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WO2002039891A1 - Procede et systeme pour l'analyse dynamique de parametres de sante - Google Patents

Procede et systeme pour l'analyse dynamique de parametres de sante Download PDF

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Publication number
WO2002039891A1
WO2002039891A1 PCT/US2001/031572 US0131572W WO0239891A1 WO 2002039891 A1 WO2002039891 A1 WO 2002039891A1 US 0131572 W US0131572 W US 0131572W WO 0239891 A1 WO0239891 A1 WO 0239891A1
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WIPO (PCT)
Prior art keywords
database
examination
subject body
data
subject
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Ceased
Application number
PCT/US2001/031572
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English (en)
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WO2002039891A8 (fr
Inventor
Jeffrey L. Garwin
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Ultratouch Corp
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Ultratouch Corp
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Filing date
Publication date
Application filed by Ultratouch Corp filed Critical Ultratouch Corp
Priority to US10/398,297 priority Critical patent/US20040030672A1/en
Priority to AU2001296750A priority patent/AU2001296750A1/en
Publication of WO2002039891A1 publication Critical patent/WO2002039891A1/fr
Publication of WO2002039891A8 publication Critical patent/WO2002039891A8/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0082—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes
    • A61B5/0091—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes for mammography

Definitions

  • This invention relates to reporting systems, and more particularly to a method and system for developing a dynamic health metric reporting system for improving the utility of diagnostic technology used in the practice of medicine.
  • the present invention is a dynamic health metric reporting system for prospectively collecting data relevant to improving the utility of medical diagnostic technology, by focusing on dynamic (changing) health metrics (measurements and statistically derived measures of phenomena and their changes in populations).
  • the system collects and stores examination data for each of multiple examinations of subject bodies.
  • the examination data from of two or more selected examination dates is compared, and differences determined, for a specific subject body.
  • the differences between two or more examination dates are characterized and stored in a database.
  • a report is generated that details the differences in the examination data to assist in predicting a likely course of health for the subject body.
  • the system similarly collects and stores examination data for each of multiple examinations of subject bodies.
  • the examination data from of two or more selected examination dates is compared for a specific subject body, differences are determined and one dynamic metric is created for the subject body, and stored in a database, for each pair of examination dates compared.
  • One or more dynamic metrics for the subject body are compared with dynamic metrics for a relevant comparison population of similarly situated subject bodies in the database and reports are generated detailing the similarities and differences in the dynamic metrics for the subject body with the dynamic metrics of similarly situated subject bodies to assist in predicting a likely course of health for the subject body.
  • the dynamic health metric reporting system of the present invention includes the database system, database application logic for incorporating the data into the database, data from the diagnostic technology instrument(s), clinical and demographic data related to the individual patients and their medical history, statistical analysis programs for analyzing the database for clinically relevant group correlations between and among the diagnostic digital data, the clinical and demographic data, and the changes in these data with time for individual patients; and report-generating logic for generating a report that compares historical data for an individual patient in the database with clinically significant trends or findings based on group data from the entire database.
  • the invention uniquely permits the acquisition of prospective data in large quantity and in consistent format, so that the data will yield insights directed to the best use of the diagnostic teclmology.
  • the prospective data acquired by this invention by virtue of its size, consistency, and digital format, allows the operator of the invention to create unique dynamic databases that provide a "moving picture" of health and development of disease, in place of disjointed snapshots.
  • a dynamic database reaches a sufficient critical size, both in numbers of patients and in time that each patient is followed, the report-generating logic informs doctors and third party payers about the likely health progression of a particular patient, given his or her record through time relative to the relevant patient database (i.e., a predictive instrument).
  • Example 1 A Dynamic Health Metric Reporting System (DHMRS) for Auditory Data related to the Heart
  • the dynamic health metric reporting system collects data prospectively from doctors using electronic stethoscopes, such as the DRG Conventional Electronic Digital Stethoscope, that digitally records (heart) sounds.
  • the digital recording is transmitted electronically to a remote DHMRS computer facility, and loaded to a relational database, including identifiers for doctor, patient, and date/time of the exam.
  • a relational database including identifiers for doctor, patient, and date/time of the exam.
  • the digital recording and identifiers are associated with additional patient data included in related records, also keyed to doctor and date/time, as well as patient and date/time.
  • the additional patient data could include tentative diagnosis, symptoms, general self-reported health, doctor's sound description (e.g. location, intensity, description), doctor's past and present prescribed treatment, patient heart history and the reason for seeking medical attention (the iatrotrophic stimulus).
  • the digital record is collected for each use of the stethoscope, the recording and identifying data transmitted to the DHMRS computer at the end of the doctor's workday.
  • Electronic transmission could be by wired or wireless communication systems, or by recordation on magnetic or optical media with transfer to the DHMRS computer by a peripheral device for reading such media. Because the electronics are inherently more sensitive than the human ear to both very low and very high frequencies, it may be possible to correlate previously unperceived changes in heart sounds with changes in other measures of health, or with various drug or behavioral changes affecting the patient.
  • the DHMRS includes algorithms for analyzing the sound (producing a sound map for each session, each map being a static metric), algorithms for comparing one sound map with another (dynamic metrics), and statistical algorithms for compiling a database of dynamic metrics (a database of how static metrics changed from one examination to the next, explicitly including a measure of the elapsed time between examinations).
  • the DHMRS can also compare the dynamic metrics for a particular patient (a sequence of examinations, and changes between examinations) with the dynamic metrics for a relevant comparison population of similar patients in the database. This comparison allows for a more accurate prediction of the likely course of health for this metric system (heart health metrics as revealed by electronic stethoscope examination). This comparison allows a more accurate prediction of the likely effect of drug or surgical interventions, based on the growing experience recorded in the dynamic metric database. The comparison could be sent to the physician or managed care organization (MCO) in the form of a standardized report, transmitted electronically. The longer the database is maintained, and the larger the number of patients included, the more useful and accurate it will be for assisting doctors in diagnostic, prognostic, and management evaluations and decisions.
  • MCO managed care organization
  • the dynamic health metric reporting system prospectively collects data from doctors, who may be using a robotic device for detecting anomalies in breast tissue.
  • One apparatus for detecting tissue anomalies illustrated in U.S. Patent No. 6,192,143, maps characteristics of breast tissue, such as density, in three dimensions, recording the data digitally for later inspection and comparison.
  • the digital recording is transmitted electronically to a remote DHMRS computer facility, and loaded to a relational database, including identifiers for doctor, patient, and date/time of the exam.
  • the digital recording and identifiers are associated with additional patient data included in related records, also keyed to doctor and date/time, as well as patient and date/time.
  • the additional patient data could include tentative diagnosis, symptoms, general self-reported health, doctor's description of the breast by visual and manual inspection, doctor's past and present prescribed treatment, personal and family history and the reason for seeking medical attention (the iatrotrophic stimulus).
  • the digital record is collected for each use of the apparatus for detecting anomalies in breast tissue, the recorded and identifying data transmitted to the DHMRS computer at the end of the doctor's workday.
  • the electronic transmission could be by wired or wireless communication systems, or by recordation on magnetic or optical media with transfer to the DHMRS computer by a peripheral device for reading such media.
  • a palpation probe of the apparatus is inherently more sensitive than the human hand for detecting tissue anomalies, and because the optical mapping system of the apparatus is more precise than the human eye, it is possible to detect previously unperceived changes in breast tissue characteristics, such as density, and to correlate the changing characteristics with the development of breast abnormalities and their associated health implications, such as fibrocystic changes or cancer.
  • the DHMRS tracks and analyzes changes in breast tissue characteristics following surgical or drug treatment.
  • the DHMRS includes algorithms for analyzing breast tissue characteristics, such as density (producing a breast density map for each session, each map being a static metric), algorithms for comparing one breast map with another (dynamic metrics), and statistical algorithms for compiling a database of dynamic metrics (a database of how static metrics changed from one examination to the next, explicitly including a measure of the elapsed time between examinations and drug or surgical treatments between examinations).
  • the DHMRS compares the dynamic metrics for a particular patient (a sequence of examinations, and changes between examinations) with the dynamic metrics for a relevant comparison population of similar patients in the database. This comparison allows for more accurate prediction of the likely course of health for this metric system (breast health metrics as revealed by robotic breast palpation examination). The comparison allows more accurate prediction of the likely effect of drug or surgical interventions, based on the growing experience recorded in the dynamic metric database.
  • the comparison can be sent to the physician or managed care organization (MCO) in the form of a standardized report, preferably via electronic transmission.
  • MCO managed care organization
  • Example 3 Dynamic Health Metric Reporting System (DHMRS) for CEA levels, related to monitoring the efficacy of cancer treatment
  • the dynamic health metric reporting system collects data prospectively from doctors or clinical laboratories, concerning the blood levels of CarcinoEmbryonic Antigen (CEA).
  • CEA CarcinoEmbryonic Antigen
  • the CEA level is a single number, together with a standard deviation for the measurement.
  • CEA can be a useful marker for the presence of cancer.
  • tracking the level of CEA provides a means for monitoring the efficacy of treatment, which can be assessed by the drop in CEA levels towards normal.
  • Subsequent elevations in CEA, after a drop are frequently thought to indicate recurrence or metastasis of the cancer.
  • the DHMRS records the CEA level (and standard deviation), along with other relevant clinical data about the patient, and statistically sorts significant trends.
  • a digital record of the CEA level and standard deviation is transmitted electronically to a remote DHMRS computer facility, and loaded to a relational database, including identifiers for doctor, patient, and date/time of the exam.
  • the digital record and identifiers are associated with additional patient data included in related records, also keyed to doctor and date/time, as well as patient and date/time.
  • the additional patient data could include tentative diagnosis, symptoms, general self- reported health, doctor's description of the cancer history, doctor's past and present prescribed treatment, personal and family cancer history and the reason for seeking medical attention (the iatrotrophic stimulus).
  • the digital record is collected for each CEA level detected.
  • the electronic transmission could be wired or wireless communication systems, or by recordation on magnetic or optical media with transfer to the DHMRS computer by a peripheral device for reading such media. Because the CEA data is placed in the database prospectively, over very large numbers of patients, the DHMRS is able to statistically detect previously unperceived patterns of change in CEA levels, correlating them with the progression or remission of cancer.
  • the DHMRS tracks and analyzes changes in CEA levels following surgical or drug treatment.
  • the DHMRS includes algorithms for comparing one CEA level with another (dynamic metrics), and statistical algorithms for compiling a database of dynamic metrics (a database of how static metrics changed from one examination to the next, explicitly including a measure of the elapsed time between examinations and drug or surgical treatments occurring therebetween).
  • the DHMRS compares the dynamic metrics for a particular patient (a sequence of examinations, and changes between examinations) with the dynamic metrics for a relevant comparison population of similar patients in the database. This comparison allows for more accurate prediction of the likely course of health for this metric system (CEA levels after detection of cancer). The comparison allows more accurate prediction of the likely effect of drug or surgical interventions, based on the growing experience recorded in the dynamic metric database. The comparison can be sent to the physician or managed care organization (MCO) in the form of a standardized report, through electronic transmission. The longer the database is maintained, and the larger the number of patients included, the more useful and accurate the DHMRS will be for assisting doctors in diagnostic, prognostic, and management evaluations and decisions.
  • MCO managed care organization
  • features include the collection and storage of digital examination data.
  • the database is prospective (i.e., examination data, demographic and treatment data, etc., is collected and stored at the time of occurrence).
  • the database is also relational, providing sort and search capability for all included criteria.
  • the system includes statistical algorithms, clinical epidemiology, meta-analytical techniques, including the capability to compare an individual patient's dynamic data with subgroups in, and the totality of, the database.
  • the report generating logic provides report generation capability relative to and sorted by a variety of criteria.
  • the DHMRS could further be directed to digital maps of any kind, density, x- ray, sonogram, thermal, CT Scan, MRI, PET, and radiographic contrast.
  • Graphs of electrical activity electrocardiogram, electroencephalogram and nerve conduction would also be adaptable to the methods and system of the present invention.
  • sound recordings such as the digital stethoscope described above, and bone conduction studies are applicable.
  • a reporting system could be developed for images obtained by systematic computer reading, histologically or immuno-histologically stained slides, and histograms of lab work (including complete blood counts).
  • any observations of the body where direct output is digital or numerical such as lab values (e.g., CEA, PSA, free PSA), or observations where direct output is analog, but can be digitized (e.g., mammogram), are also adaptable.
  • any examination data having an objective, measurable outcome could be the subject of a dynamic health metric reporting system.

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  • Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Epidemiology (AREA)
  • Data Mining & Analysis (AREA)
  • Biomedical Technology (AREA)
  • Databases & Information Systems (AREA)
  • Pathology (AREA)
  • Medical Treatment And Welfare Office Work (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

L'invention concerne un système d'analyse dynamique de paramètres de santé permettant la collecte prospective de données pertinentes pour l'amélioration des techniques de diagnostic médical, ces techniques produisant des données numériques enregistrées dans une base de données électronique parallèlement à des données démographiques et de traitement propres à différents patients. Le système d'analyse comprend la base de données, une logique d'application de base de données pour l'introduction des données dans la base, les données fournies par le ou les instruments utilisés dans les cadre des techniques de diagnostic, les données cliniques et démographiques propres aux différents patients et leur dossier médical, des programmes d'analyse statistique permettant d'analyser la base de données pour établir des corrélations entre les données numériques de diagnostic, les données cliniques et démographiques, et les variations de ces données dans le temps pour les différents patients. Le système comprend en outre une logique d'analyse qui fournit un rapport d'analyse comparant les données historiques en évolution dynamique, pour tel ou tel patient de la base de données, et les tendances ou les conclusions cliniquement pertinentes qui reposent sur des données de groupe extraites de la base de données globale.
PCT/US2001/031572 2000-10-06 2001-10-09 Procede et systeme pour l'analyse dynamique de parametres de sante Ceased WO2002039891A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US10/398,297 US20040030672A1 (en) 2001-08-01 2001-10-09 Dynamic health metric reporting method and system
AU2001296750A AU2001296750A1 (en) 2000-10-06 2001-10-09 A dynamic health metric reporting method and system

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US23834900P 2000-10-06 2000-10-06
US60/238,349 2000-10-06
US89050101A 2001-08-01 2001-08-01
US09/890,501 2001-08-01

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WO2002039891A8 WO2002039891A8 (fr) 2002-07-04

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7634301B2 (en) 2003-09-17 2009-12-15 Koninklijke Philips Electronics N.V. Repeated examination reporting
CN108185989A (zh) * 2017-12-28 2018-06-22 中国人民解放军陆军军医大学第附属医院 早期乳腺疾病多功能诊断治疗仪及控制方法

Citations (14)

* Cited by examiner, † Cited by third party
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US5079698A (en) * 1989-05-03 1992-01-07 Advanced Light Imaging Technologies Ltd. Transillumination method apparatus for the diagnosis of breast tumors and other breast lesions by normalization of an electronic image of the breast
US5632276A (en) * 1995-01-27 1997-05-27 Eidelberg; David Markers for use in screening patients for nervous system dysfunction and a method and apparatus for using same
US5706822A (en) * 1996-03-29 1998-01-13 Kozz Incorporated Method and computer program for creating individualized exercise protocols
US5730146A (en) * 1991-08-01 1998-03-24 Itil; Turan M. Transmitting, analyzing and reporting EEG data
US5733739A (en) * 1995-06-07 1998-03-31 Inphocyte, Inc. System and method for diagnosis of disease by infrared analysis of human tissues and cells
US5779634A (en) * 1991-05-10 1998-07-14 Kabushiki Kaisha Toshiba Medical information processing system for supporting diagnosis
US5940802A (en) * 1997-03-17 1999-08-17 The Board Of Regents Of The University Of Oklahoma Digital disease management system
US5957866A (en) * 1995-07-03 1999-09-28 University Technology Corporation Apparatus and methods for analyzing body sounds
US6005911A (en) * 1995-11-17 1999-12-21 Trex Medical Corporation Large area array, single exposure digital mammography
US6032678A (en) * 1997-03-14 2000-03-07 Shraga Rottem Adjunct to diagnostic imaging systems for analysis of images of an object or a body part or organ
US6058322A (en) * 1997-07-25 2000-05-02 Arch Development Corporation Methods for improving the accuracy in differential diagnosis on radiologic examinations
US6056690A (en) * 1996-12-27 2000-05-02 Roberts; Linda M. Method of diagnosing breast cancer
US6091981A (en) * 1997-09-16 2000-07-18 Assurance Medical Inc. Clinical tissue examination
US6113540A (en) * 1993-12-29 2000-09-05 First Opinion Corporation Computerized medical diagnostic and treatment advice system

Patent Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5079698A (en) * 1989-05-03 1992-01-07 Advanced Light Imaging Technologies Ltd. Transillumination method apparatus for the diagnosis of breast tumors and other breast lesions by normalization of an electronic image of the breast
US5779634A (en) * 1991-05-10 1998-07-14 Kabushiki Kaisha Toshiba Medical information processing system for supporting diagnosis
US5730146A (en) * 1991-08-01 1998-03-24 Itil; Turan M. Transmitting, analyzing and reporting EEG data
US6113540A (en) * 1993-12-29 2000-09-05 First Opinion Corporation Computerized medical diagnostic and treatment advice system
US5632276A (en) * 1995-01-27 1997-05-27 Eidelberg; David Markers for use in screening patients for nervous system dysfunction and a method and apparatus for using same
US5733739A (en) * 1995-06-07 1998-03-31 Inphocyte, Inc. System and method for diagnosis of disease by infrared analysis of human tissues and cells
US5957866A (en) * 1995-07-03 1999-09-28 University Technology Corporation Apparatus and methods for analyzing body sounds
US6005911A (en) * 1995-11-17 1999-12-21 Trex Medical Corporation Large area array, single exposure digital mammography
US5706822A (en) * 1996-03-29 1998-01-13 Kozz Incorporated Method and computer program for creating individualized exercise protocols
US6056690A (en) * 1996-12-27 2000-05-02 Roberts; Linda M. Method of diagnosing breast cancer
US6032678A (en) * 1997-03-14 2000-03-07 Shraga Rottem Adjunct to diagnostic imaging systems for analysis of images of an object or a body part or organ
US5940802A (en) * 1997-03-17 1999-08-17 The Board Of Regents Of The University Of Oklahoma Digital disease management system
US6058322A (en) * 1997-07-25 2000-05-02 Arch Development Corporation Methods for improving the accuracy in differential diagnosis on radiologic examinations
US6091981A (en) * 1997-09-16 2000-07-18 Assurance Medical Inc. Clinical tissue examination

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7634301B2 (en) 2003-09-17 2009-12-15 Koninklijke Philips Electronics N.V. Repeated examination reporting
CN108185989A (zh) * 2017-12-28 2018-06-22 中国人民解放军陆军军医大学第附属医院 早期乳腺疾病多功能诊断治疗仪及控制方法

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