Healthcare

Clinical Pathway Selection

Decision system that determines optimal treatment pathways based on diagnosis severity, comorbidities, and patient characteristics for personalized care plans.

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Solution

This clinical pathway selection system guides healthcare providers in choosing appropriate treatment regimens tailored to individual patient needs. The system evaluates primary diagnosis and severity score to determine the clinical domain and establish a base risk assessment. It factors in comorbidities, giving special attention to high-risk conditions like kidney disease, COPD, and immunocompromised status to calculate additional risk factors.

The evaluation includes patient-specific factors such as age and BMI to further refine risk stratification. Based on comprehensive risk scoring, the system recommends one of three care pathways: standard, enhanced, or intensive, each with specific follow-up frequencies and monitoring requirements. This ensures patients receive proportionate care based on their clinical needs, optimizing resource allocation while maintaining quality care standards.

How it works

The decision graph evaluates patients through multiple assessment nodes:

  1. Initial Diagnosis Assessment: Categorizes the primary diagnosis (heart failure, pneumonia, diabetes, stroke) into clinical domains and assigns a base risk score.
  2. Comorbidity Evaluation: Counts total comorbidities and identifies high-risk conditions (kidney disease, COPD, immunocompromised status) to calculate a comorbidity risk score.
  3. Patient Factor Analysis: Evaluates age and BMI to determine additional risk factors and assigns a patient risk category.
  4. Pathway Selection: Uses the total risk score to route patients to one of three treatment pathways:
    • Intensive Pathway: Daily follow-up with comprehensive monitoring for high-risk patients
    • Enhanced Pathway: Twice-weekly follow-up with extended monitoring for moderate-risk patients
    • Standard Pathway: Weekly follow-up with basic monitoring for lower-risk patients

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