WO2005087091A2 - Medical data display - Google Patents
Medical data display Download PDFInfo
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- WO2005087091A2 WO2005087091A2 PCT/GB2005/000980 GB2005000980W WO2005087091A2 WO 2005087091 A2 WO2005087091 A2 WO 2005087091A2 GB 2005000980 W GB2005000980 W GB 2005000980W WO 2005087091 A2 WO2005087091 A2 WO 2005087091A2
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- patient
- parameter
- values
- display
- condition
- Prior art date
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Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
- A61B5/087—Measuring breath flow
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/63—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
Definitions
- the present invention relates to a method and apparatus for displaying medical data, particularly data indicative of the current state of a chronic medical condition in a form which can be delivered easily to a patient and is easily understandable by them.
- asthma is a chronic condition which requires self-management by patients.
- the self-management is by use of an inhaler administering a pharmacological agent for management of the condition, for example by administration of a drug such as a steroid in powdered form by using an inhaler.
- a drug such as a steroid in powdered form by using an inhaler.
- the patient is required to keep a patient diary in which they record their symptoms, their use of the inhaler, and in which they also record measurements of their condition taken using a device such as a respiratory flow meter for measuring their Peak Expired Flow Rate (PEFR) and forced expired volume (FEV1 - integrated volume of air exhaled over the first second).
- PEFR Peak Expired Flow Rate
- FEV1 forced expired volume
- Chronic Obstructive Pulmonary Disease COPD
- hypertension require similar self-management by the patient and regular visits to a clinic or doctor's surgery.
- diabetes Another example of a chronic condition which requires self-management is diabetes. Diabetes sufferers have to manage their diet and exercise and if they are insulin- dependent (Type 1 diabetes) or insulin-treated, administer insulin themselves, usually four times a day for Type 1 diabetes, recording the dosages and their symptoms and also measuring their blood glucose levels by taking a small blood sample and using a proprietary test device. At the regular clinics the recordal of these activities and the patient diary is monitored, and also a measurement is made of their glycosylated haemoglobin (HbAl c ) which gives an indication of the average blood sugar levels over the last three months.
- HbAl c glycosylated haemoglobin
- a measurement device such as a peak flow meter or blood glucose meter can be connected directly to a GPRS or 2.5 or 3G mobile telephone, (sometimes known as a smart phone), adapted so as automatically to receive the medical data from the measurement and transmit it without patient intervention to a remote server.
- the data is processed at the remote server and a reply sent immediately to the patient.
- Figure 1 illustrates a display of data recorded for an asthma sufferer in the above system.
- an upper part of the display 1 there is a plot of the daily peak flow readings 3, together with a trend 5 calculated from those daily readings.
- the present invention provides a method of displaying values of a parameter indicative of a medical condition, comprising displaying a first graphical device indicating values of the parameter representative of a patient-specific model of normality for that parameter, and displaying a second graphical device against the first graphical device at a display position representative of a current value of the parameter.
- the patient-specific model of normality may be dynamic, for example varying with patient condition on a relatively slow time scale, such as over a period of two or more months.
- the current value of the parameter may also be based on a plurality of actual measurements, for example an average of several closely repeated measurements taken one after the other, or measurements taken over a short recent time period, such as two weeks or so.
- the patient-specific model of normality may reflect the patient condition over a first, relatively long time period whereas the current value may represent the values of the parameter over a second, shorter and more recent time period.
- the model of normality may reflect the condition over the last three months, which is long enough to be stable, but short enough to vary with seasonal variations in condition. It is also possible for the model automatically to take into account such external factors as the weather, season or pollen count.
- the current value may be calculated from three peak flow readings taken one after the other on a particular day.
- the display could comprise a colour-coded histogram showing a predetermined time period (reflecting the current state of the patient), while the colour-coding may indicate the areas of hypo and hyperglycemia defined for that patient with regard to their normal degree of control as judged over a longer time period.
- the definition of the predetermined period will vary according to the patient; for example for someone with Type I diabetes, it may be two weeks. On the other hand, for someone with Type II diabetes, who monitors much less regularly, it may be two months.
- the system is capable of self-adapting to the frequency of readings taken by the patient and to display the most appropriate time period accordingly.
- the patient-specific model of normality may be judged on the basis of a trend .value of . the parameter, such as the Kalman filtered value (see for example: PCT/GB2003/004029).
- the patient-specific model of normality may comprise thresholds based on percentages of the average value of the trend, calculated over the last 3 months, assuming that the last 3 months data have all been normal. (Abnormal data are excluded from the calculation of the normal trend value. This may be done by excluding values below a threshold, e.g. 90% of the values so far recorded.)
- a moderate warning, serious warning and clinician alert values may be calculated as increasingly smaller percentages of the normal average trend value.
- the first graphical device may represent a scale against which the second graphical device is displayed.
- the scale may be colour-coded and/or numerical and the second graphical device can represent a pointer displayed against the scale.
- the patient-specific model of normality may be calculated or learnt from measured values of the parameter, or may be established by a clinician assessing the patient condition.
- external factors such as weather in the case of asthma
- PEFR Peak Expired Flow Rate
- FEV1 Forced Expired Volume
- the apparatus can comprise a meter for measuring the current value of the parameter (for example a peak flow meter or blood glucose meter), and a wireless communications device, such as a mobile telephone, for communicating with a remote server.
- the remote server can store the data and can also process the data and provide the output for display on the patient device. It may also adapt the patient-specific model (e.g. lower the upper threshold of target blood glucose reading or cope with seasonal variations in peak flow measurements).
- a second aspect of the invention provides a method of displaying data indicative of the control of a medical condition by administration of a pharmacologically active agent, comprising:- acquiring as said data a plurality of sets of measured values of a parameter indicative of said medical condition, each set comprising a plurality of measured values of said parameter during a predetermined time period, and a plurality of sets of values of administration of said pharmacologically active agent, each set comprising a plurality of administration values during each of said predetermined time periods; displaying in a first display area a plot of the measured values of the parameter from all of said sets against a time axis representing a single predetermined time period; displaying in a second, adjacent display area a time plot of the values of administrations of said pharmacologically active agent from all of said sets against a time axis representing a single predetermined time period; displaying a visual link between each pair of displayed values formed by an administration value and the measured value of the parameter corresponding to response of the medical condition to that administration, said visual
- This aspect of the invention is particularly useful in forming an educational tool whereby the quality of control of the condition by use of the pharmacological agent can be easily seen over a period of time. ⁇ - • . . .
- the visual link can comprise colour coding of the plotted values and, to assist understanding, the time axes in the two display areas are preferably aligned.
- the predetermined time period may be a day and the corresponding pairs from each set may be pairs that temporally correspond, for example being at the same time of day, or being related to the same respective activities during the day (such as the same meals and bedtime).
- This aspect of the invention also provides apparatus for displaying such data in this way.
- the processing of the data for display and the control of the display itself may be embodied in- suitable software which runs -as an executable application on an electronic device, and optionally at a remote server too. Thus it may run as an application on a mobile telephone or PDA or other portable electronic device.
- the invention therefore extends to a computer program which when loaded on a suitable device executes the display according to the invention.
- Figure 1 illustrates a prior art display of an asthma sufferer's condition
- Figure 2 illustrates a prior art display of blood glucose measurements for diabetes management
- Figures 3(A) and (B) illustrate a first embodiment of the invention for displaying data relating to an asthma sufferer's condition
- Figures 4(A), (B) and (C) illustrate a second embodiment of the invention for displaying data related to blood glucose control of a diabetes sufferer
- Figure 5 illustrates a third embodiment of the invention for displaying further data related to a diabetes sufferer's condition
- Figure 6 illustrates a fourth embodiment of the invention, also relating to a diabetes sufferer's condition management
- Figures 7A to 7L illustrate a sequence of displays in use of one embodiment of the invention.
- Figures 3(A) and (B) illustrate alternative versions of a display according to a first embodiment of the invention for use by an asthma sufferer.
- the display consists of a first graphical element 30 in the form of a scale colour-coded from red at the left-hand side through amber and yellow to green at the right-hand side.
- Figure 3(A) shows an arcuate version of the scale and
- Figure 3(B) a straight version.
- the scale is not fixed but is based on a model of normality for the particular patient. It therefore differs from a traditional fixed scale or a representation of such a fixed scale.
- the display includes a second graphical element 32, in this case in the form of a needle, which is used to indicate the current, i.e. today's, condition of the patient. This display is based on indicating to the patient a peak flow reading as obtained from a • ⁇ - peak flow meter.
- the second graphical element 32 the needle, will be displayed pointing to a position on the scale representing the current peak flow value. Normally a peak flow reading is taken by the patient conducting three measurements in quick succession, i.e. blowing into the peak flow meter three times in succession, and then the average of the three readings can be taken, or the best of the three can be taken. This becomes the current reading and it is this which the needle displays.
- the first graphical element is a model of normality for the patient which is based on calculation of a trend of relatively recent peak flow readings.
- the trend may be calculated during an initial learning period (for example a month) in which the best peak flow readings (excluding outliers) are used to set the 100% value. It can also be made adaptive by using a Kalman filter to reflect the long-term trend (such as 3 or 6 months).
- the scale is then calculated and displayed with the green (right-hand end) set at 100%) of the best peak flow value, the green to amber transition at 75% of this value, the amber to red transition at 50% of this value.
- a GP alert value at 75% may be indicated on the scale as shown by label 33 in Figure 3(B), being the value at which a message is sent automatically to a clinician alerting them to a significant worsening in patient condition.
- label 33 the value at which a message is sent automatically to a clinician alerting them to a significant worsening in patient condition.
- different percentage values may be chosen.
- a learning set of 30 days readings may be used, or standard default values, these being replaced as the Kalman filtered trend values resulting from normal daily readings become available.
- the model may also include as a parameter a score based on the patient's own assessment of condition, taken from a patient diary as explained below.
- the scale is set according, to the model of normality for measurements on that patient.
- the scale can be judged from standard data suitable for that patient judged from the population.
- the scale would differ according to the sex, weight, age and so on of the patient.
- Figures 3(A) and (B) illustrate a further feature in that the display includes information relevant to the patient's condition such as weather 36 and air quality 34.
- This can be adapted to the location of the patient using the GPS data available in GPRS telephones, or the cell data in a normal cellular telephone system. The availability of this data allows it to be incorporated into the model if desired. For example, a greater degree of variability in the patient's condition can be expected in cold weather or if the pollen count is high. The model can take this into account and enlarge the scale shown in anticipation of higher variability.
- Figures 4(A) to (C) illustrate a second embodiment of the invention which is useful for diabetes sufferers.
- the display shows a histogram 40 of blood glucose measurements taken by the patient.
- the histogram contains the most recent 2 weeks worth of readings (usually 56 readings at 4 readings per day).
- the horizontal axis is autoscaled so as to show the full range of readings obtained.
- a patient with good blood glucose control will tend to see a smaller range of values on the horizontal axis (0-16 in Figure 4A) than a patient with less good control (0-20 in Figure 4B) or poor control (0-23 in Figure 4C).
- the histogram is also colour-coded according to a patient specific model of normality, in this case comprising thresholds for hypo and hyperglycemia for that patient. These target thresholds are set by a clinician by agreement with the patient on the basis of the patient's history of blood glucose control.
- a transition from green to blue may be set normally somewhere between BG values of 3 and 7.
- the transition from green to red may be set normally somewhere between 9 and 16.
- a patient therefore, whose blood sugar level is not being controlled properly may see a range from 0 to 25, most of which will be red.
- the range displayed will gradually narrow down until it is from 0 to 20 or 0 to 16 as illustrated, when green will be in the middle and most readings, and thus most of the histogram, will be green. So viewing the histogram gives an immediate indication of current condition.
- the target thresholds may be adjusted (e.g. the hyperglycaemic target threshold reduced), so that the colours on the histogram reflect the model of normality for that patient.
- the agreed healthcare plan to be stored on the patient's device (e.g. telephone) so that the patient can refer to it at any time.
- the plan can be updated by automatic updates from the server.
- the clinician can include a reminder to be displayed in response to certain values of the measurements made by the patient.
- the patient's condition deteriorates, they can be reminded what action to take, such as increase the use of the reliever/inhaler in the case of asthma, or if the patient's condition becomes dangerous, they can be reminded what emergency action to take, such as contacting a healthcare professional and/or administering an emergency dose of their medicament.
- the variability in the following of the plan by the patient can be reduced by providing for the display to guide the patient with a particular workflow.
- This workflow should follow a "measurement-evaluate-act" sequence so that the patient first measures their condition, then this measurement is evaluated (with the assistance of the automatic processing and display of the data) and then the appropriate action is taken, again with the assistance of the agreed plan accessed on the display.
- An example workflow, for the asthma monitoring embodiment, is as follows:-
- the questions are tailored depending on the time of day and the previous entries by the patient. For example, depending on whether the patient uses the application both in the morning or evening, or just once in a 24 hour period, they will be asked one, two or three questions. In fact, there are four cases, namely:
- Case 3 in which the patient is taking a reading in the evening and has taken one that morning (in which case the two questions displayed in Fig. 7D are displayed in sequence); and Case 4 - in which the patient is taking a reading in the evening and has not taken one that morning (in which case the three questions shown in Fig. 7E are displayed in sequence).
- the answers to these questions can be used to give a score of the severity of the symptoms.
- This score can be displayed separately, for example as shown at 9 in Fig. 1, or can be used to adjust the model of normality for the patient, or can be displayed in a similar manner to the peak flows as shown by 30 and 32 in Figure 3A.
- FIG. 7H A personalised display of the patient's condition is shown, together with local external conditions such as weather and air quality, as shown in Fig. 7H.
- the display of Fig. 7H includes a button 70 which allows the patient to access their agreed treatment plan.
- an appropriate part of the agreed treatment plan may be displayed in dependence upon the current measurement of the patient's condition.
- Fig. 7M shows an example of the treatment plan in the case that the patient's condition is in a warning zone, and in this example recommends an increased dosage of medicament.
- Fig. 7N illustrates an example of a part of the treatment plan appropriate for a reading showing that the patient's condition is dangerous, in this case an emergency administration of medicament together with a recommendation to contact a clinician.
- step 4 The readings or the best reading from the patient's measurement of their condition in step 4 is then transmitted to the server.
- Figs. 7K and 7L are shown interchangeably.
- Fig. 7K the trend of recent readings is illustrated but this display can be changed to the personalised display of Fig. 7L using the "zones" button 72.
- the trend may be accessed from the personalised display of Fig. 7L by using the "trend" button 74.
- the patient-specific model of normality is maintained on the patient's device (e.g. telephone) so that in the event of a loss of connectivity to the server, at least the personalised display of Fig. 7L can be shown, possibly absent the local condition (weather) data which is delivered from the server.
- the patient's readings are stored for later transmission to the server when connectivity is restored.
- Figure 5 illustrates another display 50 useful for diabetes sufferers.
- the patient has taken four blood sugar measurements through the day which are labeled 51, 52, 53 and 54 and these are plotted against time of day on the horizontal axis and blood sugar level on the vertical axis.
- the display also illustrates two target thresholds 55 and 57 which represent the limits of acceptable blood glucose level for this patient as discussed above.
- 57 is the lower acceptable value of blood glucose (the green to blue transition above)
- 55 is the upper acceptable value (the green to red transition above). The lower value is set to avoid hypoglycaemia.
- the upper level is the current target threshold for hyperglycaemia agreed with that patient.
- An advantage of displaying the upper threshold (and the red area in the histogram) is that the patient knows that if many of their daily blood glucose measurements are near or exceed the level on the display at which the upper limit 55 is set, their glycosylated haemoglobin ( ⁇ bAlc) is likely to rise over time above the accepted level.
- the readings taken at the patient end may be transmitted to a server and a response sent to the patient which includes the patient- specific model of normality (the server storing a model for each patient).
- the background of the display may be based on data at the server, while the current value is based on the reading at the patient end.
- the new readings are added to the data for that patient at the server, of course, and may be used to adapt the model of normality dynamically (e.g. in the display of Figures 3(A) and (B) by contributing to the trend calculation).
- Figure 6 illustrates a fourth embodiment of the invention which is useful as an educational tool for helping diabetes patients improve their control of their condition by adjusting their insulin dosage.
- the display 60 has an upper pane 61 and a lower pane 62.
- a horizontal scale corresponding to a single twenty four hour day is shown in the upper pane 61 .
- the vertical scale plots blood glucose level.
- Each of the blood glucose readings taken by the patient over a period of many days (four weeks in Figure 6) is plotted on the same plot at the appropriate point for the time of day and blood glucose level. Furthermore, all of the readings which correspond to the same time of day are colour-coded.
- all of the readings at breakfast time are coloured red, at lunchtime coloured blue, at dinnertime coloured green and at bedtime coloured purple. It will seen that some of the dinnertime readings are at a time of day which, on other days, has corresponded to bedtime. This is normal and the readings can be characterised as dinner or bedtime by requiring the patient to indicate which it is when entering the data, or by judging whether it is the second, third, fourth or fifth reading of the day and the time of day of generation of the reading.
- the display also includes a lower pane 62 which plots insulin dosage as input by the patient.
- the dosage of insulin is plotted vertically and, again, the horizontal axis represents a single 24 hour period.
- the insulin dosages for each day over the same period are plotted, and are again colour-coded according to the time of administration, namely breakfast, lunch, dinner or bedtime. It will be seen by the colour-coding that the insulin administered at breakfast time controls the blood glucose level as measured at lunchtime.
- the insulin administered at lunchtime controls the blood glucose levels at dinnertime. That at dinnertime controls the level at bedtime and that administered at bedtime (usually a much higher administration to last through the night) controls the level of blood sugar as measured the next morning.
- the use of the colour-coding as a visual link between the two plots makes it simple for the patient to see the connection between the insulin administration and the corresponding control of blood glucose.
- FIG. 6 illustrates a rather large scatter of blood glucose level in each group, thus indicating poor control. It can be seen that the insulin dosage is very stable (the scatter in dosage in each of the insulin administration groups is small). Thus in the illustrated case the patient can easily see that they are not varying the insulin dosage sufficiently to control the blood glucose level stably. A patient who is better at control would have a larger scatter of insulin dosages (i.e. the groups in the lower plot would be more spread out vertically), and have much tighter vertically distributed groups in the upper plots 61.
Abstract
Description
Claims
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
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US10/592,802 US20070179347A1 (en) | 2004-03-15 | 2005-03-15 | Medical data display |
DE602005025198T DE602005025198D1 (en) | 2004-03-15 | 2005-03-15 | MEDICAL DATA DISPLAY |
AT05718033T ATE490723T1 (en) | 2004-03-15 | 2005-03-15 | MEDICAL DATA DISPLAY |
EP05718033A EP1725163B1 (en) | 2004-03-15 | 2005-03-15 | Medical data display |
US12/823,251 US20100259543A1 (en) | 2004-03-15 | 2010-06-25 | Medical Data Display |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
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GB0405798.0 | 2004-03-15 | ||
GBGB0405798.0A GB0405798D0 (en) | 2004-03-15 | 2004-03-15 | Medical data display |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
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US12/823,251 Division US20100259543A1 (en) | 2004-03-15 | 2010-06-25 | Medical Data Display |
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WO2005087091A2 true WO2005087091A2 (en) | 2005-09-22 |
WO2005087091A3 WO2005087091A3 (en) | 2005-10-27 |
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PCT/GB2005/000980 WO2005087091A2 (en) | 2004-03-15 | 2005-03-15 | Medical data display |
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US (2) | US20070179347A1 (en) |
EP (2) | EP1725163B1 (en) |
AT (1) | ATE490723T1 (en) |
DE (1) | DE602005025198D1 (en) |
GB (1) | GB0405798D0 (en) |
WO (1) | WO2005087091A2 (en) |
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WO2006116718A2 (en) | 2005-04-28 | 2006-11-02 | Proteus Biomedical, Inc. | Pharma-informatics system |
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US9339217B2 (en) | 2011-11-25 | 2016-05-17 | Abbott Diabetes Care Inc. | Analyte monitoring system and methods of use |
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GB0405798D0 (en) | 2004-04-21 |
US20100259543A1 (en) | 2010-10-14 |
EP1725163B1 (en) | 2010-12-08 |
ATE490723T1 (en) | 2010-12-15 |
US20070179347A1 (en) | 2007-08-02 |
DE602005025198D1 (en) | 2011-01-20 |
EP1725163A2 (en) | 2006-11-29 |
WO2005087091A3 (en) | 2005-10-27 |
EP2106743A1 (en) | 2009-10-07 |
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