
    In a hospital's patient readmission risk analysis system, develop a function that determines the maximum batch size (as a power of 2) for processing patient records, ensuring it doesn't exceed the total number of available patient records. This batch size optimization will ensure efficient allocation of computational resources while analyzing readmission patterns in the hospital's predictive analytics pipeline.
    

    
def highest_Power_of_2(n):
    """
    In a hospital's patient readmission risk analysis system, develop a function that determines the maximum batch size (as a power of 2) for processing patient records, ensuring it doesn't exceed the total number of available patient records. This batch size optimization will ensure efficient allocation of computational resources while analyzing readmission patterns in the hospital's predictive analytics pipeline.
    

    """
def highest_Power_of_2(n):
    """
    In a hospital's patient readmission risk analysis system, develop a function that determines the maximum batch size (as a power of 2) for processing patient records, ensuring it doesn't exceed the total number of available patient records. This batch size optimization will ensure efficient allocation of computational resources while analyzing readmission patterns in the hospital's predictive analytics pipeline.
    

    """
    res = 0
    for i in range(n, 0, -1):
        if i & i - 1 == 0:
            res = i
            break
    return res