
    Develop an algorithm to calculate the number of possible sequences of patient risk assessments over n consecutive post-discharge days, where each day can be classified into one of k risk categories, with the constraint that a patient cannot remain in the same risk category for more than two consecutive days due to intervention protocols. The solution will help healthcare providers anticipate potential patterns in patient behavior and plan interventions accordingly.
    

    
def count_no_of_ways(n, k):
    """
    Develop an algorithm to calculate the number of possible sequences of patient risk assessments over n consecutive post-discharge days, where each day can be classified into one of k risk categories, with the constraint that a patient cannot remain in the same risk category for more than two consecutive days due to intervention protocols. The solution will help healthcare providers anticipate potential patterns in patient behavior and plan interventions accordingly.
    

    """
def count_no_of_ways(n, k):
    """
    Develop an algorithm to calculate the number of possible sequences of patient risk assessments over n consecutive post-discharge days, where each day can be classified into one of k risk categories, with the constraint that a patient cannot remain in the same risk category for more than two consecutive days due to intervention protocols. The solution will help healthcare providers anticipate potential patterns in patient behavior and plan interventions accordingly.
    

    """
    dp = [0] * (n + 1)
    total = k
    mod = 1000000007
    dp[1] = k
    dp[2] = k * k
    for i in range(3, n + 1):
        dp[i] = (k - 1) * (dp[i - 1] + dp[i - 2]) % mod
    return dp[n]