Systems and methods for monitoring medication effectiveness

US 10 463 299B1

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System for determining the effectiveness of various prescribed medications. Here a variety of different types of patient pulse wave measurements (e.g. blood pressure, pulse oximeter, ECG) and other physiological measurements are obtained. This actual data is compared to calculated measurements that would be expected based on the various patient baseline measurements in the absence of medication, schedule of medications, and impact of medications the various patient baseline measurements. If the actual data meets expectations, then the medication is likely acting as anticipated. Depending on which types of data do not meet expectations, problems with one or more previously described medications may be reported. Other types of patient physiological readings, such as temperature, motion, lung function, brain wave function (EEG) and the like may also be obtained, and these additional types of readings can be used to extend the range of different types of drugs/medications that the system can successfully monitor.

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Claims

1. A method for determining an effectiveness of at least one specific medication from a medication regimen comprising a plurality of medications, said method comprising:
obtaining patient operable instrumentation comprising a plurality of physiological monitoring devices configured to obtain a plurality of different types of actual patient pulse wave measurements comprising electrode-based time varying electrocardiograph (ECG) readings, and time varying blood oxygen saturation levels, and time varying blood pressure measurements;
said patient operable instrumentation further comprising at least one processor and memory;
wherein said patient operable instrumentation and said physiological monitoring devices are a unitized, common processor controlled, system;
wherein said time varying blood pressure measurement types are oscillometric cuff type blood pressure measurements;
obtaining a plurality of individual medication impact parameters, each individual medication impact parameter providing information on how an individual known specific medication alters a specific type of pulse wave measurements;
obtaining a plurality of patient reference information, each individual patient reference information providing information on a specific type of patient baseline pulse wave measurement in an absence of patient medication;
wherein said plurality of medication impact parameters and plurality of patient reference information further provide information associated with at least said plurality of different types of actual patient pulse wave measurements;
obtaining patient medication schedule information associated with a plurality of medications and medication dosing schedules for said patient, and storing said patient medication schedule information in said memory;
obtaining and analyzing, using said at least one processor, a plurality of different types of actual patient pulse wave measurements at a known time;
calculating, using said at least one processor, expected patient pulse wave measurements based on said patient medication schedule information and said known time and said plurality of patient reference information and said plurality of medication impact parameters;
determining, using said at least one processor, which of said plurality of different types of actual patient pulse wave measurements are inconsistent with said expected patient pulse wave measurements, thus producing specific medications with inconsistent findings
and using said processor to store at least said specific medications with inconsistent findings in said memory;
determining, with said at least one processor, said effectiveness and a medication adherence to the regimen, based on said inconsistent findings;
establishing or refining, with said at least one processor, said effectiveness based on the medication adherence;
wherein said effectiveness comprises an impact of said at least one specific medication on a patient's actual patient pulse wave measurements as compared to calculated expected patient pulse wave measurements for said medication regimen.

Show 11 dependent claims

13. A device for determining an effectiveness of at least one specific medication from a medication regimen comprising a plurality of medications, said device comprising:
patient operable instrumentation comprising physiological monitoring devices configured to obtain a plurality of different types of actual patient pulse wave measurements comprising electrode-based time varying electrocardiograph (ECG) readings, and time varying blood oxygen saturation levels, and time varying blood pressure measurements types; said patient operable instrumentation further comprising at least one processor and memory;
wherein said time varying blood pressure measurement types are oscillometric cuff type blood pressure measurements;
wherein said patient operable instrumentation and said physiological monitoring devices are a unitized system, all managed by at least one common processor;
wherein said device is configured to store a plurality of individual medication impact parameters, each individual medication impact parameter providing information on how an individual known specific medication alters a specific type of pulse wave measurement;
wherein said plurality of medication impact parameters and plurality of patient reference information further provide information associated with at least said plurality of different types of actual patient pulse wave measurements;
wherein said device is further configured to store a plurality of patient reference information, each individual patient reference information providing information on a specific type of patient baseline pulse wave measurements in an absence of patient medication;
wherein said device is further configured to store patient medication schedule information associated with at least one medication and medication dosing schedule for said patient;
said at least one processor further configured so that when said patient operable instrumentation is used on a patient with patient medication schedule information, obtaining a plurality of different types of actual patient pulse wave measurements at a known time, said at least one processor analyzes said plurality of different types of actual patient pulse wave measurements at a known time, and determines which of said plurality of different types of actual patient pulse wave measurements are inconsistent with those expected patient pulse wave measurements calculated from said patient medication schedule information, said known time, said plurality of patient reference information, and said plurality of medication impact parameters;
wherein said at least one processor is further configured to store at least those specific medications where inconsistent findings were obtained in said memory;
wherein said at least one processor is further configured to determine said effectiveness and a medication adherence to the regimen, based on said inconsistent findings, and to establish or refine said effectiveness based on the medication adherence;
wherein said effectiveness comprises an impact of said at least one specific medication on a patient's actual patient pulse wave measurements as compared to calculated expected patient pulse wave measurements for said medication regimen.

Show 7 dependent claims

Description

This application is a continuation in part of U.S. patent application Ser. No. 15/060,514, filed Mar. 3, 2016, now U.S. Pat. No. 9,946,844 issued Apr. 17, 2018; application Ser. No. 15/060,514 claimed the priority benefit of U.S. provisional application 62/138,377, COMPREHENSIVE BODY VITAL SIGN MONITORING SYSTEM WITH NECK AND EAR MOUNTED DEVICE, filed Mar. 25, 2015; application Ser. No. 15/050,514 was also a continuation in part of U.S. patent application Ser. No. 14/186,151 SIMULTANIOUS MULTI-PARAMETER PHYSIOLOGICAL MONITORING DEVICE WITH LOCAL AND REMOTE ANALYTICAL CAPABILITY, filed Feb. 21, 2014 issued as U.S. Pat. No. 10,022,053; application Ser. No. 14/186,151 in turn claimed the priority benefit of U.S. provisional application 61/767,839 SIMULTANIOUS MULTI-PARAMETER PHYSIOLOGICAL MONITORING DEVICE WITH DUAL LOCAL AND REMOTE ANALYTICAL CAPABILITY, filed Feb. 22, 2013; the entire contents of all of these applications are incorporated herein by reference in their entirety.

BACKGROUND OF THE INVENTION
Field of the Invention

This invention is in the field of patient operated medical diagnostic devices that can be used to determine if a patient is being effectively treated by health care provider medication prescriptions.

Although patients are often prescribed multiple medications, the effectiveness of such prescriptions is often suboptimal. Such ineffectiveness can be due to different causes, such as patient non-adherence to the prescriptions (e.g. not taking the prescribed drugs properly), or alternatively because the patient's body is not reacting to the drug (or drug combination) as expected or as desired (e.g. adverse drug interactions, and the like). In this later situation, the patient's body may have originally reacted as expected, but then, due to various other factors, may with time or disease progression, or unexpected interaction with other drugs may no longer be reacting with the drug as the patient's body did originally.

Patient non-adherence to health care provider mediation recommendations is a major medical problem. Center for Disease Control (CDC) materials suggest that between 20-30% of medication prescriptions are never filled, and medication is not taken as prescribed in up to 50% of all cases.

For example, studies have shown that only about 51% of patients being treated for hypertension are adherent to their medication therapy on a long term basis. In this context, long term should be viewed as being about six months, since other studies have shown that medication adherence rates drop off after the first six months of treatment. This is a large scale problem. At present over 133 million Americans have a long term chronic condition requiring medication.

It has also been estimated that medication non-adherence can result in up to 125,000 excess deaths annually; also incurring economic costs (due to higher subsequent patient expenses) estimated at $100 billion to $300 billion dollars per year.

Thus methods to monitor and encourage patent adherence to prescribed medications are of high interest in the art. Patient adherence to hypertension medication is particularly critical.

Patients, in particular elderly patients, are often put on multiple different medications at the same time. For example, to control hypertension, patients may be put on various combinations of diuretics, angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), beta-blockers, vasodilators, calcium channel blockers, aldosterone antagonists, renin inhibitors, alpha blockers, and the like. No one drug alone may be totally effective, but in combination, several drugs may produce the desired results.

Patients with other types of disorders, such as lung disease, chronic obstructive pulmonary disease, epilepsy, diabetes, and the like are of course not immune to hypertension. Many of these patients, sometimes in addition to anti-hypertension drugs, also take additional types of drugs for these disorders. It is not uncommon for these other drugs to also have an impact on cardiovascular system function as well.

In order to improve patient medication adherence, the patient should ideally receive frequent feedback that would promptly warn the patient whenever the patient is not adhering to their prescribed medication properly, or when this medication has otherwise become less than fully effective.

A few such patient operated medical diagnostic tests are presently on the market, such as home blood glucose tests, home blood pressure tests, home pulse oximeters, and even home ECG tests.

With the exception of home tests for blood glucose, there are presently few home diagnostic tests that can warn a patient when he or she is out of compliance for a particular medication. Here prior art home blood pressure tests illustrate the problemif a patient's blood pressure is non-ideal, is this because the patient skipped one of several anti-hypertensive medications that the patient has bee taking, or is it simply because the patient is having a bad day? If the patient skipped a drug, which one was skipped?

Thus further improvements in the art of using patient operated medical diagnostics to monitor patient adherence to medication would be desirable.

BRIEF SUMMARY OF THE INVENTION

The invention is based, in part, on the insight that various types of patient operated instrumentation, such as blood pressure monitors, pulse oximeters, ECG readers and the like discard a huge amount of data in the course of obtaining their various different types of pulse wave measurements and other types of measurements. This invention is also based, in part, on the insight that with proper analysis, this massive amount of blood pressure data, pulse oximeter data, ECG reading data, and other types of data could be usefully employed to help solve the major problem of monitoring issues of patient medication adherence and medication effectiveness.

In some embodiments, the invention may be a method, device or system for determining any of an efficacy of a medication regime, and any of the effectiveness of, or a patient's adherence to, a prescribed medication regime. The invention relies on a plurality of different types of measured (actual) patient pulse wave measurements, such as some combination of oscillometric blood pressure data, oscillometric pulse oximeter data, and ECG data, as well as other types of patient physiological measurements as available.

In this context, medication effectiveness represents the total impact of the various medications that the patient is actually taking on the patient's physiology (e.g. medical status), as compared to what the prescribing physician(s) (or other healthcare workers) may have intended based on the patient's medication regime. The actual medication effectiveness may differ from what the prescribing physician intended due to multiple factors, including lack of patient medication adherence (e.g. the patient just is not taking the pills properly), adverse drug interactions, changes in patient medical status, unexpected side effects, and the like. Here the term determining an effectiveness is intended to communicate that the invention is configured to report or sound an alarm when any of these problems are detected. This alerts the patient and healthcare to the fact that there is an unexpected mediation problem, and that further investigation as to the underlying cause of the problem may be needed.

As an analogy, consider a smoke detector versus a combined carbon monoxide and smoke detector. determining patient adherence is somewhat like a fire detector, while determining an effectiveness is somewhat like a combined smoke detector and carbon monoxide detector. Although lack of effectiveness is a more general problem than lack of adherence, and may require more follow up investigation to determine if the lack of effectiveness was caused by lack of adherence, adverse drug interactions, changes in patient medical status, or unexpected side effects, nonetheless determining (medication) effectiveness can sometimes be even more valuable than determining patient adherence because it can find more problems.

The invention further relies on additional information, such as patient reference (baseline) information that reports on the various patient pulse wave measurements in the absence of various types of medication, medication schedule information (which informs the invention as to what types of drugs/medications that patient should be taking, and when), and medication impact parameters, which informs the invention as to how the various individual medications would be expected to impact (alter) various specific types of patient pulse wave measurements. Additional information, such as blood glucose sensor data from blood glucose meters, patient motion data from handheld computerized devices such as smartphones, skin electrical conductance sensors (e.g. galvanic skin detectors, also called GSR), sound analysis, and patient interview data can also be used by the invention.

The invention will typically use at least one processor to obtain various different types of actual patient pulse wave measurements and optionally other types of data as well. It will then use its various types of additional information to determine if the actual data is as expected based on the patient baseline pulse wave information, expected medication schedule, and expected impact of these medications on the patient baseline pulse wave information. If the results are inconsistent, then the invention will typically conclude that the patient is not responding as expected and that either the patient is not properly adhering to his medication schedule, or that the medication is not acting as expected/desired, and will report these problems accordingly.

Other types of patient physiological readings, such as temperature, motion, lung function (e.g. stethoscope-like microphone pickups and automated sound analysis, spirometers, actual or computed respiration rate data), brain wave function (EEG), imported blood glucose data from blood glucose sensors, motion data from accelerometers or motion sensors on handheld portable computerized devices such as smartphones, and the like may also be obtained, and these additional types of readings can be used to extend the range of different types of drugs/medications that the system can successfully monitor.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a simplified drawing of patient reference pulse wave measurements for a normal (healthy patient) in the absence of medication. Three different types of patient pulse wave measurements (oscillometric blood pressure measurements, pulse oximeter type measurements, and ECG measurements) are being shown simultaneously, along with some of the underlying patient physiological mechanisms that create some of these various patient pulse waves. Here the time elapsed from the last previous ECG R pulse (in milliseconds) is shown on the X (horizontal) axis. The Y vertical axis shows (for the blood pressure measurements) the blood pressure in millimeters of mercury (mm Hg), or arbitrary units for the other pulse wave measurements.

FIG. 2 shows a simplified version the reference pulse wave measurements for a different (older patient suffering from hypertension) patient in the absence of medication. This is this patient's baseline pulse wave information. Note the overall higher blood pressure, and different timing of various components of the various pulse waves, relative to FIG. 1.

FIG. 3 shows a how a specific type medication (here type A medication) can impact the pulse wave measurements for the hypertension patient from FIG. 2 (above). The changes in the various and shapes of the curves can be considered to be the impact parameter for this type of medication. The impact parameters can be expressed either analytically in terms of the impact of the drug on the underlying patient physiology, and/or empirically in terms of the changes in the shapes of the curves (without needing to understand the mechanism by which the medication impacts the patient's physiology). Here drug A lowers the patient's blood pressure overall without otherwise causing much of a change in the timing of the various components of the various pulse waves.

FIG. 4 shows how a different specific type of medication (here type B medication) impacts the pulse wave measurements for the hypertension patient from FIG. 2 above. Here drug B has altered the timing of the ECG R pulse, and has also lowered the blood pressure overall.

FIG. 5 shows how yet another different specific type of medication (here type C medication) impacts the pulse wave measurements for the hypertension patient from FIG. 2 above. Here drug C has done several things. It has somewhat altered the timing between the ECG R pulse, and the onset in the rise in blood pressure. This drug has also altered the timing of some of the various underlying pulse waves (here direct wave and reflected waves) so that they don't superimpose (augment) with each other in an unfavorable manner. This helps reduce the peak (systolic) blood pressure.

FIG. 6 shows the effect of all three medications (type A and type B and type C) on the pulse wave measurements for the hypertension patient from FIG. 2 above. In this case, the effect of all three drugs is additive, and the hypertension patient's blood pressure is brought back to almost normal or acceptable values.

FIG. 7 shows a flow chart showing of some of the various steps that may be carried out by the medication effectiveness/adherence device's processor in order to determine if the various physiological measurements taken by the device's various sensors are showing that the patient is likely following his or her assigned medication schedule, or not.

FIG. 8 shows an example of one type of patient operable instrumentation that, with upgrades as described herein, may be used according to the present invention.

FIG. 9 shows an example of a different type of patient operable instrumentation that, with upgrades as described herein, may be used according to the present invention. In this embodiment, the patient operable instrumentation is intended to be worn by the patient over a period of time.

DETAILED DESCRIPTION OF THE INVENTION

As one example of how the invention can operate, consider the problem of hypertension. Hypertension is a very common and very serious disease that is frequently treated by multiple anti-hypertensive drugs simultaneously. Often these different types of anti-hypertensive drugs (medications) have different, and sometimes even well understood, mechanisms of action on the user's cardiovascular system.

In this discussion, we will first examine some of the various types of cardiovascular system related pulse wave data that may be obtained by patient operable instrumentation, such as the easy to use multiple sensor instrumentation discussed in more detail in U.S. patent application Ser. No. 14/186,151 and 62/138,377, and shown in FIGS. 8 and 9. In these examples, we will examine some hypothetical automated oscillometric cuff type blood pressure pulse wave profiles, automated oscillometric pulse oximeter type pulse wave profiles, and automated electrocardiogram (ECG) pulse wave profiles, as well as some of the underlying physiological changes brought about by hypertension and various drugs on these pulse wave profiles. These examples are intended to make the general principles behind the invention easier to understand, but are otherwise not intended to be limiting.

In this discussion, automated oscillometric cuff type blood pressure sensors will be commonly abbreviated as oscillometric or OSC sensors. The automated pulse oximeter type sensors will be commonly abbreviated as pulse oximeter or POX type sensors, and automated electrocardiogram sensors will be commonly abbreviated as ECG sensors. See application Ser. No. 14/186,151 and 62/138,377 for further discussion. Note that although in some embodiments, these three devices (automated oscillometric cuff type blood pressure sensors, automated pulse oximeter type sensors, and automated electrocardiogram sensors) will all be part of the same unitized device, such as the same patient operable instrumentation, in other embodiments, one or more of these devices may be separate, and instead communicate with the patient operable instrumentation via a wired or wireless channel. For example, a unitized device such as shown in FIG. 9, but lacking an automated oscillometric cuff type blood pressure sensor, might implement the invention by communicating with a separate oscillometric cuff type blood pressure sensor by any of a wired or wireless (e.g. Bluetooth) connection. For example, a processor from a device such as FIG. 9 might send commands to, and receive data from, a separate automated oscillometric cuff type blood pressure sensor via a Bluetooth or other type link.

FIGS. 1-6 are based on a simplified model of the cardiovascular system. These figures show both the actual measurements that may be obtained by the various pulse wave sensors, as well as a few details of some of the underlying physiological mechanisms that produce these actual measurements.

Citations

US 9,946,844 B2 - Systems and methods for monitoring patient medication adherence
Invention for determining a patient's adherence to various prescribed medications. Here a variety of different types of patient pulse wave measurements (blood pressure, pulse oximeter,...

US 7,142,911 B2 - Method and apparatus for monitoring drug effects on cardiac electrical signals using an implantable cardiac stimulation device
An implantable cardiac stimulation device, such as a pacemaker or Implantable Cardioverter Defibrillator, is configured to automatically monitor the effects of antiarrhythmic drugs on cardiac...

US 2018 317,859 A1 - SIMULTANEOUS MULTI-PARAMETER PHYSIOLOGICAL MONITORING DEVICE WITH LOCAL AND REMOTE ANALYTICAL CAPABILITY
Handheld medical diagnostic instrument that provides high time-resolution pulse waveforms associated with multiple parameters including blood pressure measurements, blood oxygen saturation levels, electrocardiograph (ECG) measurements,...

US 2007 287,923 A1 - Wrist plethysmograph
A pulse monitoring plethysmograph system for establishing a history of the pulses of the user over an extended period of time, comprises a housing, a...

US 2008 200,771 A1 - TREATMENT REGIMEN COMPLIANCE AND EFFICACY WITH FEEDBACK
A method and system for interaction with a community of individuals, relating to compliance with and effectiveness of treatment regimens, including supply and use of...

US 2015 186,615 A1 - MEDICATION COMPLIANCE
Systems and methods for improving or incentivizing patient compliance with a medical schedule are disclosed. A system can include a medication module and a sensing...

US 9,603,550 B2 - State characterization based on multi-variate data fusion techniques
The ingestible event marker data framework provides a uniform, comprehensive framework to enable various functions and utilities related to ingestible event marker data (IEM data)....

US 2015 112,606 A1 - Calculating Pulse Transit Time
The technology described in this document is embodied in a method that includes obtaining a first data set representing time-varying information on at least one...

US 2014 309,505 A1 - ELECTRONIC MEDICATION COMPLIANCE MONITORING SYSTEM AND ASSOCIATED METHODS
A method of monitoring a patient's compliance with a medication program includes transmitting a first signal from an electronic ingestible medication delivery device located within...

US 2016 188,839 A1 - SYSTEMS AND METHODS FOR MONITORING PATIENT MEDICATION ADHERENCE
Invention for determining a patient's adherence to various prescribed medications. Here a variety of different types of patient pulse wave measurements (blood pressure, pulse oximeter,...

US 2013 276,785 A1 - Central Site Photoplethysmography, Medication Administration, And Safety
A monitoring and control system, apparatus and method for safe administration, reduction or cessation of administration of at least on medication, fluid or both, which...

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