RU2830457C2 - Method and system for determining the relative risk of insufficient glycemic control for several patients - Google Patents

Abstract

FIELD: medicine.

SUBSTANCE: group of inventions can be used to determine the relative risk of insufficient glycemic control for at least two patients. Disclosed is a method using the device and implemented by the system, comprising: providing a first set of glucose measurements assigned to a first patient, wherein the first set of glucose measurement data is collected by conducting measurement events with a first frequency; providing a second set of glucose measurements assigned to a second patient, wherein the second set of glucose measurements is collected by conducting measurement events with a second frequency that is different from the first measurement event frequency; providing a plurality of evaluation parameters in the data storage device, wherein each of the evaluation parameters is assigned to at least one of a first measurement event frequency and a second measurement event frequency; determining, depending on the first frequency of measurement events, at least one first evaluation parameter from the plurality of evaluation parameters in the data storage device; determining, depending on the second frequency of measurement events, of at least one second evaluation parameter, which differs from at least one first evaluation parameter from the plurality of evaluation parameters in the data storage device; determining the value of the first evaluation parameter assigned to the first patient for at least the first evaluation parameter; determining a value of a second evaluation parameter assigned to a second patient for at least a second evaluation parameter which is different from the first evaluation parameter; determining a first risk score assigned to the first patient and a second risk score assigned to the second patient based on the value of the first evaluation parameter and the value of the second evaluation parameter, respectively; and determining a relative risk of insufficient glycemic control by comparing a first overall risk score comprising a first risk score and a second overall risk score comprising a second risk score.

EFFECT: group of inventions provides determining the relative risk of insufficient glycemic control for several patients.

11 cl, 10 dwg, 2 tbl

Description

The invention relates to a computer-implemented method and system for determining the relative risk of inadequate glycemic control for several patients.

State of the art

Glucose measurement data collected for one or more patients can be analysed to provide caregivers with information on whether a patient needs assistance or support. There are different types of measurements that are used to collect glucose measurement data, such as blood glucose measurement data. Continuous glucose monitoring (CGM) can also be used. For this type of measurement, the frequency of measurement events (1/T) is very high, with a typical measurement time interval T of approximately 5 to 15 minutes, which allows for high-resolution analysis. In contrast, for patients for whom so-called spot monitoring (SPM) glucose (blood) measurements are taken, the number of samples per day is relatively small, for example 3 to 8 samples, and is generally unevenly distributed over time. Spot monitoring (SPM) blood glucose measurements can also be referred to as self-monitoring blood glucose (SMBG) measurements.

Document US 2009/0171589 A1 describes the calculation of the average daily range of risk (ADRR). The parameters "low blood glucose index (LBGI)" and "high blood glucose index (HBGI)" are mentioned in this document with subsequent references.

Document US 2015/0095042 A1 discloses classifying a patient as having a first, second or third risk of hypoglycemia in the future based on a value (e.g., LBGI value) that is calculated based on blood glucose levels, and displaying the classification on a display. In addition, it can be determined whether a pattern is present in the patient's blood glucose data. The order in which the patterns found are displayed can be prioritized.

Document EP 5062615 B1 relates to a system for monitoring, diagnosing and treating medical conditions of a plurality of remote patients, comprising a central data processing system, means for receiving patient data from the remote patient monitoring systems, means for analysing the received patient data from each respective patient monitoring system to determine the medical condition of each respective patient; means for displaying the determined patient medical condition for each respective patient in a selectable priority order according to the severity of the condition. Communication between portable patient monitors (PPMs) and the central data processing system, called a physician access centre server ("PAC server"), is described.

Document WO 2016/182972 A1 discloses classification of a plurality of patients into diabetes risk categories for caregivers.

Document US 2006/0253303 A1 relates to the provision of a system for monitoring a number of patients. An overview chart is provided in which each data point represents one corresponding patient and indicates a control value, such as an average value and the period of time that has passed since the collection date of the last set of measurements collected for the patient. In addition, each icon may indicate the compliance of the corresponding patient with the prescribed measurement regimen. In this way, a physician can simultaneously view and manage the medical priorities of an entire group of patients. This also allows the physician to proactively communicate with unmotivated patients who have lost contact with the physician before these patients develop urgent medical needs.

Document WO 2017/030961 A1 discloses a patient prioritization module that sorts and prioritizes patients of a healthcare provider based on the state of each patient. The alert sorting algorithm pre-assigns a weighting factor for each glucose value and for each possible state of this glucose value.

Document WO 2007/081853 A2 relates to a system, a computer program product, a method and an algorithm for estimating blood glucose. The method uses standard self-monitoring blood glucose data collected over a period of 2 to 6 weeks based on the theory of risk analysis of blood glucose data. The average daily risk range (ADRR) is calculated as an indicator of the overall variability of the glucose level. In addition, the variability of the glucose level in the hypoglycemic range using the low blood glucose index (LBGI) and the variability of the glucose level in the high glucose range using the high glucose index (HBGI) and then combining the two indices into a single variability display can be estimated separately.

The paper by Kovatchev et al. Risk analysis of blood glucose data: a quantitative approach to optimizing the control of insulin dependent diabetes, J. Theor. Med. 3,1-10 (2000), refers to quantitative tools for online assessment of the quality of optimization based on self-monitoring of blood glucose.

The paper by Kovatchev. Metrics for glycemic control from HbAlc to continuous glucose monitoring, Nature Rev. Endocrinology 13, 425-436 (2017) addresses the assessment, quantification, and optimal control of glucose fluctuations in diabetes mellitus, with a particular focus on markers of mean glycemia, and the utility and limitations of HbAlc as a gold standard indicator of glycemic control.

The paper by Kovatchev et al. Evaluation of a New Measure of Blood Glucose Variability in Diabetes, Diabetes Care 29:11, 2433–2438 (2006) refers to the average daily risk range (ADRR) as a measure of variability calculated from standard self-monitoring blood glucose (SMBG) data.

The essence of the invention

The purpose of this disclosure is to provide a computer-implemented method and system for determining a relative risk of inadequate glycemic control for a plurality of patients, wherein the method and system can be used to reliably determine the relative risk of inadequate glycemic control for glucose measurement data collected by performing measurements under different conditions.

To solve the problem, a computer-implemented method for determining the relative risk of insufficient glycemic control for at least two patients according to claim 1 of the invention is proposed. In addition, a system for determining the relative risk of insufficient glycemic control for at least two patients according to claim 9 of the invention is proposed. In addition, claim 11 of the invention describes a data storage device with a program code stored therein, which, when loaded into a computer having one or more processors, ensures the implementation of the method proposed in the invention.

According to one aspect of the invention, there is provided a computer-implemented method for determining a relative risk of inadequate glycemic control for at least two patients, implemented in a data processing device having one or more data processors and a data storage device connected to the one or more data processors, and comprising:

- providing a first set of glucose measurement data assigned to a first patient, wherein the first set of glucose measurement data is collected by conducting measurement events at a first frequency;

- providing a second set of glucose measurement data assigned to a second patient, wherein the second set of glucose measurement data is collected by conducting measurement events at a second frequency that is different from the first frequency of measurement events;

- providing in the data storage device of estimated parameters, each of which is assigned to at least one of the first frequency of measurement events and the second frequency of measurement events;

- determining, depending on the first frequency of measurement events, first evaluation parameters from the above-mentioned evaluation parameters in the data storage device, wherein the first evaluation parameters are selected from the following group of evaluation parameters: a low blood glucose index, a high blood glucose index, an average blood glucose level and a median blood glucose level;

- determining, depending on the second frequency of measurement events, second evaluation parameters from the above-mentioned evaluation parameters in the data storage device, wherein at least one of the determined second evaluation parameters differs from the first evaluation parameters, and the second evaluation parameters are selected from the following group of evaluation parameters: a low blood glucose index, a high blood glucose index, a stability index (SI), defined as the mean value of the second set of glucose measurement data divided by the standard deviation, and an average daily risk range (ADRR);

- determining from the first set of glucose measurement data the values of the first assessment parameters assigned to the first patient;

- determining from the second set of glucose measurement data the values of the second assessment parameters assigned to the second patient;

- determining the first risk assessments assigned to the first patient and the second risk assessments assigned to the second patient based on the values of the first assessment parameters and the values of the second assessment parameters, respectively; and

- determining the relative risk of inadequate glycemic control by comparing the first overall risk assessment and the second overall risk assessment, determined by summing the first and second risk assessments for the values of the first assessment parameters and the values of the second assessment parameters, respectively, wherein the relative risk indicates that for one of the first patient and the second patient the risk of inadequate glycemic control is higher,

wherein the method further comprises at least one of the following:

a) setting a first maximum achievable overall risk assessment and a first threshold value, upon exceeding which the ratio of the first overall risk assessment and the first maximum achievable overall risk assessment initiates sending an electronic message to the first patient with a proposal to increase the frequency of measurements, wherein the first set threshold value exceeds 0.5, in particular exceeds 0.8, preferably exceeds 0.9; and

b) setting a second maximum achievable overall risk assessment and a second threshold value, upon exceeding which the ratio of the second overall risk assessment and the second maximum achievable overall risk assessment initiates sending an electronic message to the second patient with a proposal to increase the frequency of measurements, wherein the second set threshold value exceeds 0.5, in particular exceeds 0.8, preferably exceeds 0.9.

According to another aspect of the invention, a system is proposed for determining the relative risk of insufficient glycemic control for at least two patients, comprising a data processing device having one or more data processors, and a data storage device connected to the one or more data processors, wherein the data processing device is configured to:

- providing a first set of glucose measurement data assigned to a first patient, wherein the first set of glucose measurement data is collected by conducting measurement events at a first frequency;

- providing a second set of glucose measurement data assigned to a second patient, wherein the second set of glucose measurement data is collected by conducting measurement events at a second frequency that is different from the first frequency of measurement events;

- providing in the data storage device of estimated parameters, each of which is assigned to at least one of the first frequency of measurement events and the second frequency of measurement events;

- determining, depending on the first frequency of measurement events, first evaluation parameters from the above-mentioned evaluation parameters in the data storage device, wherein the first evaluation parameters are selected from the following group of evaluation parameters: a low blood glucose index, a high blood glucose index, an average blood glucose level and a median blood glucose level;

- determining, depending on the second frequency of measurement events, second evaluation parameters from the above-mentioned evaluation parameters in the data storage device, wherein at least one of the determined second evaluation parameters differs from the first evaluation parameters, and the second evaluation parameters are selected from the following group of evaluation parameters: a low blood glucose index, a high blood glucose index, a stability index (SI), defined as the mean value of the second set of glucose measurement data divided by the standard deviation, and an average daily risk range (ADRR);

- determining from the first set of glucose measurement data the values of the first assessment parameters assigned to the first patient;

- determining from the second set of glucose measurement data the values of the second assessment parameters assigned to the second patient;

- determining the first risk assessments assigned to the first patient and the second risk assessments assigned to the second patient based on the values of the first assessment parameters and the values of the second assessment parameters, respectively; and

- determining the relative risk of inadequate glycemic control by comparing the first overall risk assessment and the second overall risk assessment, determined by summing the first and second risk assessments for the values of the first assessment parameters and the values of the second assessment parameters, respectively, wherein the relative risk indicates that for one of the first patient and the second patient the risk of inadequate glycemic control is higher,

wherein the data processing device is further configured to at least one of the following:

a) initiating the sending of an electronic message to the first patient with a proposal to increase the frequency of measurements if the ratio of the first overall risk assessment and the specified first maximum achievable overall risk assessment is above a first specified threshold value exceeding 0.5, in particular exceeding 0.8, preferably exceeding 0.9; and

b) initiating the sending of an electronic message to the second patient with a proposal to increase the frequency of measurements if the ratio of the second overall risk assessment and the specified second maximum achievable overall risk assessment is higher than a second specified threshold value exceeding 0.5, in particular exceeding 0.8, preferably exceeding 0.9.

In addition, a data storage device is proposed with a program code stored therein, which, when loaded into a computer having one or more processors, ensures the implementation of the method described above.

A relative risk indicating the risk of inadequate glycemic control may indicate that a patient or group of patients has a higher or more acute need for care or management than another patient or group of patients due to a different risk assessment. Such information may be provided to a healthcare provider or specialist, for example, by displaying audio and/or video data indicating the relative risk of inadequate glycemic control.

The first set of glucose measurement data and the second set of glucose measurement data can be obtained from at least one of spot monitoring blood glucose (SPM) measurements, which are also called self-monitoring blood glucose (SMBG) measurements and continuous glucose monitoring (CGM). The data processing device can, for example, receive the first set of glucose measurement data and the second set of glucose measurement data wirelessly from portable glucometers (for performing spot monitoring blood glucose measurements) and/or from continuous glucose monitoring devices (for continuous glucose monitoring).

To determine the first value of the assessment parameter, all measurement data or a subset of measurement data from the first set of submitted glucose measurement data may be analyzed. The same applies to determining the second value of the assessment parameter; all measurement data or a subset of measurement data from the second set of submitted glucose measurement data may be analyzed. For example, data obtained for more than 30 days or more than 14 days will not be analyzed to determine the relative risk of inadequate glycemic control.

In one embodiment, the first set of measurement data may comprise or consist of data obtained for no more than 30 days or no more than 14 days, and the second set of measurement data may comprise or consist of data obtained for no more than 30 days or no more than 14 days, to determine the relative risk of inadequate glycemic control.

Different measurement event rates are assigned different sets of evaluation parameters in the data storage device. Such assignment may be provided by assignment data stored in the data storage device. The assignment data may be stored in the data storage device in response to user input indicating the assignment. Alternatively, the assignment data may be obtained from some external source, such as a remote server device or a remote input device. After receiving the assignment data, the processor of the processing device may determine the evaluation parameters assigned to the first and second measurement event rates from the assignment data. The different measurement event rates may be assigned one evaluation parameter or a group of evaluation parameters.

The method may include at least one of the following: providing a first set of glucose measurement data collected in first spot glucose monitoring measurement events using a first frequency of measurement events; and providing a second set of glucose measurement data collected in second spot glucose monitoring measurement events using a second frequency of measurement events.

Depending on the frequency of measurement events performed during glucose measurements, different assessment parameters are used to determine the relative risk of inadequate glycemic control. However, the risk assessment determined for different sets of glucose measurement data, each attributed to one or more patients, can be compared to determine the relative risk of inadequate glycemic control. Based on this relative risk information, the physician can decide whether one patient needs counseling or support more than another patient.

For at least one of the first and second sets of glucose measurement data, the following may be provided: determining one or more consecutive glucose measurement values collected after collecting a previous glucose measurement value in a previous measurement event, wherein the one or more measurement values are collected in one or more consecutive measurements within a given time window after the previous measurement event; and excluding one or more consecutive glucose measurement values from determining the first/second value of the evaluation parameter. For example, only the very first glucose measurement value (obtained in the previous measurement event) may be taken into account for determining the first/second value of the evaluation parameter, wherein one or more consecutive glucose measurement values collected subsequently are excluded. Alternatively, an average or median value may be determined for one or more consecutive glucose measurement values and the previous glucose measurement value. Further, the average or median value may be taken into account for determining the first/second value of the evaluation parameter. In an embodiment, the given time window may be about 30 minutes or 60 minutes.

In the data storage device, the time window data may be stored, for example, in response to user input specifying a time window. In the process of determining one or more consecutive glucose measurement values, the time window data may be retrieved by one of the processors from the data storage device. Then, the time window defined by the time window data is determined by the processor and applied. In addition or as an alternative, numerical data may be stored in the data storage device, wherein the numerical data indicates a specified number of consecutive glucose measurement values that are to be excluded. The numerical data may be received in one or more processors from the data storage device and applied in the process of excluding one or more consecutive glucose measurement values.

As indicated above, the method may further comprise the following: determining from the first set of glucose measurement data a plurality of values of first assessment parameters assigned to the first patient, for the plurality of first assessment parameters; and determining from the second set of glucose measurement data a plurality of values of second assessment parameters assigned to the second patient, for the plurality of second assessment parameters. The first overall risk assessment and the second overall risk assessment may be determined by summing the first and second risk assessments for the plurality of values of the first assessment parameter and the plurality of values of the second assessment parameter, respectively. The overall risk assessments are compared to determine the relative risk of insufficient glycemic control.

For both the first evaluation parameters, i.e. in the set of first evaluation parameters, and for the second evaluation parameters, i.e. in the set of second evaluation parameters, at least one common evaluation parameter may be provided.

The method may provide the following: assigning a first set of glucose measurement data to a first patient suffering from type 1 diabetes mellitus; and assigning a second set of glucose measurement data to a second patient suffering from type 2 diabetes mellitus. Furthermore, the method may include selecting at least one of at least one first assessment parameter and at least one second assessment parameter depending on type 1 diabetes mellitus and type 2 diabetes mellitus, respectively. Additional assignment data may be stored in the data storage device, for example, in response to a user input indicating the assignment of the first set of glucose measurement data to the first patient suffering from type 1 diabetes mellitus and the assignment of the second set of glucose measurement data to the second patient suffering from type 2 diabetes mellitus. In addition or as an alternative, the additional assignment data may indicate a distribution between different types of diabetes mellitus on the one hand and different sets of assessment parameters on the other hand. In the process of determining the risk assessment(s), the additional assignment data may be retrieved from the data storage device. Then, the assignment of the evaluation parameter(s) determined by the additional assignment data is determined from the additional assignment data by the processor of the data processing device and applied.

The second patient may be different from the first patient. Alternatively, the first and second sets of glucose measurement data may be collected for the same patient, but relate to different measurement time windows for that patient. In such an alternative example, the first and second risk assessments relate to the analysis of glucose measurement data for the same individual (patient), but the first and second measurement data are collected in different measurement time windows for that patient, which is referred to as the first and second patients to distinguish between the first and second measurement data collected at different times.

As stated above, the first evaluation parameter and the second evaluation parameter may be selected from the following group of evaluation parameters: low blood glucose index, high blood glucose index, signs of complications, average blood glucose level, median blood glucose level, stability index, and total daily change in blood glucose level determined by summing the peak risks of hypoglycemia and hyperglycemia events per day. The stability index is the mean value of glucose measurement data for the patient divided by the standard deviation.

The first evaluation parameter or plurality of first evaluation parameters may be selected from the following group of evaluation parameters: low blood glucose index; high blood glucose index, signs of complications, average blood glucose level, and median blood glucose level.

As indicated above, the second assessment parameter or a plurality of second assessment parameters may be selected from the following group of assessment parameters: a low blood glucose index; a high blood glucose index, a stability index, and a change in the total daily blood glucose level determined by summing the peak risks of hypoglycemia and hyperglycemia events per day.

In one embodiment, the plurality of first evaluation parameters may include a low blood glucose index (LBGI); a high blood glucose index (HBGI), signs of complications (WS), and a median blood glucose level (median). The plurality of second evaluation parameters may include a low blood glucose index (LBGI); a high blood glucose index (HBGI), a stability index (SI), and a change in the total daily blood glucose level determined by summing the peak risks of hypoglycemia and hyperglycemia events per day (ADRR). The risk estimates for the plurality of values of the first evaluation parameter and the plurality of values of the second evaluation parameter, respectively, may be determined in accordance with Table 1.

The value of the parameter a for the signs of complications can be calculated as the risk variable of the sign of complications (WI3RV) according to equation (1):

where index i denotes events, with the weight of the event with index i being denoted as w _{i ,} and variable x _i ; represents a logical value depending on whether the event occurred (logical value = 1) or not (logical value = 0).

Events may include, for example, one or more of the following: recurrent hypoglycemia < 70 mg/dL; recurrent hyperglycemia > 300 mg/dL; recurrent severe hypoglycemia < 50 mg/dL; severe hypoglycemia < 40 mg/dL; and severe hyperglycemia > 400 mg/dL; where

recurrent hypoglycemia < 70 mg/dL (Rep Ho < 70) refers to two SMBG readings below 70 mg/dL on two consecutive days in the first set of glucose measurement data;

recurrent hyperglycemia >300 mg/dL (Rep He >300) refers to more than three SMBG readings greater than 300 mg/dL in the first set of glucose measurement data;

recurrent severe hypoglycemia < 50 mg/dL (Rep SHo < 50) refers to two SMB G readings below 50 mg/dL over two days in the first set of glucose measurement data;

severe hypoglycemia < 40 mg/dL (SHo < 40) refers to a single SMBG reading below 40 mg/dL in the first glucose measurement data set; and

severe hyperglycemia >400 mg/dL (SHe >400) refers to one SMBG reading greater than 400 mg/dL in the first set of glucose measurements.

Weights will be assigned to events depending on the type of diabetes of the first patient in accordance with Table 2.

For example, if the first patient's diabetes mellitus type is type 1 diabetes mellitus (TYPE 1) or latent autoimmune diabetes mellitus in adults (LADA), a weight of 3 might be assigned to the event of severe hyperglycemia > 400 mg/dL (She > 400), whereas if the first patient's diabetes mellitus type is type 2 diabetes mellitus (TYPE 2) or maturity-onset diabetes mellitus of the young (MODY) or OTHER, a weight of 1 might be assigned to the event of severe hyperglycemia > 400 mg/dL (She > 400).

In one embodiment, the first patient has diabetes mellitus type 1 or 2, and the second patient has diabetes mellitus type 1 or 2. In one embodiment, one of the first and second patients has diabetes mellitus type 1, and the other has diabetes mellitus type 2.

Exceeding at least one of the first overall risk assessment and the second overall risk assessment above a predetermined threshold may indicate a need for a review and/or adjustment of therapy for the first and second patients, respectively. Alternatively or in addition, exceeding at least one of the first overall risk assessment and the second overall risk assessment above a predetermined threshold may trigger sending an electronic message to the first patient and the second patient, respectively.

The specified threshold value may be stored and retrieved from the data storage device to determine whether there is a need for a therapy review and/or a therapy adjustment and/or to initiate an automatic electronic message sent to the patient(s) whose score exceeds the threshold value.

As noted above, when the ratio of the first overall risk estimate to the first maximum achievable overall risk estimate exceeds the first predetermined threshold, the first patient needs to be re-evaluated and/or adjusted. Additionally or alternatively, when the ratio of the first overall risk estimate to the first maximum achievable overall risk estimate exceeds the first predetermined threshold, an email may be sent to the first patient.

Similarly, if the ratio of the second overall risk estimate to the second maximum achievable overall risk estimate exceeds the second predetermined threshold, the second patient should be given a second treatment review and/or adjustment. Additionally or alternatively, if the ratio of the second overall risk estimate to the second maximum achievable overall risk estimate exceeds the second predetermined threshold, an email may be sent to the second patient.

The specified first maximum achievable overall risk score and the specified first threshold value may be stored and retrieved from the data storage device to determine whether there is a need for a therapy review and/or a therapy adjustment for the first patient and/or to initiate an automatic electronic message sent to the first patient if the first threshold value is exceeded. The specified second maximum achievable overall risk score and the specified second threshold value may be stored and retrieved from the data storage device to determine whether there is a need for a therapy review and/or a therapy adjustment for the second patient and/or to initiate an automatic electronic message sent to the second patient if the second threshold value is exceeded.

The message may contain one or more of the following elements: i) educational material on how to improve glycemic control, ii) a request for a meeting with a healthcare professional, iii) a proposal to increase the frequency of measurements. In one embodiment, the proposal to increase the frequency of measurements is sent only if the frequency of the patient's measurement events is lower than a predetermined frequency threshold value stored in the data storage device.

Output data indicating relative risk information may be displayed through a display device connected to the data processing device.

The embodiments disclosed for the above method may be applied to the system with appropriate modifications.

Implementation of the invention

Further embodiments are described below by way of example with reference to the figures. The figures illustrate the following:

Fig. 1 Schematic representation of a system for determining the relative risk of inadequate glycemic control for a plurality of patients;

Fig. 2 Schematic representation of a method for determining the relative risk of inadequate glycemic control for a plurality of patients;

Fig. 3 table containing weights for assessing signs of complications for different types of diabetes mellitus;

Fig. 4 is a table summarizing different groups of patients with diabetes mellitus and the corresponding indicators;

Fig. 5 is a table summarizing the assessment system and including various risk indicators;

Fig. 6 is a table containing risk estimates for 23 typical patients; and Fig. 7a-7d are four graphs of blood glucose (BG) values depending on the recording time for patients in different groups.

Fig. 1 schematically shows a representation of a system 1 for determining a relative risk of insufficient glycemic control for a plurality of patients, wherein the system 1 comprises a data processing device 2 having one or more data processors 3A. The data processing device 2, which may be implemented on a mobile or non-mobile device, further comprises a data storage device 36 operatively connected to the one or more data processors 3A for exchanging electronic data. The data processing device 2 receives measurement data indicative of a glucose level for one or more patients 5 from a measuring or analytical device 4. In a typical use case, measurement data indicative of a glucose level for at least two patients will be received. Measurements for different patients may be received from different measuring or analytical devices used by different patients. For example, each patient may use his or her personal measuring or analytical device to collect measurement data indicative of a patient's glucose level (in the blood). Alternatively, the measurement data, which may also be referred to as readings, may be obtained from one or more other data processing devices 6 that have previously obtained measurement data, such as from a plurality of measuring or analytical devices.

Fig. 2 schematically shows a computer-implemented method for determining the relative risk of inadequate glycemic control for at least two patients 5a, 56. Determining the relative risk of inadequate glycemic control involves assigning risk scores to the patients 5a, 56. In an (optional) first step 10, the measurement data collected in the SMBG (self-monitoring of blood glucose), which may also be referred to as a spot monitoring measurement (SPM), are cleaned. The measurement data representing SMBG readings or measurements (events) may need to be cleaned since some of the patients 5 may have recorded multiple SMBG readings within a short period of time. This is sometimes referred to as "over-monitoring", which may be due to increased monitoring during periods of changing glycemia or high-risk activities such as exercise. SMBG readings for the same patient that occur within a given period of time, such as 30 minutes or less, are removed from the input data during the cleansing. Alternatively, a specified time period of 60 minutes may be used. This way, the data is not distorted relative to such time periods.

Then, at step 20, at least two patients 5a, 5b are grouped. For example, each patient can be assigned to one of the following groups: G ₁ - patients who record on average less than two SMBG readings per day, and G _{2 -} users who record on average two or more SMBG readings per day. In an embodiment, groups G ₁ and G ₂ can represent SMBG readings of less than 2 (or less than 5) and > 2 (or > 5), respectively, per day for 14 days out of 30 consecutive days on which most recordings or measurements were made. SMBG readings of groups G ₁ and G ₂ represent a first frequency of measurement events and a second frequency of measurement events, respectively. In this example, the second frequency of measurement events is higher than the first frequency of measurement events.

For example, if a patient checks their SMBG at least twice a day for at least 14 days in the last 30 days, they will be classified in group G ₂ . Note that this measurement allows for days when patients record less frequently or not at all, as long as they have at least fourteen days that meet the above requirement. In addition, if another patient records at least 4 SMBG data every other day for 30 days, they will also be classified in group G ₂ .

Alternatively, groups G ₁ and G ₂ may also represent <2 (or <5) and >2 (or >5) SMBG readings, respectively, per day for 7 days out of 14 consecutive days on which the majority of recordings were made. The 2-week time frame may be advantageous because it only takes into account the most recent measurement data. Measurements that occur 30 days prior may be irrelevant to the patient's current therapy regimen or may be difficult to recall. However, on the other hand, 7 days out of 14 is less data to analyze.

Referring to Fig. 2, in step 30, risk scores are determined for patients 5 in groups G ₁ and G _2. Then, in step 40, the relative risk of inadequate glycemic control is determined by comparing the (overall) risk scores for patients 5a, 5b assigned to groups G ₁ and G ₂ .

Since groups G ₁ and G ₂ represent patients who had different frequencies of SMBG readings or measurements, a different measure(s) or a different set of measures (which may have at least one measure in common) is used for patients in the two different groups to determine individual risk estimates. The use of different measures allows the risk estimate determined for patients in groups G ₁ and G ₂ to be compared, thereby determining the relative risk of inadequate glycemic control. This relative risk may be higher for a patient in one or the other group depending on the actual SBMG readings or measurements. More than two patients can also be compared. In the case of i (i > 2) patients, the patients can be divided into groups G _j (j≤i).

A first indicator is proposed, which could be called ADRR (average daily risk range), where ADRR represents an adequate indicator of risk that allows comparison of the risks of inadequate glycemic control for patients 5 falling into different groups G ₁ and G ₂ .

To calculate the risk for high and low SMBG values, the HBGI (high blood glucose index) and LBGI (low blood glucose index) transformation equations (2) and (3) are used, as well as published risk values (see Kovatchev et al. (2000)).

Where

with B G denoting the recorded blood glucose value in the SMBG record,

And

if BG values are measured in milligrams per deciliter, or

if the values for B G are measured in millimoles per liter. The function r can be interpreted as an indicator of the risk associated with a certain level of B G. The function rl, depending on BG, represents a low risk, the function rh - a high risk. The function / is a continuous function defined in the range of BG from 1.1 to 33.3 millimoles per liter. Its form can be obtained as described in Kovatchev et al. (2000).

It is known that LBGI and HBGI provide an assessment of patients’ glycemic control, covering both the risk of hypoglycemia and the risk of hyperglycemia, respectively. LB GI and HB GI are not time-dependent variables. They are a transformation and normalization of SMBG values to provide an equal risk scale for hypoglycemia and hyperglycemia. In addition, they are known to gradually increase with the increase in the severity and frequency of hypoglycemic and hyperglycemic events. Therefore, LB GI and HBGI were applied to all 5 patients in each group _G1 and _G2 , which allowed obtaining comparable indicators for patients with low and high SMBG frequency.

Based on the LBGI and HB GI values, the ADRR is calculated. ADRR provides an estimate of the risk of total daily variation in blood glucose levels, i.e. the sum of the peak risks of hypoglycemia and hyperglycemia events per day. ADRR is calculated as follows:

Where

The number of readings per day i is denoted by n _i , and the blood glucose level data per day i c (see WO 2007/081853 and Kovatchev et al. (2006)).

M is the total number of stumps for which ADRR is calculated.

A few readings per day may be sufficient to calculate the ADRR. Alternatively, a minimum of three (or five) SMB G readings are used to calculate the ADRR.

The Stability Index (SI) is the mean of a patient's glucose measurements divided by the standard deviation (SI = μ/δ). A minimum of two SBGM readings or measurements per day are required to calculate a reasonable standard deviation. Alternatively, a minimum of three (or five) SMBG readings are used to calculate the SI.

Because both ADRR and SI require a minimum number of indications for use, two additional indices were developed to represent comparable risk for patients with low incidence (group G ₁ ). These indices are discussed below. Because HB GI and LB GI do not require a minimum number of SMB G indications, HB GI and LB GI are used for all patients 5 (G ₁ and G ₂ ) to determine the risk of high and low glycemic excursion.

The median of the SMBG values of patients in group G ₁ may be used as an equivalent metric for ADRR. In one embodiment, the mean of the SMBG values of patients in group G ₁ may be used. However, the median is less sensitive to outliers than the mean.

As an equivalent of SI, WS scores are used as a way to create a G ₁ risk score that is comparable to the G ₂ SI risk score.

If a patient meets the requirements for a certain percentage of WS, he or she is considered to be insufficiently stable. WS can be weighed with healthcare providers (depending on the type of diabetes) to determine the appropriate risk as follows.

The parameter value for the complication signs can be calculated as the complication signs risk variable (WSRV), which is calculated according to equation (1) above.

Below is an example of how to calculate WSRV for a patient. The patient has had Rep Hypo (BG < 70 mg/dL) and Rep Severe Hypo (BG < 50 mg/dL) readings in the last month.

The patient had neither a hyperglycemic event nor a severe hypoglycemic event. The following values were obtained:

Substituting the values into equation (1) yields:

Following the table in Fig. 5, the patient falls into the intermediate risk category for the complication features. Thus, for the WS risk score or the SMBG magnitude (MM) score, the patient is assigned a score of 2. The patient also received a medium risk score for the low SMBG (LM) score = 2, no risk for the high SMB G (HM) score = 0, and low risk = 1 for the average (AM) score (e.g., ADRR or median).

Thus, the patient's overall risk assessment is:

A patient's overall risk score can also be described as the ratio of the patient's overall risk score to the maximum achievable overall risk score for that patient.

The weights are set in such a way that they can be adjusted according to the patient's needs.

In another embodiment (e.g., for patients with type 2 diabetes mellitus), severe hyperglycemic events (> 400 mg/dL) may be weighted more heavily than recurrent hypoglycemic events (< 70 mg/dL). The weight values in Fig. 3 for patients with type 2 may, for example, be modified as follows:

WS can be used as follows:

- The set of readings contains hypoglycemia events below 70 mg/dL, where two SMBG values below 70 mg/dL on two consecutive days constitute a hypoglycemia event. To determine if a hypoglycemia event is occurring, recurring events are looked for. For example, values BG 67 (day 1), BG 56 (day 2), BG 50 (day 6), BG 65 (day 7) contain two events for BG below 70 mg/dL on 2 recurring days.

- In a set of indications, search for a hyperglycemia event greater than 300 mg/dL, where the hyperglycemia event corresponds to more than three SMBG indications greater than 300 mg/dL.

- In the indication set, search for an acute hypoglycemia event below 50 mg/dL, with two consecutive SMBG values below 50 mg/dL over two days.

- In a set of indications, search for one very acute hypoglycemia event corresponding to one indication below 40 mg/dL.

- In a set of indications, search for one very acute hyperglycemia event corresponding to one indication above 400 mg/dL.

The weight of WS depends on the type of diabetes. For example, a recurring high BG value in a patient with type 1 diabetes may be more or less important than a recommendation for a patient with type 2 diabetes.

Thus, in addition to dividing the 5 patients into groups G ₁ and G ₂ , the 5 patients are also divided into the following types of diabetes mellitus to determine the corresponding weight: type 1 diabetes mellitus, LAD A (latent autoimmune diabetes mellitus of adults); type 2 diabetes mellitus, MODY (maturity-onset diabetes of the young), NOT LISTED (diabetes mellitus not specified), OTHER; and GEST (gestational diabetes mellitus).

The weights (absolute and normalized to 100%) for the _G1 group and each type are shown in Fig. 3. The table can also be used to determine trends in the G2 group, but not for risk assessment. The weights were estimated and normalized for the assessment analysis as described above. Gestational diabetes mellitus (GEST) and pregnant diabetics form a separate group. Gestational WS are more stringent than all other WS (for both mother and child). Thus, their assessment differs from the other types (see the last two rows of the table in Fig. 3).

Referring to Fig. 3, gestational diabetes mellitus is scored based on the following indicators: low SMBG values (hypoglycemic events); high SMBG values (hyperglycemic events); morning fasting SMBG values greater than 92 mg/dL; and any hyperglycemic event in 24 hours greater than 140 mg/dL. This scoring is similar to groups G ₁ and G ₂ , except for the last two items in Fig. 3. The last two indicators in the table in Fig. 3 are set up the same as for WS, except that when the patient meets the requirements, he or she is assigned the highest possible score.

Each of the groups G ₁ and G ₂ includes indicators comparable to the risk classification (high, low, stable and average daily value). Risk levels are assigned to the corresponding assessments (assessment - risk): 0 - no risk; 5 - low risk; 2 - medium risk; and 3 - high risk.

Figure 4 shows a table summarizing the values used for the different _G1 , _G2, and GEST groups of patients with diabetes 5 to determine the individual risk score for the different groups and to take into account the relative risk of inadequate glycemic control. The term "fasting morning hyperglycemia" refers to any BG value obtained before 9 a.m. that is greater than 92 mg/dL. This usually corresponds to not eating (fasting) in the middle of the night. The term "24-hour hyperglycemia" refers to any BG value in 24 hours that is greater than 140 mg/dL. These values are set very conservatively because they apply to the child and the mother.

Fig. 5 shows a table that summarizes the scoring system and includes various risk indicators. The scoring criteria for various indicators such as LBGI, HBGI, and ADRR are shown. Scores from 0 to 3 are used, and such scores refer to no risk (0), low risk (1), moderate risk (2), and high risk (3).

In Fig. 5, A1C refers to (HbAlc). If the patient has the corresponding WS percentage, he is assigned the corresponding assessment category from 0 to 3. Average risk values refer to hemoglobin A1C (HbAlC) below 7.0%, 8.0%, 9.0% and more than 9.0%.

An alternative scoring system is described in Table 1 above.

Figure 6 shows a table containing risk scores for 23 typical patients. The table is divided into an upper and lower part for better display. The columns of the lower part continue the columns of the upper part of the table. The first column ("User") lists the 23 patients from 1 to 23. The risk scores for all four risk categories (see Figure 5) were summed to determine the overall risk score ("Score" in Figure 6, upper part in Figure 6) for groups G ₁ and G ₂ . For example, the overall risk score for patient 1 in Figure 6 is 11 (a score of 3 for "HGBI Risk" plus a score of 3 for "BG Risk" plus a score of 3 for "ADRR Risk" plus a score of 2 for "SI Risk").

For the two groups G ₁ and G _2, different indicators were applied. For example, the indicators "Risk ADRR" (ADRR) and "Risk SI" (SI) were not applied to the group G ₁ . For the group G _2, "Risk BG" and "Risk WS" (WS) were not applied. The absence of application or failure to consider any indicator is indicated by "NaN" in Fig. 6.

The lower part of Fig. 6 shows the actual values (not risk estimates) for HBGI, LBGI, SI, WS, and ADRR. "RSHypo" corresponds to a recurrent severe hypoglycemic event with BG < 50 mg/dL, "RHypo" corresponds to a recurrent hypoglycemic event with BG < 70 mg/dL, and "SH" corresponds to a severe hypoglycemic event with BG < 40 mg/dL.

Subsequently, patients 5 in groups G ₁ and G ₂ were sorted from highest to lowest overall risk. The individual overall risk determined for groups G ₁ and G ₂ can provide healthcare professionals with the opportunity to screen by "diabetes type" and "risk score" to determine which patients 5 most need support.

The WS complication indicators from previous days can be used for automatic messaging, for example, to a healthcare provider. For example, an automatic message is sent each time the user experiences severe hypoglycemia below 40 mg/dL. If during the week (or specified time period) the patient reaches a certain threshold determined by the healthcare provider, the healthcare provider can be notified and can contact the patient directly. This means that automatic messages or notifications can help patients 5 with low need for support, while patients 5 with higher risk can be treated personally by the healthcare provider.

Figures 7a-7d show four graphs of BG values (SMBG readings) versus recording or measurement time for different patients. Each graph represents one of four patients 5 in the following four groups with the following overall risk, defined as described above: G ₁ , intermediate risk (Figure 7a); G2, high risk (Figure 7b); G _1, high risk (Figure 7c); and G ₂ , no risk (Figure 7d). The desired range of BG values is 70 mg/dL to 180 mg/dL.

Claims (42)

1. A computer-implemented method for determining the relative risk of inadequate glycemic control for at least two patients, carried out in a data processing device (2) having one or more data processing processors (3a) and a data storage device (3b) connected to the one or more data processing processors (3a), and comprising: - providing a first set of glucose measurement data assigned to a first patient, wherein the first set of glucose measurement data is collected by conducting measurement events at a first frequency; - providing a second set of glucose measurement data assigned to a second patient, wherein the second set of glucose measurement data is collected by conducting measurement events at a second frequency that is different from the first frequency of measurement events; - providing in the device (3b) for storing data of estimated parameters, each of which is assigned to at least one of the first frequency of measurement events and the second frequency of measurement events; - determining, depending on the first frequency of measurement events, first evaluation parameters from the above-mentioned evaluation parameters in the data storage device (3b), wherein the first evaluation parameters are selected from the following group of evaluation parameters: low blood glucose index, high blood glucose index, average blood glucose level and median blood glucose level; - determining, depending on the second frequency of measurement events, second evaluation parameters from the above-mentioned evaluation parameters in the data storage device (3b), wherein at least one of the determined second evaluation parameters differs from the first evaluation parameters, and the second evaluation parameters are selected from the following group of evaluation parameters: a low blood glucose index, a high blood glucose index, a stability index (SI), defined as the mean value of the second set of glucose measurement data divided by the standard deviation, and an average daily risk range (ADRR); - determining from the first set of glucose measurement data the values of the first assessment parameters assigned to the first patient; - determining from the second set of glucose measurement data the values of the second assessment parameters assigned to the second patient; - determining the first risk assessments assigned to the first patient and the second risk assessments assigned to the second patient based on the values of the first assessment parameters and the values of the second assessment parameters, respectively; and - determining the relative risk of inadequate glycemic control by comparing the first overall risk assessment and the second overall risk assessment, determined by summing the first and second risk assessments for the values of the first assessment parameters and the values of the second assessment parameters, respectively, wherein the relative risk indicates that for one of the first patient and the second patient the risk of inadequate glycemic control is higher, wherein the method further comprises at least one of the following: (a) setting the first maximum achievable overall risk assessment and the first threshold value, upon exceeding which the ratio of the first overall risk assessment and the first maximum achievable overall risk assessment initiates sending an electronic message to the first patient with a proposal to increase the frequency of measurements, wherein the first set threshold value exceeds 0.5; and b) setting a second maximum achievable overall risk assessment and a second threshold value, upon exceeding which the ratio of the second overall risk assessment and the second maximum achievable overall risk assessment initiates sending an electronic message to the second patient with a proposal to increase the frequency of measurements, wherein the second set threshold value exceeds 0.5. 2. The method according to claim 1, comprising at least one of the following: - providing a first set of glucose measurement data collected in first spot glucose monitoring measurement events using a first measurement event rate; and - providing a second set of glucose measurement data collected in second spot glucose monitoring measurement events using a second measurement event frequency. 3. The method according to claim 1 or 2, comprising for at least one of the first and second sets of glucose measurement data: - determining one or more consecutive glucose measurement values collected after the collection of a previous glucose measurement value in a previous measurement event, wherein the one or more measurement values are collected in one or more consecutive measurement events within a specified time window after the previous measurement event; and - excluding one or more consecutive glucose measurement values from the determination of the first/second value of the evaluation parameter. 4. The method according to one of the preceding paragraphs, wherein at least one common evaluation parameter is provided for both the first evaluation parameters and the second evaluation parameters. 5. The method according to one of the preceding paragraphs, in which - the first set of glucose measurement data is assigned to the first patient suffering from type 1 diabetes mellitus; and - the second set of glucose measurement data is assigned to the second patient suffering from type 2 diabetes mellitus; wherein the method further comprises selecting at least one first evaluation parameter and/or at least one second evaluation parameter depending on type 1 diabetes mellitus and type 2 diabetes mellitus, respectively. 6. The method according to one of the preceding paragraphs, wherein the second patient is different from the first patient. 7. The method according to one of the preceding claims, wherein exceeding at least one of the first overall risk assessment and the second overall risk assessment a predetermined threshold value indicates a need for revision and/or adjustment of therapy for the first and second patient, respectively. 8. The method according to one of the preceding claims, wherein the first and/or second predetermined threshold value exceeds 0.7, in particular exceeds 0.8, preferably exceeds 0.9. 9. A system for determining the relative risk of insufficient glycemic control for at least two patients, comprising a data processing device (2) having one or more data processors (3a) and a data storage device (3b) connected to the one or more data processors (3a), wherein the data processing device (2) is configured to: - providing a first set of glucose measurement data assigned to a first patient, wherein the first set of glucose measurement data is collected by conducting measurement events at a first frequency; - providing a second set of glucose measurement data assigned to a second patient, wherein the second set of glucose measurement data is collected by conducting measurement events at a second frequency that is different from the first frequency of measurement events; - providing in the device (3b) for storing data of estimated parameters, each of which is assigned to at least one of the first frequency of measurement events and the second frequency of measurement events; - determining, depending on the first frequency of measurement events, first evaluation parameters from the above-mentioned evaluation parameters in the data storage device (3b), wherein the first evaluation parameters are selected from the following group of evaluation parameters: low blood glucose index, high blood glucose index, average blood glucose level and median blood glucose level; - determining, depending on the second frequency of measurement events, second evaluation parameters from the above-mentioned evaluation parameters in the data storage device (3b), wherein at least one of the determined second evaluation parameters differs from the first evaluation parameters, and the second evaluation parameters are selected from the following group of evaluation parameters: a low blood glucose index, a high blood glucose index, a stability index (SI), defined as the mean value of the second set of glucose measurement data divided by the standard deviation, and an average daily risk range (ADRR); - determining from the first set of glucose measurement data the values of the first assessment parameters assigned to the first patient; - determining from the second set of glucose measurement data the values of the second assessment parameters assigned to the second patient; - determining the first risk assessments assigned to the first patient and the second risk assessments assigned to the second patient based on the values of the first assessment parameters and the values of the second assessment parameters, respectively; and - determining the relative risk of inadequate glycemic control by comparing the first overall risk assessment and the second overall risk assessment, determined by summing the first and second risk assessments for the values of the first assessment parameters and the values of the second assessment parameters, respectively, wherein the relative risk indicates that for one of the first patient and the second patient the risk of inadequate glycemic control is higher, wherein the data processing device is further configured to do at least one of the following: (a) initiating the sending of an electronic message to the first patient with a proposal to increase the frequency of measurements if the ratio of the first overall risk estimate to the specified first maximum achievable overall risk estimate is above the first specified threshold value exceeding 0.5; and b) initiating the sending of an electronic message to the second patient with a proposal to increase the frequency of measurements if the ratio of the second overall risk assessment to the specified second maximum achievable overall risk assessment is above a second specified threshold value exceeding 0.5. 10. The system according to claim 9, wherein the first and/or second specified threshold value exceeds 0.7, in particular exceeds 0.8, preferably exceeds 0.9. 11. A data storage device with a program code stored therein, which, when loaded into a computer having one or more processors, ensures the execution of the method according to one of paragraphs 1-8.