def categorize_data(md):
    """
    Categorize medical data (MD) based on sensitivity level (SL).
    
    Args:
        md (dict): Medical data to be categorized.
    
    Returns:
        dict: Categorized data with sensitivity level.
    """
    # Stage I: Determining Sensitivity Level
    sensitivity_criteria = {
        "public": 1,
        "widespread": 2,
        "restricted": 3,
        "limited": 4,
        "highly_restricted": 5
    }
    
    # Example criteria based on predefined logic
    if 'type' in md:
        if md['type'] == "public_info":
            sl = sensitivity_criteria["public"]
        elif md['type'] == "research_data":
            sl = sensitivity_criteria["widespread"]
        elif md['type'] == "internal_project":
            sl = sensitivity_criteria["restricted"]
        elif md['type'] == "consultation":
            sl = sensitivity_criteria["limited"]
        elif md['type'] == "sensitive_health_data":
            sl = sensitivity_criteria["highly_restricted"]
        else:
            raise ValueError("Unknown medical data type!")
    else:
        raise KeyError("Medical data type is missing!")
    
    # Stage II: Categorizing data
    categorized_data = {
        'data': md,
        'sensitivity': sl
    }
    
    # Stage III: Returning categorized data
    return categorized_data