WO2016145063A1

WO2016145063A1 - Inr control system and method

Info

Publication number: WO2016145063A1
Application number: PCT/US2016/021537
Authority: WO
Inventors: Roger L. Frick
Original assignee: Frick Roger L
Priority date: 2015-03-09
Filing date: 2016-03-09
Publication date: 2016-09-15

Abstract

Improved control of INR levels of a patient is achieved by periodically sampling INR at a sampling period of five days or less. The dosage of daily blood thinner medication is determined using a programmable digital controller based on INR readings and a dosage control algorithm.

Description

INR CONTROL SYSTEM AND METHOD

REFERENCE TO COPENDING APPLICATION

This application claims priority from Application No. 62/130,262 filed March 9,

2015, which is incorporated by reference.

BACKGROUND

Atrial fibrillation and mechanical heart valve replacement result in high rates of ischemic strokes due to blood clots travelling from the heart to the brain. Atrial fibrillation alone increases the stroke rate by a factor of five. The drug Warfarin (a blood thinner medication) can drastically reduce the risk of stroke but present methods of determining Warfarin doses are inadequate. Usual care Warfarin dose control only reduces the risk factor to about two. This patent application describes systems, devices, and methods that significantly improve Warfarin dosing.

INR (international normalized ratio of prothrombin time of blood coagulation) is a measure of clotting time. Laboratory instruments at a clinic or point of care (POC) INR meters measure INR. INR increases as doses increase and clotting time decreases. The normal INR is 1.0 with no anti-coagulation therapy. The usual therapeutic range for Warfarin controlled INR is 2.0-3.0 for patients with atrial fibrillation and 2.5-3.5 for patients with mechanical heart valves. If the INR is too low, strokes due to blood clots in the brain will occur. If the INR is too high, strokes due to bleeding in the brain will occur. Arch Intern Med Vol. 169, Issue 13, pp. 1203- 1209. Unfortunately, the Warfarin dose required in maintaining a given INR for a typical patient varies significantly with time. It is necessary to periodically monitor INR and adjust Warfarin dosage.

About 4 million people in the U.S. are presently taking Warfarin. About 1 million patients are out of the therapeutic range at any point in time and large numbers of preventable ischemic strokes and bleeding events occur. INR measures the degree of anticoagulation. The resulting preventable ischemic strokes and bleeding events have been estimated at over 10,000 per year with an annual Medicare cost exceeding a billion dollars. (Lader et al. 2012, 375-377), (Amin et al. 2014, 150-159), (White et al. 2007, 239-245), (Koton et al. 2014, 259-268; Oden, Fahlen, and Hart 2006, 493-499). (Stafford and Singer 1998, 1231-1233). The usual therapeutic range for INR is 2.0-3.0 with atrial fibrillation (AFib). A low INR results in strokes due to blood clots in the brain. A high INR results in bleeding including strokes due to bleeding. (Oden, Fahlen, and Hart 2006, 493-499). TTR is the percent of time spent in this therapeutic range. The required warfarin dose to maintain a therapeutic TTR varies from day-to-day and patient to patient.

INR can be measured with a lab instrument or with a point of care (POC) meter.

A POC meter makes increased sampling rates practical since it can be used at home. The meter can be leased from an independent diagnostic testing facility (IDTF) or purchased outright. The

American College of Chest Physicians (Geerts et al. 2008, 381S-453S) has endorsed patient self- testing and self-management for competent patients. The FDA approves the Coaguchek XS and other meters for patient self-testing under prescription from an M.D. (FDA K06292t5 - 349 pages (FOL09002143)

Self-management is presently discouraged in the U.S. but is used by about

200,000 patients in Germany. The THINRS study found no significant health benefit for weekly self-testing with a POC meter vs. monthly testing at a clinic using a usual care algorithm.

(Matchar et al. 2010, 1608-1620). Medicare reimbursement thus limits test frequency to no more than once per week.

SUMMARY

A method for controlling INR in a patient comprises sampling the patient's blood for INR at an INR sampling period of 5 days or less, and using a closed loop digital controller to calculate and provide to the patient daily blood thinner medication doses based on the INR sampling results and a dosage control algorithm.

A device for controlling INR in a patient comprises a computing device that provides instructions to the patient to use a point of care INR meter to take INR sample readings at an INR sampling period of five days or less, that calculates daily blood thinner medication doses based upon a medical professional provided dosage control algorithm and INR sample readings, and communicates the INR readings and the daily blood thinner medication doses.

A system of controlling INR in a patient comprises a point of care INR meter, a first device usable by the patient, and a second device usable by a medical professional. The first device provides instructions to the patient to use the point of care INR meter to take INR sample readings at an INR sampling period of five days or less, calculates daily blood thinner medication doses based upon a stored dosage control algorithm and INR sample readings, and communicates the INR readings and the daily blood thinner medication doses.

BRIEF DESCRIPTION OF THE DRAWINGS FIGs. 1A and IB are diagrams illustrating prior art systems and methods of controlling INR of patients using clinic INR testing every 1 to 4 weeks and using a POC INR meter and an independent diagnostic testing facility with testing every 1 to 4 weeks, respectively.

FIG. 2 is a graph illustrating aliasing errors that can occur using the state of the art systems and methods of FIG. 1.

FIG. 3 is a diagram of an improved method and system for INR control.

FIGs. 4A and 4B are graphs showing TTR vs Method for stable INR and unstable

INR, respectively.

FIG. 5 is a graph of event rate per 100 patient years vs TTR%, showing that better control of TTR results in reduced rates of adverse events.

FIG. 6 shows a system and method for use to control Warfarin doses. FIG. 7 is a block diagram of a patient's computing device shown in FIG. 6.

DETAILED DESCRIPTION

A process cannot be controlled if it cannot be measured. Aliasing occurs when a process is sampled slower than a critical rate. It introduces large measurement errors. Stagecoach wheels in western movies appear to turn at random rates and directions due to aliasing. Cruise control for a stagecoach based on this aliased data would fail. Atrial fibrillation patients on warfarin therapy face the same problem. Typical anticoagulation sampling rates are too slow and aliasing makes accurate control of normal daily or weekly variation in INR impossible.

Atrial fibrillation increases the risk of stroke due to blood clots by a factor of more than five. Warfarin is an anticoagulant that could potentially eliminate this risk if the degree of anticoagulation could be adequately controlled. Usual care warfarin dose control only reduces the risk factor to about two.

An improved warfarin dose control method, device, and system provide near perfect control of anticoagulation. They combine digital control of doses with an increased sampling rate. They are compatible with the present health care system and is cost effective. Computer simulation demonstrates this approach is superior to all present methods of controlling clotting rate. The inventor has used this approach to decrease his time spent outside the therapeutic anticoagulation range by a factor of about ten.

FIGs. 1A and IB are flow charts representing the present (prior art) methods for controlling INR. Whether testing is performed at a clinic (FIG. 1A) or with an at home POC INR meter in conjunction with an independent diagnostic testing facility), the sampling rate is between once a week and once a month. The testing frequency of INR in clinics has a practical maximum limit of about once per week due to cost and patient compliance. Warfarin doses are not adjusted unless INR is out of range. State of the art methods currently achieve a TTR (Ratio of time in the therapeutic range to total time) of 50% to 80%. The average patient TTR is about 68%. Journal of Clinical Pharmacy and Therapeutics, Lader et al, 2012, Volume 37, pgs. 375- 377. The inventor has found that the primary reason for this poor performance is aliasing due to low sampling rates. It is presently necessary for a physician or anti-coagulation clinic to control INR since lack of control can result in stroke or death. The physician or medical professionals under his direction determine patient Warfarin doses. Informing the patient via telephone or Internet of the required Warfarin dosing for a period of time is presently used to accomplishes the INR control.

FIG. 2 illustrates the aliasing errors inherent in this current approach. Present methods of INR control update INR at maximum frequencies of once per week. The fundamental problem is that the INR can change significantly over a one-day period. If we assume a time constant T of one day, then we are trying to compensate for a change with a cut off frequency of about: f_c{signal) ^ ^- ^ Q. \6^^ (Eq. 1)

2πι day

Sampling at a rate of twice this frequency (>0.32 cycles/day) minimizes aliasing errors. This corresponds to a sampling period of about three days. If the sampling rate for INR is less than this rate the average of the sampled data will not be equal to the average of the INR. The result is an output that does not represent the average of the input signal. If this signal is used to control INR, large errors will be encountered. If the sampling period is larger than the signal period, low frequency oscillations will occur. The overall result is poor performance.

Presently used control algorithms provide a "dead band". INR variations within this band are ignored. This is illustrated in FIG. 1. This forms a crude anti-aliasing filter but it is not very effective for sampling rates exceeding once per week, as shown in FIGs. 4A and $B, which will be discussed later. This is one reason that higher sample rates (or shorter sampling periods) are not presently recommended.

Aliasing is responsible for poor TTR results in present methods of warfarin dose control. A poor TTR is associated with increased stroke risks. Using POC meters to increase testing frequency in conjunction with digital control will increase TTR and should decrease stroke risk. This is practical and cost effective for many patients using warfarin. Some patients could manage their own INR.

FIG. 3. shows one embodiment of an improved system for INR control. The advent of affordable and easy to use INR monitors has increased the practical and affordable sampling frequency to once per day for home testing. POC meters measure INR by receiving a test strip that is inserted in the meter, accepting a small blood sample provided to the test strip, and then giving an immediate measure of INR. The improved system takes advantage of this ability. It is assumed that the sampling period (i.e. the time interval between successive samples) is 5 days or less. A POC meter thus can measure INR at a sampling rate high enough to prevent or minimize aliasing errors. The system shown is far superior to the present state of the art. The INR readings are inputted to and processed by a programmable digital controller that provides daily Warfarin dosing information to the patient. This controller implements a control algorithm that provides closed loop control of dosage based upon the INR readings. One example of a control algorithm that can be used is a Proportional + Integral + Derivative (PID) control function, although other closed loop control algorithms can also be used (see, for example, the algorithm used in Table 1 of the RESULTS section). The physician or other health care professional can view this data periodically and decide whether to change the control algorithm that is implemented in the control device. The system is thus fine tuned to the patient's needs.

Adequate control can be achieved with only the P term in the PID control algorithm. This proportional only control algorithm is:

Dose = Gain(INR_goal - INR) + Dose_Average (Eq. 2)

K. Astrom, K. and T.Hagglund, "PID Controllers: Theory, Design, and Tuning", Instrument Society of America, ISBN 1-55617-516-7, 1995.

The INR goal is set at the midpoint of the therapeutic range. The average dose is the dose that on average gives the midpoint INR. If this is known from past experience it can be used. Otherwise the average dose can be set at about 5 mg until more data is accumulated. Gains of 2.5mg/INR and 5 mg/INR result in doses that can be achieved by splitting available pill sizes. Other gains can be used if doses are rounded off to available pill sizes. Gains between 2 mg/INR and 5 mg/INR work well. Lower gains work best with lower average doses. Higher gains work well with higher average doses. If the gain is too high, the INR will oscillate. If the gain is too low, the INR goal will not be achieved.

Periodically updating the average dose will effectively introduce an integral term to the PID algorithm. The derivative term may also be useful in some circumstances.

RESULTS FIGs. 4A and 4B illustrate the results of the improved method vs. usual care.

Various algorithms were tested with a common table of INR variations. Using a common data set allowed me to make valid comparisons of methods without resorting to large-scale trials. INR variations that occur faster than a critical rate will be aliased. In the illustration shown in FIG. 2, the rate is about one sample every three days. TTR decreases rapidly when longer test intervals are used. It has been found that a sampling period of 5 days will result in TTR% of about 90%, which is a significant improvement over Usual Care sampling periods of 1 week to 4 weeks. A sampling period rate of 4 days yields a TTR% of 95% to 98%.

These graphs are based on a realistic table of INR variations at a constant dose derived from a 42-day record of my INR while using a daily dose control algorithm. This is shown as a straight line. The derivation is described further in the METHODS section. Equation 4 was used with Equation 1-g to calculate Digital Control values. Loop gain was adjusted to the optimum value for each trial. I computed TTR as the number of readings outside the 2.0 INR to 3.0 INR range divided by the total number of readings. INR was updated every day to compute TTR and the adjustments were only made at the testing intervals.

About 75% of patients have INRs that are considered stable. If the INR under usual care (>7-day test intervals) has an INR standard deviation of less than 0.5 it is considered stable. If the standard deviation is greater than 0.5 it is considered unstable. In the stable INR graph this standard deviation was 0.46. This represents a stable patient. The standard deviation in the unstable graph was 0.8. This is typical of unstable patients. The constant dose INR data for the second graph was obtained by multiplying the constant dose INR variations in the first graph by 1.5X. (Sconce, Blood 2007). In either case the suggested method provides superior control of TTR. Better control of TTR results in reduced rates of adverse events. This is illustrated in FIG. 5.

The model used for FIGs. 4A and 4B was verified experimentally as shown in Table 1 and was also plotted as "Experimental" in FIG. 4A. Warfarin was used by the inventor because of paroxysmal AFib. A Coaguchek XS™ POC meter to check INR daily and compute TTR on a daily basis. According to the testing schedule some INR readings were ignored for control purposes. The first trial had a goal of 2.25 rather than 2.5. Table 1 Experimental Data

Osty 2. w& D&yS Do^s— Average D««e

METHODS

Equation 1 is a model of daily INR changes vs. historic dose changes. The coefficients of the model give a response delayed by 12 hours followed by a half-life of 40 hours. They also satisfy the INR vs. Dose relationship given by Dalere. Equation 1-f was used to generate a data set for a fixed dose. This data set was folded repeatedly to generate a larger data set useful for examining monthly test intervals. The deviations from an INR goal could be multiplied to simulate a patient with a larger variation in INR. Equation 1-g was used to generate the digital control data in Figure 1. Dose is the average dose required to attain the INR goal.

Equation 1 a AD_N =ADos =Dos%—Dose

bAD_N

+A£DN-6 +4Δ¾_₇ +A£D_N-* +4Δ¾_₈) cA =0.19 =0.28 A, =0.18 A₄ =0.08 A, =0.05 =.03 A, = .03 A, =.02 4₀ =.01 d∑A_N =ι

ixedDo

^/NR, =/NR,_OA -A NR,

Although there are many usual care algorithms they are similar in that they only adjust doses when INR is outside the therapeutic range. The algorithm found by the recent RE- LY study to give the best results was used as representative of Usual Care for the purpose of FIGs. 4A and 4B. (Van Spall et al. 2012, 2309-2316). "The algorithm dose recommendations were as follows: no change for INR 2.00 to 3.00; +15% change for INR less than or equal to 1.50, +10% for INR 1.51 to 1.99, -10% for INR 3.01 to 4.00. For INR 4.00 to 4.99, the recommendation was to hold the dose for 1 day and then reduce it by 10%. For INR 5.00 to 8.99, the dose was to be held until the INR was therapeutic and then decreased by 15% per week. Weekly INR monitoring was recommended for out-of-range INR values".

The RE-LY algorithm performs worse than the correct fixed dose although it compensates for long-term drift in a patient's required average dose. My control algorithm reduces the time spent out of range by a factor of about ten if the sampling time is 3 days or less. If the data is sampled at more than 3 day intervals aliasing errors become significant and TTR suffers.

CONTROL

Toilet level valves, nuclear power plants and other critical processes are controlled by proportional + integral + derivative controllers (PID control). INR control is inherently a sampled data digital process that can be controlled only if aliasing is avoided. I explored two methods of digital control based on Equation 2.

Equation 2

DOSE = DOSE + ADose

Equation 3 ADose = K_c(Goal - INR_N)

Equation 4

-0.65

Dose

ADose_N = F(Dose,INR) = K₇ (Goal - INR_N)

w^Z 0.96INR ^{K n}

Equation 3 is standard proportional only control. Equation 4 compensates for the log-linear relationship between a fixed dose change and the ultimate INR change. (Dalere, Coleman, and Lum 1999, 461-467). The doses were rounded to the nearest 0.25 mg. This required pill splitting.

Loop gain is the product of the body's gain (dINR/dDose) and Kc. In Equation four, loop gain is constant and is equal to Kz. Loop gain should be high enough to control INR and low enough to prevent oscillation in INR. (Liptak 2013). This can be determined experimentally and is generally between one and four for my method. (Hagglund and Astrom 1995). Longer test intervals and larger dose variations require lower gains.

An alternative to PID control is shown in conjunction with Table 1 above. In that embodiment, the Day 1 dose is calculated using an equation, while Day 2 and Day 3 doses are equal to the Average Dose. Many other control strategies can be used to model with an algorithm the human body's variation in coagulation over time and its response to blood thinner medication (i.e INR response vs. dose taken).

IMPLEMENTATION

Present practice calls for a physician to control warfarin dosing. In one embodiment shown in FIGs. 6 and 7, this is implemented with two devices in addition to an INR POC meter.

System 10 includes first local device 12, second remote device 14 and INR POC meter 16. First local device 12 is a computing device that includes user interface 18, communication interface 20, programmable digital processor 22 and memory 24 (shown in FIG. 7). In some embodiments, INR POC meter 16 can be incorporated within a common housing with first local device 12 and can share components such as user interface 18 with first local device 12. INR POC 16 can also directly deliver INR sample readings to processor 22.

First device 12 calculates dosage using a spreadsheet stored in memory 24. The spreadsheet contains INR readings and the dosage control algorithm used by processor 22 in dosage calculation. The dosage control algorithm can define, for example, the Day 1, Day 2, and Day 3 dosages as described in conjunction with Table 1 above. In that example, Day 1 dosage is calculated using an equation. Day 2 and Day 3 dosages are defined by the stored Average Dose.

Use of the stored spreadsheet by device 12 is limited - device 12 can calculate dosages, but it can not modify the algorithm based on input from the patient. The stored spreadsheet may also be limited in the extent of data that it contains, in contrast to the complete spreadsheet available to the physician.

First local device 12 determines daily warfarin doses when INR data is inputted on a predetermined schedule, and the dosage can be displayed using words, icons or images of the required tablets on user interface 18 along with the INR reading. The patient then verifies that he/she has taken the dose. The patient cannot alter the device in any other way. First device 12 has 2-way communication through communication interface 20 (for example via the Internet) with second device 14, but can also function (e.g. the calculate daily doses) when communication is not available.

Second device 14 is a computing device that tabulates results and controls the dosage control algorithm stored in memory 24 of first device 12. Second device 14 receives instructions from the physician (M.D.) or other medical professional relating to the dosage control algorithm to be used by first device 12 and relating to data transfer and storage through the Internet and Cloud. Second device 14 generates the complete spreadsheet as well as TTR and graphical information for the patient so that it can be reviewed by the physician. In addition, second device 14 handles the transfer of the dosage control algorithm (or updated coefficients used to adjust the dosage control algorithm) to first device 12, and provides protection of data being sent to and from the physician and patient.

The physician can review data on the complete spreadsheet as well the TTR and graphical data to determine whether any change to the dosage control algorithm is needed. A change in the dosage control algorithm may involve sending modified coefficients or an entirely new equation or equations.

An Android phone or similar device can be used as first device 12. INR as determined by POC INR meter 16 is entered (manually through user interface 18 or by a connection between meter 16 and first device 12) and doses are immediately displayed on user interface 18. When the Internet is available, first device 12 is Cloud coupled to second remote device 14 that securely controls the dosage control algorithm in first device 12 and compiles the results. Cloud controls restrict algorithm changes to second device 14. The control of the dosage control algorithm by second device 14 may be by changing constants used in the dosage control algorithm stored in memory 24 of first device 12, or by substituting a new algorithm for the dosage control algorithm that had been used by first device 12.

The method of INR control depicted in FIG. 6 is patient self-testing (PST) if a physician is responsible for adjusting the dosage control algorithm parameters. It is patient self- management (PSM) if the patient does this adjusting. A patient could test and adjust daily for a few weeks to determine the required average dose for the desired INR goal and then switch to two to four day testing.

In FIG. 6, first device 12 is used to control Warfarin daily doses. It could automatically alarm or query the patient as well as confirm proper entry of data. User interface 18 can also be voice based. Communication with the medical professional could be via the Internet, phone modem, cloud computing or by a physical data link at the clinic. Security codes would be used to prevent unauthorized access to the control algorithm. It would also be possible to introduce this functionality to a POC INR meter.

REFERENCES

Amin, Alpesh, Steve Deitelzweig, Yonghua Jing, Dinara Makenbaeva, Daniel Wiederkehr, Jay Lin, and John Graham. 2014. Estimation of the impact of warfarin's time-in- therapeutic range on stroke and major bleeding rates and its influence on the medical cost avoidance associated with novel oral anticoagulant use-learnings from ARISTOTLE, ROCKET - AF, and RE-LY trials. Journal of Thrombosis and Thrombolysis 38 (2): 150-9.

Dalere, Gloriann M., Robert W. Coleman, and Bert L. Lum. 1999. A graphic nomogram for warfarin dosage adjustment. Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy 19 (4): 461-7.

Geerts, William H., David Bergqvist, Graham F. Pineo, John A. Heit, Charles M.

Samama, Michael R. Lassen, and Clifford W. Colwell. 2008. Prevention of venous thromboembolism: American college of chest physicians evidence-based clinical practice guidelines. Chest Journal 133 (6_suppl): 381S-453S.

Hagglund, Tore, and KJ Astrom. 1995. PJT controllers: Theory, design, and tuning. Published by ISA: The Instrumentation, Systems, and Automation Society, 2nd Edition, ISBN 1556175167 (1). Koton, Silvia, Andrea LC Schneider, Wayne D. Rosamond, Eyal Shahar, Yingying Sang, Rebecca F. Gottesman, and Josef Coresh. 2014. Stroke incidence and mortality trends in US communities, 1987 to 2011. JAMA 312 (3): 259-68.

Lader, E., N. Martin, G. Cohen, M. Meyer, P. Reiter, A. Dimova, and D. Parikh. 2012. Warfarin therapeutic monitoring: Is 70% time in the therapeutic range the best we can do? Journal of Clinical Pharmacy & Therapeutics 37 (4) (08): 375-7, Liptak, Bela G. 2013. Process control: Instrument engineers' handbook Butterworth-Heinemann.

Matchar, David B., Alan Jacobson, Rowena Dolor, Robert Edson, Lauren Uyeda, Ciaran S. Phibbs, Julia E. Vertrees, Mei-Chiung Shih, Mark Holodniy, and Philip Lavori. 2010. Effect of home testing of international normalized ratio on clinical events. New England Journal of Medicine 363 (17): 1608-20.

Oden, Anders, Martin Fahlen, and Robert G. Hart. 2006. Optimal INR for prevention of stroke and death in atrial fibrillation: A critical appraisal. Thrombosis Research 117 (5): 493-9.

Stafford, Randall S., and Daniel E. Singer. 1998. Recent national patterns of warfarin use in atrial fibrillation. Circulation 97 (13) (April 07): 1231-3.

Taylor, T. N., P. H. Davis, J. C. Torner, J. Holmes, J. W. Meyer, and M. F.

Jacobson. 1996. Lifetime cost of stroke in the united states. Stroke; a Journal of Cerebral

Circulation 27 (9) (Sep): 1459-66.

Van Spall, Harriette GC, Lars Wallentin, Salim Yusuf, John W. Eikelboom,

Robby Nieuwlaat, Sean Yang, Conrad Kabali, Paul A. Reilly, Michael D. Ezekowitz, and Stuart

J. Connolly. 2012. Health services and outcomes research. Circulation 126 : 2309-16.

White, Harvey D., Michael Gruber, Jan Feyzi, Scott Kaatz, Hung-Fat Tse, Steen

Husted, and Gregory W. Albers. 2007. Comparison of outcomes among patients randomized to warfarin therapy according to anticoagulant control: Results from SPORTIF III and V. Archives of Internal Medicine 167 (3): 239-45.

While the invention has been described with reference to an exemplary embodiment(s), it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment(s) disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.

Claims

CLAIMS:

1. A method for controlling INR in a patient comprising sampling the patient's blood for INR at an INR sampling period of 5 days or less, and using a closed loop digital controller to calculate and provide to the patient daily blood thinner medication doses based on INR sampling results and a dosage control algorithm.

2. The method of claim 1, wherein the INR sampling period is 4 days of less.

3. The method of claim 2, wherein the INR sampling period is 3 days or less.

4. The method of claim 1, wherein the dosage control algorithm is stored in the closed loop digital controller and can not be modified by the patient.

5. The method of claim 4, wherein the dosage control algorithm is modifiable by a medical professional.

6. The method of claim 1, wherein sampling the patient's blood for INR is performed using a point of care INR meter.

7. The method of claim 1, wherein the closed loop digital controller communicates with a remote computing device associated with a medical professional by Internet connection to report INR sampling results and to receive modifications to the dosage control algorithm.

8. The method of claim 1, wherein the closed loop digital controller includes a user interface, a communication interface, a digital processor, and a memory.

9. The method of claim 8, wherein:

the memory stores the dosage control algorithm;

the user interface provides a prompt to the patient to take an INR reading and provides daily blood thinner medication dose instructions to the patient; the communication interface transmits INR and daily dose information and receives adjustments to the dosage control algorithm stored in the memory; and

the digital processor provides instructions to the user interface for notifying the patient to take an INR reading at a sampling period of five days or less, determines daily doses of blood thinner medication based upon the INR reading and the dosage control algorithm, and provides the daily dose instructions to the user interface.

10. A device for controlling INR in a patient comprising a computing device that provides instructions to the patient to use a point of care INR meter to take INR sample readings at an INR sampling period of five days or less, that calculates daily blood thinner medication doses based upon a medical professional provided dosage control algorithm and INR sample readings, and communicates the INR readings and the daily blood thinner medication doses.

11. The device of claim 10, wherein the computing device includes a user interface, a communication interface, a digital processor, and a memory.

12. The device of claim 11, wherein:

the memory stores the dosage control algorithm;

13. The device of claim 12, wherein the device further includes the point of care INR meter, which is in communication with the digital processor.

14. The device of claim 12, wherein the dosage control algorithm is not modifiable by the patient.

15. The device of claim 12, wherein the communication communicates by Internet connection with a remote computing device associated with a medical professional.

16. The device of claim 15, wherein the digital processor determines the daily doses of blood thinner medication regardless of whether Internet connection is present.

17. The device of claim 10, wherein the INR sampling period is 4 days or less.

18. A system of controlling INR in a patient, the system comprising:

a point of care INR meter;

a first device usable by the patient, the first device being programmed to: provide instructions to the patient to use the point of care INR meter to take INR sample readings at an INR sampling period of five days or less;

calculate daily blood thinner medication doses based upon a storage dosage control algorithm; and

communicate the INR readings and daily blood thinner medication doses; and

a second device, remote from the first device and associated with a medical professional, that receives the INR readings and daily blood thinner medication doses communicated by the first device, tabulates the INR and daily dose information relating to the patient, and transmits adjustments to the dosage control algorithm to the first device.

19. The system of claim 18, wherein the first device includes a user interface, a communication interface, a digital processor, and a memory.

20. The system of claim 19, wherein:

the memory stores the dosage control algorithm;

the user interface provides a prompt to the patient to take an INR reading and provides daily blood thinner medication dose instructions to the patient; the communication interface transmits INR and daily dose information and receives adjustments to a dosage control algorithm stored in the memory; and

21. The system of claim 18, wherein the dosage control algorithm is not modifiable by the patient.

22. The system of claim 18, wherein the first device and the second device communication by Internet connection, and wherein the first device determines daily doses of blood thinner medication regardless of whether Internet connection is present. The system of claim 18, wherein the INR sampling period is 4 days or less.