WO2016027102A1

WO2016027102A1 - Apparatus and method for remote monitoring of a medical condition

Info

Publication number: WO2016027102A1
Application number: PCT/GB2015/052436
Authority: WO
Inventors: James Orr; Stephan Kiefer; Michael Schäfer
Original assignee: The University Of Newcastle Upon Tyne; Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V.
Priority date: 2014-08-21
Filing date: 2015-08-21
Publication date: 2016-02-25
Also published as: GB201414895D0

Abstract

The present invention relates to a device for monitoring a medical condition of a patient. The device is configured to run an electronic monitoring test for the patient, wherein the test generates test results for the patient. The device is further configured to receive patient data relating to the medical condition of the patient. The device is further configured to compare the test results and the patient data with reference data to derive output data. The device is further configured to output the output data. The output data comprises a condition indicator and a drug dose recommendation.

Description

Apparatus and method for remote monitoring of a medical condition

Field The present invention relates to apparatus and methods to monitor a patient's medical condition remotely and to control dosage of a drug to treat that condition.

Background Monitoring a patient's medical condition and controlling dosage of medication without the presence of a clinician is known, for example in control of diabetes using insulin, in which a blood glucose reading made by a patient may be used to control administration of insulin, for example by an infusion pump. This allows greatly improved control of the condition than would be the case if such monitoring and control of dosage were done infrequently by a clinician. The latter situation is true for most conditions: monitoring is done at infrequent clinical consultations and dosage may be checked and changed at those consultations, but rarely in between, which may lead to poor control of the condition, and often poor quality of life for the patient and deterioration in their condition over time. In particular some chronic conditions such as liver disease, and specifically hepatic encephalopathy (HE) resulting from liver disease, may be managed sub-optimally at present, owing to the lack in the prior art of monitoring and control devices and methods suitable for use by a patient outside a clinical setting, and without a clinician's supervision. In the case of cognitive neurological or neuropsychiatric disorders such as HE, diagnosis is presently made using known cognitive tests administered by a clinician, such as the Number Connection Test (NCT) or the Stroop test. However, in their present form as used in current medical practice these tests are unsuitable for use in routine monitoring of a patient or for use by a patient in an unsupervised home setting.

The ability to monitor the patient's condition and to provide warning to a remote clinician if the condition deteriorates, or that such deterioration is imminent or likely, would be valuable in a range of indications. In particular, devices that are able to recommend drug dosage that a patient might take in order to control their condition, would provide a huge step forward over current practice.

Specifically in the case of HE, control of the condition is typically done using doses of laxative such as lactulose, which is prescribed at infrequent clinician visits as described above. However, episodes of overt HE may have a rapid onset and a patient's condition may deteriorate rapidly between visits; increased doses of laxative may be beneficial but if a patient fails to improve despite taking the maximum recommended dose, attention from a clinician may be required, for example in the first instance to arrange administration of an enema, or in some cases to investigate possible precipitating causes of HE. A remote monitoring system for symptoms of HE and having the capability of making drug dosage recommendations would have major value for both patients and clinicians.

Description of the invention

In known systems, as exemplified by glucose monitors adapted to control diabetes by outputting a recommended dose of insulin such that a patient may take the recommended amount, the measurement means is calibrated against a standard and as such provides an output in the form of test results that does not depend primarily on the individual patient. In this example, a reading of say 5mmol/L glucose is just that, regardless of the particular patient for whom it is measured. However, a problem arises in measurement situations in which the calibration of the measurement is significantly or mainly dependent on the patient. For example in tests such as cognitive tests or motor control tests capability to do the test may vary widely between individuals of the same health status, and may vary widely between younger and older people, people of greater or lesser inherent dexterity, and between people who suffer from additional comorbidities and those who do not. The same situation may arise with some biochemical measurements, for example blood ammonia levels in liver disease: such levels may vary widely between individuals who do not show any difference in apparent health status or symptoms. In such cases the problem is to provide a meaningful interpretation of test results for which absolute calibration is impossible or unreliable in practice and, for test results that are calibrated against standards, when those test results may vary between individuals of similar medical condition. This problem is made more difficult in situations in which it is desirable to monitor a patient's condition remotely.

If a drug is to be used to control a chronic medical condition on the basis of such monitoring there is the possibility of adverse side effects, which must be allowed for in devices or methods for such remote monitoring or control.

According to a first aspect, a device is provided for monitoring a medical condition of a patient, the device being configured to:

run an electronic monitoring test for the patient, wherein the test generates test results for the patient;

receive patient data relating to the medical condition of the patient;

compare the test results and the patient data with reference data to derive output data; and output the output data;

wherein the output data comprises a condition indicator and a drug dose recommendation.

An electronic monitoring test may be selected according to the medical condition and may be a cognitive test, a motor control test, or a biochemical test such as measurement of a measurand in a body fluid, such as the level of a species in the body fluid or a pulmonary function test such as spirometry. Patient data may be data input by a patient regarding the patient's health status, such as a perceived effect of the drug on the symptoms of the condition, or a side effect of the drug, such as a Patient Reported Outcome Measure (PROM). Patient data may comprise a patient data value, for example representing an effect of the drug such as a side effect. Such a value may be a number on a numeric scale or may represent a yes/no answer. Patient data may be received via an input/output device forming part of the device, for example a touchscreen, in the form of an input by the patient in response to a question regarding patient data generated by the device and displayed by the input/output device.

In some embodiments the device is further configured to:

operate in a reference mode and a monitoring mode, wherein the reference mode enables the reference data to be set for the patient,

and wherein the monitoring mode uses the reference data which is set in the reference mode to derive the condition indicator and the drug dosage recommendation.

In some embodiments the device is further configured to:

operate in a reference mode and a monitoring mode, wherein the reference mode enables the reference data to be set for the patient and wherein the monitoring mode uses the reference data which is set in the reference mode;

output, in the reference mode, the test results for the patient; and

receive a confirmation that the test results are to be used as reference data in the monitoring mode. Comparing the test results and the patient data with reference data to derive output data may comprise comparing the test results with an action threshold forming part of the reference data.

In some embodiments the device is configured such that the drug dose recommendation is modified in response to the test result reaching or passing the action threshold forming part of the reference data. The drug dose recommendation may increased in response to the test result reaching or passing the action threshold forming part of the reference data.

In some embodiments the reference data comprises (i) a test action threshold for the test results and (ii) a patient data action threshold for the patient data, and comparing the test results and the patient data with reference data to derive output data further comprises comparing patient data with the patient data action threshold to derive the drug dosage recommendation.

In some embodiments the device is configured to increase the drug dosage recommendation when both of:

(i) the test result reaches or passes a test action threshold, and (ii) the patient data value lies within a range of values, or above a first patient data action threshold, stored as part of the patient reference data.,

In some embodiments the device is configured to increase the drug dosage recommendation if:

(iii) the resulting drug dosage recommendation does not exceed a maximum drug dose value.

In this way the device may use patient data, for example regarding an adverse side effect, to override the test result in deriving a drug dose recommendation. For example, a patient data value above an action threshold may prevent an increase in the drug dosage recommendation. Such a configuration allows for flexible and safe operation of the device in remote monitoring of a medical condition and control by means of a drug.

In some embodiments the device is configured such that the drug dosage recommendation is reduced in response to comparison of patient data with the action threshold for the patient data.

In some embodiments the device may be configured to reduce the drug dosage recommendation if the patient data value lies outside the said stored range of values, such as in a second range stored as part of the reference data, , or reaches a second patient data action threshold.

In some embodiments the device may be configured to reduce the drug dosage recommendation when a test result or a number of test results over a period of time or an average derived from them does not reach the said test action threshold. In some embodiments, the drug dosage recommendation may be reduced when both of:

(i) the test result does not reach the said test action threshold for a single test for multiple tests over a time period, and

(ii) a patient data value lies outside the said stored range. It will be understood that a value at the end of a range as described above represents an action threshold, at which the operation of the device may change. Accordingly, the device may be configured to increase the drug dosage recommendation if both:

(i) the test result reaches a test action threshold

(ii) the patient data value does not reach a first patient data action threshold.

and to reduce the drug dosage recommendation if the patient data value reaches a second patient data action threshold.

(iii) the resulting drug dosage recommendation does not exceed a maximum drug dose value. The action thresholds and range(s) forming part of the reference data may be derived from test results and patient data received by the device in a reference mode of operation during a reference phase, or may be parameters of the device, for example entered by a user such as a clinician.

Accordingly in some embodiments the device is further configured to:

operate in a reference mode and a monitoring mode, wherein the reference mode enables the reference data to be set for the patient and wherein the monitoring mode uses the reference data which is set in the reference mode to derive output data comprising a condition indicator and a drug dosage recommendation,

output, in the reference mode, the test results for the patient,

receive a confirmation that the test results are to be used as reference data in the monitoring mode, and

derive an action threshold from the test results and store the action threshold as reference data.

In this way the device may be configured to increase the drug dosage when both the result from the electronic monitoring test and patient data are within selected ranges forming part of the reference data (such as reaching an action threshold). That is, the device may be configured such that patient data input by the patient is able to override the test result in deriving the drug dosage recommendation. In this way the device allows patient data, such as data indicating that an adverse side effect is present, that may outweigh the benefit of the drug in treating the condition, to be used to override an increase in the drug dosage recommendation. Such patient data may comprise a PROM such as stool frequency in HE, a subjective assessment of wellbeing or lack of it, or a physical measurement such as weight, heart rate, temperature, urination frequency or volume, measurement of breathing capacity such as by spirometry, or digestive disturbance such as nausea.

In some embodiments the device is configured such that the drug dosage recommendation may be increased or decreased by an amount that is set for the said patient, for example by input from a clinician device.

In some embodiments the device is configured to communicate with a remote clinician device via a data link, the clinician device being configured to receive data from the device and the device being configured to receive data and commands entered into the clinician device.

The device may comprise a computer, comprising a display screen and data entry capability adapted to allow a patient to do the monitoring test and to enter patient data, such as an input/output (i/o) device such as a touchscreen interface; a processor, and a data store, and an expert system configured to derive the output data. The expert system may be part of the device or may be part of the clinician device. The device may comprise a computer program to operate the device, and in some embodiments the program is adapted for monitoring of a specific medical condition. In some embodiments a device is provided for monitoring a patient's medical condition, the device being configured to:

receive patient data relating to the patient's medical condition;

compare the test results with reference data to derive output data comprising a condition indicator; and

output the output data;

wherein the device is configured to operate in a reference mode and a monitoring mode, wherein the reference mode enables the reference data to be set for the patient and wherein the monitoring mode uses the reference data which is set in the reference mode.

In some embodiments the device is configured to compare patient data with reference data to derive output data. In some embodiments the device is configured to:

output, in the reference mode, the test results for the patient; and

receive a confirmation that the test results are to be used as reference data in the monitoring mode. In some embodiments the device is configured to:

output, in the reference mode, the test results for the patient to a clinician device; and receive a confirmation from the clinician device that the test results are to be used as reference data in the monitoring mode. In some embodiments the device is configured to switch from the reference mode to the monitoring mode in response to receiving the confirmation.

In some embodiments the device is configured to:

compare the test results with a predetermined criterion for the test results to be set as reference data; and

if the criterion is met, to set the test results as reference data.

The device may be configured to receive a predetermined criterion entered into the device or from a clinician device. The criterion may be a parameter forming part of a computer program selectable for operation on the device according to the condition and the patient to be monitored. A predetermined criterion for setting test results as reference data may be entered or stored in the device prior to the start of operation in the reference mode. It may for example comprise a limiting value for variation in the test data during the reference phase, such that if the variation is below the limiting value, indicating that the patient's responses to the electronic monitoring test are stable during the reference phase, then the test results are set as reference data and the device switches automatically in the monitoring mode.

In some embodiments, the device is configured to receive reference data entered into the device or received from a clinician device. The reference data may represent expected results for a patient based on previous administration of the test or of other clinical assessments, or may represent typical results expected for patients of a certain group or subpopulation.

In this way the device may be used during a reference phase, in which typically the patient's condition will be observed and known by a clinician, and in which the device is configured to operate in a reference mode to receive reference data characteristic of an individual patient's results from the electronic monitoring test. The patient's health status during the reference phase may thereby be used as a known reference state against which later changes may be monitored during a monitoring phase that follows the reference phase. Typically during the monitoring phase the patient's condition will not be observed directly by the clinician - rather it will be assessed remotely in terms of the patient's test results and patient data received by the device and processed by the device, for example in the form of a condition indicator. During the monitoring phase the device is configured to operate in a monitoring mode in which it compares the test results with the reference data to determine whether, and to what degree, the patient's condition has changed from their known condition during the reference phase.

In some embodiments the device is configured to receive patient data while in the reference mode and to enable the patient data to be set as reference data. The device may be configured to operate in a monitoring mode to compare patient data with reference data. In this way the device is configured to allow interaction of a clinician with the device to determine reference data representative of a known medical condition of the patient, against which test results received during operation of the device may be interpreted, in contrast with prior art devices which are simply directed to monitoring change without such determination of reference data. The device may comprise a computer and a set of instructions to configure the device to perform the functions described herein. The device may comprise a display screen to allow display of output data on the screen. The device may comprise an input device such as a keyboard, a mouse or a touch-sensitive screen provided with appropriate icons, questions, reply buttons or data entry fields. The device may be in the form of a computer, a tablet computer having a touch-sensitive screen, a smartphone or a dedicated device comprising computing, input and output devices. In some embodiments the device may be adapted to communicate with a further input/output device, such as a smartphone or computer, such that the device communicates data to the input/output device in order run tests, request and receive patient data, or to display output data, while the instructions, such as an expert system, to configure the device to compare test results with reference data remain on the device itself. Data may be stored in a data store accessible to the device, for example forming part of the device itself or linked to it by means of a data link. A clinician device is typically a computer remote from the device and connected to it by a data link such as a LAN, wireless LAN or remote data link such as an internet or wireless data link, and having a computer program operable on it to allow operation with the device as described herein.

An electronic monitoring test may be run by the device by presenting instructions to a patient via a display screen and receiving patient responses or actions via the input device.

The monitoring test may be a cognitive test, for example a Number Connection Test (NCT) or a Stroop test. The monitoring test may be a motor control test, for example in which the patient is required to respond to a stimulus presented on a display device, for example by moving a mouse or touching a touch-sensitive screen.

In embodiments adapted for monitoring HE, the electronic monitoring test may be an electronic form of a monitoring test that is appropriate for use in diagnosing HE, such as a NCT, a Stroop test, an inhibitory control test, a critical flicker frequency test, or electronic tests based on the Psychometric Hepatic Encephalopathy Score (PHES) tests such as a serial dotting test, a line tracing test or a digit symbol test. A NCT is a test known in the art in which a series of numbers are presented to a patient who has to indicate or join the numbers in rank order. The completion time taken to do this correctly is the test result. In cases of transiently impaired cognition a patient's completion time is longer than would be the case for the same patient when well, or in severe cases they may not be able to complete the test. The device may run an electronic NCT by carrying out the following steps:

(i) presenting to the patient on a touch-sensitive screen of an input/output device a set of numbers, typically 2-digit numbers, arranged in a pattern on the screen. The pattern and numbers may be random or they may be selected from a pre-programmed set of numbers and/or patterns.

(ii) requesting the patient to touch the numbers in rank order

(iii) timing the patient's response, to derive the completion time as a test result.

Repeat tests may be done to derive a mean, standard deviation, or range of the completion times, or to select the lowest completion time as the basis for comparison with reference data, such as an action threshold. The device may record if the patient did not complete the test. Other cognitive tests may be implemented in electronic form by the device by presenting a pattern on a touch-sensitive screen and requesting the patient to follow instructions to complete the test by touching the screen, timing the patient's response. An electronic monitoring test may comprise a biochemical test such as measurement of a measurand in a body fluid such as blood, plasma, serum, sweat, saliva, urine or exhaled air. In general such a test is one in which the levels of the measurand in different individuals having the same health status will show significant variation, such that there is a need for comparison with reference data received in a reference mode of operation of the device. For example, a test of the level of ammonia or of creatinine in blood, serum or plasma in liver disease patients of the same apparent health status may show significant differences between the levels in different patients and so such measurements need to be referenced to a known state of health of the patient during a reference phase. As a second example, in measurement of spirometry or oxygen saturation in respiratory disease (e.g. Chronic Obstructive Pulmonary Disease, COPD), individual patients will have an individual baseline with some able to tolerate poorer lung function and lower blood oxygen saturation than others, and such referencing is essential to enable reliable remote monitoring of their condition. The electronic monitoring test may be carried out by an analysing instrument separate from the device and in data communication with it. The device may be configured to run an electronic monitoring test in the sense that it is configured to be operable with an instrument to initiate a test carried out by an instrument and to receive test results from the instrument. For example the device may be configured to be operable with a blood biochemistry analysing instrument for one of the following measurands: ammonia, creatinine, blood oxygen and electrolytes such as sodium, potassium and calcium, bilirubin and albumin. Herein, measurements referred to as being in blood include those in blood fractions such as serum and plasma. The device may be adapted to run more than one electronic monitoring test for a specific patient, for example a computerised cognitive or motor function test and a further monitoring test such as a biochemical test. The device may run a test by sending a command to a remote instrument to initiate the test. In some embodiments the device may run a test by instructing a user to start a test on the instrument and then receive the test results via a data link, as for example in the case that a patient needs to perform a physical action in order to do a test such as a spirometry test or to measure their weight.

Test results are data resulting from a patient completing the monitoring test that is run by the device, and may be in the form of a number, such as in cognitive tests or motor control tests the time to complete a single test, an average result from a completing a number of tests, such as the mean time, or a measure of variation over a number of tests such as the standard deviation (SD) about the mean. Test results may be derived from data from more than one type of test, for example the data being combined according to a formula to allocate a first weighting to a first test, such as a cognitive or motor function test, and a second weighting to a second test of a different type, such as a patient's weight or a body fluid biochemistry test. Reference data may be a set of test results from a series of tests run by the device in the reference mode; an average and a variation, such as the mean and SD of the set of test results; a value of the range, or an extreme high or low value of the set. In some embodiments reference data may also include patient data, for example a statement or a numerical value allocated to a response to a question asked of the patient. The device may be configured to allow reference data to be updated while the device is in the monitoring mode, once an initial reference period has been completed. In some embodiments, the reference data may comprise a value of a condition indicator derived from test results in comparison with other items of reference data. For example, in a reference mode the device may first receive reference data entered into the device, for example by a clinician. The device may then run a monitoring test on a number of occasions to receive test results, and may receive patient data. The device may then derive a condition indicator from the test results and optionally the patient data using the entered reference data. The device may then update the reference data using the test results and store the condition indicator as part of the reference data. The reference data may then be set and the device may enter the monitoring mode, with the condition indicator then showing the patient's condition relative to a reference condition in the reference phase.

The patient data may comprise one or more of patient physiology data such as a measurement made by a measuring instrument and entered into the device or received from a clinician device, such as weight, heart rate, blood pressure, or a blood biochemistry measurement, or patient behavioural data, such as stool frequency, frequency or quantity of water intake to judge hydration status, or a patient-reported measure of their condition, such as a health related quality of life measure or a subjective sense of wellbeing.

In the case that the medical condition is HE, patient data typically comprises a value of stool frequency.

Confirmation that test results or patient data are to be set as reference data may follow observation that the patient's medical condition during the reference phase was appropriate for use as a baseline condition against which future changes in their condition may be judged. For example, the patient might be categorised by the clinician as relatively well during the reference phase, and subsequent changes in test results or patient data from the reference data would indicate a worsening in the patient's condition.

The reference phase may be defined by a period of time over which reference data is collected, or by a number of occasions on which the test is run while the device is operating in the reference mode. The device may be configured to operate in a reference mode during the reference phase for a predetermined period of time or for a predetermined number of tests, following which it prompts a clinician to review the test results and optionally the patient data and to set the reference data based on the test results and patient data. The device may be configured to derive reference data from a combination of the test results and the patient data, for example according to an algorithm forming part of the device. The device may be configured to exit the reference mode and to enter the monitoring mode when the reference data is set. The device may be configured such that it indicates which mode it is in, for example by an indication on an output device connected to the device.

One or more of test results, patient data, the condition indicator may be stored by the device as a function of time to form historic data of each kind, which in some embodiments may be used to derive the present condition indicator or to indicate the trend in the patient's condition over time. Historic data may be stored in a data store forming part of the device or linked to it via a data link.

The device may be configured such that if test results differ from reference data or from historic test data the test may be repeated, or other tests done, to avoid a false positive result. The device may process the results from repeated tests to provide test results in the form of an average and variation, a 'best' or a 'worst' result, or an average and/or variation from a subset of the results to exclude outliers.

A condition indicator may be a number or category derived from the test results, patient data and optionally historic test data and historic patient data to indicate the patient's medical condition. In some embodiments it may be used to prioritise patient care by a clinician.

Output data may comprise test results, patient data, a condition indicator and a finding in the form of a statement about the patient's condition, a clinician alert to show a specific need for clinical intervention and its degree of urgency.

Output data may be derived from the test results and the patient data by the device using an algorithm configured to receive the test results and the patient data and produce output data as described above. For example, such derivation may be done using an algorithm in which comparison of the test results with reference data is used together with patient data associated with answers to questions asked of the patient by the device to determine the output data, in terms of a condition indicator and optionally a finding in the form of a statement about the patient's condition.

The algorithm may be a decision tree algorithm, an example of which will be described more fully herein with regard to a specific embodiment.

In some embodiments output data may be derived using an equation in which test results and patient data are used to provide numerical values of variables in the equation, and the resulting numerical output from the equation may be the condition indicator. The equation may have coefficients for each of the variables, the coefficients being a predetermined part of the algorithm for a specific medical condition, according to the desired weightings of the test results and the patient data in determining the condition indicator. In some embodiments the device is configured to allow the coefficients to be entered into the device via the input device or the clinician device. In some embodiments the device may be configured such that the coefficients may be specific to a patient, to allow some patients to have certain test results or patient data to be more heavily weighted in deriving the output data than others.

The device allows monitoring by a clinician of a patient's test data and patient data over time to indicate changes in condition relative to a defined reference condition of the patient at the time the reference data was received. The clinician may observe the trend in the patient's test results, or the trend in an average or variation of a condition indicator derived from it. The condition indicator may be derived using an average of the test results over a time period or a variation in the test results over that time period. For example, an increase in the variation in the test results may itself be indicative of a change in the patient's medical condition. In some circumstances it may indicate poor compliance with the test method, distraction or distress of the patient that might need a clinician's intervention.

The condition indicator may be stored as a function of time to provide historic condition indicator data, and the actual condition indicator may be derived using historic condition indicator data.

In some embodiments the device is configured to provide the condition indicator to the patient via the patient device to indicate that their condition is stable, worsening or improving.

The device may be configured to allow one or more action thresholds to be set for the test results or for the condition indicator and to compare the test results or the condition indicator with the action threshold in order to derive the output data. In some embodiments when the test results or the condition indicator reaches the action threshold the device may initiate further actions, for example to output a request to the patient for a further test or to output a clinician alert, which may form part of the output data. A clinician alert may be communicated by data link to a clinician device and may further be sent via other means, such as email or mobile phone communication.

An action threshold may be set for one or more of the test results, the patient data and the condition indicator. An action threshold may be used in an algorithm forming part of the device, for example as a decision criterion used within a decision tree.

The device may be configured to derive an action threshold from the reference data according to predetermined criteria entered or confirmed by a user. For example, the reference data may comprise values of the mean and a standard deviation (SD) of test result such as the response time to a cognitive test, and the action threshold for the test results in the monitoring phase may be set as a multiplier times the SD of the test result above or below the reference data mean. An action threshold may take into account the variation of the present test results and be set such that the mean over a number of recent test results should be greater than a multiplier times the SD of the recent data above the reference data mean. Different ways of deriving an action threshold will be apparent to the skilled person, and may be chosen according to the medical condition.

The device may be configured such that a clinician may modify the reference data or the action threshold after the start of the monitoring phase, when the device is operating in the monitoring mode. In this way a patient whose condition improves during monitoring might have their reference data or an action threshold modified to narrow the range outside which a test result may trigger an action, or a patient whose test results show a large variation around the average may have their reference data or action threshold modified to widen that range.

Running of tests and receiving patient data may be carried out according to a test schedule, and that schedule may be personal to an individual patient. For example, some patients may best be tested once per week if their medical condition is stable and others once per day if their condition is unstable. The device may be configured to receive and to operate a test schedule, which may be a specific to an individual patient. The test schedule may be a predetermined test schedule appropriate for a subpopulation of which the patient is a member. A patient using the system may feel their condition is worsening, and so may choose to trigger additional testing to check their condition. Accordingly, the device may be configured to receive a patient request via the input device to initiate a test cycle including running a test and receiving patient data. Such requests may be logged by the system and reported to the clinician device. Test results and patient data received following initiation by a patient may be flagged in the historic test results and the historic patient data and may be treated differently in deriving a condition indicator from data received from scheduled tests.

In some situations it may be advantageous to modify the test schedule during the course of monitoring a patient. For example if the patient's condition is worsening, it may be advantageous to increase the frequency or change the type of the tests. The device may be configured such that the test schedule may be modified by the clinician device, or by the device itself according to predetermined criteria. Change in a patient's condition might be determined by comparing test results with historic or reference data or by comparing a condition indicator with a historic condition indicator.

The device may comprise an expert system configured to carry out the functions described herein. The device may comprise an algorithm operated by a computer program running on a computer forming part of the device. The algorithm may form part of an expert system and may comprise a decision tree. The algorithm may initiate and run monitoring tests and may request and receive patient data conditionally according to preceding test results or patient data received by the device. The algorithm may request monitoring tests or patient data according to a pathway through a decision tree. The algorithm may derive a condition indicator from scores associated with pathways through a decision tree, for example by summing or averaging the scores or by adopting an extreme value of the score as the condition indicator. The algorithm may generate a clinician alert when a predetermined score is reached or a branch in the decision tree is traversed.

To enable monitoring of multiple patients by a single clinician, in some embodiments the device is configured to allow comparison of the condition of more than one patient and to prioritise the patients for attention. In some embodiments output data is output at a clinician device to indicate a patient's priority for clinical attention according to one of: a value of a condition indicator or a clinical alert forming part of the output data.

For example by operating with a clinician device such that the clinician device outputs a list of two or more patients identified by a patient identifier such as a patient ID code, the patient's name or initials, together with output data relating to them including their condition indicators. Accordingly in some embodiments the device is configured to form part of a system comprising two or more devices linked to a clinician device, the clinician device being operable to:

receive output data comprising a condition indicator, and

output output data comprising the condition indicator and a patient identifier.

In some embodiments the clinician device is operable to highlight or position on an output device such as a display the output data and patient identifier according to a value of the condition indicator, so as to alert a clinician to the highest priority patient. The output data may further comprise a clinician alert, and the clinician device may be operable to indicate the existence of a clinician alert associated with the output data and/or patient identifier.

In some embodiments the device is configured such that patients may be ranked or highlighted according to their condition indicators or the presence of a clinician alert in output data.

In some situations a patient may take medication such as a drug to control their medical condition. Accordingly, in some embodiments the device is adapted to provide output data comprising a drug dose recommendation. The device may be configured to output a drug dose recommendation only when operating in the monitoring mode. The device may be adapted to output a drug dose recommendation only to the clinician device when operating in the reference mode.

A drug dose recommendation may comprise a single dose of the drug to be taken at a single time by the patient. The device may provide a prompt for a patient to take the single dose of medication for example by a visible or audible alert. The drug dose recommendation may comprise a schedule defining a drug dose to be taken by the patient at one or more future times, or a timing interval or a frequency at which the drug dose is to be taken over a specified future dose time interval.

The device may comprise an algorithm operable to derive a drug dose recommendation based on one or more of test results, historic test results, reference data, the condition indicator and historic condition indicator data.

The device may be configured such that when a value of the test results or the condition indicator reaches an action threshold a change in drug dosage recommendation is triggered. Such an action threshold may be set by the device according to a predetermined criterion or may be entered via a clinician device.

The device may be configured such that the drug dose recommendation is limited to be no greater than a maximum drug dose value. In some embodiments the maximum drug dose value is a maximum dose to be taken on any single occasion. In some embodiments the device may be configured such that the total of the drug dose recommendations over a dose time interval is no greater than a maximum drug dose value.

A maximum drug dose value may be a value determined before first operation of the device with a specific patient, for example a maximum dose recommended by a drug manufacturer for all patients, or may be a value appropriate for a subpopulation of patients of which the patient is a member.

For some conditions there may be a minimum drug dose level below which a patient's dose should not fall to avoid loss of control of the patient's condition. For example, with some drugs, complete cessation of the drug dose should not happen without close clinical oversight. Accordingly the device may be configured such that the total of the drug dose recommendations over the dose time interval is no less than a minimum drug dose value. In this way the device is able to operate safely in an automatic manner when in the monitoring mode, having the additional feature of providing a drug dose recommendation.

In some embodiments the device is configured to enable a maximum or a minimum dose value to be specified for an individual patient. In some embodiments a maximum (or minimum) drug dose value may be entered by a clinician, for example before first use of the device with a patient in the reference mode. In some embodiments the device is configured such that the maximum (or minimum) drug dose value may later be modified according to the patient's condition. Such modification may be done via a clinician device connected to the device via a remote data link. In this way the device is adapted for use in situations where the maximum (or minimum) drug dose value may vary from patient to patient, for example according to the patient's weight, age, other medical conditions, or individual aspects of the patient's physiology that may determine their tolerance for a drug, and may vary with time for a single patient according to their condition or their response to the drug dose recommendation. In this way the device provides a means to control a patient's drug dose automatically and safely while allowing a clinician to monitor and to control the operation of the device remotely.

In some embodiments the device is configured to derive output data comprising a condition indicator that depends on the drug dose recommendation and historic drug dose recommendation data, namely the history of the drug dosage recommendations over time.

The device may be adapted to be tuneable for a given patient so as to give improved control over their condition. The device may be adapted to learn from a patient's response to a drug in order to control the timing, frequency or dose in the drug dosage recommendation. In some embodiments the device is configured to analyse one or more of historic test results, historic patient data, historic condition indicator data and historic drug dosage recommendation data, and to determine a drug dose recommendation based on those data in order to control one or both of average test results or variation in test results over time. The said data may be controlled to lie within one or more action thresholds. Such action thresholds may be derived by the device from the reference data or may be entered by a clinician.

The device is applicable to a variety of medical conditions according to the configuration with the type of electronic monitoring test and the algorithm forming part of the device. According to the embodiment the device is adapted for use in the following conditions: a hepatological disease, cardiovascular disease, a respiratory disease, a gastrointestinal disease, a rheumatological disease, an endocrine disease, a neurological disease, cancer, pain. In some embodiments the device is adapted to monitor inflammation.

Examples of conditions in which the device may be used include the following:

Liver disease in which hepatic encephalopathy (HE) is a condition associated with the disease, and in which the device may be used to monitor cognitive function and indicate whether cognitive function has declined, potentially indicating HE. In such cases a patient may then be treated with a laxative such as a non-absorbable disaccharide laxative, such as lactulose or lactitol, according to a drug dose recommendation provided by the device. The device may also communicate with a clinician device to provide a condition indicator for the patient, and a system for managing liver disease may comprise a clinician device and a plurality of patients devices linked to it. Intervention by the clinician may be prioritised by the system according to the condition indicator, or other data such as patient data or a change in the test results. An alert message may be sent by the system to the clinician, for example by means of a message sent within the system, an email sent to an external email system, a data message or voice message by a telephone network.

Ascites, for example associated with liver disease, which is managed by diuretics, may be monitored and controlled by an embodiment of the device adapted such that the monitoring tests comprise the patient's weight and blood electrolyte measurements, and the output data comprises a drug dose recommendation wherein the drug is a diuretic. In some embodiments wherein the condition is ascites the monitoring tests further comprise a test of creatinine levels in a body fluid such as blood, serum or plasma.

Dementia, in which the device may monitor for acute cognitive decline, which may be the result of superimposed delerium, for example due to infection. A patient's baseline cognitive function and variation about their average level of function may be determined in the reference mode and then set as reference data against which later changes may be detected, in particular acute decline overlying possible longer-term slow decline.

Conditions in which fatigue is a major symptom, such as PBC (primary biliary cirrhosis) and chronic fatigue syndrome, may usefully be monitored using a test of reaction time or other marker of fatigue.

Conditions in which a Patient Reported Outcome Measure (PROM) can be used as patient data entered into the device to monitor a patient's health status. PROMs may be used to give an objective measure on patient symptoms such as pain, fatigue, depression, or sleepiness. Monitoring based on measurement of patient physiology data such as heart rate or blood pressure together with receiving patient data may allow better observation and control of a range of such conditions.

Control of neurological conditions such as Parkinson's disease, in which the monitoring test might monitor motor function or muscle tone, or upper limb tone.

Monitoring and control of side-effects of drugs, in which there is a balance to be struck between therapeutic effect and cognitive or neurological side-effects such as disorientation, drowsiness and impaired motor co-ordination. Further medical conditions to which the device may be applied and appropriate measurands for the monitoring test and patient data useable by the device in monitoring and/or controlling the condition are listed in table 1 , with appropriate outcomes in terms of monitoring and control of the condition.

Table 1 Disease Test measurands and Remote monitoring potentia!

patient data (PROMS)

Cardiovascular disease

Heart failure Weight and electrolytes Optimisation of diuretics

Heart failure Patient Reported Early identification of exacerbation

Outcome Measures

(PROMS) e.g.

breathlessness

Respiratory disease

Chronic Obstructive Spirometry Early identification of acute exacerbation Pulmonary Disease 0_? Sats Directed physio exercises

(COPD) PROMS

Interstitial lung Spirometry Monitoring aggressiveness of disease disease (pulmonary 0₂ Sats (speed of deterioration)

fibrosis) PROMS Early identification of acute exacerbation

Gastrointestinal disease

Inflammatory bowel PROMS (e.g. Crohn's Early identification of acute flare. Monitoring disease disease activity index- response to biological therapies (e.g. for

CDAi) loss of efficacy over time)

Inflammation markers

(e.g. C-Reactive Protein

(CRP), faecal

caiprotectin)

Liver disease As described herein As described herein

Rheu atologic disease

Arthritis PROMS Monitoring severity of joint symptoms to

Inflammation markers tailor therapy e.g. biological therapies. (e.g. CRP) Identification/timing of joint replacement surgery

Chronic fatigue PROMS Monitoring symptoms (c.f. symptom diary), syndrome/ ME/ directing interventions (e.g. graduated fibromyalgia exercise)

Diabetes/endocrine dh »ease

Diabetes (especially Glucose identification of patients who would benefit Type 2 Diabetes from early escalation of treatment (real time Meilitus) transmission of results to a clinician device rather than review at next clinic)

Neurological disease

Parkinson's disease PROMS Monitoring symptoms

Computerised test (e.g. identification of loss of efficacy and need for for upper limb tone) increase in therapy

Stroke PROMS Monitoring progress

Computerised test Directing physiotherapy

Cancers

Various cancers (e.g. Tumour markers (e.g. Monitoring for recurrence post

prostate) PSA) chemo/radiotherapy/surgery

Various cancers PROMS Monitoring for chemotherapy side-effects with directed (pharmacological) intervention if necessary.

Pain (also non-cancer PROMS Optimisation of analgesic therapy causes e.g. Identification of patients likely to benefit osteoarthritis) from non-pharmacological intervention

Accordingly, in certain embodiments the device is adapted such that: The condition is selected from heart failure and ascites and a monitoring test is selected from the patient's weight and a blood electrolyte measurement, in some embodiments the device being configured to run both a test of a patient's weight and a blood electrolyte measurement;

The condition is a lung disease and a monitoring test is selected from spirometry and measurement of blood oxygen saturation;

The condition is selected from inflammatory bowel disease and arthritis and the monitoring test measures an Inflammation marker;

The condition is a rheumatological disease and the monitoring test is a motor control test;

The condition is a neurological disease and the monitoring test is a motor control test or a test of sensory function;

The condition is cancer and the monitoring test measures a cancer marker or a manifestation of cancer such as pain; or

The condition is dementia and the monitoring test is a cognitive test. In the above embodiments the patient data may comprise a Patient Reported Outcome Measure.

According to a second aspect a computer readable medium is provided comprising computer- executable instructions to operate a device as described herein. According to a third aspect a kit is provided, comprising a device as described herein and a drug, wherein the device is configured to provide a dose recommendation for the drug. In some embodiments the monitoring test is a cognitive test and the drug is a laxative.

According to a fourth aspect a method is provided for monitoring a medical condition of a patient, the method implemented on an electronic device, the method comprising:

running an electronic monitoring test for the patient, wherein the test generates test results for the patient;

receiving patient data relating to the medical condition of the patient;

comparing the test results with reference data and comparing the patient data with patient reference data to derive output data; and

outputting the output data;

wherein the output data comprises a condition indicator and a drug dosage recommendation. In some embodiments the method comprises:

operating the electronic device in a reference mode, wherein the reference mode enables the reference data to be set for the patient; and

operating the electronic device in a monitoring mode, wherein the monitoring mode uses the reference data which is set in the reference mode. In some embodiments the method comprises receiving a confirmation that the test results are to be used as reference data in the monitoring mode.

The method may comprise providing, in the reference mode, the test results for the patient to a clinician device; and receiving a confirmation from a clinician device that the test results are to be used as reference data in the monitoring mode.

In some embodiments the method further comprises:

comparing the test results with a predetermined criterion for the test results to be set as reference data; and

if the criterion is met, setting the test results as reference data.

In some embodiments, the method comprises receiving reference data from a clinician device. In some embodiments the method comprises running a monitoring test selected from a cognitive test, a motor control test and a biochemistry test on a body fluid.

The monitoring test may be a cognitive test adapted for monitoring of HE as described herein. The method may comprise receiving patient data by means of the process of presenting a question to the patient via an interface of the electronic device and receiving via the interface a value indicating the response to the question, the value forming the patient data.

In some embodiments the drug dosage recommendation may be modified in response to comparison of the test result with an action threshold for the test result stored as part of the reference data. The drug dosage recommendation may be increased in response to comparison of the test result with an action threshold for the test result stored as part of the reference data. In some embodiments the drug dosage recommendation may be reduced in response to comparison of patient data with an action threshold for the patient data stored as part of the reference data. In some embodiments the drug dosage recommendation may be increased when both of (i) a test result reaches or passes an action threshold stored as part of the reference data and (ii) a value of patient data lies within a range of values stored as part of the reference data.

In some embodiments the drug dosage recommendation may be reduced when a value of patient data lies outside the said stored range of values.

In some embodiments the method comprises limiting the drug dose recommendation to be no more than a maximum dose value or to be no less than a minimum dose value. In some embodiments the method comprises setting a maximum or a minimum dose value for an individual patient.

In some embodiments the method comprises outputting output data at a clinician device to indicate a patient's priority for clinical attention according to one of a value of a condition indicator or a clinical alert.

In some embodiments the condition is selected from: a hepatological disease, cardiovascular disease, a respiratory disease, a gastrointestinal disease, a rheumatological disease, an endocrine disease, a neurological disease, cancer, pain, inflammation, a haematological disease, an immunological disease, a psychiatric disease.

In some embodiments the method comprises one of the following:

The condition is selected from heart failure and ascites and a monitoring test is selected from the patient's weight and a blood electrolyte measurement, in some embodiments the method comprising both a test of a patient's weight and a blood electrolyte measurement;

The condition is a neurological disease and the monitoring test is a motor control test;

The condition is cancer and the monitoring test measures a cancer marker; or

The condition is dementia and the monitoring test is a cognitive test.

In the above embodiments the method may further comprise receiving patient data comprising a Patient Reported Outcome Measure.

In some embodiments the condition is hepatic encephalopathy and the drug is a laxative.

In a further embodiment a method is provided of operating an electronic device for monitoring a patient's medical condition, the method comprising:

receiving patient data relating to the patient's medical condition;

comparing the test results with reference data to derive output data comprising a condition indicator;

outputting the output data;

operating the electronic device in a reference mode, wherein the reference mode enables the reference data to be set for the patient; and operating the electronic device in a monitoring mode, wherein the monitoring mode uses the reference data which is set in the reference mode.

According to a fifth aspect a method is provided of treating a patient suffering from a medical condition using an electronic device as described herein, comprising the steps of

(i) monitoring the medical condition to output a drug dosage recommendation for a drug, and then

(ii) administering to the patient, or causing to be self-administered by the patient, the said drug at the said recommended dosage.

The method may comprise repeating steps (i) and (ii) at time intervals such as similar to or longer than the time for effect of the drug.

Preferred features of the second, third, fourth and fifth aspects of the invention are as for the first aspect mutatis mutandis

Brief description of the figures Illustrative embodiments of the present disclosure will now be described, by way of example only, with reference to the drawings, in which:

Figure 1 is a schematic illustration of the functional components of the device.

Figure 2 is a flow diagram showing the operations performed by a device in a reference mode . Figure 3 is a first part of flow diagram showing the operations performed by a device in a monitoring mode.

Figure 4 is a second part of a flow diagram continued from figure 2.

Figure 5 shows a first part of a tree diagram for an algorithm for monitoring or control of HE.

Figure 6 shows a second part of the tree diagram shown in figure 5.

Figure 7 shows the structure of a computer system adapted to form part of the device and to perform the operations and implement the methods described herein.

Figure 8 shows a result from operation of the system with a patient, in which the medical condition is hepatic encephalopathy.

Figure 9 shows a portion of the result in figure 8 on an expanded timescale.

Throughout the description and the drawings, like reference numerals refer to like parts.

Description of embodiments Referring to figure 1 , an embodiment of a device according to the invention comprises a device 10 adapted to communicate with a clinician device 12 via a data link. The device comprises:

an i/o device 14 comprising a display screen and a data input device, for example in the form of a touch sensitive display device as known in the art, adapted to present an electronic monitoring test to a patient in terms of a display on the screen and to receive patient input in response to the test in terms of touching an area of the screen;

a test module 16 adapted to run an electronic monitoring test and to receive test results, which in this embodiment comprises computer instructions to run a Number Connection Test (NCT) and to receive the patient's response;

a patient data acquisition module 18 comprising computer instructions to present questions and receive the patient's responses visa the i/o device 14;

an expert system 20 configured to receive test results from he test module and patient data from the patient data acquisition module and which comprises computer instructions to operate an algorithm to carry out the device functions as described herein; and

a control and test schedule module 22 that controls the operation of the device.

The expert system is configured to output the output data to the clinician device 12 and to the i/o device 14. Optionally the device may receive further information from a data linked external device 24 such as weighing scales, a blood pressure measurement device, a blood glucose meter, or a thermometer

Figures 2 to 6 show operations performed by an embodiment of the device adapted to monitor a patient for hepatic encephalopathy and further adapted to output a drug dose recommendation as part of the output data. In this embodiment the monitoring test is a cognitive test such as a Number Connection Test (NCT) with a test result in the form of the response time for a patient to complete the test, and the patient data comprises the patient's stool frequency in units of numbers of stools per day. It will be understood that the flow diagrams in figures 2 to 4 are general for a range of conditions, figures 5 and 6 showing an embodiment of an algorithm specifically adapted for monitoring and control of HE.

Figure 2 is a flow diagram showing operations performed by the device in a reference mode. The device at operation 30, receiving patient information including a patient identifier either entered by a clinician via the i/o device 14 or remotely via the clinician device 12, and optionally a patient specific maximum or minimum drug dose value for use in deriving the drug dose recommendation.

The device is configured to have three pre-selectable modes of operation indicated as (i), (ii) and (iii), the mode being selected at decision point 32, for example by means of a parameter included in the computer instructions or by a user in response to a prompt by the device. If mode (i) is selected, in which reference data is entered by a clinician, the process moves to operation 34 in which the reference data is entered via the i/o device 14 or the clinician device 12. If mode (ii) is selected, in which the device runs a chosen number of tests and then compares the results with a predetermined criterion stored in the device to set the test results as reference data, the process moves to operation 36 in which the device receives the criterion, for example from a data store in which it has previously been stored, or via entry to the device via 14 or 12. The device then runs the tests in operation 38 according to a test schedule and compares the results, or output data derived from them, with the criterion in operation 40. If the results meet the criterion then the device moves to operation 42 to set the reference data. Optionally the device may run the tests until the criterion is met by means of a return loop from 40 to 38, with appropriate limits on the operation of the return loop and error traps as known in the art (not shown). If mode (iii) is selected, in which the device runs a number of tests and reference data is set by a clinician following review of the test results, the process moves to operation 44 in which the chosen number of tests are run according to a test schedule and then provided to a clinician for review in operation 46. The device receives confirmation in operation 48 that the test results are to be set as reference data and then moves to set the reference data in operation 42. If confirmation is not received then optionally the process returns to operation 44 to run further tests, again with a limit on the number of returns and error trapping in the return loop.

Following setting of reference data, in operation 50 optionally one or more action thresholds are set, for example by data entry via the i/o device or the clinician device, or automatically by the device according to one or more predetermined criteria. In this embodiment in which the test is a Number Connection Test and the test result is a response time to complete the test, a criterion may be that the action threshold is a multiple or a fraction of the standard deviation of the test results from the reference mode above the mean of those tests. Other criteria may be used in other embodiments according to the condition to be monitored and the type of test to be run. The device then moves automatically from the reference mode to the monitoring mode at operation 52.

Figures 3 and 4 are a flow diagram showing operations performed by the device in a monitoring mode. The device initiates a test according to the test schedule at operation 60, runs a test and receives test results at operation 62, receives patient data in response to questions presented to the patient at operation 64, and stores the test results and patient data as historic data at operation 66. The test results are compared with reference data to derive a condition indicator at operations 68 and 70, and optionally patient data is used to derive the condition indicator at operation 72. In this embodiment, to monitor hepatic encephalopathy (HE), the patient data comprising data on the patient's stool frequency is used to modify the condition indicator according to its value as described in more detail with reference to figures 5 and 6. In other embodiments the condition indicator may be derived in operation 74 using in addition one or more of the following: (i) historic test results; (ii) historic patient data; (iii) historic condition indicator data. It will be understood that operations 72 and 74 may be part of a single combined operation. In this embodiment adapted to monitor HE historic test results are used to modify the condition indicator from the value initially derived in operation 70 as described in more detail with reference to figure 6. The condition indicator is stored as historic condition indicator data in operation 76. One or more of the condition indicator, the test results and an item of patient data are compared with an action threshold in operation 78, and if the action threshold is reached then the action is initiated. For example, in this embodiment two action thresholds are used: a monitoring test action threshold is a test response time beyond which the patient is deemed to be cognitively impaired and a patient data action threshold is that the stool frequency is greater than 3 per day. If both action thresholds are reached, then an action to alert a clinician is initiated.

The process then passes to point A on figure 4. The device uses the test result and the patient data to derive a drug dosage recommendation in operation 80. The device also uses a maximum drug dose value beyond which the drug dose recommendation does not pass. This value is a predetermined criterion in this embodiment to monitor HE, though in variants of the embodiment the maximum drug dose value may be an individual maximum drug dose value for a specific patient that may be entered to the device during or before the reference phase, for example in the starting operation 30. In some embodiments one or more of: (i) the condition indicator; (ii) historic test results; (iii) historic patient data; (iv) historic condition indicator data; (v) historic drug dosage recommendation data are used in operation 82 to derive the drug dosage recommendation. In operation 84 the drug dose recommendation is stored as historic drug dose recommendation data, and in operation 86 the output data is outputted to the screen on the patient device and to the clinician device. In this embodiment the condition indicator is only outputted to the clinician device. The device then waits for the next initiation from the test schedule.

Figure 5 shows an algorithm adapted for operation in an embodiment of the invention in the monitoring mode, for monitoring of HE and control of doses of a laxative drug, lactulose, for treating it. The algorithm is in the form of a decision tree comprising input stages of cognitive test data and patient data and a number of decision points to define a plurality of pathways through the tree. The device is configured with the algorithm so that in use the device is able to perform the depicted process. In this embodiment the cognitive test results comprise a response time to a test, such as a NCT, operated on the patient device and the action threshold (referred to with regard to figures 5 and 6 as simply the 'threshold') is a threshold response time, which is derived from reference data in the form of a mean response time for a given patient and a variance about the mean. For example, in some embodiments the action threshold may be one SD above the mean. In use, if the response time is greater than the threshold the patient's condition is deemed to have deteriorated. In this embodiment the patient data comprises data on the patient's stool frequency and the acquisition process comprises a simple question and answer procedure. In some versions of the embodiment further questions may be asked, for example regarding the patient's hydration, such as how many glasses of water have they drunk that day. Each route through the decision tree provides one or more findings associated with it, and each finding has a numerical severity score associated with it. The condition indicator in this embodiment is the highest severity score for any finding along the route the algorithm takes through the decision tree. Some routes prompt enquiries by the algorithm to historic cognitive test results, the response to the enquiry being used to derive the severity score. In some versions of this embodiment some routes through the decision tree may prompt enquiries by the algorithm to historic patient data or historic drug dose recommendations.

In this embodiment both the test results and the patient data have action thresholds associated with them, with the branches of the decision tree being traversed according to whether the results or the data reach the action threshold.

In this embodiment the device is configured to output a drug dosage recommendation in terms of ml of lactulose per day, and the present and historic drug dosage recommendation data are stored by the device. In figures 5 and 6 the start and end of the process are shown as circles, an action in the algorithm is shown as a rectangle, a decision point is a lozenge and the meeting point of two branches in the tree is a lozenge with arrows leading to it. A lozenge having a plus sign within it shows a junction point where the process follows both branches from the junction simultaneously. The algorithm starts when initiated according to a test schedule at operation 100. The test schedule operation may be part of a control program operating as part of the device, in this embodiment operating to schedule a test once per day. When a test is to be done, the device runs a cognitive test 102. At decision point 104 if the response time is less than the threshold the algorithm moves to a patient inquiry 108 at which patient data is acquired by means of a question and answer process. If it is greater, the algorithm moves to a repeat cognitive test 106 and the lower of the two response times is taken as the test result at decision point 1 10. The patient inquiry is in the form of a question on the patient's stool frequency and the patient data is a numerical value of stool frequency per day. At decision point 1 10 if the response time is greater than the threshold then the algorithm moves to the cognitive impairment branch and to decision point 1 12, at which if the stool frequency is less than 3 it moves to decision point 1 16, otherwise to decision point 1 18. At decision point 1 16 if the current drug dosage recommendation is less than the maximum drug dose value then the drug dose recommendation is increased by a drug dose increment at step 120 and finding 1 is established at step 138, with a severity score associated with the finding.

Finding 1 : Impaired cognitive function, lactulose increased: Score 30

If the current drug dosage recommendation is greater than or equal to the maximum drug dose value then the drug dose recommendation is not increased, and a clinician alert is sent at step 122, in this embodiment to recommend a clinical decision on whether to administer an enema, and finding 2 is established at step 140, with a severity score associated with the finding.

Finding 2: Impaired cognitive function, patient taking maximum dose of lactulose, consider enema: Score 80

The algorithm then moves to point A from which the diagram continues in figure 6.

In this embodiment the maximum drug dose value is 120ml/day. In some embodiments the algorithm is adapted to allow the maximum drug dose value to be set as a parameter for an individual patient. In this embodiment the drug dose increment is 30ml/day, and in some embodiments this may also be set as a parameter. It will be understood that for different conditions and different drugs the maximum drug dose value and the drug dose increment may be different. If at decision point 1 12 the stool frequency is not less than 3 the algorithm moves to decision point 1 18. If at that point the stool frequency is greater than 3 then the algorithm moves to decision point 124, otherwise the stool frequency is equal to 3 and the algorithm moves to finding 5 at step 132 and then to point A Finding 5: Impaired cognitive function, stool frequency =3/day, lactulose unchanged: Score 40

If at decision point 1 18 the stool frequency is greater than 3 then lactulose is likely to be being used at too high a dose, or there is a more serious underlying problem causing cognitive impairment despite the high stool frequency. Either is a significant finding that merits a higher score. At decision point 124 if the current drug dose is less than 30ml/day then lactulose is stopped at step 128 and finding 3 is established at step 142:

Finding 3: Impaired cognitive function, stool frequency greater than 3/day, lactulose stopped: Score 70

At point 124 if the current drug dose is greater than 30ml/day then lactulose is reduced by the drug dose increment, 30ml/day, at step 130 and finding 4 is established at step 144:

Finding 4: Impaired cognitive function, stool frequency less than 3/day, lactulose reduced: Score 70

The algorithm then moves to point A.

Moving back along the decision tree to decision point 1 10, if the response time is less than the threshold, then the patient's cognitive status is unchanged, and the algorithm moves to the non- cognitive impairment branch. At decision point 1 14 if stool frequency is greater than 3 per day then the algorithm moves to decision point 126. If the current drug dose recommendation is less than the minimum dose, equal to the drug dose increment, 30ml/day, then lactulose is stopped at step 134 and finding 7 is established at step 146. Finding 7: Cognitive function unchanged, stool frequency greater than 3/day, lactulose stopped: Score 0

If the current drug dose recommendation is greater than the minimum dose then lactulose is decreased by the drug dose increment, 30ml/day at step 136 and finding 8 is established at step 148.

Finding 8: Cognitive function unchanged, stool frequency less than 3/day, lactulose reduced: Score 0

The algorithm then moves to point B.

Referring to figure 6, the cognitive impairment branch continues from point A to decision point 150, where the algorithm questions historic test results to determine whether the response time has been greater than the threshold for 2 days. If so, finding 6 is established at step 152 with an increased severity score:

Finding 6: Impaired cognitive function for more than 2 days: Score 90

The non-cognitive impairment branch joins from point B and the algorithm then moves to decision point 154, where if the drug dose recommendation has been modified then the laxative prescription is confirmed at step 162, which may be a clinician response from a remote clinician device, and the algorithm also moves to decision point 158 where if laxative intake has been prescribed by the device in the form of a drug dose recommendation, the patient takes the laxative at step 160. In some embodiments the device may request confirmation by patient input via the patient device that the laxatives have been taken. If the dosage has not been modified at decision point 154 then the same process to that from decision point 158 takes place via decision point 156 and intake at step 164. The algorithm then ends at end point 168.

In this embodiment the algorithm derives the condition indicator as the maximum severity score encountered as it moves along its pathway from start to end. For example, on a pathway via points 1 10, 1 12, 1 16, 120, 138, 150 and 152, the severity score is 30 from finding 1 and 90 from finding 6. The condition indicator is then a severity score of 90. It will be apparent that other ways of combining individual severity scores from branches in a decision tree may provide effective condition indicators and may be used in this or another condition. For example, a score established in an upstream portion of the algorithm pathway might be multiplied or divided by a multiplier on passing along a downstream branch. The multiplier may be a coefficient or a function characteristic of the condition and may be specific to a patient or to a subpopulation of patients.

In this embodiment the output data comprises the condition indicator, the drug dose recommendation and optionally the test results and patient data. Output data outputted to the clinician device at the end of the process includes the condition indicator and the drug dose recommendation and may include a clinician alert such as that generated at step 122 or an alert generated when the severity score reaches an alert threshold that may be a parameter in the algorithm. Output data outputted to the patient at the i/o device 14 includes the drug dosage recommendation at steps 160 and 164 but in this embodiment does not include the condition indicator, which is used only by the clinician for alerts, prioritisation and review of the patient's condition.

The described operations, processes and methods may be implemented by a computer program. The computer program which may be in the form of a web application or 'app' comprises computer- executable instructions or code arranged to instruct or cause a computer or processor to perform one or more functions of the described methods. The computer program may be provided to an apparatus, such as a computer, on a computer readable medium or computer program product. The computer readable medium or computer program product may comprise non-transitory media such as a semiconductor or solid state memory, magnetic tape, a removable computer memory stick or diskette, a random access memory (RAM), a read-only memory (ROM), a rigid magnetic disc, and an optical disk, such as a CD-ROM, CD-R/W, DVD or Blu-ray. The computer readable medium or computer program product may comprise a transmission signal or medium for data transmission, for example for downloading the computer program over the Internet.

An apparatus or device such as a computer may be configured to perform one or more functions of the described methods. The apparatus or device may comprise a mobile phone, tablet, laptop or other processing device. The apparatus or device may take the form of a data processing system. The data processing system may be a distributed system. For example, the data processing system may be distributed across a network or through dedicated local connections.

The apparatus or device typically comprises at least one memory for storing the computer- executable instructions and at least one processor for performing the computer-executable instructions.

Figure 7 shows the architecture of an example apparatus or device 200. The apparatus or device 200 comprises a processor 210, a memory 215, and a display 235. These are connected to a central bus structure, the display 235 being connected via a display adaptor 230. The example apparatus or device 200 also comprises an input device 225 (such as a mouse and/or keyboard) and a communications adaptor 205 for connecting the apparatus or device to other apparatuses, devices or networks. The input device 225 and communications adaptor 205 are also connected to the central bus structure, the input device 225 being connected via an input device adaptor 220. In operation the processor 210 can execute computer-executable instructions stored in the memory 215 and the results of the processing can be displayed to a user on the display 235. User inputs for controlling the operation of the computer may be received via input device(s) 225.

Example

General description of the exemplified embodiment

The example shows the operation of an embodiment of the invention in which the device is configured to:

compare the test results with an action threshold forming part of the reference data, compare a value forming part of the patient data with patient reference data, and output a drug dose recommendation derived from the said comparison.

In this embodiment the device is configured to increase the drug dosage recommendation if all of the following are true:

(i) the test result reaches the said action threshold

(ii) the patient data value lies within a selected range forming part of the patient reference data, and

(iii) the resulting drug dosage recommendation does not exceed the maximum drug dose value,

and to reduce the drug dosage recommendation if the patient data value lies in a second range forming part of the reference data, outside the said selected range.

It will be understood that a value at the end of a range as described above represents an action threshold, at which the operation of the device may change. Accordingly, the device is configured to increase the drug dosage recommendation if all of the following are true:

(i) the test result reaches a test action threshold

(ii) the patient data value does not reach a first patient data action threshold and

(iii) the resulting drug dosage recommendation does not exceed the maximum drug dose value;

It will be understood that while this example is directed to monitoring and treatment of HE, the same embodiment, with appropriate choice of parameters, may monitor or control other cognitive disorders, or, with a different electronic monitoring test, other medical conditions. Example - Monitoring and control of Hepatic Encephalopathy

In the embodiment of figures 5 and 6 the device is configured to monitor HE, wherein monitoring test is an electronic NCT, the patient data is a value of the stool frequency, and treatment of HE is done using a laxative such as lactulose.

The device is configured to increase the lactulose dose recommendation if the following are true: (i) a first and a second NCT test result both give a response time t(NCT) that reaches an action threshold value tc

(ii) the patient data value (stool frequency) does not reach a first patient data action threshold of 3/day, and

(iii) the present lactulose dose is less than the maximum drug dose value of 120ml/day;

and to reduce the lactulose dose recommendation if the patient data value (stool frequency) reaches a second patient data action threshold of 4/day.

To clarify the relation between the said ranges and action thresholds for the patient data, in this embodiment the range of the patient reference data within which the drug dosage recommendation may be increased is the range at or below the first action threshold, i.e. the range is 'less than 3/day'. The second range of the patient reference data within which the drug dosage is reduced, irrespective of the test result, is the range at or above the second action threshold, i.e. the range is 'greater than or equal to 4/day'.

The dosage at or below the second action threshold is the range of stool frequency at which the drug effect (of the lactulose) is considered to be sufficient, and the range above the second action threshold, i.e. a stool frequency of greater than 3 per day, is regarded as an excessive effect, more than is needed to achieve the clinical objective. An excessive stool frequency is also considered to be an adverse side-effect of use of laxatives, which affects the patient's quality of life and leads to poor compliance with treatment, but also potentially leads to dehydration, in itself a cause of cognitive deficit. In prior art practice effective control of HE without such excessive stool frequency is difficult or impossible to achieve over the long term, and the invention provides a means to control both HE and this side effect.

Method A device according to the embodiment as shown in figure 1 and operating an algorithm according to figures 5 and 6 was used to monitor hepatic encephalopathy in a patient and to produce output data comprising a drug dosage recommendation for lactulose and a condition indicator. The device was first operated in a reference phase to run an electronic NCT and to store test results, which were then used to determine the patient's baseline response time and derive an action threshold for the NCT test. The action threshold was stored as reference data. The patient was under observation by a clinician during this phase, and their condition was considered to be stable. The action threshold for the NCT test, tc, was selected by a clinician to be 2 standard deviations (SD) above the mean of the patient's response time during the reference phase (n=16 tests, 8 on each of a first and second day of tests, obvious outliers were excluded), tc = 92 seconds, and this was entered as reference data by the clinician overseeing the trial. The device was then operated in a monitoring phase to test the patient's response time t(NCT) and to request patient data on stool frequency once daily and to step the lactulose dose recommendation up or down daily in steps of 30ml/day. Patients were asked to use the system daily each morning and to follow the dosing recommendation. The clinician observed the test results and output data communicated from the patient device to the clinician device and followed up results that gave concern by telephone conversation.

Results The results from operation of the device in the monitoring phase are shown in figures 8 and 9. Figure 8 shows the operation over a period of 10 weeks, and figure 9 shows the same data for a two week period within the 10 weeks. At the start of the monitoring period the patient was being treated under prescription by a clinician and had an NCT response time t(NCT) of 60-70s, i.e. below tc, and was on a relatively high dose of lactulose (60ml/day), with a resulting high stool frequency (5/day). As the patient data input was stool frequency greater than 3/day (i.e. reached the action threshold of 4/day), the device reduced the dosage recommendation to 30ml/day, and in the next step, as stool frequency was still greater than 3/day, reduced the dosage to zero. Stool frequency fell following this from 5/day to 2/day, and then t(NCT) and stool frequency varied within a range below the action thresholds over the following days. A reading of t(NCT) greater than tc on 3/6/15 was not confirmed by the repeat test and so did not trigger an increased drug dosage. However, a sudden rise in t(NCT) with 3 tests over threshold on 10/6/15, together with a stool frequency of 1/day resulted in the system re-starting lactulose with a dose recommendation of 30ml/day. Over the following 2 weeks the results are shown in more detail in figure 9. Following re-start of lactulose the patient's t(NCT) results were stable at around 70s, less than tc, and stool frequency was moderate at 3/day, so the dose recommendation remained at 30ml/day. On 23/6/15 the reported stool frequency rose to 5/day; t(NCT) rose suddenly and dramatically on the same day but, owing to the configuration of the device that the patient data, namely the stool frequency, overrides the test results, the device reduced the drug dosage recommendation to zero. The following day, the lower of the repeat t(NCT) results was below tc and the stool frequency was reported as zero, which meant the drug dosage recommendation output from the algorithm was zero. However, the results from 23/6/15 had triggered a clinician alert and, following a consultation, the clinician used the clinician device to override the algorithm output, to cause a drug dosage recommendation output to re-start lactulose at 30ml/day. The device then continued automatic operation to monitor t(NCT) and stool frequency, and increased the dose again on 29/6/15 when t(NCT) again exceeded tc.

The patient's condition was controlled stably after the HE episode on 24/6/15. The t(NCT) results then fell steadily from 1/7/15 and stool frequency increased to 5/day on 3/7/15 and 5/7/15, so the device reduced the dose recommendation in two steps again to zero. The patient's condition was stable over the following two weeks from 5/7/15, with two high t(NCT) results not being supported by repeat tests, until 22/7/15 when a pair of t(NCT) values above tc again caused the device to raise the dosage recommendation. Overall, the results show (a) the device operating to give highly effective control of the patient's condition by varying the drug dosage recommendation in response to test results from the NCT test and to patient data (stool frequency) entered by the patient, and (b) the configuration of the device to allow effective clinician oversight of the output data and to provide a manual drug dosage recommendation to the patient, overriding the output from the algorithm.

The device shows the following beneficial effects compared with the prior art. Improved control of the medical condition. The device and method, and combination of the device and method with a drug, provide a paradigm shift in the treatment of chronic time-varying medical conditions such as HE. In present clinical practice the kind of control of the condition shown in the example is not possible. Routine monitoring of cognitive function in HE and control of the condition using drug dosage based on such monitoring is not done in current practice, as no device or method suitable for such monitoring or control has been available hitherto.. Current practice for management outside hospital is to allow patients to titrate their lactulose dose independently based solely on stool frequency, without any monitoring of cognitive function. This leads to excessive drug use, poor compliance through patients wishing to avoid side effects, and poor control of HE. Episodes of HE as indicated by t(NCT) above the action threshold are treated rapidly and effectively by the device: t(NCT) drops quickly below tc with increased dosage. Use of the device prevents more serious development of HE that would occur in prior art practice if a patient has to wait for a clinician's decision based on gross symptoms when they become apparent. The combination of the device and the drug for the purpose of treating HE is more effective than use of the drug alone in conventional therapy. The patient in the trial was considered in conventional clinical practice to have unstable disease. Monitoring and control using the device and method of the invention produced a situation where the condition was stably controlled.

Ability to monitor the effect of the drug on the condition - personalised dosage. The device allows the effect of the drug to be monitored, in a way not possible in the prior art, by (i) rapid testing of the patient's response to an electronic test sensitive to symptoms of the condition at one or more intervals after taking the drug, and (ii) reporting this to a clinician along with the patient data and the drug dosage recommendation. The device provides a means to monitor the change in a patient's condition, resulting from use of the drug, in real time in a way that is not possible with prior art diagnostic methods. This allows the sensitivity of the patient to the drug to be assessed by a clinician, who may configure the operation of the device to suit a specific individual patient, such as setting the testing interval, the step size by which the dose recommendation may be changed by the device, and/or the action threshold(s). The device in the example was configured to use a step size of 30ml/day for lactulose. For other patients, who may have lower body weight, or may be more sensitive to lactulose, or may have more stable disease, the step size may be set to a lower level, such as 15ml/day or 10ml/day. The step size may be set to a higher level, such as 40ml/day, for example for less sensitive or heavier patients. The increasing dose step size and the decreasing dose step size may be set separately and may be different from each other. In general the step size may be set as a parameter of the device such that the device is appropriate for use with a specific drug. The step size may be varied during operation of the device in the monitoring mode, such as in response to output data from the device; for example the step size may be reduced as the dosage is reduced, or vice-versa, in order to give finer control over dosing. In some embodiments, the device may be configured to determine automatically whether a patient responds sensitively to a drug and to set the step size for changes in the drug dosage recommendation accordingly. In conventional practice, drug dosages are prescribed to suit the patient's condition as it presents at the time, and so often become unsuitable as the condition evolves or resolves, in the time before the next consultation. The device allows a drug to be dosed based on its effect rather than using an 'average' dose expected to be suitable to treat the condition. The device may store historical output data and historical test results and operate an algorithm to derive a step size for drug dosage, for example increasing the step size in the case of larger or more frequent excursions of the test result above the action threshold and may derive a larger step size in increasing the dosage and a smaller step size in reducing it, or vice-versa. The device may be configured to have a limit on the step size to prevent too rapid an increase or decrease in dose. The limit may be set as a parameter in a device dedicated for use with a specific drug, and may be such that it is not alterable by a clinician, so as to act as a safety limit.

Use of the device with fast-acting drugs.

The device and method are suitable in particular for use with fast-acting drugs, such as having a time for effect on the patient within 1 day, within a few hours, or less than 1 hour. In this way the device may control the effect of the drug a closed-loop feedback manner. The invention encompasses use of the device with any drug that has a rapid action and a drug effect that may be monitored using an electronic test run by the device for the patient. Laxatives are examples of a fast-acting drug and the device may be used with other laxatives than lactulose for treatment of HE, such as any non-absorbable disaccharide laxative, such as lactitol. The device may be configured to operate as described herein at a first time point, then at a second time point at a time interval after the first, the time interval being around the same as, or longer than, the time said time for effect. The drug may be selected from drugs that have a rapid action, wherein the time for the effect of the drug on the patient is less than around 1 day, less than 12 hours, less than 8 hours, less than 4 hours, less than 2 hours, or less than 1 hour. In some embodiments a kit is provided comprising a device as described herein and a drug having a rapid action, having a time for effect on the patient in the range up to around 1 day, or in the ranges above.

Improved usage of the drug.

In some embodiments a device and method are provided for optimising the amount of a drug used for treatment of a medical condition, and a kit comprising the device and a drug for treatment of a medical condition using an optimised dosage of the drug. An optimised amount of the drug means an amount selected for effective treatment of a condition based on observation of the results of the treatment, such as a test result for a symptom or marker of the condition. Typically an optimised amount means a reduced amount of a drug for treatment of the condition compared with prior art practice, and in some cases means an amount near the minimum amount needed for effective treatment of the condition. An optimised amount or dosage may mean an amount of drug that varies with time, such as reducing with time as the condition resolves. The example shows that the device provides a means to reduce the amount of lactulose used in treatment of the patient's condition. The device is configured to monitor the condition and, if the condition is stable, to reduce the drug dosage recommendation. If the condition then worsens, the device is able rapidly to increase the dosage recommendation to bring the condition under control once more. This results in a lower average drug consumption than if the dosage were to be kept constant in cases of stable disease, as is usual in prior art practice. This has several benefits, including reduced side effects and reduced total drug consumption, which may be important if the drug is costly or is one to which a patient may develop insensitivity.

In the example shown in figure 8 the patient was discharged from hospital at the start of the trial with a prescribed lactulose dose of 60ml/day, which in prior art practice would have been continued during the period of the trial, leading to the patient taking a total of 3660ml during that period. With use of the device the patient took a total of 1050ml during the trial period.

Extension of use of a drug to 'unsuitable' patients - or use of poorly tolerated drugs

The device may be used with patients who are highly sensitive to a drug, or who are insensitive so that the effective dose is close to the overdose limit for a drug, or who suffer severe adverse side effects. The ability of the device to control dosage of the drug and rapidly to provide information on its effects allows drugs to be used with patients for whom the drug might be considered to be unsuitable in conventional practice.

Compliance

The device provides a means to recommend a drug dosage that is as low as is effective to control a condition, so minimising adverse side effects, which tend to reduce compliance. The device may be configured to determine and report on compliance, and in some embodiments the output data comprises a compliance indicator to report to a clinician the degree of compliance with the monitoring or drug dosage process operated by the device. For example, the patient may be asked to take an electronic test and/or report patient data at a certain time, or number of times, during the day and the actual time or number of times that the test is taken many be monitored, and a compliance indicator may be derived from the said monitoring. Consistency of response by the patient may be taken to indicate high compliance. Lower compliance may be used to trigger contact by a clinician.

Referring to figure 8, the data shows that the patient took the NCT test and entered patient data every day as requested by the trial protocol. The patient's condition responded rapidly (within 1 day) to each change in drug dosage recommendation, showing both effectiveness of the dosage recommendation and good compliance by the patient in taking the recommended dose.

Lack of response of the patient to a change in drug dosage recommendation may indicate unsuccessful control of the condition, or may indicate lack of compliance in taking the drug. The device may be configured to compare a change in a test result or in a condition indicator with a change in drug dosage recommendation to derive a compliance indicator. The compliance indicator may be stored and over time such an indicator may be used to show a higher or lower degree of effectiveness of control of the condition, or a higher or lower degree of compliance. Results from monitoring the time or number of tests taken may be used together with results from comparison of the change in test results with change in drug dosage recommendation to derive the compliance indicator. In this way a kit comprising a drug and a device is provided, wherein the device is adapted to monitor the compliance of the patient in taking the drug.

Reduced use of clinical resources The example shows good control of the patient's condition involving regular changes in drug dosage without intervention from a clinician. Overall use of clinical resources was dramatically less for this patient than in prior art practice. In this way the device provides a method of reducing clinical resource use and/or of allocating clinical resources, by providing a drug dosage recommendation to the patient and by outputting a condition indicator to a remote clinician device, so enabling the clinician to monitor the patient's condition remotely. In particular, in-patient admissions to hospital, number of outpatient consultations and consultations with primary care clinicians are reduced. Additionally, good control of the condition is achieved using a relatively inexpensive first line drug, so the need for expensive second line drug treatment, such as rifaximin for HE, is avoided.

Other medical conditions and drugs, such as use for treatment of neurological conditions

The example shows that the device is suitable for use in treating a chronic medical condition over the long term without the presence of a clinician. The results from the example may be generalised to further medical conditions and drugs. Some examples are given in the description of the invention above.

In particular, the device, method and kit are suitable for treatment of neurological conditions such as Parkinson's disease (PD). The device and method may be used to optimise dosage of drugs to control motor symptoms of PD as the symptoms vary with time and it is desirable to use the lowest effective drug dose to minimise adverse side effects. Some drugs to control symptoms of PD may be considered as fast-acting, having a time for effect of less than around 2 hours. First line treatment is levodopa together with carbidopa and the device may be configured to control dosage of these drugs. Other suitable drugs for use with the device are dopamine agonists and apomorphine; in particular apomorphine is administered subcutaneously by patients as required and a device according to the invention having an electronic motor control test as the input test would be valuable to control use of the drug.

Accordingly, in some embodiments a device is provided for use in treatment of Parkinson's disease (PD), the device being configured to:

receive patient data relating to the patient's medical condition;

compare the test results with reference data to derive output data comprising a condition indicator and a drug dose recommendation; and

output the output data;

and wherein the electronic monitoring test is a motor control test and the drug is a drug for treatment of Parkinson's disease. The drug may be L-dopa or a derivative or analogue of L-dopa or of dopamine, levodopa, carbidopa, a dopamine agonist, or apomorphine.

In some embodiments the device is configured to compare the patient data with reference patient data forming part of the reference data, and to use the comparison to derive the drug dosage recommendation. In some embodiments the device is configured to operate in a reference mode and a monitoring mode, wherein the reference mode enables the reference data to be set for the patient and wherein the monitoring mode uses the reference data which is set in the reference mode,

In some embodiments a method is provided for treatment of Parkinson's disease using an electronic device comprising:

receiving patient data relating to the patient's medical condition;

comparing the test results with reference data to derive output data comprising a condition indicator and a drug dose recommendation, and

outputting the output data,

wherein the electronic monitoring test is a motor control test and the drug is a drug for treatment of Parkinson's disease.

In some embodiments the method comprises comparing the patient data with reference patient data forming part of the reference data, and using the comparison to derive the drug dosage recommendation.

In some embodiments the method comprises running the said monitoring test after a time interval to generate second test results for the patient, and comparing the first and second test results to determine the effect of the drug. The time interval may be in the range up to 2 hours, up to 1 hour or up to 30 minutes.

In some embodiments the method comprises:

operating the electronic device in a monitoring mode, wherein the monitoring mode uses the reference data which is set in the reference mode.

The invention has been described by way of examples only and it will be appreciated that variation may be made to the above-mentioned embodiments without departing from the scope of invention. With respect to the above description then, it is to be realised that the optimum dimensional relationships for the parts of the invention, to include variations in size, materials, shape, form, function and manner of operation, assembly and use, are deemed readily apparent and obvious to one skilled in the art, and all equivalent relationships to those illustrated in the drawings and described in the specification are intended to be encompassed by the present invention. Therefore, the foregoing is considered as illustrative only of the principles of the invention. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the invention to the exact construction and operation shown and described, and accordingly, all suitable modifications and equivalents may be resorted to, falling within the scope of the invention.

Claims

1 . A device for monitoring a medical condition of a patient, the device being configured to:

receive patient data relating to the medical condition of the patient; compare the test results and the patient data with reference data to derive output data; and

output the output data;

2. A device according to claim 1 , wherein the device is further configured to:

output, in the reference mode, the test results for the patient; and receive a confirmation that the test results are to be used as reference data in the monitoring mode.

3. A device according to claim 1 or claim 2, wherein the monitoring test is a cognitive test.

4. A device according to claim 3, wherein the cognitive test is selected from a Number Connection Test, a Stroop test, an inhibitory control test, a critical flicker frequency test, a serial dotting test, a line tracing test or a digit symbol test, the test being implemented by the device.

5. A device according to claims 1 or claim 2, wherein the monitoring test is a motor control test.

6. A device according to claim 1 or claim 2, wherein the monitoring test is adapted to monitor a measurand in a body fluid.

7. A device according to any preceding claim, wherein the patient data comprises one or more of weight, heart rate, blood pressure, a blood biochemistry measurement, stool frequency, and a patient reported measure of their condition.

8. A device according to any preceding claim, wherein comparing the test results and the patient data with reference data to derive output data comprises comparing the test results with an action threshold forming part of the reference data.

9. A device according to claim 8, wherein the device is configured such that the drug dose recommendation is modified in response to the test result reaching or passing the action threshold forming part of the reference data.

10. A device according to any preceding claim, wherein comparing the test results and the patient data with reference data to derive output data comprises comparing the patient data with an action threshold for the patient data to derive the drug dose recommendation.

1 1 . A device according to claim 10, wherein the device is configured such that the drug dose recommendation is reduced in response to comparison of patient data with the action threshold for the patient data.

12. A device according to claim 10, wherein the device is configured such that the drug dose recommendation is increased when both of (i) a test result passes an action threshold stored as part of the reference data and (ii) a value of patient data lies within a range of values stored as part of the reference data.

13. A device according to claim 12, wherein the device is configured such that the drug dose recommendation is reduced when a value of patient data lies outside the said stored range of values.

14. A device according to any preceding claim, wherein the drug dose recommendation is increased or decreased by an amount that is set for the patient.

15. A device according to any preceding claim, wherein the device is further configured to limit the drug dose recommendation to be no more than a maximum dose value that is specified for the patient.

16. A device according to any preceding claim, wherein the device is further configured to store the drug dose recommendation as a function of time and the condition indicator is derived using a stored drug dose recommendation.

17. A device according to any preceding claim, wherein the condition is selected from a hepatological disease, cardiovascular disease, a respiratory disease, a gastrointestinal disease, a rheumatological disease, an endocrine disease, a neurological disease, cancer, pain, inflammation.

18. A device according to claim 17, wherein the condition is hepatic encephalopathy, the test is a cognitive test and the drug is a laxative.

19. A device according to claim 17, wherein the condition is selected from heart failure and ascites and a monitoring test is selected from the patient's weight and a blood electrolyte measurement.

20. A device according to claim 17, wherein the condition is a lung disease and a monitoring test is selected from spirometry and measurement of blood oxygen saturation.

21 . A device according to claim 17, wherein the condition is selected from inflammatory bowel disease and arthritis and the monitoring test measures an inflammatory marker.

22. A device according to claim 17, wherein the condition is a rheumatological disease and the monitoring test is a motor control test.

23. A device according to claim 17, wherein the condition is a neurological disease and the monitoring test is a motor control test.

24. A device according to claim 17, wherein the condition is cancer and the monitoring test measures a cancer marker.

25. A device according to claim 17, wherein the condition is dementia and the monitoring test is a cognitive test.

26. A computer readable medium comprising computer-executable instructions to operate a device as claimed in any preceding claim.

27. A system comprising a device according to any of claims 1 to 25 and a clinician device configured for data communication with the device and operable to determine the drug dose recommendation.

28. A kit comprising a device according to any of claims 1 to 25 and a drug, wherein the device is configured to provide a dose recommendation for the drug.

29. A kit according to claim 28, wherein the test is a cognitive test and the drug is a laxative.

30. A method for monitoring a medical condition of a patient, the method implemented on an electronic device, the method comprising:

receiving patient data relating to the medical condition of the patient; comparing the test results and patient data with reference data to derive output data; and

outputting the output data;

31 . A method according to claim 30, further comprising:

operating the electronic device in a monitoring mode, wherein the monitoring mode uses the reference data which is set in the reference mode outputting, in the reference mode, the test results for the patient; and

receiving a confirmation that the test results are to be used as reference data in the monitoring mode.

32. A method according to claim 30 or claim 31 , wherein the monitoring test is a cognitive test.

33. A method according to claim 32, wherein the cognitive test is selected from a Number Connection Test, a Stroop test, an inhibitory control test, a critical flicker frequency test, a serial dotting test, a line tracing test or a digit symbol test, the test being implemented by the device.

34. A method according to claim 30 or claim 31 , wherein the monitoring test is a motor control test.

35. A method according to claim 30 or claim 31 , wherein the monitoring test is adapted to monitor a measurand in a body fluid.

36. A method according to any of claims 30 to 35, wherein the drug dose recommendation is modified in response to comparison of the test result with an action threshold forming part of the reference data.

37. A method according to any of claims 30 to 36, wherein the drug dose recommendation is reduced in response to comparison of patient data with an action threshold for the patient data.

38. A method according to any of claims 30 to 37, wherein the drug dose recommendation is increased when both of (i) a test result passes an action threshold stored as part of the reference data and (ii) a value of patient data lies within a range of values stored as part of the reference data.

39. A method according to claim 38, wherein the drug dose recommendation is reduced when a value of patient data lies outside the said stored range of values.

40. A method according to any of claims 30 to 39, comprising setting the amount by which the drug dose recommendation is increased or decreased for the patient.

41 . A method according to any of claims 30 to 40, wherein the drug dose recommendation is limited to be no more than a maximum dose value that is specified for the patient.

42. A method according to any of claims 30 to 41 , wherein the condition is selected from: a hepatological disease, cardiovascular disease, a respiratory disease, a gastrointestinal disease, a rheumatological disease, an endocrine disease, a neurological disease, cancer, pain, inflammation.

43. A method according to claim 42, wherein the condition is hepatic encephalopathy, the monitoring test is a cognitive test and the drug is a laxative.

44. A method according to claim 42, wherein the condition is selected from heart failure and ascites and a monitoring test is selected from the patient's weight and a blood electrolyte measurement.

45. A method according to claim 42, wherein the condition is a lung disease, wherein the monitoring test measures one or both of spirometry and blood oxygen saturation.

46. A method according to claim 42, wherein the condition is selected from inflammatory bowel disease and arthritis and the monitoring test measures an inflammatory marker.

47. A method according to claim 42, wherein the condition is a rheumatological disease and the monitoring test is a motor control test.

48. A method according to claim 42, wherein the condition is a neurological disease and the monitoring test is a motor control test.

49. A method according to claim 42, wherein the condition is cancer and the monitoring test measures a cancer marker.

50. A method according to claim 42, wherein the condition is dementia and the monitoring test is a cognitive test.

51 . A method according to any of claims 30 to 50, wherein the patient data comprises a Patient Reported Outcome Measure.

A device for monitoring a medical condition of a patient, the device being configured to: run an electronic monitoring test for the patient, wherein the test generates test results for the patient;

receive patient data relating to the medical condition of the patient; compare the test results with reference data to derive output data comprising a condition indicator; and

output the output data;

53. A method of operating an electronic device for monitoring a medical condition of a patient, the method comprising:

receiving patient data relating to the medical condition of the patient; comparing the test results and patient data with reference data to derive output data comprising a condition indicator;

outputting the output data;