A computer-implemented method of monitoring glycemia of a patient, the method comprising: storing a patient's data that includes glucose measurements; generating a hypoglycemic pattern, wherein the generating comprises; obtaining a number of glucose measurements over a total time period; dividing the total time period into a plurality of time intervals; determining a percentage of hypoglycemic incidence for each of the time intervals wherein the time interval recurs daily and is equal to one eighth of a day; determining whether the percentage of hypoglycemic incidence for at least one of the time intervals is statistically different using a chi-squared test, wherein the chi-squared test uses a confidence level ranging from 95% to 99%, wherein the number of glucose measurements is greater than 20, comprising calculating chi-squared χ 2 using the following: χ 2 = ∑ i = 1 n L i − L i, pre 2 L i. pre + ∑ i = 1 n L i ′ − L i, pre ′ 2 L i. pre ′ where χ 2 = chi-squared, i represents a particular time interval, n is a total number of time intervals, L i is a number of substantially hypoglycemic glucose concentration measurements that occur during time interval i, L i,pre is a predicted number of hypoglycemic glucose concentration measurements that will occur during time interval i, and L i ' is a number of non-hypoglycemic glucose concentration measurements that occur during time interval i, L i, pre ′ is a predicted number of non-hypoglycemic glucose concentration measurements that will occur interval time i; comparing a calculated χ 2 to a χ 2 value in a table based on a number of degrees of freedom for each of the time intervals i; and determining that at least one of the time intervals are statistically different if the calculated χ 2 is greater than the χ 2 value on the table; calculating L i, pre and L i, pre ′ using estimation equations comprising: L i, pre = ∑ i = 1 n L i ∑ i = 1 n N i ∗ N i and L i, pre ′ = ∑ i = 1 n L i ′ ∑ i = 1 n N i ∗ N i where N i represents the total number of glucose concentration measurements performed during timer interval i; using a Z- test to identify one of the time intervals as statistically different, comprising calculating Z i using a Z test, the Z test comprising: Z i = L i − L i, pre SE i where Z i represents a Z value at a particular time interval i and SE i represents a standard error for a particular time interval i; comparing a calculated Z i, to a Z value in a table; and identifying that one of the time intervals is statistically different if the calculated Z i is greater than the Z value; and displaying a message indicating a high incidence of hypoglycemia occurring on a particular time interval if the hypoglycemic incidence is greater than a pre-determined threshold, wherein the determining steps are performed by a computer program. storing a patient's data that includes glucose measurements; generating a hypoglycemic pattern, wherein the generating comprises; obtaining a number of glucose measurements over a total time period; dividing the total time period into a plurality of time intervals; determining a percentage of hypoglycemic incidence for each of the time intervals wherein the time interval recurs daily and is equal to one eighth of a day; determining whether the percentage of hypoglycemic incidence for at least one of the time intervals is statistically different using a chi-squared test, wherein the chi-squared test uses a confidence level ranging from 95% to 99%, wherein the number of glucose measurements is greater than 20, comprising calculating chi-squared χ 2 using the following: χ 2 = ∑ i = 1 n L i − L i, pre 2 L i. pre + ∑ i = 1 n L i ′ − L i, pre ′ 2 L i. pre ′ where χ 2 = chi-squared, i represents a particular time interval, n is a total number of time intervals, L i is a number of substantially hypoglycemic glucose concentration measurements that occur during time interval i, L i,pre is a predicted number of hypoglycemic glucose concentration measurements that will occur during time interval i, and L i ' is a number of non-hypoglycemic glucose concentration measurements that occur during time interval i, L i, pre ′ is a predicted number of non-hypoglycemic glucose concentration measurements that will occur interval time i; comparing a calculated χ 2 to a χ 2 value in a table based on a number of degrees of freedom for each of the time intervals i; and determining that at least one of the time intervals are statistically different if the calculated χ 2 is greater than the χ 2 value on the table; calculating L i, pre and L i, pre ′ using estimation equations comprising: L i, pre = ∑ i = 1 n L i ∑ i = 1 n N i ∗ N i and L i, pre ′ = ∑ i = 1 n L i ′ ∑ i = 1 n N i ∗ N i where N i represents the total number of glucose concentration measurements performed during timer interval i; using a Z- test to identify one of the time intervals as statistically different, comprising calculating Z i using a Z test, the Z test comprising: Z i = L i − L i, pre SE i where Z i represents a Z value at a particular time interval i and SE i represents a standard error for a particular time interval i; comparing a calculated Z i, to a Z value in a table; and identifying that one of the time intervals is statistically different if the calculated Z i is greater than the Z value; and displaying a message indicating a high incidence of hypoglycemia occurring on a particular time interval if the hypoglycemic incidence is greater than a pre-determined threshold, wherein the determining steps are performed by a computer program.