integrated kms@ews of conceptual implementation model for clinical dengue fever environment

8/12/2019 INTEGRATED KMS@EWS OF CONCEPTUAL IMPLEMENTATION MODEL FOR CLINICAL DENGUE FEVER ENVIRONMENT

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Integrated KMS@EWS of Conceptual Implementation Model for

Clinical Dengue Fever Environment

Norzaliha Mohamad Noor, Rusli Abdullah, Mohd Hasan SelamatFaculty of Computer Science and Information Technology,

Universiti Putra Malaysia, 43400 Serdang, [email protected],{rusli ,hasan}@fsktm.upm.edu.my

ABSTRACT

Early warning system (EWS) is atechnology to mitigate risk is used todisseminate timely information. Then

knowledge management system (KMS) isused to support for decision facilitation willintegrate with EWS to disseminate timelyinformation with proactive early warning.Issues on timeliness for timely reporting anddecision facilitation are regarded as mainchallenge for mitigation of risk. Therefore inthis paper, we suggest the model ofintegration between KMS and EWS knownas KMS@EWS as a solution to supportearly warning for timely reporting and toguide on decision facilitation. The

integration model is to combine theknowledge management (KM) processes,activities and technologies with the EWSfunctionalities. The proposed model is basedon empirical study by using literatures onEWS and KMS. In which we synthesize theanalysis and findings of both EWS andKMS for the integration. We propose theimplementation model in clinical diagnostic(CD) environment of dengue fever (DF)manifestation. This model is intended to

provide early warning when any

abnormalities or peculiar pattern of DF andsymptoms arise and detected during theinteraction between physicians and patientsin the CD environment. Thus, this paperattempts to integrate relevant enabling KMtechnologies and processes with EWScomponents and functionalities into anenvironment that would support activitiesfor early warning thru organizational

knowledge creation, use and managementfor timely reporting and detection by

providing decision facilitation and initiateearly warning of DF during CD processes.

KEYWORDS

Early warning system, Knowledgemanagement, Knowledge managementsystem, Dengue fever, Clinical diagnostic.

1 INTRODUCTION

EWS is a technology to mitigate risk isused to disseminate timely informationcan be integrated with KM processes,activities and technologies. In which KM

is regarded as confluence of processes,activities and techniques to facilitate thecreation, codification, dissemination andapplication of knowledge that can beintegrated with EWS functionalities toenable the knowledge flow in CDenvironments. CD environment whichcomprises activities for interaction

between physician and patient to obtaina diagnosis of the disease and to selecttherapy [1] is used for implementation ofintegrated model between KMS andEWS known as KMS@EWS. The ideaof using CD environment for theimplementation is due to the activitiesinvolved during CD process namelyhistory taking (HT), physicalexamination (PE) and investigation (IV)can provide early warning of disease

International Journal on New Computer Architectures and Their Applications (IJNCAA) 1(3): 743-756The Society of Digital Information and Wireless Communications, 2011 (ISSN: 2220-9085)

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outbreak. In order to realize theimplementation, DF manifestation wereopt to address the disease outbreak.

Disease outbreaks can be extremelyserious threats to the public health that

can cause a sudden disaster. Bravata et al(2004) [2] emphasized the significant ofearly warning in disease outbreak for

preparation, tracking and monitoringoutbreak. Extensive research and studyhas been carried out to provide effectivedetection, controlling and monitoring ofdisease outbreak, but still timeliness andvalidity of knowledge are crucial factorsas it will impact the decision forresponse, forecasting and preparedness

[3] [4] [5]. Madoff (2004) [6] andBrownstein (2007) [7] highlightedtimeliness as a crucial factor in

preventing the spreading of diseases.Simultaneously Choo (2009) [8] lookedat the validity of knowledge to determinethe effectiveness of early warning.Several research studies have been madeon EWS to detect disease outbreakrapidly [9] [10] [11]. However, issues

providing timely detection and validity

of knowledge are still regarded as mainconcern as it can influence the decisionfacilitation regarding the prevention and

preparedness pertaining outbreak [3][12].

Therefore, we propose a model ofKMS@EWS that can support themanaging of data and information fortimely reporting and detection by

providing decision facilitation and toinitiate early warning during the CD

process. Since KMS is an IT basedsystem to support activities forknowledge creation, codification,dissemination and application, thenEWS as a technology to mitigate risk isused to disseminate timely information.In relation to this, we integrate KMS

processes and technologies with EWS

functionalities to proactively providetimely reporting, detection and responseof decision facilitation couple withknowledge validity. By providing earlywarning during CD process, medical

practitioners and hospitalsadministration can be notified of theoutbreaks and potential outbreaksituation and thus can acceleratedecision facilitation with appropriateknowledge and implementation ofactions to deal with the outbreaks.

This paper is organized as follows;Section 2 is a literature review on EWScomponents and functionalities; KMS

processes, technologies and techniques;

overview of CD processes and DFmanifestation. Section 3 discussedmethodology used to derive the model ofKMS@EWS. Subsequently, Section 4will explain the integration model in CDenvironment of DF. Finally Section 5 isthe conclusion and discussion on thedirection and future works of the study.

2 LITERATURE REVIEW

2.1 Early Warning System

EWS as a technology to mitigate risk isused to disseminate timely informationin multi-disciplinary area [13]. Austin(2004) [14] defined EWS as a mean toobtain knowledge and to use thatknowledge to assist in the mitigation ofconflict. In relation, he also emphasizedthat response to any conflict situation

require knowledge to facilitate acommon awareness regarding problemsor risks and thus accelerate decisionmaking with appropriate implementationaction to deals with the risks. Whilefrom the healthcare perspective, Ebi andSchmier (2005) [15] identified the maincomponents of EWS should include


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identification and forecasting of theevent, prediction of the possible healthoutcomes, an effective and timelyresponse plan and an ongoing evaluationof the systems and components. To be

effective, EWS implementation shouldcomprises four main components namelyi) risk knowledge (RK), ii) monitoringand warning service (M&WS), iii)disseminate and communication (D&C)and iv) response capability (RC) [16].The relationship of each component isillustrated in Figure1.

Fig. 1. Relationship of EWS Four Main

Components.

Risk knowledge which is known as riskassessment is related to knowledgeidentification and acquisition, analysisstorage, detection and manipulation. Insecond component, the monitoring andwarning service deals with technicalcapacity to track and forecast that can

provide timely estimation of the potential risk faced by the communities.The dissemination and communicationmeans delivering, sharing and distributewarning messages to alert thecommunities with a reliable, syntheticand simple message for preparedness ofaction. Finally, response capabilityinvolves coordination, good governancefor timely and appropriate action plan byauthorities. These components can be

further classified into four main EWSfunctionalities as shown in Table 1.

Table 1. EWS Functionalities

There are many research studies have been made on EWS that are associatedto natural hazard, aquaculture anddisease outbreak. For instance, disasterssuch as the Indian Ocean tsunami in2004 and Katrina hurricane in 2005,highlighted inadequacies in earlywarning process towards disaster

mitigation lead to the development ofalert system known as GEAS [5].Moreover, the risk of misdiagnosis,incorrectly treatment or over-treatmentthat exists after disease outbreak is amotivational factor to develop aknowledge-based EWS for fish disease[17]. While TeCoMed is the EWStelecommunication on medical eventsdevelopment was inspired due to theinadequacies of information system to

confront the healthcare worker timely oncommunicable disease [18].For the purpose of this study, wereviewed and analyzed several previousresearch studies pertaining diseaseoutbreaks which adopted EWS approachand functionalities. There are numerousresearch studies that can be referred forsuccessfully and effectively implementthe EWS for disease outbreak. Hence,we came out with seven types of

different research studies which provideearly warning with KM activities toinvoke or initiate early warning. Table 2summarizes the related study with KMactivities and Table 3 aggregate theliterature studies according to EWSfunctionalities namely detection,


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prediction, warning and response toaddress the significant of EWS.

Table 2. EWS with KM activities from theliterature

Table 3. EWS functionalities address by

literature studies

2.2 Knowledge Management System

Before pursue into KMS perspective,there is a need to understand thedistinction between data, informationand knowledge in the context of thisstudy. It has been pointed out by otherresearchers that data, information andknowledge are not the same and isdefined differently. Data is referring toraw numbers and facts, information is

processed data and knowledge isinformation made actionable.

While, KM is viewed as a process ofturning data into information andforming information into knowledge that

can lead to decision making. In whichthis process is subdivided into creatinginternal knowledge, acquiring externalknowledge, storing knowledge as well asupdating the knowledge and sharingknowledge internally and externally.Then KMS is referring to a class ofinformation systems applied to manageorganizational knowledge and to supportthe organizational processes ofknowledge creation, storage, transfer and

application [24]. There are four commonactivities of KM which are cyclic process namely knowledge creation oracquisition, knowledge codification orstoring, knowledge dissemination orsharing and knowledge application.Table 4 depicted the example of KMcycle from the related studies which are

based on four common activities asmentioned earlier [25] [26] [27] [28][29] [30]

Table 4 KM Processes from literature studies

From the technical perspective, KMcan be viewed in terms of how the KM

processes can be applied using IT as atool to facilitate knowledge sharingcollaboratively. KM tools is defined astechnologies to support and facilitateknowledge sharing of communities forthe performance of application, activitiesor actions such as knowledge generation,knowledge codification and knowledgetransfer [31]. Meanwhile, Alavi (2001)


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[29] listed few supporting technologiesfor KM processes such as data mining(DM), knowledge repositories,databases, discussion forums, knowledgedirectories, expert system (ES) and

workflow systems. Then Liao (2003)[32] classified KM technologies andapplication into six categories namelyknowledge-based system (KBS), datamining, information communicationtechnology (ICT), artificial intelligent(AI), database technology and finallymodeling.

2.3 Overview of Clinical DiagnosticEnvironment

Generally CD environment deals withinteraction between patient and

physician involves three main processesknown as history taking, physicalexamination, and investigation [33] [34][1] [35]. History taking (HT) is theinitial process in CD where theconversation between patient and

physician is captured to obtain generalidea of the patients personality, the kind

of disease and the degree of severity.HT process is important in obtaining aseries of information from patient indetermining the etiology or cause of a

patients illness. Then, the physicalexamination (PE) is to identify the

physical sign of the disease. PE processrequires physician studies or examinescarefully a patients body to determinethe presence or absence of physical

problems. Hence, in this process, skilland experience of the physician iscrucial in eliciting sign of disease.Finally, investigation (IV) is to further

perform a laboratory test or screeningtest to solve clinical problems and tocomplement the history taking and

physical examination.

CD process is a face-to-facecommunication and observation between

patients and physicians in obtaininginformation for diagnosis and treatment.CD process is knowledge driven and

depends heavily on the medicalknowledge, intuition, expertise and judgment to diagnose or prognosis andto determine appropriate treatment. Datais collected during a HT, andinformation is obtained during the PE.Meanwhile, IV by laboratory orscreening test will also provide data andinformation for analysis and comes to aconclusion. Therefore, a CDenvironment can be used as a platform to

facilitate EWS because each of the CD process can be used to initiate earlywarning for disease outbreak. Figure 2illustrate the process flow of CDenvironment.

Fig. 2. CD Environment Process Flow

2.4 Overview of Dengue Fever

Dengue is an infectious disease,transmitted by Aedes mosquito that can

cause high rates of morbidity andmortality. This infectious disease cancauses a severe flu-like illness known asDF, and sometimes a potentially lethalcomplication called haemorrhagic fever(DHF). Studies had shown few factorsthat can contribute to the spread of DFand DHF among the communities. Such


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factors include demographic and societychanges that is closely related tosubstandard housing, crowding, anddeterioration in water, sewer, and wastemanagement system have created ideal

conditions for increased transmission ofmosquito-borne disease in tropical urbancenters. Additionally, lack of effectivemosquito control in areas where dengueis endemic is also one of the factors forincrease of the DF or DHF cases [36].Specifically during the fogging orspraying with insecticides to kill adultmosquitoes required proper method.

DF is an acute febrile viral diseasewith frequently presenting of headaches,

bone or joint and muscular pains, rash,nausea and vomiting. While, DHF isdefined as an acute febrile illness withminor or major bleeding,thrombocytopenia, and evidence of anincreased vascular permeability result inloss of plasma from the vascularcompartment. When plasma loss

becomes critical, it may result in Dengueshock syndrome (DSS) which may causedeath. Figure 3 adopting from Mairuhu

et al (2004) [37] depicted thesymptomatic dengue virus infection.Accurate and efficient diagnosis ofdengue is important for clinical care,surveillance support, pathogenesisstudies, and vaccine research. Moreover,the diagnosis is also significant for caseconfirmation of DF, DHF and DSS [38].Hence, early detection and managementof DF is essential to prevent death. Inrelation to this, we study the clinical

manifestation of DF as a sample diseaseoutbreak use for integration system ofKMS@EWS in CD environment.Whereby, all the dengue symptoms can

be obtain during the CD processes whichinclude the HT, PE or IV. At each of the

processes, early warning can be initiatedwhen one or all the symptoms exist.

Fig. 3. Knowledge Map of Dengue FeverManifestation

(Adopted source from Mairuhu et al (2004))

3 RESEARCH METHODOLOGY

For this study, we are currently performing an initial study to proposethe model of the integration betweenKMS and EWS known as [email protected] conduct a literature reviews (LR)that collect and understand the existingknowledge or information about the titleto research. Compile and analyzerelated topic to learn from othersknowledge, showing the paths of

previous research and how the study can be related to it. The reviews and analysisare on academic journals, articles, booksand information search on tools,technologies and techniques used thatrelate to the research. Based on the seventypes of different research studies fromSection 2.1, we segregated into two

processes in order to map and combine between KMS and EWS. Firstly, wemapped the EWS four key componentsto KM processes. The mapping is toidentify appropriate matching of KM

processes and technologies to EWS fourkey components. Then, the second

process is to identify critical function ofEWS to be combined into KM processesand activities. Thus, the results from

both processes will be used to construct


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the framework and model [email protected] LR is divided into four main stepsas illustrated in Figure 4. Step 1 is theframework construction which is the

synthesizing between the reviews andanalysis from EWS, KMS, CD processesand DF manifestation literature, articlesand books. This step is the initial steptowards the framework development.We adapt Bose KM cycle to complementthe KMS@EWS cycle for theintegration. Next, Step 2 is the modelformulation which obtained informationfrom the reviews and analysis of generalinformation about KM, EWS, CD

processes and DF. In this step, definitionand theories of EWS, KMS, and CDenvironment are analyzed and seek forcommon or identical functionalities

between KM and EWS. In order to getan overview of the DF, we studied DFmanifestation. Analysis on CDenvironment is to get an overview of CD

process workflow in order to use as a platform for model implementation.Besides the definition, we also analyze

the technologies and techniques used orrequired for the application of KM andEWS. We looked and identified thetechnical perspective requirement interms of knowledge acquiring,codification and dissemination for theintegration between KM and EWS.Then, Step 3 is the development modelof KMS@EWS for the CD environment.For the model development, weidentified the integration components

and provide its functionalities based onthe EWS framework reviewed earlier.Finally in step 4, we synthesize and mapthe analysis and findings of KMS andEWS to model the integration. We

perform empirical analysis on the EWSfunctionalities in order to evaluate andrank the EWS components requirements.

Then, we derived a model of theintegration between KMS and EWSknown as KMS@EWS for clinicaldiagnostics environment.

Literature Review

Model Formulation

Model Development

Review and Analyze articles,books, journals, publication andsystem

Identify technical integration foracquisition, codification anddissemination

Combined KM processes,technologies into EWScomponents

Step 1

Step 2

- KM, KMS- EWS- CD processes- DF manifestation

Preliminary ResultsEmpirical analysis on thefunctionalities and evaluate EWScomponents requirement

Step 3

Framework DevelopmentMapping and Combine KMSprocesses and technologies withEWS components andfunctionalities.

Step 4

Fig. 4. Research Methodology DesignFramework

4 A MODEL OF KMS AND EWSFOR CD ENVIRONMENT OF DF

The concept of KM has been stronglysupported as a process for acquiring,organizing and dissemination knowledgein order to promote effectiveness andefficiency [24]. Due to this concept, thisstudy attempt to integrate the KM

processes and technologies with EWSfour main components andfunctionalities. Therefore KM is asolution chosen to address the principles

of building integrated model of KMSand EWS in CD process to provide proactive early warning for decisionfacilitation to react and respond on theoutbreak. KMS@EWS will provideearly warning when any abnormalities or

peculiar pattern of disease andsymptoms arise and detected during CD


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process of DF. In which this system seekto provide proactive early warning of DFsymptom obtain from patients visit toclinic or hospital for treatment.Moreover, this also can assist physician

to make right decision pertaining thediagnosis and treatment.

4.1 EWS and KMS ConceptualIntegrated Proposal

KM deals with how best to leverageknowledge involves the strategies and

processes for identifying, capturing,structuring, sharing and applyingknowledge in order to promote

effectiveness and efficiency [39] [40].While, EWS is a process of gathering,sharing and analyzing information toidentify a threat or hazard timely andsufficiently in advance for preventiveaction to be initiated [14] [5]. Hence,KM processes and tools can helpstrengthen the EWS to facilitate theacquisition, codification anddissemination of knowledge in order toidentify and forecast the event,

prediction of possible outcomes andtimely reporting on the risks forimmediate response. Derived from theISDR guidelines, a complete andeffective development of EWS shouldinclude four main interactingcomponents as mention in Section 2.1.The purpose of these components can becombined into KM processes andtechnologies to provide a KMSenvironment as depicted in Figure 5.We propose the KMS environment withthe concept for knowledge sharingsystem organize and distributeknowledge.

RISKKNOWLEDGE

MONITORING&WARNING

SERVICE

DISSEMINATION&COMMUNICATION

RESPONSECAPABILITY

Data collection

OUTPUT

EWS

KMS Environment

(Knowledge Acquisition)

(Knowledge Dissemination)

Visualization

Awareness

Education

USER1

USER 2

(Knowledge Codification)Repositories

(Knowledge Application)

Reporting

Internalization

Fig. 5. EWS in KMS EnvironmentConceptual Proposal

4.2 Expansion of Conceptual

Implementation FrameworkDevelopment

Both EWS and CD processes areknowledge driven, where EWS requiresknowledge in order to notify and initiatewarning. While, CD processes dealswith interaction between patients and

physician requires communication andknowledge in order to identifysymptoms for proper and right treatment.

So KMS can support activities for bothEWS and CD processes to initiate earlywarning and to facilitate decisionmaking by providing capabilities foridentifying, capturing, structuring,sharing and applying knowledge. A welldesigned KMS@EWS shall provide

physician a clinical information andknowledge where, when, and how

pertaining the disease. Further, it alsocan help to report any occurrence of

disease timely by early identifying anddetecting at any level of CD processes.Furthermore, this framework willindicates the critical KM activities withEWS components and functionalities inCD processes using IT technologies tosupport the integration.


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A KMS design framework should

integrate business processes and theneeded IT with the related function tofacilitate the KMS design [24] [30].KMS@EWS is an IT based system

developed to enhance the knowledgecreation, codification, sharing andapplication to facilitate decision andinitiate early warning. Based on thereview and analysis of EWS, KMS, CD

process and DF manifestation, wecombine and match the critical KM

processes, technical functions andenabling IT with EWS components andfunctionalities to support the CD

processes. Table 5 summarizes the

matching results. We synthesize andcombine the analysis reviews fromSection 2 for the frameworkdevelopment as shown in Table 5.

Table 5. A framework using enabling ITtechnologies to support integration of

KMS@EWS in CD processes

4.3 Conceptual ImplementationSystem

Based on LR in Section 2 on KMS processes and technologies jointly with

EWS components and functionalitiesand CD processes, we proposed animplementation integrated model ofKMS@EWS in CD processes asdepicted in Figure 6. KMS@EWS will

generate alert at every stage of CD process. Each of the alerts will indicatethe severity of the risks. Figure 7illustrate a conceptual model ofKMS@EWS.

Fig. 6. Implementation proposed model ofKMS@EWS in CD processes

Fig. 7. Conceptual model of KMS@EWSArchitecture

From Figure 7, the input or source ofdata is obtained from patients andmedical practitioner. First component ofKMS@EWS is knowledge creationwhich is map to risk knowledge plays


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important function for data acquisition,analysis, storage and manipulation. TheCD process that relate to this componentis HT, PE and IV. Second component inKMS@EWS deals with continuous

monitoring to generate warnings timelyis known as knowledge codification.This component is to supportfunctionalities for identification anddetection; prediction and forecasting;warning and finally response withactivities for categorize, indexing,maintaining and retrieving information.This component comprises databasesand knowledge repositories. Thirdcomponent known as knowledge

dissemination is related to disseminateand communication deals withfunctionalities to visualize, distribute,display, delivering and transferinformation for notification and alerting.Finally the fourth component isknowledge application is link toresponse capability with functionalitiesfor decision facilitation and earlywarning capability. In conjunction,KMS@EWS is looked as a response

capability for collaboration to promotegood coordination and be used as aneducation platform and finally to

promote awareness within thecommunity or organization.

4.4 Preliminary Results and Findingsof EWS Processes and Functionalities

We found two significant findings fromthe analysis and reviews of the previousresearch as discussed in Section 2. Firstis the mapping of KM processes withEWS four main components to constructthe integrated model. Secondly is EWSfunctionalities to be incorporated intothe model.

Drawing from Table 2, we groupedthe EWS processes into EWS four maincomponents that later to be map can

combine with KM processes as shown inTable 6. The total and percentage fromthe Table 6 exhibit the overallrequirements of EWS components basedon the EWS activities. From the matrix

in Table 6, we conduct an empiricalanalysis on the EWS to look for the mostsalient component to develop EWS. Theresult shown that risk knowledge andmonitoring & warning are equallyimportant (on average about 33 %) forthe EWS development. Bothcomponents are critical requirement forknowledge creation or acquisition andknowledge codification to timelyidentify, detect and forecast a potential

risk. The communication & warningservice with average of 20 % is fordelivering and distribute warningmessages with the support of goodinfrastructure. The average of 13 % isthe response capability which involvesgood coordination, governance forappropriate action plan. Figure 8 exhibitthe EWS component requirements thatmap to KM processes.

Table 6. Matrix of EWS Components andactivities


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Fig. 8 . EWS Components Requirements

Next, we also perform empirical analysison the EWS main functionalities namelyi) detection; ii) prediction; iii) warningand iv) response. From Table 2 we alsogrouped the EWS processes into EWSmain functionalities as in Table 7. Thetotal percentages from Table 7demonstrate the significant of EWSfunctionalities to address early warning.Functionality for detection with 100 % isthe highest requirement to address earlywarning. It shows that detection is aninitial requirement during the process fordata creation and acquisition.Meanwhile, functionality for warning toaddress the dissemination andcommunication shows 86 % of therequirement in early warning. Thisfunctionality is to distribute, display,delivering and transfer of informationfor notification. The functionality for

prediction about 43 % indicates that notall early warning required prediction orforecasting. But still, this functionality issignificant to address early warning forthe purpose of planning and precaution.Lastly is the functionality for response toaddress early warning which takes only

14 % of the requirement. Althoughresponse functionality is the leastimportance, it cannot be eliminate fromthe requirement. This function is tofurnish the awareness and education onrisk mitigation. Figure 9 demonstratethe ranking of EWS functionalities to

address the criticality of the EWSfunctions requirement.

Table 7. Aggregation according to EWSfunctionalities

Fig. 9. EWS Functionalities

5 CONCLUSION AND FUTUREWORK

The use of EWS in KM has somesignificant process that can strengthenEWS to enable knowledge floweffectively and efficiently. Response toany conflict situation needs knowledgeto facilitate a common awarenessregarding problems or risks and thusaccelerate decision making and toinitiate early warning with appropriateimplementation of actions to deal with

problems or risks. The adoption oftechnology is improving informationaccess and dissemination, also isincreasing the need to better understandhow information can be managed andutilized to improve the performance ofEWS.To our knowledge which based on theLR, there is currently no specific designof the integration model between KMS


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integrated kms@ews of conceptual implementation model for clinical dengue fever environment

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