WO2002019246A2 - Systeme de reconnaissance de foyers presumes de maladies infectieuses - Google Patents

Systeme de reconnaissance de foyers presumes de maladies infectieuses Download PDF

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Publication number
WO2002019246A2
WO2002019246A2 PCT/US2001/027044 US0127044W WO0219246A2 WO 2002019246 A2 WO2002019246 A2 WO 2002019246A2 US 0127044 W US0127044 W US 0127044W WO 0219246 A2 WO0219246 A2 WO 0219246A2
Authority
WO
WIPO (PCT)
Prior art keywords
data
outbreak
syndromic
host computer
screens
Prior art date
Application number
PCT/US2001/027044
Other languages
English (en)
Other versions
WO2002019246A3 (fr
Inventor
Andrew Lee Corwin
James R. Campbell
Ria Purwita Larasati
Maidy Pranata Putri
Cyrus H. Simanjuntak
Original Assignee
The Government Of The United States Of America, As Represented By The Secretary Of The Navy
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by The Government Of The United States Of America, As Represented By The Secretary Of The Navy filed Critical The Government Of The United States Of America, As Represented By The Secretary Of The Navy
Priority to AU2001288551A priority Critical patent/AU2001288551A1/en
Publication of WO2002019246A2 publication Critical patent/WO2002019246A2/fr
Publication of WO2002019246A3 publication Critical patent/WO2002019246A3/fr

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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
    • 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
    • G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Definitions

  • the invention relates generally to a computer-based system and method for aiding in the collection of standardized medical data and in particular, for making area-specific and regional comparisons for trend analysis of the standardized data to target early warning outbreak recognition of infectious diseases.
  • Database is a method of using electronic data communications or an Internet link between the physician and one or more entities, such as a hospital, local lab, diagnostic center, pharmacy, Center for Disease Control database, a patient, or medical database service for the purpose of diagnosing and/or treating disease for a particular patient.
  • entity such as a hospital, local lab, diagnostic center, pharmacy, Center for Disease Control database, a patient, or medical database service for the purpose of diagnosing and/or treating disease for a particular patient.
  • One such entity contains an epidemiological database computer facility which collects epidemiological transaction records from physicians, hospitals and other institutions which have medical facilities, such as schools and large businesses.
  • the method is intended to assist the clinician in the diagnosis and treatment of an individual's disease.
  • the method relies quite necessarily on diagnostic not syndromic information which is warehoused and is available to the physician to aid in the diagnosis of a particular patient.
  • the method of Sloane does not target early warning recognition of infectious outbreak conditions and does not aggregate the data representing many cases with like syndromic conditions.
  • the patient's identifying information is essential in matching various data bases, with the expressed purpose of contributing to the clinical, presumptive diagnosis and treatment of the patient.
  • Epidemiological study using database generated information is possible using the Sloane method; however, analysis is not a programmed function.
  • Another object of the present invention is to develop a system to allow for real-time data collection and transfer that is specifically configured to detect early outbreak situations.
  • Yet another important object of the present invention is to develop a standardized system that uses syndromic rather than disease specific case detection in enhancing reporting reliability for more targeted and effective response type actions.
  • the early warning outbreak recognition/responsesystem fills a technology gap in predetermined locations surveillance capabilities that targeted early warning outbreak recognition.
  • the EWORS invention provides for timely and accurate dissemination of outbreak recognition.
  • the EWORS invention provides for timely and accurate dissemination of outbreak information leading to effective intervention measures, including investigative and containment activities.
  • the EWORS invention is designed as a complementary, rather than an alternative system for conventional surveillance methodologies.
  • the EWORS invention is predicated on same day transfer of information from local hospital sites to a host site for instant, menu driven analysis provided via screens generated by local and host site computer programs.
  • the success of the EWORS invention is predicated on a prompt and appropriate response to suggestive outbreak findings.
  • FIG. 1 is a view of the surveillance and response system (EWORS) for infectious diseases
  • FIG.2 is a pictorial flowchart of symptomatic data from the local hospital site to the host site;
  • FIG. 3 shows an EWORS syndromic data entry screen;
  • FIG.4 shows an EWORS syndromic data entry screen
  • FIG. 5 shows an EWORS syndromic data analysis screen
  • FIG. 6 shows an EWORS syndromic data analysis screen
  • FIG. 7 shows an EWORS syndromic data graph parameter screen
  • FIG. 8 shows an EWORS syndromic data graph screen
  • FIG. 9 shows an EWORS syndromic data map parameter screen
  • FIG. 10 shows an EWORS syndromic data cluster map screen
  • FIG. 11 shows a pictorial diagram of the EWORS system according to the present invention to explain the operation of the invention
  • FIG. 12 shows an EWORS data entry screen having an expanded list of signs and symptoms for EWORS site (hospital or other medical treatment facility) data collection purposes;
  • FIG. 13 shows an EWORS data enty screen shows an expanded list of signs and symptoms that will be reflected in additional analytical options for use in graphic interpretation
  • FIG. 14 shows an EWORS- AID screen that provides more detailed interpretation of analysis (based on signs and symptoms) at EWORS (hospital or other medical treatment facility) site and HOST locations, to reflect possible (presumptive-disease specific) working diagnoses, the lower portion of the screen lists, for analytical purposes, specific diseases of possible outbreak potential that correspond with signs/symptoms, reported either singularly or in combination;
  • FIG. 15 is a flowchart of an integrated process of outpatient admission at a medical treatment facility to data entry of the patient symptomatic/syndromic data from the local hospital site to the host site to trend analysis of the syndromic data to predict a suspected infectious disease outbreak;
  • FIG. 16 is a pictorial flowchart of an integrated process of outpatient admission at a medical treatment facility to data entry of the patient symptomatic/syndromic data from the local hospital site to the host site to trend analysis of the syndromic data to predict a suspected infectious disease outbreak;
  • FIG. 17 shows a representative EWORS patient record database.
  • Fig. 1 shows the early warning outbreak and response system (EWORS) 10.
  • EWORS 10 comprises a plurality of local hospital sites 12 which are disposed in predetermined locations.
  • a plurality of field hospital sites 14 may be associated with the local hospital sites 12 or they may be stand alone sites in highly remote areas.
  • a host site 16 is operatively connected to a plurality of local hospital sites 12 and a plurality of field hospital sites 14 via a communication medium 18.
  • the communications medium 18 could be modem, internet, telephone, mail, or wireless means.
  • the plurality of local hospital sites 12 each comprises an operatively connected local hospital computer 22, a local hospital entry device 24, and a local hospital monitor 26.
  • the plurality of field hospital sites 14 each comprises an operatively connected field hospital computer 28, a field hospital entry device 30, and a field hospital monitor.
  • the single host site 16 comprises an operatively connected host computer 34, a host entry device 36, and a host monitor 38.
  • Fig.2 shows the flow of syndromic data from a local hospital site 12, which may comprise a pediatric clinic 40, internal medicine clinic, and emergency room 44.
  • Syndromic data is data on a patient's signs or symptoms that can be used to determine a trend in such symptoms that would indicate an infectious disease outbreak.
  • the local hospital site 12 could comprise a plurality of different clinics for any medical purpose where syndromic data could be collected.
  • the arrow at 46 illustrates the syndromic data collected from any of the clinics of the local hospital Site 12 and is recorded on form containing a partial list of standardized syndromic systems represented by the block at 48.
  • the arrow at 50 depicts the input of the syndromic data to be displayed on the local hospital monitor 26 as directed by the local hospital computer program which has been installed in each local hospital computer 22 via communications medium 18 to the host computer 34 where screens are displayed on the host site monitor 38. More detail on the operation of this program will be discussed on in the "Statement of the Operation" Section.
  • the arrow at 52 depicts the flow of data through mailing of diskettes or other communication media 18 to a Local Health Authority of a state or foreign government, as a matter of comity.
  • Fig. 3 shows a syndromic data entry screen 54
  • Fig. 4 shows a syndromic data entry screen 56
  • Fig. 5 shows a syndromic data entry screen 58
  • Fig. 6 shows a syndromic data entry screen 60
  • Fig. 7 shows a syndromic data graph parameter screen 62
  • Fig. 8 shows a syndromic data graph screen 64
  • Fig. 9 shows a syndromic data map parameter screen 66
  • Fig. 10 shows a syndromic data map cluster screen 68 through which standardized syndromic data is entered, transferred, received, and analyzed for suspected trends indicating an infectious disease outbreak.
  • the syndromic data entry screen 54 of Fig. 3 is used to enter syndromic data by a user at Block 78 of Fig. 11.
  • This syndromic data is collected at block 76 of Fig. 11 via an EWORS patient form, which lists the standardized symptoms.
  • the syndromic data is entered at block 78 of Fig.11 into the local hospital computer 22 of Fig. 1.
  • the syndromic data is subsequently transferred at block 80 of Fig. 11 from a plurality of local sites 12 to the host site 16, both of Fig. 1 via communications medium 18.
  • the communications medium 18 may be modem, internet, telephone, or regular mail delivery.
  • the remote and mobile field hospital sites 14 are operatively connected to the host site 16 via communications medium 18 which maybe any of the above means or by hand-held wireless communication means.
  • the syndromic data retrieval screen 56 of Fig. 4 is used at the host site 16 to retrieve the data. Referring now to Figs. 4 and 11 concurrently, this retrieval of data occurs at Block 82 of Fig. 11.
  • the syndromic data analysis screen 58 of Fig. 5 is used to provide input as to how the data is to be treated and analyzed.
  • the observed parameters could include one or more standardized symptoms by age range and sex.
  • the syndromic data analysis screen 60 of Fig.6 is used to provide a range of time and the demographics over which the syndromic data is to be treated.
  • the syndromic data graph parameter screen 62 of Fig.7 sets the parameters of the syndromic data graph screen 64 of Fig. 8, which shows a 5-month trend for coughs and colds.
  • the data graph screen 64 depicts the male incidence of cases of coughs and colds as displayed by the red line on top. Females are depicted by the green line on the bottom of the graph.
  • the syndromic data map parameter screen 66 of Fig. 9 depicts the signs and symptoms and the age range which may be used to display data on the syndromic data cluster map screen 68, Fig. 10.
  • Screens 66 and 68 allow data to be analyzed and displayed by province and district and could be modified to indicate the region, county, or state of interest.
  • a rapid, graphic geographical map cluster can be created based upon syndromic data treated using any of the standard parameters of interest.
  • a cluster is an aggregation of cases in a given area over a particular period without regard to whether the number of cases is more than expected. This provides a useful tool in determining the frequency and distribution of symptoms and conditions, reported as syndromic data, which may constitute an outbreak of an infectious disease.
  • FIG. 12 shows an EWORS data entry screen having an expanded list of signs and symptoms for EWORS site (hospital or other medical treatment facility) data collection purposes;
  • FIG. 13 shows an EWORS data enty screen shows an expanded list of signs and symptoms that will be reflected in additional analytical options for use in graphic interpretation;
  • FIG. 14 shows an EWORS-AID screen that provides more detailed interpretation of analysis (based on signs and symptoms) at EWORS (hospital or other medical treatment facility) site and HOST locations, to reflect possible (presumptive-disease specific) working diagnoses, the lower portion of the screen lists, for analytical purposes, specific diseases of possible outbreak potential that correspond with signs/symptoms, reported either singularly or in combination;
  • FIG. 15 is a flowchart of an integrated process of outpatient admission at a medical treatment facility to data entry of the patient symptomatic/syndromic data from the local hospital site to the host site to trend analysis of the syndromic data to predict a suspected infectious disease outbreak;
  • FIG. 16 is a pictorial flowchart of an integrated process of outpatient admission at a medical treatment facility to data entry of the patient symptomatic/syndromic data from the local hospital site to the host site to trend analysis of the syndromic data to predict a suspected infectious disease outbreak;
  • FIG. 17 shows a representative EWORS patient record database.
  • the invention is a hospital- or medical treatment facility-based network of computerized linkages that provide surveillance for early detection of outbreaks of infectious diseases, by establishing trend information that distinguishes epidemic from endemic disease.
  • the invention further provides standardized information, for example, by using a standardized EWORS form, over time for trend analysis of infectious diseases.
  • the invention provides reliable data, as a care giver may not be adequately trained to provide an accurate medical diagnosis, while having sufficient training to provide an accurate medical description of a patient's symptoms.
  • the invention also provides for real-time data relay and early recognition of possible outbreaks.
  • Another significant feature of the invention is to provide for identification of outbreaks in both temporal and spatial clustering.
  • An additional feature of the invention is to provide for rational interpretation of data into meaningful presentations.
  • the invention collects standardized data for making area-specific and regional comparisons.
  • the invention is predicated on "same day" transfer of information from network hospitals to a central hub.
  • the invention may be used to employ a syndromic approach in conjunction with a working diagnosis, which allows for reliable analysis of aggregate data to determine appropriate response measures.
  • the invention relies on EWORS reporting to insure recognition of an incipient epidemic, by detecting similar signs and symptoms in the index and early cases associated with the same outbreak.
  • the invention has been described in regional or area-specific context. In fact, more than 150,000 case entries have resulted during two years of pilot implementation only in Indonesia.
  • An indication of the utility and effectiveness of the software is the translation of the original Indonesian into English, Vietnamese, and Laotian.
  • Use of the software has resulted in the recognition of five outbreak occurrences: two dengue outbreaks and two diarrheal outbreaks in Indonesia, as well as one possible febrile outbreak in Vietnam.
  • Sanglah Hospital, Bali, Indonesia a dengue outbreak was recognized early on, so the hospital could prepare the blood stocks in their blood bank in anticipation of the possiblitily of numerous patients in the worst medical condition. No death was found during the outbreak.
  • the EWORS invention was also validated by the recognition of an absence of cholera cases in association with flooding in Cambodia.
  • the invention may be used in refugee or disaster situations to stop the spread of infectious disease that typically occurs in high-density populations that lack adequate sanitation and medical care.
  • the invention may also be deployed as a biological and/or chemical defense monitoring and surveillance system for civilian or military populations.
  • the inventors specifically wish to point out that the description of "local computers" includes desktop, laptop, notebook, subnotebookand hand-held computers such Palm and Handspring personal data assistants.
  • the invention has been validated in a variety of settings. Obviously, many modifications and variations of the present invention are possible in light of the above teachings. It is therefore to be understood that, within the scope of the appended claims, the invention may be practiced otherwise than as specifically described.

Abstract

La présente invention concerne un système et un procédé informatiques permettant de réunir des données syndromiques, et d'établir des comparaisons locales et régionales dans l'analyse des tendances des données syndromiques, afin de cibler la reconnaissance de foyers présumés de maladies infectieuses. Le système présente une capacité en 'temps réel' assurant le transfert périodique des données syndromiques, par exemple, chaque jour, chaque semaine ou chaque mois, d'un ou de plusieurs sites locaux à un site hôte. L'analyse quotidienne des données syndromiques est utilisée pour détecter un foyer présumé de maladie infectieuse. On utilise une analyse plus détaillée pour confirmer le foyer présumé de la maladie infectieuse.
PCT/US2001/027044 2000-09-01 2001-08-31 Systeme de reconnaissance de foyers presumes de maladies infectieuses WO2002019246A2 (fr)

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Application Number Priority Date Filing Date Title
AU2001288551A AU2001288551A1 (en) 2000-09-01 2001-08-31 Early warning outbreak and recognition system

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US22928600P 2000-09-01 2000-09-01
US60/229,286 2000-09-01

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Cited By (14)

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WO2004030512A2 (fr) * 2002-08-19 2004-04-15 Stout Solutions, Llc. Systeme de bio-surveillance
EP1488355A1 (fr) * 2002-03-26 2004-12-22 Ibex Healthdata Systems Inc. Systeme et methode pour le depistage d'evenements lies a la sante
US7725565B2 (en) 2008-02-25 2010-05-25 Georgetown University System and method for detecting, collecting, analyzing, and communicating event related information
US8862448B2 (en) 2009-10-19 2014-10-14 Theranos, Inc. Integrated health data capture and analysis system
US8881040B2 (en) 2008-08-28 2014-11-04 Georgetown University System and method for detecting, collecting, analyzing, and communicating event-related information
US9529974B2 (en) 2008-02-25 2016-12-27 Georgetown University System and method for detecting, collecting, analyzing, and communicating event-related information
US10318875B2 (en) 2015-12-07 2019-06-11 International Business Machines Corporation Disease prediction and prevention using crowdsourced reports of environmental conditions
US10503347B2 (en) 2008-02-25 2019-12-10 Georgetown University System and method for detecting, collecting, analyzing, and communicating event-related information
CN111403048A (zh) * 2020-03-18 2020-07-10 唐宓 一种未知传染病预警及追溯方法
CN112115580A (zh) * 2020-08-12 2020-12-22 科技谷（厦门）信息技术有限公司 一种基于大数据的新发重大传染病监测、预警及应对系统
CN112117010A (zh) * 2020-07-13 2020-12-22 北京大瑞集思技术有限公司 一种传染病智能预警系统及管理平台
WO2021168796A1 (fr) * 2020-02-28 2021-09-02 京东方科技集团股份有限公司 Système de gestion d'événements publics
CN115394455A (zh) * 2022-05-31 2022-11-25 北京乾图科技有限公司 基于空间聚类离散格网的传染病时空扩散预测方法及装置
CN115910374A (zh) * 2022-11-09 2023-04-04 杭州杏林信息科技有限公司 一种医院感染性疾病聚集或爆发时间预警方法及介质

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Cited By (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1488355A1 (fr) * 2002-03-26 2004-12-22 Ibex Healthdata Systems Inc. Systeme et methode pour le depistage d'evenements lies a la sante
EP1488355A4 (fr) * 2002-03-26 2007-10-10 Ibex Healthdata Systems Inc Systeme et methode pour le depistage d'evenements lies a la sante
WO2004030512A2 (fr) * 2002-08-19 2004-04-15 Stout Solutions, Llc. Systeme de bio-surveillance
WO2004030512A3 (fr) * 2002-08-19 2004-12-09 Stout Solutions Llc Systeme de bio-surveillance
US10055502B2 (en) 2008-02-25 2018-08-21 Georgetown University System and method for detecting, collecting, analyzing, and communicating event related information
US9489495B2 (en) 2008-02-25 2016-11-08 Georgetown University System and method for detecting, collecting, analyzing, and communicating event-related information
US9529974B2 (en) 2008-02-25 2016-12-27 Georgetown University System and method for detecting, collecting, analyzing, and communicating event-related information
US7725565B2 (en) 2008-02-25 2010-05-25 Georgetown University System and method for detecting, collecting, analyzing, and communicating event related information
US10503347B2 (en) 2008-02-25 2019-12-10 Georgetown University System and method for detecting, collecting, analyzing, and communicating event-related information
US8881040B2 (en) 2008-08-28 2014-11-04 Georgetown University System and method for detecting, collecting, analyzing, and communicating event-related information
US8862448B2 (en) 2009-10-19 2014-10-14 Theranos, Inc. Integrated health data capture and analysis system
US11139084B2 (en) 2009-10-19 2021-10-05 Labrador Diagnostics Llc Integrated health data capture and analysis system
US11195624B2 (en) 2009-10-19 2021-12-07 Labrador Diagnostics Llc Integrated health data capture and analysis system
US11158429B2 (en) 2009-10-19 2021-10-26 Labrador Diagnostics Llc Integrated health data capture and analysis system
US10318875B2 (en) 2015-12-07 2019-06-11 International Business Machines Corporation Disease prediction and prevention using crowdsourced reports of environmental conditions
WO2021168796A1 (fr) * 2020-02-28 2021-09-02 京东方科技集团股份有限公司 Système de gestion d'événements publics
EP4113400A4 (fr) * 2020-02-28 2023-04-19 BOE Technology Group Co., Ltd. Système de gestion d'événements publics
CN111403048A (zh) * 2020-03-18 2020-07-10 唐宓 一种未知传染病预警及追溯方法
CN112117010A (zh) * 2020-07-13 2020-12-22 北京大瑞集思技术有限公司 一种传染病智能预警系统及管理平台
CN112115580A (zh) * 2020-08-12 2020-12-22 科技谷（厦门）信息技术有限公司 一种基于大数据的新发重大传染病监测、预警及应对系统
CN115394455A (zh) * 2022-05-31 2022-11-25 北京乾图科技有限公司 基于空间聚类离散格网的传染病时空扩散预测方法及装置
CN115910374A (zh) * 2022-11-09 2023-04-04 杭州杏林信息科技有限公司 一种医院感染性疾病聚集或爆发时间预警方法及介质

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