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Publication numberUS20030130871 A1
Publication typeApplication
Application numberUS 10/287,098
Publication dateJul 10, 2003
Filing dateNov 4, 2002
Priority dateNov 2, 2001
Also published asCA2464374A1, CA2464613A1, CA2465531A1, CA2465533A1, CA2465702A1, CA2465706A1, CA2465712A1, CA2465725A1, CA2465760A1, CN1582443A, CN1613068A, CN1613069A, CN1613070A, CN1613086A, CN1613087A, CN1613088A, CN1636210A, CN100449531C, EP1440385A2, EP1440387A2, EP1440388A2, EP1440389A2, EP1440390A2, EP1440409A2, EP1440410A2, EP1440412A2, EP1442415A2, US7181375, US7617078, US7711404, US7744540, US7917377, US8214224, US8214225, US8280750, US8626533, US8949079, US9165116, US20030120133, US20030120134, US20030120458, US20030120514, US20030125984, US20030125985, US20030125988, US20030126101, US20050159654, US20090259487, US20100222646, US20150100352, WO2003040878A2, WO2003040878A8, WO2003040879A2, WO2003040879A3, WO2003040964A2, WO2003040964A3, WO2003040965A2, WO2003040965A3, WO2003040966A2, WO2003040966A8, WO2003040987A2, WO2003040987A3, WO2003040987A8, WO2003040988A2, WO2003040988A3, WO2003040989A2, WO2003040989A3, WO2003040990A2, WO2003040990A3
Publication number10287098, 287098, US 2003/0130871 A1, US 2003/130871 A1, US 20030130871 A1, US 20030130871A1, US 2003130871 A1, US 2003130871A1, US-A1-20030130871, US-A1-2003130871, US2003/0130871A1, US2003/130871A1, US20030130871 A1, US20030130871A1, US2003130871 A1, US2003130871A1
InventorsR. Rao, Satrajit Misra, Linda Best
Original AssigneeRao R. Bharat, Misra Satrajit Chandra, Linda Best
Export CitationBiBTeX, EndNote, RefMan
External Links: USPTO, USPTO Assignment, Espacenet
Patient data mining for clinical trials
US 20030130871 A1
Abstract
The present invention provides a system and method for selecting prospective patients for a clinical trial. In various embodiments, a clinical trials brokerage is configured to receive requests from drug companies for lists of persons meeting specified criteria for clinical trials. Patient records are retrieved from a structured computerized patient record (CPR) data warehouse populated with comprehensive patient information mined from unstructured hospital records. A list of persons for whom consent was obtained can be outputted and forwarded to the entity interested in performing the clinical trial and which requested the list. Anonymity of a patient can be maintained until the patient provides consent to participate in the clinical trial.
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Claims(37)
What is claimed is:
1. A system for selecting prospective participants in a clinical trial, comprising:
a data source containing patient information, at least some of the patient information obtained from mining unstructured patient records; and
a clinical trials brokerage for retrieving a set of patient records from the data source and generating a list of persons who meet specified criteria associated with the clinical trial.
2. The system of claim 1, wherein the clinical trials brokerage is configured to obtain consent from one or more the person meeting the specified criteria.
3. The system of claim 1, wherein the list of persons meeting the specified criteria is requested from an entity interested in performing the clinical trial.
4. The system of claim 1, wherein the anonymity of the persons meeting the specified criteria is preserved until consent is provided.
5. The system of claim 1, wherein the list of persons meeting specified criteria includes persons pre-qualified for the clinical trial.
6. The system of claim 1, wherein the data source includes information collected from a plurality of hospitals.
7. The system of claim 1, wherein the specified criteria includes probability criteria.
8. The system of claim 1, wherein the obtained patient records include probabilistic information.
9. The system of claim 1, wherein information needed to determine whether a patient qualifies in all respects is not included in the obtained patient records.
10. The system of claim 1, wherein information about each person in the list is provided.
11. The system of claim 10, wherein the information includes information regarding previous clinical trials that the person participated in.
12. A method for selecting prospective participants in a clinical trial, comprising the steps of:
receiving a request for a list of persons meeting specified criteria associated with a clinical trial; and
retrieving a set of patient records from a data source to determine persons meeting the specified criteria.
13. The method of claim 12, further comprising the steps of:
obtaining consent to participate in the clinical trial from one or more of the persons meeting the specified criteria; and
outputting a list of persons from whom consent was obtained.
14. The method of claim 13, further including the step of forwarding the list of persons to an entity interested in performing the clinical trial.
15. The method of claim 13, wherein the step of obtaining consent comprises the steps of:
selecting physicians associated with the persons meeting the specified criteria;
requesting approval to participate from each of the selected physicians; and
providing consent information to persons meeting the specified criteria if their physician provided approval to participate in the clinical trial.
16. The method of claim 13, wherein obtaining consent includes notifying physicians of their Institutional Review Board (IRB) statuses.
17. The method of claim 16, wherein obtaining consent further includes forwarding to accepted status physicians expiration dates of their IRB approvals.
18. The method of claim 14, wherein the request for the list of persons is received from the entity interested in performing the clinical trial.
19. The method of claim 12, wherein the anonymity of the persons meeting the specified criteria is preserved until consent is provided.
20. The method of claim 12, further comprising the step of providing questionnaires.
21. The method of claim 20, wherein the questionnaires are used to ascertain qualification for the clinical trial.
22. The method of claim 14, wherein the entity requesting the list of patients is charged a fee for the list of patients.
23. The method of claim 14, wherein persons participating in the clinical trial are compensated.
24. The method of claim 15, wherein a participating physician is compensated.
25. The method of claim 12, wherein the data source is a data warehouse.
26. The method of claim 25, wherein the data warehouse is populated with structured patient information obtained from mining unstructured patient records.
27. The method of claim 12, wherein the request is received from a drug company.
28. The method of claim 12, wherein the data source includes information collected from a plurality of hospitals.
29. The method of claim 12, wherein the specified criteria includes a probability value.
30. The method of claim 29, wherein the probability value includes a confidence interval.
31. The method of claim 12, wherein the obtained patient records include probabilistic information.
32. The method of claim 12, wherein information needed to determine whether a patient qualifies in all respects is not included in the obtained patient records.
33. The method of claim 12, wherein information about each person in the list is generated.
34. The method of claim 12, wherein the information includes information regarding previous clinical trials that the person participated in.
33. A program storage device readable by a machine, tangibly embodying a program of instructions executable on the machine to perform method steps for selecting prospective participants in a clinical trial, the method steps comprising:
receiving a request for a list of persons meeting specified criteria associated with a clinical trial; and
retrieving a set of patient records from a data source to determine persons meeting the specified criteria.
34. A system for selecting prospective clinical trials for an individual patient, comprising:
a clinical trials database;
a data source containing patient information; and
a clinical trials brokerage for generating a list of clinical trials for patients meeting specified criteria associated with the clinical trials.
35. The system of claim 34, wherein at least some of the information in the data source containing patient information is obtained from mining unstructured patient records.
Description
    CROSS REFERENCE TO RELATED APPLICATIONS
  • [0001]
    This application claims the benefit of U.S. Provisional Application Serial No. 60/335,542, filed on Nov. 2, 2001, which is incorporated by reference herein in its entirety.
  • FIELD OF THE INVENTION
  • [0002]
    The present invention relates to medical information processing systems, and, more particularly to a computerized system and method for selecting persons for clinical trials.
  • BACKGROUND OF THE INVENTION
  • [0003]
    Selection of persons for clinical trials is an expensive process. It is estimated that it costs drug companies several thousand dollars for each participant selected. Furthermore, sometimes even after being selected, persons must be dropped from a trial because of inaccurate or incorrect information. This may delay the trial, causing an even greater expense.
  • [0004]
    Although drug companies try to get the word out by placing advertisements or through direct contact with physicians, the selection process is generally quite inefficient. Physicians tend to be busy and do not always have time to respond to requests for patients, and patients may not see the advertisements for clinical trials or subscribe to the periodicals where they are placed.
  • [0005]
    Moreover, physicians at a specialized medical center tend to refer patients to trials sponsored at that center. Many physicians are unaware of all the available clinical trials because of the time it takes to keep current on all available trials for every patient that the physician sees.
  • [0006]
    In addition, clinical trials often call for very specific selection criteria and it may be difficult to ascertain if a particular person qualifies for a trial. Furthermore, because hospitals typically store information in an unstructured manner, it may be impossible using hospital records to select patients qualifying for particular clinical trials.
  • [0007]
    An equally important problem is that of matching clinical trials to specific patients. For example, for cancer alone, at any point in time there are over 600 trials in progress. Statistics show that clinical trial web sites total 75,000 hits every week, mostly from patients seeking information about trials, who are trying to fet added to a trial. Estimates from National Cancer Institute indicate that only two percent of those patients eligible for a trial are in a trial. Thus, it is critically important for an individual to know if he or she may be eligible for a trial.
  • [0008]
    Given the importance and expense of selecting qualified persons for clinical trials, it would be desirable and highly advantageous to provide improved techniques for automatically selecting prospective participants for clinical trials.
  • SUMMARY OF THE INVENTION
  • [0009]
    The present invention provides a technique for selecting prospective participants in a clinical trial.
  • [0010]
    In various embodiments of the present invention, a method is provided that includes receiving a request for a list of prospective participants meeting specified criteria for a clinical trial. A set of patient records is then retrieved to determine persons meeting the specified criteria.
  • [0011]
    The specified criteria may include probability information, thus allowing the selection of patients likely to meet the specified criteria for the clinical study (e.g., 90% likelihood of diabetes, 70% likelihood of hypertension). In this case, the relevant patient records would include probabilistic information to allow for such selection. Additional information for each prospective participant may also be retrieved. This additional information may include information about other clinical trials that the person participated in, including whether a placebo was administered.
  • [0012]
    Furthermore, persons may still be selected even though not all information needed to determine whether a person qualifies in all respects for a clinical trial is present.
  • [0013]
    Consent to participate in a clinical trial should be obtained. A list of persons for whom consent was obtained can be outputted and forwarded to an entity interested in performing the clinical trial. Typically, this is a drug company. Physicians may be notified of their Institutional Review Board (IRB) statuses (e.g., ‘approved’, ‘pending’, or ‘not approved’. Expiration dates of their status may be forwarded to approved physicians.
  • [0014]
    Because patient confidentiality is important, the anonymity of a person meeting the specified criteria must be preserved. The process of obtaining consent may include selecting physicians associated with the persons meeting the specified criteria, requesting approval to participate from each of the selected physicians, and providing consent information to persons meeting the specified criteria whose physician provided approval to participate in the clinical trial.
  • [0015]
    To further facilitate the process, questionnaires may be provided. These questionnaires may be used to ascertain qualifications for the clinical trial.
  • [0016]
    Additionally, compensation and fees can be determined for the parties involved. For example, participating physicians may be compensated. The entity requesting the list may be charged a fee. The patients participating in the clinical trial may also be compensated.
  • [0017]
    The data source used to determine the persons eligible for the clinical trial may include a data warehouse. Further, it may be populated with structured information obtained from mining unstructured patient records. The patient records may include patient information obtained from a plurality of participating health care providers, such as hospitals.
  • [0018]
    In various alternative embodiments of the present invention, a system for selecting prospective clinical trials for an individual patient is provided. The system includes a clinical trials database, a data source containing patient information, and a clinical trials brokerage for generating a list of clinical trials for patients meeting specified criteria associated with the clinical trials. At least some of the information in the data source containing patient information may be obtained from mining unstructured patient records.
  • [0019]
    These and other aspects, features and advantages of the present invention will become apparent from the following detailed description of preferred embodiments, which is to be read in connection with the accompanying drawings.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • [0020]
    [0020]FIG. 1 is a block diagram of a computer processing system to which the present invention may be applied according to an embodiment of the present invention;
  • [0021]
    [0021]FIG. 2 shows an exemplary clinical trials brokerage system according to an embodiment of the present invention;
  • [0022]
    [0022]FIG. 3 shows an exemplary clinical trials brokerage system according to another embodiment of the present invention; and
  • [0023]
    [0023]FIG. 4 shows a flow diagram outlining an exemplary technique for selecting a person for a clinical trial according to an embodiment of the present invention.
  • DESCRIPTION OF PREFERRED EMBODIMENTS
  • [0024]
    To facilitate a clear understanding of the present invention, illustrative examples are provided herein which describe certain aspects of the invention. However, it is to be appreciated that these illustrations are not meant to limit the scope of the invention, and are provided herein to illustrate certain concepts associated with the invention.
  • [0025]
    It is also to be understood that the present invention may be implemented in various forms of hardware, software, firmware, special purpose processors, or a combination thereof. Preferably, the present invention is implemented in software as a program tangibly embodied on a program storage device. The program may be uploaded to, and executed by, a machine comprising any suitable architecture. Preferably, the machine is implemented on a computer platform having hardware such as one or more central processing units (CPU), a random access memory (RAM), and input/output (I/O) interface(s). The computer platform also includes an operating system and microinstruction code. The various processes and functions described herein may either be part of the microinstruction code or part of the program (or combination thereof) which is executed via the operating system. In addition, various other peripheral devices may be connected to the computer platform such as an additional data storage device and a printing device.
  • [0026]
    It is to be understood that, because some of the constituent system components and method steps depicted in the accompanying figures are preferably implemented in software, the actual connections between the system components (or the process steps) may differ depending upon the manner in which the present invention is programmed.
  • [0027]
    [0027]FIG. 1 is a block diagram of a computer processing system 100 to which the present invention may be applied according to an embodiment of the present invention. The system 100 includes at least one processor (hereinafter processor) 102 operatively coupled to other components via a system bus 104. A read-only memory (ROM) 106, a random access memory (RAM) 108, an I/O interface 110, a network interface 112, and external storage 114 are operatively coupled to the system bus 104. Various peripheral devices such as, for example, a display device, a disk storage device(e.g., a magnetic or optical disk storage device), a keyboard, and a mouse, may be operatively coupled to the system bus 104 by the I/O interface 110 or the network interface 112.
  • [0028]
    The computer system 100 may be a standalone system or be linked to a network via the network interface 112. The network interface 112 may be a hard-wired interface. However, in various exemplary embodiments, the network interface 112 can include any device suitable to transmit information to and from another device, such as a universal asynchronous receiver/transmitter (UART), a parallel digital interface, a software interface or any combination of known or later developed software and hardware. The network interface may be linked to various types of networks, including a local area network (LAN), a wide area network (WAN), an intranet, a virtual private network (VPN), and the Internet.
  • [0029]
    The external storage 114 may be implemented using a database management system (DBMS) managed by the processor 102 and residing on a memory such as a hard disk. However, it should be appreciated that the external storage 114 may be implemented on one or more additional computer systems. For example, the external storage 114 may include a data warehouse system residing on a separate computer system.
  • [0030]
    Those skilled in the art will appreciate that other alternative computing environments may be used without departing from the spirit and scope of the present invention.
  • [0031]
    Referring to FIG. 2, a clinical trials brokerage 250 is illustrated. The clinical trials brokerage 250 is shown operatively connected to a data repository which contains patient information typically collected from one or more health care organization, such as hospitals. This data repository is called a structured clinical patient record (CPR) 280. In various embodiments of the present invention, a plurality of drug companies, such as drug company 210, request lists of persons meeting specified criteria for clinical trials. The structured CPR 280 is then consulted to obtain the lists of persons meeting the specified criteria.
  • [0032]
    The specified criteria may include probability information, thus allowing the selection of patients likely to meet the specified criteria for the clinical study (e.g., 90% likelihood of diabetes, 70% likelihood of hypertension). In this case, the relevant patient records would include probabilistic information.
  • [0033]
    Furthermore, persons may still be selected even though not all information needed to determine whether a patient qualifies in all respects for a clinical trial is present. In this case, the list would include “persons of interest” some of whom might later be excluded from participating in the clinical trial for various reasons. Information about each person meeting the selection may additionally be provided, including information about other clinical trials that the person participated in and whether a placebo was administered.
  • [0034]
    The system may keep track of a plurality of clinical trials, and maintain a list of person who were administered a placebo instead of the drug being tested. In many cases, a person is disqualified from a trial if he or she participated in a trial for a similar drug; however, if it is determined that a placebo was administered, the system may be configured to not exclude the person. In other cases, the system would provide information about the trial(s) that the person participated in.
  • [0035]
    A physician, such as physician 230, may be contacted if one of their patients meets the specified criteria for a clinical trial. Prior to releasing information to a drug company, it is generally necessary to obtain agreement of the patient's physician and an informed consent of the patient to participate in the trial. For example, the physician 230 may recommend to a patient that a clinical trial being conducted by the drug company 210 would be beneficial. The details of the trial may have been forwarded to the physician 230. Furthermore, physicians may be notified of their Institutional Review Board (IRB) statuses (e.g., ‘approved’, ‘pending’, or ‘not approved’. Expiration dates of their status may be forwarded to approved physicians.
  • [0036]
    The clinical trials brokerage 250 can be notified that the patient provided an intent to participate. When the necessary informed consent information is obtained, the clinical trials brokerage 250 can provide the identity of the patient (and other patient information) to the drug company 210.
  • [0037]
    Preferably, the structured CPR 280 is populated with patient information using data mining techniques described in “Patient Data Mining,” by Rao et al., Attorney Docket No. 2001P20906US01, copending U.S. patent application Ser. No. 10/___,___, filed herewith, which is incorporated by reference herein in its entirety.
  • [0038]
    That disclosure teaches a data mining framework for mining high-quality structured clinical information. The data mining framework includes a data miner that mines medical information from a computerized patient record based on domain-specific knowledge contained in a knowledge base. The data miner includes components for extracting information from the computerized patient record, combining all available evidence in a principled fashion over time, and drawing inferences from this combination process. The mined medical information is stored in a structured computerized patient record.
  • [0039]
    To determine the specified criteria for the clinical study, multiple data sources typically need to be consulted. For example, to determine whether the patient is diabetic, the system might have to examine the following information:
  • [0040]
    (a) ICD-9 billing codes for secondary diagnoses associated with diabetes;
  • [0041]
    (b) drugs administered to the patient that are associated with the treatment of diabetes (e.g., insulin);
  • [0042]
    (c) patient's lab values that are diagnostic of diabetes (e.g., two successive blood sugar readings over 250 mg/d);
  • [0043]
    (d) doctor mentions that the patient is a diabetic in the H&P (history & physical) or discharge note (free text); and
  • [0044]
    (e) patient procedures (e.g., foot exam) associated with being a diabetic.
  • [0045]
    As can be seen, there are multiple independent sources of information, observations from which can support (with varying degrees of certainty) that the patient is diabetic (or more generally has some disease/condition). Not all of them may be present, and in fact, in some cases, they may contradict each other. Probabilistic observations can be derived, with varying degrees of confidence. Then these observations (e.g., about the billing codes, the drugs, the lab tests, etc.) may be probabilistically combined to come up with a final probability of diabetes.
  • [0046]
    Note that there may be information in the patient record that contradicts diabetes. For instance, the patient is has some stressful episode (e.g., an operation) and his blood sugar does not go up.
  • [0047]
    It should be appreciated that the selection of patients for clinical trials may be based on probabilistic information. Thus, a list of patients that meet the specified criteria may comprise a list of patients likely (e.g., according to a particular degree of confidence) to have met the criteria for the clinical trial.
  • [0048]
    Since it may be necessary to obtain additional information or to verify information about a participant, the clinical trials brokerage 250 may output, or otherwise provide, questionnaires. These questionnaires may be used to ascertain qualifications for the clinical trial. For example, the patient may be asked to provide a detailed family history of particular diseases.
  • [0049]
    In addition to providing a list of persons meeting the specified criteria, the clinical trials brokerage 250 may also calculate various charges and fees. For example, participating physicians may need to be compensated. The drug company may be charged a fee for the list. Additionally, participants in the clinical trial may also be compensated.
  • [0050]
    In various embodiments of the present invention, lists of persons who are pre-qualified for certain types of clinical trials may be generated. These lists of pre-qualified individuals may be made available to drug companies or other entities interested in conducting a clinical trial.
  • [0051]
    Referring to FIG. 3, an alternate embodiment of the present invention is illustrated. In this embodiment, a clinical trials brokerage 350 is able to access a structured CPR 380 containing mined structured patient information, and also a clinical trials database 390 containing information about various clinical trials. The information in the clinical trials database 390 may include information regarding the qualifications for clinical trials along with other information regarding the trials. A patient, such as patient 335, may request information about a particular clinical trial. The patient may either directly access the clinical trials brokerage 350 or go through a physician, such as physician 330. The clinical trials brokerage 330 may access the structured CPR 380 (populated with information in the same manner as the CPR 280) to retrieve information about the patient, and attempt to match clinical trials of interest to the patient based on the medical history of the patient and available trials.
  • [0052]
    Referring to FIG. 4, a flow diagram outlining an exemplary technique for selecting a person for a clinical trial is illustrated. Beginning at step 401, a person is selected from among a set of persons meeting specified criteria. This step may include receiving a request for a list of persons meeting specified criteria for a clinical trial, and retrieving a set of patient records from a data source to determine persons meeting the specified criteria.
  • [0053]
    For example, a drug company might be interested in selecting black males who are diabetic and have had a heart attack within the last three years. This might be used to test a new drug.
  • [0054]
    Using conventional approaches, satisfying the above-mentioned selection criteria could be difficult because computerized hospital databases generally do not store such information. However, by employing the data mining techniques described in “Patient Data Mining,” by Rao et al., Attorney Docket No. 2001P20906US01, copending U.S. patent application Ser. No. 10/___,___, filed herewith, a structured CPR can be populated with such patient information, thus allowing this selection criteria to be satisfied.
  • [0055]
    In step 402, the person's physician can be notified that the person has been selected for the clinical trial. At this point, a hospital's Institutional Review Board (IRB) can also be notified. The physician can also be notified if IRB approval has already been granted for this trial at this site, or if he needs to wait for the IRB approval for this trial. Next, in step 403, a determination is made as to whether the physician will participate in the study. If it is determined that the physician will participate, control continues to step 404; otherwise control terminates at step 408.
  • [0056]
    In step 404, the person is notified that he or she may qualify for the clinical trial. The patient can be directly contacted, or, indirectly contacted through a physician. At this point, the patient may be given detailed information about the clinical trial. The patient may be asked for additional information, such as through a questionnaire. The questionnaire may be used to determine qualification for the study and/or as a way to obtain additional useful information.
  • [0057]
    Next, in step 405, a determination is made as to whether the person indicated a desire to participate in the clinical trial. If the person notified his or her physician of an intent to participate, control continues to step 406; otherwise control terminates at step 408.
  • [0058]
    In step 406, release information is obtained. At this point the person may be provided with a consent form or be directed to complete one provided to him by his or her physician. Any information regarding participant compensation, including reimbursements, may also be provided. Control continues to step 407.
  • [0059]
    In step 407, fees and charges may be determined. For instance, the entity requesting the list of patients may be charged an appropriate fee for the list of patients. Furthermore, the physician and trial participants may also be compensated for their participation in the study. Control continues to step 408 where the operation stops.
  • [0060]
    As shown in FIGS. 1-4, this invention is preferably implemented using a general purpose computer system. However the systems and methods of this invention can be implemented using any combination of one or more programmed general purpose computers, programmed microprocessors or micro-controllers and peripheral integrated circuit elements, ASIC or other integrated circuits, digital signal processors, hardwired electronic or logic circuits such as discrete element circuits, programmable logic devices such as a PLD, PLA, FPGA or PAL, or the like. In general, any device capable of implementing a finite state machine that is in turn capable of implementing the flowchart shown in FIG. 4 can be used to implement this system.
  • [0061]
    Although illustrative embodiments of the present invention have been described herein with reference to the accompanying drawings, it is to be understood that the invention is not limited to those precise embodiments, and that various other changes and modifications may be affected therein by one skilled in the art without departing from the scope or spirit of the invention.
Patent Citations
Cited PatentFiling datePublication dateApplicantTitle
US4946679 *Sep 29, 1989Aug 7, 1990Thys Jacobs SusanMethod for the treatment of premenstrual syndrome
US5172418 *Aug 8, 1990Dec 15, 1992Fuji Photo Film Co., Ltd.Image processing apparatus using disease-based image processing conditions
US5619991 *Apr 26, 1995Apr 15, 1997Lucent Technologies Inc.Delivery of medical services using electronic data communications
US5657255 *Apr 14, 1995Aug 12, 1997Medical Science Systems, Inc.Hierarchical biological modelling system and method
US5664109 *Jun 7, 1995Sep 2, 1997E-Systems, Inc.Method for extracting pre-defined data items from medical service records generated by health care providers
US5724573 *Dec 22, 1995Mar 3, 1998International Business Machines CorporationMethod and system for mining quantitative association rules in large relational tables
US5737539 *Oct 28, 1994Apr 7, 1998Advanced Health Med-E-Systems Corp.Prescription creation system
US5738102 *Jul 31, 1996Apr 14, 1998Lemelson; Jerome H.Patient monitoring system
US5811437 *Apr 22, 1997Sep 22, 1998Eli Lilly And CompanyMethods of increasing nitric oxide synthesis
US5845253 *Aug 24, 1994Dec 1, 1998Rensimer Enterprises, Ltd.System and method for recording patient-history data about on-going physician care procedures
US5903899 *Apr 23, 1997May 11, 1999Sun Microsystems, Inc.System and method for assisting exact Garbage collection by segregating the contents of a stack into sub stacks
US5908383 *Sep 17, 1997Jun 1, 1999Brynjestad; UlfKnowledge-based expert interactive system for pain
US5924074 *Sep 27, 1996Jul 13, 1999Azron IncorporatedElectronic medical records system
US5935060 *Jul 11, 1997Aug 10, 1999First Opinion CorporationComputerized medical diagnostic and treatment advice system including list based processing
US5939528 *Oct 31, 1997Aug 17, 1999Cornell Research Foundation, Inc.Crystalline FRAP complex
US5991731 *Feb 1, 1999Nov 23, 1999University Of FloridaMethod and system for interactive prescription and distribution of prescriptions in conducting clinical studies
US6039688 *Oct 31, 1997Mar 21, 2000Salus Media Inc.Therapeutic behavior modification program, compliance monitoring and feedback system
US6067466 *Nov 18, 1998May 23, 2000New England Medical Center Hospitals, Inc.Diagnostic tool using a predictive instrument
US6076088 *Feb 6, 1997Jun 13, 2000Paik; WoojinInformation extraction system and method using concept relation concept (CRC) triples
US6081786 *Apr 1, 1999Jun 27, 2000Triangle Pharmaceuticals, Inc.Systems, methods and computer program products for guiding the selection of therapeutic treatment regimens
US6083693 *Jun 14, 1996Jul 4, 2000Curagen CorporationIdentification and comparison of protein-protein interactions that occur in populations
US6108635 *Apr 30, 1997Aug 22, 2000Interleukin Genetics, Inc.Integrated disease information system
US6125194 *Feb 4, 1998Sep 26, 2000Caelum Research CorporationMethod and system for re-screening nodules in radiological images using multi-resolution processing, neural network, and image processing
US6139494 *Oct 15, 1997Oct 31, 2000Health Informatics ToolsMethod and apparatus for an integrated clinical tele-informatics system
US6173280 *Apr 24, 1998Jan 9, 2001Hitachi America, Ltd.Method and apparatus for generating weighted association rules
US6196970 *Mar 22, 1999Mar 6, 2001Stephen J. BrownResearch data collection and analysis
US6212519 *Jun 30, 1998Apr 3, 2001Simulconsult, Inc.Systems and methods for quantifying qualitative medical expressions
US6212526 *Dec 2, 1997Apr 3, 2001Microsoft CorporationMethod for apparatus for efficient mining of classification models from databases
US6259890 *Mar 27, 1997Jul 10, 2001Educational Testing ServiceSystem and method for computer based test creation
US6272472 *Dec 29, 1998Aug 7, 2001Intel CorporationDynamic linking of supplier web sites to reseller web sites
US6322504 *Mar 27, 2000Nov 27, 2001R And T, LlcComputerized interactive method and system for determining a risk of developing a disease and the consequences of developing the disease
US6468210 *Feb 14, 2001Oct 22, 2002First Opinion CorporationAutomated diagnostic system and method including synergies
US6478737 *May 18, 2001Nov 12, 2002Cardiac Intelligence CorporationSystem and method for analyzing normalized patient voice feedback an automated collection and analysis patient care system
US6484144 *Sep 15, 1999Nov 19, 2002Dental Medicine International L.L.C.Method and system for healthcare treatment planning and assessment
US6523019 *Oct 28, 1999Feb 18, 2003Choicemaker Technologies, Inc.Probabilistic record linkage model derived from training data
US6529876 *Mar 26, 1999Mar 4, 2003Stephen H. DartElectronic template medical records coding system
US6551266 *Dec 28, 1999Apr 22, 2003Occulogix CorporationRheological treatment methods and related apheresis systems
US6587829 *Jul 30, 1998Jul 1, 2003Schering CorporationMethod and apparatus for improving patient compliance with prescriptions
US6611825 *Jun 9, 1999Aug 26, 2003The Boeing CompanyMethod and system for text mining using multidimensional subspaces
US6611846 *Oct 30, 1999Aug 26, 2003Medtamic HoldingsMethod and system for medical patient data analysis
US6641532 *Aug 7, 2001Nov 4, 2003First Opinion CorporationComputerized medical diagnostic system utilizing list-based processing
US6645959 *Nov 8, 2000Nov 11, 2003Warner-Lambert CompanyMethod for treating postoperative ileus
US6678669 *Aug 14, 1997Jan 13, 2004Adeza Biomedical CorporationMethod for selecting medical and biochemical diagnostic tests using neural network-related applications
US6754655 *Nov 12, 1998Jun 22, 2004Simulconsult, Inc.Systems and methods for diagnosing medical conditions
US6802810 *Sep 21, 2001Oct 12, 2004Active Health ManagementCare engine
US6804656 *Nov 18, 1999Oct 12, 2004Visicu, Inc.System and method for providing continuous, expert network critical care services from a remote location(s)
US6839678 *Feb 11, 1999Jan 4, 2005Siemens AktiengesellschaftComputerized system for conducting medical studies
US6903194 *Sep 24, 1997Jun 7, 2005Chungai Seiyaku Kabushiki KaishaAntibody against human parathormone related peptides
US6941271 *Feb 15, 2000Sep 6, 2005James W. SoongMethod for accessing component fields of a patient record by applying access rules determined by the patient
US6961687 *Aug 3, 2000Nov 1, 2005Lockheed Martin CorporationInternet based product data management (PDM) system
US7058658 *Mar 28, 2001Jun 6, 2006Dana-Farber Cancer Institute, Inc.Molecular database for antibody characterization
US7130457 *Jul 17, 2001Oct 31, 2006Accuimage Diagnostics Corp.Systems and graphical user interface for analyzing body images
US7249006 *Mar 23, 2001Jul 24, 2007The Johns Hopkins UniversityMethod and system for bio-surveillance detection and alerting
US7307543 *Sep 26, 2005Dec 11, 2007Visicu, Inc.System and method for video observation of a patient in a health care location
US7353238 *Jun 11, 1999Apr 1, 2008Outcome Sciences, Inc.Apparatus and methods for determining and processing medical outcomes
US7630908 *Dec 8, 2009John AmrienWireless electronic prescription scanning and management system
US20010011243 *Mar 20, 2001Aug 2, 2001Ron DemboRisk management system, distributed framework and method
US20010023419 *Aug 14, 1997Sep 20, 2001Jerome LapointeMethod for selecting medical and biochemical diagnostic tests using neural network-related applications
US20010032195 *Dec 19, 2000Oct 18, 2001Graichen Catherine MarySystem and method for identifying productivity improvements in a business organization
US20010041991 *Feb 6, 2001Nov 15, 2001Segal Elliot A.Method and system for managing patient medical records
US20010051882 *Mar 30, 2001Dec 13, 2001Murphy Kevin M.Integrated care management system
US20020002474 *Aug 8, 2001Jan 3, 2002Michelson Leslie DennisSystems and methods for selecting and recruiting investigators and subjects for clinical studies
US20020019746 *Mar 13, 2001Feb 14, 2002Rienhoff Hugh Y.Aggregating persons with a select profile for further medical characterization
US20020026332 *Jul 18, 2001Feb 28, 2002Snowden Guy B.System and method for automated creation of patient controlled records
US20020029155 *Jul 30, 2001Mar 7, 2002Frank HetzelRegistration and ordering system
US20020032581 *Jun 1, 2001Mar 14, 2002Reitberg Donald P.Single-patient drug trials used with accumulated database: risk of habituation
US20020077853 *Sep 14, 2001Jun 20, 2002Kevin BoruSystem for selecting clinical trials
US20020082480 *Aug 29, 2001Jun 27, 2002Riff Kenneth M.Medical device systems implemented network scheme for remote patient management
US20020099570 *Aug 23, 2001Jul 25, 2002Knight Stephen C.Recruiting a patient into a clinical trial
US20020107641 *Oct 5, 2001Aug 8, 2002Schaeffer Anthony J.Methods and kits for managing diagnosis and therapeutics of bacterial infections
US20020173990 *May 14, 2002Nov 21, 2002Dominic A. MarascoSystem and method for managing interactions between healthcare providers and pharma companies
US20020177759 *Sep 5, 2001Nov 28, 2002Ido SchoenbergMedical information text display system
US20030028401 *Jul 17, 2001Feb 6, 2003Leon KaufmanCustomizable lung report generator
US20030046114 *Oct 23, 2001Mar 6, 2003Davies Richard J.System, method, and apparatus for storing, retrieving, and integrating clinical, diagnostic, genomic, and therapeutic data
US20030108938 *Nov 6, 2002Jun 12, 2003David PickarPharmacogenomics-based clinical trial design recommendation and management system and method
US20030135391 *Oct 31, 2002Jul 17, 2003Edmundson Catherine M.Method and system for analyzing health information
US20040078216 *Apr 12, 2002Apr 22, 2004Gregory TotoClinical trial process improvement method and system
US20040184644 *Jan 12, 2004Sep 23, 2004Cadvision Medical Technologies Ltd.Display for computer-aided evaluation of medical images and for establishing clinical recommendation therefrom
US20040243586 *May 27, 2003Dec 2, 2004Byers Frank HughMethod and apparatus for obtaining and storing medical history records
US20050191716 *Apr 27, 2005Sep 1, 2005Zycare, Inc.Apparatus and methods for monitoring and modifying anticoagulation therapy of remotely located patients
US20060136259 *Dec 17, 2004Jun 22, 2006General Electric CompanyMulti-dimensional analysis of medical data
Referenced by
Citing PatentFiling datePublication dateApplicantTitle
US6826578 *Oct 25, 2002Nov 30, 2004Ge Medical Systems Information Technolgoies, Inc.Method, system, and computer product for collecting and distributing clinical data for data mining
US7181375Nov 4, 2002Feb 20, 2007Siemens Medical Solutions Usa, Inc.Patient data mining for diagnosis and projections of patient states
US7244230Nov 6, 2003Jul 17, 2007Siemens Medical Solutions Usa, Inc.Computer aided diagnostic assistance for medical imaging
US7630947Dec 8, 2009Siemens Medical Solutions Usa, Inc.Medical ontologies for computer assisted clinical decision support
US7650321Feb 15, 2006Jan 19, 2010Siemens Medical Solutions Usa, Inc.Two classifier based system for classifying anomalous medical patient records
US7711404Nov 4, 2002May 4, 2010Siemens Medical Solutions Usa, Inc.Patient data mining for lung cancer screening
US7744540Jun 29, 2010Siemens Medical Solutions Usa, Inc.Patient data mining for cardiology screening
US7805385Apr 16, 2007Sep 28, 2010Siemens Medical Solutions Usa, Inc.Prognosis modeling from literature and other sources
US7840511Sep 5, 2007Nov 23, 2010Siemens Medical Solutions Usa, Inc.Learning or inferring medical concepts from medical transcripts using probabilistic models with words or phrases identification
US7844560Apr 16, 2007Nov 30, 2010Siemens Medical Solutions Usa, Inc.Personalized prognosis modeling in medical treatment planning
US7865373 *Oct 15, 2003Jan 4, 2011Medical Web Technologies, Inc.Method and apparatus for sharing healthcare data
US7899764Mar 1, 2011Siemens AktiengesellschaftMedical ontologies for machine learning and decision support
US7917377Nov 4, 2002Mar 29, 2011Siemens Medical Solutions Usa, Inc.Patient data mining for automated compliance
US8214224Nov 4, 2002Jul 3, 2012Siemens Medical Solutions Usa, Inc.Patient data mining for quality adherence
US8214225Nov 4, 2002Jul 3, 2012Siemens Medical Solutions Usa, Inc.Patient data mining, presentation, exploration, and verification
US8280750May 14, 2010Oct 2, 2012Siemens Medical Solutions Usa, Inc.Patient data mining for cardiology screening
US8392152Aug 13, 2008Mar 5, 2013Siemens Medical Solutions Usa, Inc.Early detection of disease outbreak using electronic patient data to reduce public health threat from bio-terrorism
US8620677Apr 9, 2002Dec 31, 2013Pcrs, Inc.Online, interactive evaluation of research performance
US8626533Nov 4, 2002Jan 7, 2014Siemens Medical Soultions Usa, Inc.Patient data mining with population-based analysis
US8670997Feb 8, 2007Mar 11, 2014Siemens Medical Solutions Usa, Inc.Quality metric extraction and editing for medical data
US8682693Jun 6, 2007Mar 25, 2014Siemens Medical Solutions Usa, Inc.Patient data mining for lung cancer screening
US8688475 *Nov 10, 2006Apr 1, 2014General Electric CompanyMethod and system for clinical trial compliance
US8700649 *Mar 28, 2011Apr 15, 2014Optuminsight, Inc.Analyzing administrative healthcare claims data and other data sources
US8751495Sep 28, 2010Jun 10, 2014Siemens Medical Solutions Usa, Inc.Automated patient/document identification and categorization for medical data
US8949079Jun 19, 2009Feb 3, 2015Siemens Medical Solutions Usa, Inc.Patient data mining
US8949082Jun 6, 2011Feb 3, 2015Siemens Medical Solutions Usa, Inc.Healthcare information technology system for predicting or preventing readmissions
US9129054Sep 19, 2013Sep 8, 2015DePuy Synthes Products, Inc.Systems and methods for surgical and interventional planning, support, post-operative follow-up, and, functional recovery tracking
US9298764 *May 1, 2013Mar 29, 2016Oracle International CorporationPartial source verification of EDC data
US20030120133 *Nov 4, 2002Jun 26, 2003Rao R. BharatPatient data mining for lung cancer screening
US20030120134 *Nov 4, 2002Jun 26, 2003Rao R. BharatPatient data mining for cardiology screening
US20030120458 *Nov 4, 2002Jun 26, 2003Rao R. BharatPatient data mining
US20030120514 *Nov 4, 2002Jun 26, 2003Rao R. BharatPatient data mining, presentation, exploration, and verification
US20030125984 *Nov 4, 2002Jul 3, 2003Rao R. BharatPatient data mining for automated compliance
US20030125985 *Nov 4, 2002Jul 3, 2003Rao R. BharatPatient data mining for quality adherence
US20030125988 *Nov 4, 2002Jul 3, 2003Rao R. BharatPatient data mining with population-based analysis
US20030126101 *Nov 4, 2002Jul 3, 2003Rao R. BharatPatient data mining for diagnosis and projections of patient states
US20040083217 *Oct 25, 2002Apr 29, 2004Cameron BrackettMethod, system, and computer product for collecting and distributing clinical data for data mining
US20040093238 *Nov 8, 2002May 13, 2004Deakter Daniel R.System and process for matching patients with clinical medical trials
US20040147840 *Nov 6, 2003Jul 29, 2004Bhavani DuggiralaComputer aided diagnostic assistance for medical imaging
US20040172293 *Nov 19, 2003Sep 2, 2004Paul BruschiMethod for identifying and communicating with potential clinical trial participants
US20050086074 *Oct 15, 2003Apr 21, 2005Medical Web Technologies, Inc.Method and apparatus for sharing healthcare data
US20050192649 *Feb 27, 2004Sep 1, 2005Cardiac Pacemakers, Inc.Systems and methods for providing variable medical information
US20050192836 *Feb 27, 2004Sep 1, 2005Cardiac Pacemakers, Inc.Systems and methods for delivering and gathering medical diagnostic data
US20050192838 *Feb 27, 2004Sep 1, 2005Cardiac Pacemakers, Inc.Systems and methods for accessing and distributing medical information
US20050192842 *Feb 27, 2004Sep 1, 2005Cardiac Pacemakers, Inc.Systems and methods for authorizing and processing reimbursements for services provided in the collection of implantable medical device data
US20050192843 *Feb 27, 2004Sep 1, 2005Cardiac Pacemakers, Inc.Systems and methods for validating patient and medical devices information
US20050192844 *Feb 27, 2004Sep 1, 2005Cardiac Pacemakers, Inc.Systems and methods for automatically collecting, formatting, and storing medical device data in a database
US20060184475 *Feb 15, 2006Aug 17, 2006Sriram KrishnanMissing data approaches in medical decision support systems
US20060210133 *Feb 24, 2006Sep 21, 2006Sriram KrishnanPerformance adjustments in medical decision support systems
US20060265253 *May 17, 2006Nov 23, 2006Rao R BPatient data mining improvements
US20070067189 *Sep 18, 2006Mar 22, 2007Numoda CorporationMethod and apparatus for screening, enrollment and management of patients in clinical trials
US20070094188 *Aug 16, 2006Apr 26, 2007Pandya Abhinay MMedical ontologies for computer assisted clinical decision support
US20070106531 *Mar 11, 2004May 10, 2007Daniel DeakterMethod and process that automatically finds patients for clinical drug or device trials
US20070150372 *Dec 19, 2006Jun 28, 2007Roy SchoenbergVendor and Consumer Matching
US20070168345 *Jan 17, 2007Jul 19, 2007Andrew GibbsSystem and method of identifying subject matter experts
US20070250347 *Apr 25, 2006Oct 25, 2007Klaus Abraham-FuchsBroker service and system architecture for health care data
US20070255584 *Sep 8, 2004Nov 1, 2007Pavlatos Christ JPatient Physician Connectivity System and Method
US20070276777 *Apr 16, 2007Nov 29, 2007Siemens Medical Solutions Usa, Inc.Personalized Prognosis Modeling In Medical Treatment Planning
US20080033894 *Apr 16, 2007Feb 7, 2008Siemens Medical Solutions Usa, Inc.Prognosis Modeling From One or More Sources of Information
US20080059391 *Sep 5, 2007Mar 6, 2008Siemens Medical Solutions Usa, Inc.Learning Or Inferring Medical Concepts From Medical Transcripts
US20080114616 *Nov 10, 2006May 15, 2008General Electric CompanyMethod and system for clinical trial compliance
US20080195600 *May 24, 2007Aug 14, 2008Deakter Daniel REfficient method and process to search structured and unstructured patient data to match patients to clinical drug/device trials
US20080201280 *Jun 15, 2007Aug 21, 2008Huber MartinMedical ontologies for machine learning and decision support
US20080228769 *Mar 13, 2008Sep 18, 2008Siemens Medical Solutions Usa, Inc.Medical Entity Extraction From Patient Data
US20090076851 *Aug 13, 2008Mar 19, 2009Siemens Medical Solutions Usa, Inc.Early detection of disease outbreak using electronic patient data to reduce public health threat from bio-terrorism
US20090313045 *Dec 17, 2009Boyce Mark DSystem and Method for Medical Research and Clinical Trial
US20100169115 *Dec 31, 2009Jul 1, 2010Tamis Robert HSystem for matching individuals with health care providers and methods thereof
US20100222646 *May 14, 2010Sep 2, 2010Siemens Medical Solutions Usa, Inc.Patient Data Mining for Cardiology Screening
US20100235378 *Aug 22, 2007Sep 16, 2010Lead Horse Technologies, Inc.Medical assessment support system and method
US20110078145 *Sep 28, 2010Mar 31, 2011Siemens Medical Solutions Usa Inc.Automated Patient/Document Identification and Categorization For Medical Data
US20110184761 *Jul 28, 2011Siemens Medical Solutions Usa, Inc.Method and Apparatus for Estimating Patient Populations
US20110231422 *Sep 22, 2011Ingenix Inc.Analyzing administrative healthcare claims data and other data sources
US20110238438 *Sep 29, 2011Numoda Technologies, Inc.Automated method of graphically displaying predicted patient enrollment in a clinical trial study
US20120209628 *Apr 25, 2012Aug 16, 2012Tamis Robert HSystem for matching individuals with health care providers and methods thereof
US20120316898 *Dec 13, 2012Levitt Tod SScalable determination of probable patient eligibility for clinical trials and associated process for active solicitation of patients for clinical trials via their healthcare providers
US20130318049 *May 1, 2013Nov 28, 2013Oracle International CorporationPartial source verification of edc data
US20140122113 *Dec 23, 2013May 1, 2014Cerner Innovation, Inc.Providing indications of clinical-trial criteria modifications
WO2005081084A2 *Feb 1, 2005Sep 1, 2005Siemens AktiengesellschaftMethod for selecting a potential participant for a medical study on the basis of a selection criterion
WO2005081084A3 *Feb 1, 2005Dec 1, 2005Klaus Abraham-FuchsMethod for selecting a potential participant for a medical study on the basis of a selection criterion
WO2006096364A2Feb 27, 2006Sep 14, 2006Siemens Medical Solutions Usa, Inc.Performance adjustments in medical decision support systems
WO2007079442A1 *Jan 3, 2007Jul 12, 2007Invivodata, Inc.Apparatus and method for prediction and management of participant compliance in clinical research
WO2015139115A1 *Mar 17, 2015Sep 24, 2015Eqol Inc.System and method for managing illness outside of a hospital environment
Classifications
U.S. Classification705/2, 707/E17.058, 707/E17.005, 705/3
International ClassificationG06F19/00, G06Q10/00, A61B5/00, G06F17/30
Cooperative ClassificationG06F19/3443, G06F19/325, G06F19/345, G06F19/3437, G06F19/3406, G06F19/3431, G06Q10/10, G06F19/322, G06F19/3418, G06F19/363, G06F19/328, G06F19/3481, G06Q50/24, Y10S128/92, G06F17/3061, G06Q50/22, G06F19/321, G06F19/324, G06F19/3487, G06F19/327
European ClassificationG06Q10/10, G06F19/32C, G06F19/34J, G06F19/36A, G06F19/34H, G06F19/34G, G06F19/32G, G06F19/34N, G06F19/34P, G06Q50/22, G06F19/32E1, G06F19/32E, G06Q50/24, G06F17/30T
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