
    Given a patient's current calculated risk score, determine the next standardized risk assessment threshold, which is represented by the next perfect square number above the current score, to properly categorize and monitor patient readmission risk. The risk assessment model requires perfect square values as standardized threshold boundaries, and identifying the next threshold helps healthcare providers implement appropriate monitoring protocols.
    

    
import math

def next_Perfect_Square(N):
    """
    Given a patient's current calculated risk score, determine the next standardized risk assessment threshold, which is represented by the next perfect square number above the current score, to properly categorize and monitor patient readmission risk. The risk assessment model requires perfect square values as standardized threshold boundaries, and identifying the next threshold helps healthcare providers implement appropriate monitoring protocols.
    

    """
import math

def next_Perfect_Square(N):
    """
    Given a patient's current calculated risk score, determine the next standardized risk assessment threshold, which is represented by the next perfect square number above the current score, to properly categorize and monitor patient readmission risk. The risk assessment model requires perfect square values as standardized threshold boundaries, and identifying the next threshold helps healthcare providers implement appropriate monitoring protocols.
    

    """
    nextN = math.floor(math.sqrt(N)) + 1
    return nextN * nextN