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  • RealTimeBiosurveillancePilotinIndiaandSriLanka

    1NuwanWaidyanatha,2GanesanM.,3PubudiniWeerakoon,4GordonGow,5MaheshkumarSabhnani,5ArturDubrawski

    1LIRNEasia,SriLanka,email:[email protected]'sRuralTechnologyandBusiness

    Incubator,India,email:[email protected],SriLanka,email:

    [email protected],Canada,email:[email protected]'sAutonLab,USA,email:[email protected],

    [email protected]

    ABSTRACT

    Thelatterpartsof2007andearlymonthsof2008witnessedanalarmingnumberofdeathsduetoaLeptospriosisoutbreakinSriLanka[Agampodietal,2008].Thisdiseasepresentswithflulikesymptoms, and it is not easy to identify because other more commondiseases with similarsymptomstendtoemergenaturallyduringthemonsoonseasons.Thescatterednumberofpatientcomplaints went unnoticed, during the rainy season, until a few deaths were reported byindividual hospitals. An unusual number of flulike symptoms concentrated in particulargeographicareas(NorthCentralandNorthWesternProvinceinSriLanka)couldhavesignalledtheepidemiologistsofanabnormalevent.ThepresentdaypaperbaseddiseasesurveillanceandnotificationsystemsinSriLankaandIndia[PrashantandWaidyanatha,2009],confinedtoasetof notifiable diseases, often require 1530 days to communicate data and for the centralEpidemiologyUnit toprocess it. This latencydoesnotallowfor timelydetectionofdiseaseoutbreaks,anditlimitstheabilityofthehealthsystemtoeffectivelyrespondandmitigatetheirconsequences.TheRealTimeBiosurveillanceProgram(RTBP)isapilotaimingtointroducemoderntechnologytohealthdepartmentsinTamilNadu,India,andSriLankatocomplementtheexisting disease surveillance and notification systems. The processes involve digitizing allclinicalhealthrecordsandanalysingtheminnearrealtimetodetectunusualeventstoforewarnhealthworkersbeforethediseasesreachepidemicstates.Healthrecordsfromhealthfacilities,namelythepatientcasedisease,syndrome,anddemographicinformation,arecollectedthroughthemHealthSurveymobilephoneapplication[KannanandSheebha,2009]andfedintotheTCubeWebInterface[Rayetal,2008],whichisabrowserbasedsoftwaretoolthatusestheTCubedatastructureforfastretrievalanddisplayoflargescalemultivariatetimeseriesandspatialinformation. Interfaceallowstheusertoexecutecomplexqueriesquicklyandtorunvarioustypesofcomprehensivestatisticaltestsontheloadeddata[Sabhnanietal,2005,Dubrawskietal,2007].TheSahanaMessaging/AlertingModuleisusedtodisseminatedetectedadverseeventstotargeted health officials and health workers. The SahanaAlerting module adopts the globalcontent standard: Common Alerting Protocol (CAP) for structuring the messages that aretransportedviaSMS,Email,andWeb[GowandWaidyanatha,2009].EvaluationoftheRTBP

    mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]

  • involvesareplicationstudyandparallelcohortstudy.Thispaperdiscussesthetechnologiesusedinthepilotandtheinitialfindingsinrelationtousabilityofthesystem.TheRTBPresearchismadepossiblethroughagrantreceivedfromtheInternationalDevelopmentResearchCentreofCanada(105130).

    INTRODUCTION

    TheRealTimeBiosurveillanceProgram(RTBP)isapilotprojectaimingtoanswerthequestionwhethersoftwareprogramsthatdetecteventsinhealthsymbolicandcategoricaldatasetsandmobilephonesthatcollecthealthdataandreceivehealthalertsareabletopredictandprevent diseaseoutbreaksinnearrealtime.

    ThesuccessoftheintroducedICTdependsnotonlyonthequalityofthetechnologyartifactsbutalsoontheactors(i.e.thepeopleandtheorganizationalenvironment)[Ammenwerthetal,2004].Hence, there are three main components that the RTBP researches are investigating: theworkabilityofthetechnologyinthegivenenvironments(whetherthetechnologycanactuallyliveuptotheexpectations),understandthesetofnewlyintroducedprocessesthatimpactthehumanelement(willitaidthehealthcareworkerswiththeprotocolsasitwasproventobethecaseintheUgandastudy[DeRenzietal, 2008]),andthepolicyimplications(arethehealthworkers and epidemiological units ready to accept the changes; i.e. business processimprovementsorreengineering).

    RTBP provides the ability to detect and monitor a wide variety of health events, involvingmultiple kinds of diseases, including communicable and noncommunicable, as well asreportable and nonreportable ones, following WHOs general recommendations for diseasesurveillancesystems[WHO,2004].

    RESEARCHDESIGN

    ImplementationofRTBPessentiallymeanstomakeavailabletherightinformationattherightplace,attherighttimeandinthecorrectform[GanapathyandRavindra,2008].Inthatrespect,thissectiondiscussestheinformationflowthatcompletesacycle(steps18,Figure1)whereinformationprovidedbyhealthworkersisprocessedandresultingdecisionsarecommunicatedbacktothehealthworkers.

    Step 1 Health workers record patient information in various registries such as outpatientregistry,inwardregistry,morbidityreport,etc.Oncepoliciesareinplaceforawiderscaledeployment, the paper registries can be obsolete and same data can be supplied viaelectronicmeans;i.e.skipdirectlystep2.

    Step 2 Patient complained symptoms, healthcare provider identified signs, and diagnoseddiseasealongwithpatientsgender,age,andpointofcarelocation(i.e.hospital,clinic,orvillagename)areenteredintothemHealthSurveymobileapplication.

  • Step3InformationissenttothecentraldatabasethroughtheGSMcellularnetworkovertheGPRStransportlayer.Intheeventthesignalisabsent,therecordisstoredintheofflinestorageinthemobileRMS(RecordManagementSystem)untilconnectivityisestablishedanddataistransferred.

    Step4Periodically(ontheaverageonceaday),EpidemiologistanalyzetheinformationusingtheTCube,timeseriesandspatialscan,webinterfacesoftware.

    Step5IftheEpidemiologistdetectsanadverseevent,thenadecisionismadewhetherornottointervene.

    Step6Eventsofinterestthatrequireinterventionandpreventionorareworthyofnotifyingaredisseminated to targeted health workers, in the formof a CAPmessage, through theSahanaAlertingModule,bytheauthorizedhealthofficials.

    Step7AtoneddownversionoftheCAPmessagesthatcanfitinaSMSaretransmittedviaGSMcellularnetworkstothehealthworkermobilephones.ThecompleteCAPmessageispublishedonthewebforhealthworkerstoaccessthroughWAP.

    Step8Basedonthereceivedalertmessage,thehealthworkers,ifnecessary,activaterelevantresponseplans.

    Figure1:RTBPactors,technologies,processesandinformationflow

  • TECHOLOGIES

    mHealthSurveymobileapplication

    The main menu of the mHealthSurvey comprises: download list, profile, location, offlinesurvey,andhealthsurvey,showninFigure2(a).Afterinstallingtheapplicationthefirststepis

    Figure2:mHealthSurveyScreens(a)mainmenu(b)profile(c)location(d)patient recordpage1(e)patientrecordpage2

  • executingthe downloadlist function,whichwillretrievethelookupvaluesfromthedatabasesuchasthelistofdisease,sign,symptoms,agegroups,gendernames,locationtypes,andhealthworkertypes.Thisisusuallyaonetimestepbuttheusersareencouragedtoexecutethisfunctionfromtimetotimetoupdatethelistofdisease,signs,andsymptomsontheirmobilephonestoreflectthechangesintheglobaldatabase.Thereafter,theusermustconfiguretheapplicationwiththeirpreferencessuchastheirprofile,Figure2(b),andworkinglocations,Figure2(c).mHealthSurveyallowsformultipleprofilespermittingformorethanonehealthworkertosharethesamemobilephone.Afterinstallationandconfigurationtheuserisreadytobeginsendingdatathroughthe healthsurvey form(Figure2(d)and2(e)).Forconfidentiality,theprojectsinitialdesignhadnot incorporated thepatients name;however, theTamil Naduhealth departmentinsistedthatthesefieldsbeincluded.However,thesevaluesareoptional.IntheSriLankacasethesefieldsaredisabled(i.e.hidden)astheyarenotarequirement.

    AutonLabTCubeWebInterface

    TCubeWebInterface(TCWI)isagenerictooltovisualizeandmanipulatelargescalemultivariatetemporalandspatiotemporaldatasetscommonlyencounteredinpublichealthapplications[Rayetal,2008].Theinterfaceallowstheusertoexecutecomplexqueriesquicklyandtorunvarioustypesofstatisticaltestsontheloadeddata.Uponuploadingtheworkingdataset,theusercanmanipulateandvisualizedatathroughtheTimeSeries,Map,andPivotTablepanels.

    Theusermaychoosetoapplyoneoftheavailablestatisticalmodellingandanomalydetectiontechniques.Thelistofchoicesincludesmovingaverage,movingsum,cumulativesum,temporalscan,changescan,lineartrend,peakanalysisandrangeanalysis.Theuserscaninteractivelymanipulate,navigate,summarizeandvisualizedataatinteractivespeeds.Thatsupportsfocusedinvestigations,drilldownsaswellassummarizingandreportingoperations.TheusersmaychoosetosimplyexecuteaMassiveScreeningprocedure,whichperformsanautomaticandcomprehensivesearchforanomalouspatternsacrosslargenumberofqueriesspanningmultipledimensionsofdata.Thisfunctioncouldbeinvokedinteractivelybytheuser,oritcouldbescheduledtoexecuteperiodicallytogenerateasetofalerts.Thealertsaresortedaccordingtostatisticalsignificanceofthecorrespondinganomaliesfoundindata,andtheycanbeinteractivelyreviewedbytheEpidemiologistsforthefactualconfirmationoftheirpracticalimportance.TCWIsupportstheseeffortsbyallowingfocusingattentiononthemostsurprisingpatternsincurrentdataandbyprovidingtheabilitytoquicklydrilldownorrollupthedataforfurtherexplanations.

    ThecoreoftheTCWIMassiveScreeningprocedureistheTemporalScanbivariateanomalydetectionalgorithm[Dubrawski,2009].ItleveragestheefficiencyoftheTCubedatastructuretoperformamassivenumberoftestsofstatisticalhypothesesinordertofindthemostsignificantlyanomalouspatternsincurrentdata.TheTCWIalsoimplementsMultivariateBayesianSpatialScanalgorithm[NeillandCooper,2009],thatcomplementstheanalysesbytestingthespatialaswellastemporalcorrelationsbetweenhealthevents.Thisalgorithmcomputestheoverall

  • probabilityofadiseaseo