safety and Risk Mitigation',
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'patterns': [
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(r'adverse.*effect|side effect|risk|complication', 'Adverse effects mentioned'),
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(r'monitoring|warning sign|emergency|when to call', 'Safety monitoring plan')
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]
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},
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'medication': {
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'name': 'Medication Documentation',
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'patterns': [
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(r'\\d+\s*mg|\\d+\s*mcg|dose|dosage', 'Specific doses'),
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(r'daily|BID|TID|QID|once|twice', 'Frequency specified'),
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(r'rationale|indication|because|for', 'Rationale provided')
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]
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}
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}
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def read_file(filepath: Path) -> str:
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"""Read and return file contents."""
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try:
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with open(filepath, 'r', encoding='utf-8') as f:
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return f.read()
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except Exception as e:
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print(f"Error reading file: {e}", file=sys.stderr)
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sys.exit(2)
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def validate_content(content: str) -> Dict[str, Tuple[int, int, List[str]]]:
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"""
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Validate content against criteria.
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Returns dict with results: {category: (passed, total, missing_items)}
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"""
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results = {}
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for category, checks in VALIDATION_CHECKS.items():
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patterns = checks['patterns']
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passed = 0
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missing = []
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for pattern, description in patterns:
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if re.search(pattern, content, re.IGNORECASE):
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passed += 1
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else:
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missing.append(description)
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total = len(patterns)
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results[category] = (passed, total, missing)
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return results
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def check_icd10_codes(content: str) -> Tuple[bool, int]:
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"""Check for ICD-10 code presence."""
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# ICD-10 format: Letter followed by 2 digits, optionally more digits/letters
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pattern = r'\b[A-TV-Z]\d{2}\.?[\dA-TV-Z]*\b'
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matches = re.findall(pattern, content)
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has_codes = len(matches) > 0
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count = len(matches)
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return has_codes, count
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def check_timeframes(content: str) -> Tuple[bool, List[str]]:
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"""Check for specific timeframes in goals."""
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timeframe_patterns = [
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r'\d+\s*week',
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r'\d+\s*month',
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r'\d+\s*day',
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r'within\s+\d+',
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r'by\s+\w+\s+\d+'
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]
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found_timeframes = []
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for pattern in timeframe_patterns:
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matches = re.findall(pattern, content, re.IGNORECASE)
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found_timeframes.extend(matches[:3]) # Limit to avoid too many
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has_timeframes = len(found_timeframes) > 0
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return has_timeframes, found_timeframes[:5]
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def check_quantitative_goals(content: str) -> Tuple[bool, List[str]]:
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"""Check for quantitative/measurable goals."""
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# Look for numbers with units in goal context
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patterns = [
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r'\d+\s*%', # Percentages (HbA1c 7%)
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r'\d+/\d+', # Ratios (BP 130/80)
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r'\d+\s*mg/dL', # Lab values
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r'\d+\s*mmHg', # Blood pressure
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r'\d+\s*feet|meters', # Distance
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r'\d+\s*pounds|lbs|kg', # Weight
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r'\d+/10', # Pain scales
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r'\d+\s*minutes|hours' # Time
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]
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found_metrics = []
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for pattern in patterns:
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matches = re.findall(pattern, content, re.IGNORECASE)
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found_metrics.extend(matches[:2])
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has_metrics = len(found_metrics) > 0
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return has_metrics, found_metrics[:5]
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def assess_readability(content: str) -> str:
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"""Basic readability assessment (very simplified)."""
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# Remove LaTeX commands for word count
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text_content = re.sub(r'\\[a-zA-Z]+(\{[^}]*\})?', '', content)
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text_content = re.sub(r'[{}%\\]', '', text_content)
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words = text_content.split()
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word_count = len(words)
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# Very rough sentences (periods followed by space/newline)
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sentences = re.split(r'[.!?]+\s+', text_content)
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sentence_count = len([s for s in sentences if s.strip()])
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if sentence_count > 0:
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avg_words_per_sentence = word_count / sentence_count
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if avg_words_per_sentence < 15:
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return "Simple (good for patient materials)"
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elif avg_words_per_sentence < 25:
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return "Moderate (appropriate for professional documentation)"
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else:
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return "Complex (may be difficult for some readers)"
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return "Unable to assess"
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def display_validation_results(filepath: Path, results: Dict,
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has_icd10: bool, icd10_count: int,
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has_timeframes: bool, timeframe_examples: List[str],
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has_metrics: bool, metric_examples: List[str],
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readability: str):
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"""Display comprehensive validation results."""
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print("\n" + "="*70)
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print("TREATMENT PLAN QUALITY VALIDATION")
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print("="*70)
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print(f"\nFile: {filepath}")
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print(f"File size: {filepath.stat().st_size:,} bytes")
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# Overall quality score
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total_passed = sum(r[0] for r in results.values())
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total_checks = sum(r[1] for r in results.values())
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quality_pct = (total_passed / total_checks) * 100 if total_checks > 0 else 0
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print("\n" + "-"*70)
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print("OVERALL QUALITY SCORE")
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print("-"*70)
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print(f"Validation checks passed: {total_passed}/{total_checks} ({quality_pct:.0f}%)")
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# Detailed category results
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print("\n" + "-"*70)
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print("QUALITY CRITERIA ASSESSMENT")
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print("-"*70)
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for category, (passed, total, missing) in results.items():
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category_name = VALIDATION_CHECKS[category]['name']
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pct = (passed / total) * 100 if total > 0 else 0
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status = "✓" if passed == total else "⚠" if passed > 0 else "✗"
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print(f"\n{status} {category_name}: {passed}/{total} ({pct:.0f}%)")
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if missing:
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print(" Missing:")
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for item in missing:
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print(f" • {item}")
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# Specific checks
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print("\n" + "-"*70)
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print("SPECIFIC VALIDATION CHECKS")
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print("-"*70)
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# ICD-10 codes
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if has_icd10:
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print(f"✓ ICD-10 diagnosis codes present ({icd10_count} found)")
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else:
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print("✗ No ICD-10 diagnosis codes detected")
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print(" Recommendation: Include ICD-10 codes for all diagnoses")
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# Timeframes
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if has_timeframes:
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print(f"✓ Time-bound goals present")
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if timeframe_examples:
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print(" Examples:", ", ".join(timeframe_examples[:3]))
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else:
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print("✗ No specific timeframes found in goals")
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print(" Recommendation: Add specific timeframes (e.g., 'within 3 months', '8 weeks')")
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# Measurable metrics
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if has_metrics:
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print(f"✓ Quantitative/measurable goals present")
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if metric_examples:
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print(" Examples:", ", ".join(metric_examples[:3]))
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else:
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print("⚠ Limited quantitative metrics found")
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print(" Recommendation: Include specific measurable targets (HbA1c <7%, BP <130/80)")
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# Readability
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print(f"\nReadability assessment: {readability}")
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# Summary and recommendations
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print("\n" + "="*70)
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print("SUMMARY AND RECOMMENDATIONS")
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print("="*70)
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if quality_pct >= 90:
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print("\n✓ EXCELLENT quality - Treatment plan meets high standards")
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elif quality_pct >= 75:
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print("\n✓ GOOD quality - Treatment plan is well-developed with minor areas for improvement")
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elif quality_pct >= 60:
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print("\n⚠ FAIR quality - Several important elements need strengthening")
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else:
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print("\n✗ NEEDS IMPROVEMENT - Significant quality issues to address")
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# Specific recommendations
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print("\nKey Recommendations:")
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recommendations = []
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# SMART goals
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if results['smart_goals'][0] < results['smart_goals'][1]:
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recommendations.append("Ensure all goals meet SMART criteria (Specific, Measurable, Achievable, Relevant, Time-bound)")
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# Evidence-based
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if results['evidence_based'][0] == 0:
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recommendations.append("Add evidence-based rationale and cite clinical practice guidelines")
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# Patient-centered
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if results['patient_centered'][0] < results['patient_centered'][1]:
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recommendations.append("Incorporate patient preferences and functional quality-of-life goals")
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# Safety
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if results['safety'][0] < results['safety'][1]:
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recommendations.append("Include comprehensive safety monitoring and risk mitigation strategies")
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# Medication documentation
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if results['medication'][0] < results['medication'][1]:
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recommendations.append("Document medications with specific doses, frequencies, and rationales")
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if not has_icd10:
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recommendations.append("Add ICD-10 diagnosis codes for billing and documentation support")
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if not has_timeframes:
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recommendations.append("Add specific timeframes to all treatment goals")
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if recommendations:
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for i, rec in enumerate(recommendations, 1):
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print(f"{i}. {rec}")
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else:
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print("None - Treatment plan demonstrates excellent quality across all criteria!")
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print("\n" + "="*70)
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# Return exit code
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return 0 if quality_pct >= 70 else 1
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def main():
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parser = argparse.ArgumentParser(
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description='Validate treatment plan quality and compliance',
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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# Validate a treatment plan
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python validate_treatment_plan.py my_plan.tex
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# Use in automated workflows (exits with error if quality <70%)
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python validate_treatment_plan.py plan.tex && echo "Quality check passed"
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Validation Categories:
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- SMART goals criteria (Specific, Measurable, Achievable, Relevant, Time-bound)
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- Evidence-based practice (guidelines, citations)
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- Patient-centered care (preferences, functional goals)
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- Safety and risk mitigation (adverse effects, monitoring)
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- Medication documentation (doses, frequencies, rationales)
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- ICD-10 coding, timeframes, measurable metrics
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Exit Codes:
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0 - Quality ≥70% (acceptable)
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1 - Quality <70% (needs improvement)
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2 - File error or invalid arguments
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"""
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)
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parser.add_argument(
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'file',
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type=Path,
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help='Treatment plan file to validate (.tex format)'
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)
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args = parser.parse_args()
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# Check file exists
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if not args.file.exists():
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print(f"Error: File not found: {args.file}", file=sys.stderr)
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sys.exit(2)
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# Read and validate
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content = read_file(args.file)
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# Run validation checks
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results = validate_content(content)
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has_icd10, icd10_count = check_icd10_codes(content)
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has_timeframes, timeframe_examples = check_timeframes(content)
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has_metrics, metric_examples = check_quantitative_goals(content)
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readability = assess_readability(content)
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# Display results
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exit_code = display_validation_results(
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args.file, results,
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has_icd10, icd10_count,
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has_timeframes, timeframe_examples,
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has_metrics, metric_examples,
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readability
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)
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sys.exit(exit_code)
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if __name__ == '__main__':
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main()
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