
    In a hospital's readmission risk monitoring system, develop a function that calculates the nth risk threshold value in the established pattern sequence, where each value is determined by adding the two preceding risk scores, starting with initial values of 2 and 1. This predictive model helps healthcare providers identify critical monitoring periods for patients based on historical readmission patterns.
    

    
def find_lucas(n):
    """
    In a hospital's readmission risk monitoring system, develop a function that calculates the nth risk threshold value in the established pattern sequence, where each value is determined by adding the two preceding risk scores, starting with initial values of 2 and 1. This predictive model helps healthcare providers identify critical monitoring periods for patients based on historical readmission patterns.
    

    """
def find_lucas(n):
    """
    In a hospital's readmission risk monitoring system, develop a function that calculates the nth risk threshold value in the established pattern sequence, where each value is determined by adding the two preceding risk scores, starting with initial values of 2 and 1. This predictive model helps healthcare providers identify critical monitoring periods for patients based on historical readmission patterns.
    

    """
    if n == 0:
        return 2
    if n == 1:
        return 1
    return find_lucas(n - 1) + find_lucas(n - 2)