
    Given historical hourly patient volumes in the emergency room, determine the highest potential patient load impact by calculating the maximum product of any increasing sequence of hourly visit counts. This calculation will help identify the most critical staffing demands during periods of escalating patient volumes and optimize resource allocation during peak times.
    

    
def max_product(arr):
    """
    Given historical hourly patient volumes in the emergency room, determine the highest potential patient load impact by calculating the maximum product of any increasing sequence of hourly visit counts. This calculation will help identify the most critical staffing demands during periods of escalating patient volumes and optimize resource allocation during peak times.
    

    """
def max_product(arr):
    """
    Given historical hourly patient volumes in the emergency room, determine the highest potential patient load impact by calculating the maximum product of any increasing sequence of hourly visit counts. This calculation will help identify the most critical staffing demands during periods of escalating patient volumes and optimize resource allocation during peak times.
    

    """
    n = len(arr)
    mpis = arr[:]
    for i in range(n):
        current_prod = arr[i]
        j = i + 1
        while j < n:
            if arr[j - 1] > arr[j]:
                break
            current_prod *= arr[j]
            if current_prod > mpis[j]:
                mpis[j] = current_prod
            j = j + 1
    return max(mpis)