Patent Application
20070276197
These and other features, aspects, and advantages of the present invention will become better understood with regard to the following description, appended claims, and accompanying drawings where:
As shown, data source 102 is connected to processing station 106 via communications link 104 and may comprise any known or future developed wired or wireless communications link. Examples of communications link 104 include a direct serial or USB cable, a TCP/IP or Ethernet based network connection and a wireless connection using protocols such as IEEE 802.11, InfraRed or Bluetooth. Alternatively, data source 102 can be connected directly to processing station 106 via an appropriate cable or the like.
Processing station 106 preferably includes a device to save and store information (e.g., a memory, a disk drive, or other removable storage device, a database, etc.) and a device to process data (e.g., a central processing unit or CPU) from data source 102 using algorithms within and desired software, such as within program 112. Examples of processing station 106 include a personal or networked computer, a personal digital assistant (PDA), a blood glucose metering system, and a mobile telephone. Examples of input devices 108 include, a keyboard, keypad, a mouse, a joystick, a stylet, as well as others which are usable with central processing unit devices. Examples of visual display 110 include, a display monitor for a personal or networked computer, and a Liquid Crystal Display (LCD) for a personal digital assistant (PDA), mobile telephone, and a blood glucose metering system. Alternatively, one or more lights, such as LED's, may be used on the device to communicate information by glowing and/or blinking. Examples of output devices 114 include, a printer, a fax machine, an email message, a text message, and a file that is stored to memory on processing station 106.
Processing station 106 further includes computer program or instructions 112 for providing exception-based pattern analysis in combination with exception-based reporting in accordance with the present invention. Exception-based pattern analysis can automatically notify the professional user (e.g. a physician or nurse practitioner, or anyone with an administrative function) or a patient user when any physician-defined metric or condition established in advanced is not being met or is being met. Exception-based reporting is designed to focus the attention of the professional user or a patient user on the exceptions to planned compliance to treatment and/or to praise appropriate behavior.
In general, data is collected by metering device 102 over a time period and typically includes plural samples. Exception based pattern analysis is preferably used to analyze the collected data and provide alerts, messages, or other information to a user (patient or professional). Pattern analysis preferably is used to identify general trends or patterns in data that is collected over time or from a number of samples. Exception based pattern analysis is generally a way in which to identify data which may fall outside acceptable data limits, and preferably exceptions to data limits of the disease management regimen. Pattern analysis rules are used to set acceptance levels for data in disease management. By looking for occurrences and/or average of occurrences that are outside acceptance limits, it may be apparent that the patient is not subscribing to the treatment regimen, or that there are other problems in the way that the disease is being treated or managed.
In a system in which the disease management can be customized to a patient, it is desirable that characteristics of a patient and their disease be assessed by a physician or other medical personnel such that the impact and significance associated with each of the pattern analysis rules is customized to the particular patient. For example, for glucose management, a rule might be set to track the number of times a glucose measurement or an average of all measurements is outside of a range, such as indirectly hypoglycemic or hyperglycemic conditions such a rule may be “report when averages for last 14 days are 20% below/over target or above upper target” where the impact is set to negative and the significance is set to the middle between low and high. Thus, every time the average over the last 14 days is outside the predetermined range, the rule is considered violated and, an exception is triggered. Once the exception is triggered, program 112 is configured to determine, based on the impact and significance parameters and the settings for reporting, whether a report, alert, or other indicator should be provided to a patient and/or professional user. The impact level and significance parameters and the settings for reporting are typically set by the professional user as detailed and explained below.
Computer program 112 preferably controls processing station 106 to perform many steps. Computer program 112 preferably utilizes standard user interfaces (e.g. menus and dialogs) to permit a user to access its functions. Computer program 112 may be written in any computer language, such as, for example, structured query language (SQL), Visual Basic, C++, as a matter of design choice and may be stored on any computer-readable memory device such as a hard drive coupled with a computer processing unit such as processing station 106.
Computer program 112 preferably includes both an exception-based pattern analysis unit and an exception-based reporting unit. Each of these units may be viewed as subroutines, or subprograms of computer program 112. Alternatively, these units can be separate programs which are called and initialized by computer program 112. Pattern analysis and reporting units may provide access to algorithms provided in software 112 or other separate software also provided in memory of device 106 for data sorting and analysis as well as expert system tools to help users control processes of computer program 112. Input data from data source 102 is incorporated into computer program 112 and the exception-based pattern analysis unit analyzes input data to determine if specific pattern criteria are met. The exception-based reporting unit then preferably generates reports for a patient user and an associated professional user (e.g., a physician, a diabetes educator, or a nurse). Such reports may be generated and viewed on any of a variety of devices, including device 102, processing station 106, display 110, and printer 114.
Optionally, the professional user may select in any order the physician-defined pattern analysis rules and provide settings therefore. The professional user may be a physician, nurse, other medical technician, data input personnel, any other administrative personnel, etc., having access to computer program 112. Also, a physician or other healthcare provider may redefine the physician-defined pattern analysis rules to customize to a particular disease or individual. The professional user may chose to select or not to select any of the pattern analysis rules, as well, depending upon the course of treatment for a patient user.
For each pattern analysis rule that a professional user selects, the professional user may set the limits for reporting the exceptions to and the properties of that pattern analysis rule. Limits are preferably set according to the rule and may include, for example, a duration (e.g., hours or days) and a percentage. For example, a physician may wish to set up the properties of a rule such that if the data source 102 measurement is on average at least 20% below the target for 2 days, then action (alarm, alert, report, etc.) is triggered. Properties that may be set up may also include an impact 210 and a significance 216. Impact may be a determination as to whether the measurement associated with the rule will have a positive or negative impact on the health of the patient. Significance may be how important the impact associated with the rule will be to the health of the patient. The significance may be viewed as a weighting of the impact to the rule. Further, the significance and impact may be viewed as rule parameters, among others that may be used to trigger reporting activities. The professional user may set impact 210 by clicking on a radio button preceding either Negative 212 or Positive 214 for each pattern analysis rule. The professional user may set significance 216 of a pattern analysis rule at either Low 218 or High 220 or some designation in between Low 218 or High 220 by moving a sliding bar 221 on a sliding scale. Thus, based upon a professional user's analysis or assessment of a patient, a professional user may decide whether violation (or compliance) of the rule has a negative or positive effect on a patient's treatment and how significant the violation (or compliance) with that rule is to the particular patient's treatment, including consideration of individual characteristics of the patient, (i.e., how the patient is likely to respond during disease management). Alternatively, other user interface setting options and mechanisms may be used, such as numerical choices, drop down menus, buttons, not limited to the radio buttons and slider bar illustrated in
Still referring to
In accordance with the present invention, TARGET AND LIMITS 222 tab preferably includes sections for setting one or more rules for an OVERALL AVERAGE OUTSIDE OF TARGET 232, an OVERALL TESTING IS WITHIN TARGET 234, a PATTERN OF LOW RESULTS 236, and a PATTERN OF HIGH RESULTS 238. For OVERALL AVERAGE OUTSIDE OF TARGET 232, a professional user may select limits X and Y for reporting exceptions by checking a box 240 preceding “Report when overall average for last X day(s) is Y % below lower target or above upper target” and by entering values for X and Y in boxes 242 and 244 (
If an exception to this pattern analysis rule is triggered by collecting data over time, then a patient user may be prompted with the following exemplary statement: “Your overall average is not within your target range (you may want to discuss with your physician ways to improve your level of control by changes to your diet, insulin, and/or medication),” as shown in a reporting box 246. Interface window 200 provides customization of the trigger messages, e.g. as a text box allowing input thereto, or alternatively by a drop down or other access to predetermined message lists. A professional user may set the messages in reporting boxes 246, 250, 256 and 260 to be customized to a particular patient and to a particular disease. Computer program 112 may determine if the criteria for an exception to this pattern analysis rule are met and then may determine if the criteria for reporting this exception to a patient user are met. As an alternative to conventional systems, the present invention advantageously provides customization of the rules by the use of the impact and significance parameters determined via the physician's assessment of the patient's characteristics and the disease. The significance parameter is used in such a way that only rule violations that have at least a specified minimum significance are aggregated until a time is reached when the reporting criteria are met. Once the reporting criteria are met, the message is provided to the patient or professional user in order to affect behavior of the patient or for use by the physician as a way to better manage the patient's disease treatment.
For OVERALL TESTING IS WITHIN TARGET 234, a professional user may select limits Y and X for reporting exceptions by checking a box 248 preceding “Report when Y % or more of all results for the last X day(s) is (are) within lower and upper targets” and by entering values for Y and X. Y may range from about 0 percent to 100 percent and X may range from about 0 days to 21 days. A professional user may also select a percent by toggling up and down arrows adjacent to percent box 244. A professional user also may select a number of days by toggling up and down arrows adjacent to days box 242. A professional user can also select impact 210 by clicking a radio button preceding either Negative 212 or Positive 214 (as discussed previously) and by sliding bar 221 for significance 216 (as discussed previously). If an exception to this pattern analysis rule is triggered, then a patient user may be prompted with the following exemplary statement: “Congratulations, overall you are staying within your target range (you may want to discuss with your physicians the reasons for your success and the benefits to your health)” as shown in a reporting box 250. In this case, the message is positive which, when provided to a patient user may provide positive reinforcement to the patient user in order to reinforce the patient's good management of the patient's disease. Computer program 112 preferably determines if the criteria for an exception to this pattern analysis rule are met and may determine if the criteria for reporting this exception to a patient user are met, as described in more detail below.
For PATTERN OF LOW RESULTS 236, a professional user may select limits Z and X for reporting exceptions by checking a box 252 preceding a selection for “Report when Z or more (or less) low results in last X day(s)” and by entering values for Z and X in boxes 254 and 242 respectively. Z may range from about 0 to about 5 and X may range from about 0 days to about 21 days. A professional user may also select a number of low results by toggling up and down arrows adjacent to a numbers box 254. A professional user may also select a number of days by toggling up and down arrows adjacent to days box 242. A professional user can also select impact 210 by clicking a radio button preceding either Negative 212 or Positive 214 (as discussed previously) and by sliding bar 221 for significance 216 (as discussed previously). If an exception to this pattern analysis rule is triggered, then the patient user may be prompted with the following exemplary statement: “You are experiencing a pattern of low results (you may want to discuss with your physician the reasons for this fall and whether changes to insulin and/or medications is required to reduce the risk of complications)” as shown by a reporting box 256. In this case, the message is negative which, when provided to a patient user may provide negative reinforcement to the patient user in order to reinforce the patient's poor management of the patient's disease or to alert the patient that the treatment provided by a medical personnel is not effective and may need to be modified. Computer program 112 preferably determines if the criteria for an exception to this pattern analysis rule are met and may determine if the criteria for reporting this exception to a patient user are met, as described in more detail below.
For PATTERN OF HIGH RESULTS 238, a professional user may select limits Z and X for reporting exceptions by checking a box 258 preceding a selection for “Report when Z or more (or less) high results in last X day(s),” and by entering values for Z and X. Z may range from about 0 to about 10 and X may range from about 0 day to about 21 days. A professional user may also select a number of high results by toggling up and down arrows adjacent to numbers box 254. A professional user may also select a number of days by toggling up and down arrows adjacent to days box 242. A professional user can then select impact 210 by clicking a radio button preceding either Negative 212 or Positive 214 (as discussed previously) and by sliding bar 221 for significance 216 (as discussed previously). If an exception to this pattern analysis rule is triggered, then a patient user may be prompted with the following statement: “You are experiencing a pattern of high results (you may want to discuss with your physician the reasons for this fall and whether changes to insulin and/or medications is required to reduce the risk of complications)” as shown in a reporting box 260. In this case, the message is negative which, when provided to a patient user may provide negative reinforcement to the patient user in order to reinforce the patient's poor management of the patient's disease or to alert the patient that the treatment provided by a medical personnel is not effective and may need to be modified. Computer program 112 preferably determines if the criteria for an exception to this pattern analysis rule are met and may determine if the criteria for reporting this exception to a patient user are met, as described in more detail below.
It should be noted that for all of the pattern analysis rules 232, 234, 236 and 238, the system may not be limited to the rules shown and described. Any number of pattern analysis rules may be implemented in accordance with the present invention. The system shown and described provides a great deal of user flexibility by giving the users the ability to create nearly any type of rule.
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As shown in
In addition to the rules listed in Table I and described previously, those skilled in the art will recognize that the limit statements can be provided as “positive” rules instead of “negative” rules. For example, the first limit statement in Table I could be written as “Report when overall standard deviation for last_day(s) is less than_mg/dL. Rules may also be included for other measured values (e.g., HbAlc results for a diabetic patient) or to implement an intensive insulin therapy protocol for use by nurses at the point-of-care. Also, the impact setting may be characterized as a less than or greater than setting.
For MINIMUM THRESHOLD FOR REPORTING EXCEPTIONS 312, a professional user may activate the rule either by checking a box 328 preceding the selection for “Report only negative impact exceptions with a minimum significance of:” and/or by checking a box 330 preceding a selection for “Report only positive impact exceptions with a minimum significance of.” In either case, a professional may select a significance 216 by dragging a tab 332 of a sliding scale toward either a Low 334 or a High 336 end of the scale. The significance setting here may be generally seen as a rule parameter threshold setting. Upon assessing the patient characteristics, a physician preferably determines what rules, when violated, may most significantly impact the patient's disease management. Therefore by changing the significance settings, a professional user is able to control which rules should be monitored to manage the patient's disease in the most significant way.
For MAXIMUM REPEATABILITY OF EXCEPTIONS REPORTED 314, a professional user may set either by checking a box 338 preceding a selection for “Report a specific negative impact exception a maximum of Z time(s) for every E exception(s) reported or X day(s)” and/or by checking a box 340 preceding a selection for “Report a specific positive impact exception a maximum of Z time(s) for every E exception(s) reported or X day(s)” where Z may range from about 1 to about 10, E may range from about 1 to 5, and X may range from about 1 day to about 21 days. A professional user may set a number of times a specific negative or positive impact exception is reported by toggling up and down arrows adjacent to numbers box 320. The professional user may set the rate at which a specific negative or positive impact is reported by toggling up and down arrows adjacent to a frequency box 342 and by clicking on a radio button 344 preceding “exceptions” or by clicking on a radio button 346 preceding “day(s).” To accept all of the appropriate reporting rates for all patients, the professional user clicks an APPLY button 348 or an OK button 350 and to cancel without accepting any changes to the reporting rates the professional user clicks a CANCEL button 352.
To obtain more information about any feature in this window a professional user may click on an information button 354. Although a number of specific settings and ranges of settings have been provided, the invention is not limited to those disclosed. Other settings and ranges of settings in accordance with the present invention may be used.
At least one patient-specific, physician-defined pattern analysis rule is defined and programmed into the system 100 and at least one limit for reporting the at least one patient-specific, physician-defined rule is set, as set forth in steps 620 and 630, respectively, and as illustrated in
At least one property for triggering the at least one patient-specific, physician-defined rule is set by a physician as set forth in step 640 and as illustrated in
At least one rate for reporting the at least one patient-specific, physician-defined rule is preferably set by the physician as set forth by step 650 and as illustrated in
Next, at least one patient-specific, physician-defined rule is triggered when at least one result or at least one lifestyle event is expected or recorded as set forth by step 660. Computer program 112 preferably tracks exceptions and whether or not they are reported, which can be used for processing future pattern analysis exceptions. When input data is recorded or expected, computer program 112 analyzes pattern analysis rules and determines if an exception to any pattern analysis rule is triggered. If a pattern analysis rule is triggered then computer program 112 preferably determines if an exception to a reporting rate is triggered.
Computer program 112 then preferably provides an exception-based pattern analysis report to the physician or displays a suggestion to the patient on a metering system or to a physician or patient on an alternative output device as set forth by step 670. When computer program 112 determines an exception to a pattern analysis rule and a reporting rate is triggered, computer program 112 preferably generates a patient summary 512 that is displayed on a visual display 502 of a metering system 504 for a patient user. Computer program 112 also preferably generates the professional report 400 for the professional user when data from data source 102 is transferred to processing station 106 of professional user.
The software components as described above may comprise a stand alone computer program 112 or a computer module integrated into an existing computer program 112 such as, for example, the OneTouch™ Diabetes Management Software from LifeScan, Inc. In either configuration, computer program 112 preferably allows processing station 106 to accept data from data sources 102, to store incoming data, to process accepted and stored data using a main computer program 112 and a plurality of associated plug-ins in conjunction with a set of physician-defined control options, and to generate statements for both a patient user and the professional user to see.
Criteria of analysis and criteria of reporting are preferably stored in a non-volatile semiconductor storage element such as a ROM, flash memory, or a non-volatile storage device such as a hard disk or the like so that individual criterion can be added, deleted or modified as needed by the professional user. The function of each unit is realized by cooperative operation of hardware and computer program 112.
The present invention has now been described with reference to several embodiments thereof. The entire disclosure of any patent or patent application identified herein is hereby incorporated by reference. The foregoing detailed description and examples have been given for clarity of understanding only. No unnecessary limitations are to be understood therefrom. It will be apparent to those skilled in the art that many changes can be made in the embodiments described without departing from the scope of the invention. Thus, the scope of the present invention should not be limited to the structures described herein, but only by the structures described by the language of the claims and the equivalents of those structures.
