Customisation guidance document for CAREGIVERSPROMMD … · 2017-04-27 · D1.5 Customisation...

D1.5CustomizationguidancedocumentforC-MMDplatformScreening

andInterventionsservicesCAREGIVERSPRO-MMD

D1.5CustomisationguidancedocumentforC-MMDplatformScreeningandInterventionsservices:Page1of42

DeliverableNumber:D.1.5,version:1

CustomisationguidancedocumentforCAREGIVERSPROMMDplatformScreeningand

Interventionsservices

CAREGIVERSPRO-MMDPROJECT

Ref. Ares(2017)1747797 - 31/03/2017




Documentinformation

ProjectNumber 690211 Acronym CAREGIVERSPRO-MMD

Fulltitle Self-management interventions and mutual assistance community services,helping patients with dementia and caregivers connect with others forevaluation,supportandinspirationtoimprovethecareexperience

Projectcoordinator UniversitatPolitècnicadeCatalunya-BarcelonaTechProf.UlisesCortés,[email protected]

ProjectURL http://www.caregiversprommd-project.eu

Deliverable Number 1.5 Title Customisation guidance document for

CAREGIVERSPRO-MMD platform Screening andInterventionsservices

Workpackage Number 1 Title ScreeningandInterventionscontents

Dateofdelivery Contractual Actual

Nature ReportþDemonstratorpOtherp

DisseminationLevel PublicþConsortiump

Keywords Customisation,screening,interventions,platform,interoperability

Authors(Partner) Marco Antomarini (COOSS), Francesca Scocchera (COOSS), Francesca Cesaroni(COOSS),CristianBarrue(UPC),UlisesCortes(UPC),IoannisPaliokas(CERTH/ITI),Konstandinos Votis (CERTH/ITI), Konstantinos Glykos (CERTH/ITI), LamprosMakris (CERTH/ITI), Sofia Segkouli (CERTH/ITI), Dimitrios Tzovaras (CERTH/ITI),Fred Tetard (MDA),EmmaLWolverson (HullUniv), IsabelleLaundrin (CHU),PetrosPapadionisiou(Qplan),DimitriosDaskalakis(Qplan),AnastasiaMatonaki(Qplan),

ResponsibleAuthor MarcoAntomarini Email [email protected]

Partner COOSS Phone +3907150103261




DocumentVersionHistory

Version Date Status Author Description

0.1 06-02-2017 Draft MarcoAntomarini(COOSS) Deliverable structure anddraftofcontents

0.1 06-02-2017 Draft UPC,CERTH Comments and review ofthedraft

0.1 06-02-2017 Draft COOSS Developmentofcontents

0.1 06-02-2017 Draft CERTH Technicalcontribution

0.2 17.3.2017 Draft COOSS Firstdraft

0.2 18.3.2017 Draft UPC Firstdraft

0.2 19.2.2017 Draft CERTH FirstDraft

0.3 22.2.2017 Draft COOSS SecondDraft

0.4 23.2.2017 Draft COOSS Third Draft withintegrations

0.4 23.2.2017 Draft MDA Comments,suggestions

0.4 23.2.2017 Draft CHU Comments,suggestions

0.4 23.2.2017 Draft HUL Comments,review

0.4 23.2.2017 Draft QPL Comments,corrections

0.41 26.3.2017 Draft UPC Review

0.5 28.3.2017 Draft CERTH Datarelatedtointeractiveinterventions

1 28.3.2017 Finaldraft COOSS Finalversion




Executivesummary

Thedocument shows that the data generated byC-MMDPlatformwill be processed andcollectedwithinaSummaryReport (hereinafterSR)which isexpectedtohaveclinicalandsocial meanings and to be able to support specialists in providing more and morecustomizedandtailoredclinicalandsocialinterventionstopersonslivingwithdementiaandtheirmain.

TheobjectiveoftheC-MMDplatformisprimarilyintendedtodetectchangesintheclinicaland social status of the dyads. These changes may be notified to the health and socialprofessionals through a report, as well as to caregiver. This report should improvediagnostics and therapeutic processes as well as the most important driver for financialsavings.

The SR aims to provide information about the health and social conditions of PLWD andtheircaregivers,withthepurposeofintegratingetheirgeneralhealthpicturewithatailoredand specific insights onMMD andMCI, according to thethis is in linewith the EuropeanUnion’ recommendations in terms of interoperability with other systems andmeaningfulnessoffortheresearchforoftheinnovationinthemedicalHealthrecords.

Thelackofinteroperability is,asstatedbytheEuropeanCommissionitself,adelicateandproblematic issue for the use of electronic health record systems. Fully interoperableelectronic health record systems should ease the access to users’ information, enhancingthe quality and safety of user care and ensuring the accuracy and the safety of the userdata.Accordingtoservicescurrentlyimplementedintotheplatformandtestedforusabilityevaluation, theC-MMDplatform,while enabling tomonitor the activitiesof its users andrecord their behaviours, as well as psychological and health conditions, it also providesmore than just a static repository for specific data, but a combination of information,knowledgeandfeedback,inordertofacilitatetheintegrationwiththeEHRsystem.

TherearesemanticandtechnicalissuesinordertotransformtheSRintodigitaldatawhichshallbemeaningfuland interoperable;butgiven the requestsof informationexpectedbysocialandhealthprofessionals,theSRgeneratedbythishugeamountofdatacanrepresentawaytooverlapthelackof interoperabilityandprovideaddedvaluestowardtheanalysisand treatmentofdementia across Europe. The research sphere, therefore, canbenefit ofthestudydescribedinthedocument.Thereisnolackofdatafordementiaresearch,buttheneedtobetterexploitmorethesedata:thepossibilitytoproducesharabledataproducedbyacontinuousmonitoringmaysignificantlyimprovetheresearchinthefield,andthedatay can be exploited in different ways. To fully capture its potential, C-MMD SR may beconsideredasatooltoproduceroutinelybigdatawhichallowabetterunderstandingofthebehaviours and environments of dementia people living with dementia, not only afterdiagnosis,but forprevention,early identificationanddiagnosis,oreventoretrospectivelyanalysetheyearsleadinguptodiagnosis.




ListofAcronyms

Acronym Title

API ApplicationProgrammingInterface

CALLIOPE CALLforInterOPErability

C-MMDSR C-MMDSummaryReport

CRS ClinicalReportingService

EHR ElectronicHealthRecords

eHGI eHealthGovernanceInitiative

EMR ElectronicMedicalRecords

epSOS EuropeanPatients’SmartOpenServices

FHIR FastHealthcareInteroperabilityResources

GDS GeriatricDepressionScale

HL7 HealthLevelSevenInternational

MCI MildCognitiveImpairment

MMD MildtoModerateDementia

MR MedicalRecord

MRS MedicalReportingService

NHS NationalHealthService

PHR PersonalHealthRecord

PLWD PersonLivingwithDementia

PS PatientSummary

SR SummaryReport

SRS SocialReportingService




ListofTablesTable1.SourcesofdataandinformationtobeincludedintheC-MMDSummaryReport_________ 13Table2.Datafromthenon-pharmaceuticalinterventionstobereportedintheSummaryReport__ 16Table3.FunctionalandNon-FunctionalrequirementsofC-MMDSR_________________________ 23Table4.DimensionforevaluationoftheC-MMDSR______________________________________ 25

ListofFiguresFigure1.DataflowtocreatetheSummaryReport _______________________________________ 17Figure2.Designexampleofthecontentadaptation(userselection)_________________________ 28Figure3.Designexampleofanewsensitivedataaccessrequest____________________________ 28Figure4.Designexampleofstructureadaptation________________________________________ 29Figure5.Designexampleofstructureadaptation________________________________________ 29Figure6.Screenshotfromademomedicalreportingtemplate _____________________________ 33Figure7.Screenshotfromademosocialreportingtemplate _______________________________ 34Figure8.Screenshotfromademosocialreportingtemplate _______________________________ 35Figure9.Mind-mapofthedatamodelbehindtheshortsocialreportingservice________________ 36Figure10.Exampleofriskdetectionusingout-of-rangedataplotoverhistoricaldatainthesocial,medicaland/orpersonalreporting____________________________________________________ 37




Tableofcontents

1 Introduction 8

2 Stateoftheart:towardtheintegrationtoEHRstandards 9

2.1 Modelsofrecords 9

2.2 EUforewords 10

2.3 Requirementsforinteroperability 11

3 C-MMDprocessforthecreationofa“SummaryReport” 12

3.1 Datasources 12

3.1.1User’sprofile 13

3.1.2Screening 14

3.1.5TreatmentPharmacologicalAdherence 18

3.2Expectedresults:Interviewswithhealthandsocialprofessionals 18

4 C-MMDUserSummaryReport 22

4.1 Structure 22

4.2 FunctionalandNon-functionalrequirements 23

4.3 UserConsentandAccess 24

4.4 Contents 25

4.5 Evaluation 25

5 TechnicalRequirements:TheClinicalandSocialreportingservice 27

5.1 TheClinicalReportingServicesofC-MMDSR 30

Functionalitydescriptions 32

DescriptionoftheAvailableData 32

ValueDependenciesandTypesofGraphs 32

MedicalReporting 33

5.2 TheSocialReportingServicesofC-MMDSR 34

5.3 ThePersonalReportingService 36

6 Recommendationsandconsiderations 39




1 IntroductionThis current deliverable aims to provide recommendations and guidance for thedevelopment and the exploitation of the set of meaningful information about platformusers,intermsofscreeningandinteractionwiththefunctionsoftheC-MMDPlatform.

One of the functionalities of C-MMDplatform is, indeed, to provide reliable,meaningful,structuredandpersonallyexperiencedinformationandfeedbackstobeprocessedandusedby the Health and Social professionals as well as by the platform itself to continue theprocessofprovisionoftailoredandpersonalisedservices.

D1.5 introduces, therefore, a proposal of C-MMD Summary Report (SR), in line withEuropean recommendations as well as national requirements, and responding to theinteroperability specification in order to act as an instrument for an integrated caringapproach to the PLWD and the caregivers. The C-MMD SR is sourced by data andinformation gained by the services and functionalities of the C-MMD platform (profiling,screening,on-lineinteraction,gamification,tailoredintervention,preferences)aswellasbythecollectionof feedbackregardingusers’ satisfactionsandexpectations; itbenefits fromthe customisation of the information gathered in terms of personalisation andcustomisation of the treatment provided by the platform to its users (in connectionwithD2.2.Customisationguidancedocument–CAREGIVERSPROMMD1stversion);itthenresultson summary of multi-disciplinary information allowing health and care professionalsentering theC-MMDplatformtoaccess relevant informationand tomakedecisionat thepointofcare.

TheC-MMDSR represents the resultofaprocesswhichbeginswith theuserprofile, andcontinueswiththescreeningperformedbyhealthandsocialprofessionals(offline)andbythe Platform itself (online); the overview created by such a process integrates also theresults of monitoring the online activities and behaviours of the users and it take intoaccountalsothepreferencesexpressedbythemonline.

TheC-MMDSRhastwomainobjectives:(1),toprovidemeaningfuldataandinformationtomaximisethecustomisationandpersonalisationofC-MMDplatformservicestowardsPLWDandcaregivers;(2)tobeamulti-disciplinaryandinteroperabletooltoidentifyusers’statusandtobeintegratedinthefuturesystemofElectronicsHealthRecords.

TheDeliverable is expected toprovide information to technicalworkpackageswithin theproject,particularlyWP2.Ithas,assaid,astronginterconnectionwithD2.2.Customisationguidance document –CAREGIVERSPROMMD1st version,which is a deliverable describing,fromatechnicalpointofview,howsuchaSummarywillbetranslatedintodigitallanguageadopting existing technical standards to facilitate its interoperability, and D3.2 APIs forintegration with the 4 clinical partners’ IT systems that provides the technicalimplementationofsuchstandardthroughtheAPIdescription.




2 Stateoftheart:towardtheintegrationtoEHRstandards

C-MMDPlatformisexpectedtoprovideinformationaboutthehealthandsocialconditionsof PLWD and caregiverswho shall be integrated into electronic records system,with thepurposeofintegratethegeneralhealthpicturewithatailoredandspecificinsightonMMDandMCI. To do this, C-MMD platform has to provide an output which adopts the samestandards of existing Electronic Health Record (EHR) systems, adopting languages andtechnicalrequirementsthatcanensuretheinteroperabilitywithnationalNHSsystems.

2.1 Modelsofrecords

The introduction of Medical Records has started, since the 80’eighties, with the aim ofsupporting health professions to better take care of people; it has been focusing theorganisation, the systematisation and the management of health information, involvingtechnicians,healthdecisionmakersandnationalgovernments,aswellashealthmanagersandprofessionals.TheideabehindthefirstapproachofMedicalRecordswasthetransferofpaper-basedhealth information to ICT-basedtools, focusingoncommercial strategiesandleading to some examples of failure of implementation. So differentMRs are have beenproducedwithdifferentaimsandrespondingtodifferentneeds.

ElectronicMedicalRecords (EMR): isunder thecustodianshipofahealthcareprovider(s)thatholdsaportionoftherelevanthealthinformationaboutapersonoverhislifetime.Theapproach is that of provider-centric or health organization-centric health records of aperson. Hospital wards and professionals mainly use it, as it is the record for themanagementof specificdiseaseandofmedical specialities.The focusof therecord is themanagement of clinical information related to specific disease and not the longitudinalclinicaldataoftheuser.

ElectronicHealthRecords (EHR): represents the longitudinal recordof theuser, as it is acompletehealthrecordunder thecustodianshipofahealthcareprovider(s) thatholdsallrelevant health information about a person over his lifetime. The approach is that of aperson-centric health records,whichmany approvedhealth careproviders or health careorganisationsdealingwiththehealthoftheusercanuse.Itcontainshealthrelevantdataoftheuser,includinginformationaboutwellness,lifestyleandnutrition,collectedbydifferentencounters in different organisation, with the purpose of supporting continuity of care,educationandresearch.

PatientSummary(PS):istherecordreportingsummaryclinicaldataandhealthinformationof thepatient; it isusedwhen it isnotpossibletoaccessthecompletehealthandclinicalinformation (EMR or EHR), generally in emergency cases or when detailed data is notavailable. The approach gives the opportunity to provide a summary of key healthinformation tobeaccessedbycliniciansanywhere. It canbeconsideredasapartofEHR,but is deeply different from EMR, as this contains specific clinical information or specificdiseasedataofthepatientusedinhospitalwardormedicaldepartment.




Personal Health Record (PHR): is a new concept introduce in the USA, based on theapproach of involving and enabling the patients to interact within the health area; itforesees the opportunity for the patient to interact directlywith the health professionalsand, eventually, to add directly personal health information and details, in order to letcliniciansbetterunderstandthehabitsandthelifestyleofthepatient.PHRisdefinedasanelectronic application through which patient can access, manage and share their healthinformationandthatofothersforwhomtheyareauthorised;theidealframeworkisthatofan“interconnected”PHR.

2.2 EUforewords

The contribution of the European Union in the promotion of the research and theinnovation in the Health area, has allowed reaching remarkable progresses in terms ofimpactandeffectiveness,alsointheframeworkofmedicalrecords

.As prior and essential framework, the Directive 95/46/EC (1995)1 on the protection ofpersonaldataandfreemovementofsuchdatarepresentsthelegalbasisforusingpersonalhealth information; according toArticle8of theDirective, the legal foundations forusingpersonaldatawillbe theexplicit consent to theprocessingofdata (Article8 (2) (a)),vitalinterests(Article8(2)(c))orthenecessityforhealthcarepurposes(Article8(3)(b)).

In 2008, the EU Commission published a Commission Recommendation (COM(2008)3282final)on cross-border interoperabilityof electronichealth record system, trying tohandlethe proliferation of incompatible ICT formats and standards in healthcare due to recentdevelopmentsinICTsystemsandservicesofEUMemberStates;themainconsequenceofsucha lackof interoperabilitycausesproblemsfortravellingEUcitizensandforEUhealthprofessionalswhomighttreatthem.

In 2011, theDirective 2011/24/EU recognised the exchange of clinical information of theuserasfundamentalrequirementsforachievingacross-borderhealthcare,identifyinginthePSthetoolfortheexchangeofhealthinformation;then,thePSbecomeapriorinformationasset when an individual accesses health services in a different EU member state, asemergency as well as planned care. Pursuant to article 14 of Directive 2011/24/EU, theeHealthNetworkwas set up to facilitate the cooperation between the European eHealthsystemsandtodrawupaseriesofguidelinestofacilitatethecross-bordertransferabilityofmedicaldata.

In the end of 2012, the Commission adopted a new Action Plan 2012-2020, proposing aseriesofmeasuresandexpressingitscommitmenttoremovetheexistingbarrierstoa“fullymatureandinteroperableeHealthsysteminEurope”.

InNovember2013,theDGHealthandConsumersandtheDGCommunicationsNetworks,Content and Technology proposed the “Guidelines on minimum/non-exhaustive UserSummarydataset forElectronicExchange”, representing the fundamental step toproceed

1TheupcomingEUregulationregardingpersonaldata(GeneralDataProtectionRegulation-GDPR)willsupersedethecurrentDataProtectionDirective(95/46/EC)from25May2018.




with the implementationof theDirective2011/24/EUon theapplicationofuser's right incrossborderhealthcare.

Research and innovation leading activities in the field of eHealth are the European LargeScalePilot“EuropeanPatients’SmartOpenServices”(epSOS2),theThematicNetwork“CALLfor InterOPErability” (CALLIOPE Network3) and the eHealth Governance Initiative (eHGI),providingsolidandreliablefoundationfortheprogressesofcross-borderhealthandfortheguidelinesforthePatientSummary.

2.3 Requirementsforinteroperability

As mentioned in the Commission Recommendation of 2nd July 2008, the lack ofinteroperability isasensitiveandproblematicissuefortheuseofelectronichealthrecordsystems. Fully interoperable electronic health record systems should ease the access tousers’information,enhancingthequalityandsafetyofusercareandensuringaccuracyandsafetyofuserdata.

The interoperability is fully addressed by the “Guidelines on minimum/non exhaustivePatientSummarydatasetforElectronicExchange”,thatisdefinedinArticle1(2)asessentialtotheprovisionofhigh-qualitycare,andthereforeaskingthefullengagementofMemberStates to take appropriatemeasures to make their respective Patient Summary datasetsinteroperable,bothtechnicallyandsemantically.

Interoperability of EHR systems involves transfer of personal data concerning a user’shealth.ThesedatashouldbeabletoflowfreelyfromoneMemberStatetoanother,butatthe same time the fundamental rights of the individual should be safeguarded.With theCommissionRecommendationandtheGuidelines,MemberStatesandtheirrelevantbodiesareequippedwiththebasicprinciplesonhowtoaddressinteroperabilityinacross-bordersetting, applicable eventually as concerning a cross-disciplinary and cross-sectoral healthandcareenvironment.

AsconcerningtheinteroperabilityofEHRsystems,therecent“Guidelinesonminimum/nonexhaustive Patient Summary dataset for Electronic Exchange” address the followingobjectives:

1. To outline and to settle the principles for the broad agreement and engagement asregardtocooperationonsharedandinteroperableeHealthinformation;2. To enable interoperability between health information shared among differenthealthcaresystems,possiblymakinguseofexistingstandards(ISO)andbeingbasedontheapproaches and achievements of relevant initiatives already providing interoperable andviableoutputs.3. To face and to solve the challenges of interoperability of EHR systems, buildingappropriate networked systems and services supported by appropriate legal, regulatory,medicalandcarerequirements.

2(http://www.epsos.eu)3www.calliope-network.eu/




3 C-MMDprocessforthecreationofa“SummaryReport”

According to services currently implemented into the platform and tested for by theusabilityevaluation,theC-MMDplatformenableisabletomonitortheactivitiesofitsusers(ofPLWDandcaregivers,byHealthandSocialProfessionals)and record theirbehaviours,psychologicalandhealthconditions,inordertoevaluatetheirstatus;alsotheplatformcanrecord the scores of online questionnaires filled in by users, the screening results andfollow-up of the treatment adherence. All these this raw data made available by in theplatformwillhavetobeprocessedandorganizedintoausablesetofinformationforhealthand social professionals’ analysis. The reporteddatawill fill in aunique report containingdifferent sections, one for clinical interpretation and another for social interpretation.Finally, they should be integrated in the existing systems for sharing medical data; tofacilitatethedecision-makingprocessformorepersonalizedinterventions.

3.1 Datasources

The C-MMD SR is expected to identify PLWD, caregivers and dyads health status, socialconditions, weaknesses strengths and difficulties, in order to generate health and socialinformationable toallowtheProfessionals toplan interventions.Theseresultingdataarealso meant to be used to update health and social report, possibly through EHR system(T1.6). Fromamoregeneralpointof view, theScreeningStrategywithinCC-MDDprojectandplatformisexpectedtoprovideconsistentandvaluableassessmentoutcomesfromtheprofilingandfromthemonitoringlevelsscreening,aimingtoallowthecontentsadaptationsandtheprofessionalpersonalisedinterventions.

Therefore, the SRwill be generated by the collection of raw data derived from differentsources; at first, theuser’s profile itself,which provides information on the demographicand living conditions of each user, the dyad’s status, and level of memory problemsexperienced e.g. MCI or mild dementia. Educational level, working conditions, homestructure, and other profile information can bemade available as an optional.Other keyinformationcomesfromthescreeningprocess,which,accordingtotheScreeningStrategydescribedinD1.3isdouble:offlinescreeningperformedbyHealthandSocialProfessionalsusing scales; then the online screening, the monitoring process performed within theplatformusingasatoolonlinescreeningscalessubmittedasquestionnaires.Othersourcesofinformationtobeconsideredarethetreatmentadherence,thatismeantasamonitoringof if andhow theuser followedornot the setof interventions she/hehasbeenasked toperform. Then, theusers’ preferences, the satisfaction for contents provided, the “likes”and the “dislikes” expressed. Finally, the users’ interactions, which means the level ofparticipation, the discussion joined, contents shared and the achievements reached(gamification).TheexpectedresultsoftheC-MMDScreeningStrategy is the interactionofdifferent actors (Dyads andHealth and Social Professionals) in the platform, allowing theachievementofacoherentpersonalisationoftheinterventionsandconfirmingthebottomup and multidisciplinary approach of the project. The following table organises thementionedlistofdatasourcesandshowstheconnectionofthechosenapproachwiththe




previousdocumentsoftheproject.Informationprovidedbyuserprofilesshallcontainsomeusability information, as those organised in D1.1, and they shall be derived from theProfilingleveloftheScreeningStrategyasdefinedinD1.3.

TheScreeningoftheuserswillgeneratescoresfromthequestionnairesandscalesusedtomonitortheirsymptomsandthebehaviours.ThescalesareclassifiedandorganizedinthedocumentsD1.2andD1.3.TreatmentAdherenceisdescribedinD1.1,whiletheimportanceofusers’preferencesandinteractionsforthecreationoftailoredandpersonalizedcontentsinD1.4.

Table1.SourcesofdataandinformationtobeincludedintheC-MMDSummaryReport

References Sources Meaning ReporteddataD1.1D1.3

Profiling Demographicinformation Basicinfo

D1.2D1.3

Screening Scales Scores

D1.4 Preferences listofinterventionsanduser’sevaluation

Listofpreferences

D2.2 Interactions Frequency,qualityandquantityofinteractions

withnon-pharmacologicaltreatment

Performance/Gamification

scores

D1.1D3.1D3.3

TreatmentAdherence

Adherencetopharmacological

treatment

Prescribedtherapyandadherence

rate

Herefollowsadetaileddescriptionofeachsource.

3.1.1User’sprofile

PLWD. Profile information: demographic information, such as age, gender, education;contactdetails,livingconditions(whereshe/helivesandwithwhom),relationshipwiththe caregiver; neuro-cognitive status initial level, comorbidity symptoms, treatments,physicalimpairments(audio-visual).

Caregiver. Demographic information, such as age, gender, education; contact details,living conditions (livingwith PLWD or not), relationshipwith the PLWD, frequency ofcareprovided;peersupport.

First and last names, spoken language, nationality, date of birth, and their gender areinformationcollected.Livingconditionsmayberelevant forabetterunderstandingof theusers’socialsupport:whodotheylivewithoriftheyliveinprivatepremisesorinsheltered




accommodationsbenefitingofprofessionalcareneedalsoneedstobecollected(Itcouldbeinteresting to know part of PLWD at home (asset/liability…) and within family relations,rules of caregiver (administrative, financial, activities of daily living…). Are there othersecondarycaregiversandwhatdotheydo?Toaddeducational levelandwork(currentorpast). Both for PLWD and caregivers, their profiles may reveal useful information for aninitial sketching of the individual and also information about the dyad dynamics: thestrength or the weaknesses of the relationship between caregiver and care receiver canchangethedirectionoftheprocesstoselectasuitabletheproperinterventionandprovideinformation to theprofessionalswhendefining the tailoredandpersonalised interventionstrategy.

3.1.2Screening

PLWD. Neuro-cognitive level, scores of online and offline scales; comorbidities,treatmentadherence.

Caregiver. Scores of online and offline scales; stress, depression, reactivity,impairments,etc.

AccordingtotheScreeningStrategydescribedinD1.3,theC-MMDplatformcanmonitortheusers’healthandsocialconditionsbysubmittingonlinescaleswhoseresultscanbereadbyexperts in order to support their decision-making about the intervention strategy orchangesintreatments.Scalesrepresentatoolwithadoublescope:revealusers’conditionsaccordingtothescorestheyreach,aswellastotesttheusers’capabilityofinteractionwiththeplatform,creatingmotivationandengagement(viagamification).

Thisperiodicscreeninggeneratesdatathatcanbeadded(summarised) intheC-MMDSR.Thisdatacanbeclassifiedbydomains:Clinicalandcognitivescalesrevealingchangesinthecognitive status andwellbeing of the PLWD and the Caregivers’ stress;Psychological andbehavioural scales providingdata related todepression symptoms, anxietyand significantchanges inmoodthatcanaffect the interventionsandthetreatmentplanned.Caregivers’depressionsymptomscanbemeasuredalso,aswellastheirpositivegoalsincareactivities:suchdatacanassistthedecisionmakingofexpertsinrelationtosupportrequired.

FunctionalscalesandQualityoflifeassessmentsprovideanimportantadditiontoscreeningwith their focus on actual ability rather than presumed capacity. A person’s ability tocompleteactivitiesofdailylivinghasclearimplicationsfortheirqualityoflife,andthereforetheinterventionsandthetreatmentsmayvaryaccordingly.

Health related scales allowmonitoring of the health conditions, both for Caregivers andPWLD.ScalessubmittedbyC-MMDplatformgeneratescoresthatareintegratedintodataalreadyaccessedbyhealthprofessionals;inthisscenario,professionalsbenefitfromtheSRin terms of continuous screening andmonitoringwhich can aid their decision-making. Inaddition, the Treatment adherence is monitored, and consequently the success andsuitabilityofthetreatmentapproachcanbeevaluatedtoo.




Dyad’s relationship assesses PLWD and their caregivers’ quality/strength of relationship.This brief self-report measure can introduce into the SR specific needs of social andpsychologicalnatureforbothmembersofthedyad.

3.1.3Preferences–RecommenderSystem

• PLWD. Preferred Intervention domains, contents consumed, contents liked;contentsdisliked;visualpreferences;

• Caregiver. Preferred intervention domains, contents consumed, contents liked;contentsdisliked;visualpreferences;

The personalization of interventions within the platform is allowed by a RecommenderSystem that definemeaning, scope, forms, and shape of platform contents according tousers’needsandpreferences.Fromthispointofview,theSRshallsomehowdealwiththepreferencesofusers,as theyhavetobetaken intoaccount todecideabout furthermoretailored interventions,aswellas theyallowtheunderstandingofusers’onlinebehavioursthat are significant insights to evaluate residual abilities and capability to socialize andremain active. The data collected reflects the health and social domains that the userprefers to receive support about, the health and social domains established as goals fortheirhealthcareprofessionals,theamountofinterventionsreceived,thedomainareas,theamountofthoseinterventionsthatwereactuallyacceptedbytheuser,thesatisfactionlevelandprecisionoftherecommendations.

Viewingtherecommendersystemasanimportantstepinthepersonalizationprocess,thetypeoftheuser(Caregiver,PLWD,etc.)andthepersonalmedicalinformationwillbetakeninto account before presenting to the user highly personalized recommendations foravailable interventions. In the reverse, the participation of the users in the proposedinterventionsaswell as theirperformance -whenavailable-willbe taken intoaccount fordecisionmakingontheinterventionsstrategy.Additionaldataliketheratingtheyawardtheinterventionandthelevelofuser’ssatisfactioncanbetakenintoaccountfortheevaluationof the interventions themselves in order to have a good fit betweenmedical conditions,personalpreferencesandrequiredtreatment.

3.1.4Interactions

• PLWD. Frequency and quality of posts; frequency and quality of interactionswithcaregivers and other friends; discussions joined; communicationwith the GeneralPractitioner.

• Caregiver.Frequencyandqualityofposts;frequencyandqualityofinteractionswithfriendsandpeers;frequencyofrequestofhelp;discussionsjoined;communicationwiththeGP.

The C-MMD Platform is able to provide interventions, both to PLWD and to caregivers,withinphysical,cognitive,socialandpsychologicaldomains(seeD1.4formoredetails).An




intervention, inthiscase,canbeconsideredasasetofcontentsprovidedbytheplatformand aiming to screen symptoms, monitor users’ abilities and reactions, allow theprofessional interventionofexpert.So it issignificantfromboththesocialandtheclinicalperspectivetohaveareportonhowauserisabletoreacttosuchinterventions:dataabouttheacceptanceortherefusalofagiveninterventioncanberelevant,(1)tounderstandthestatus and the care needs of the single individual, and (2) to allow the evaluation of thetreatment within a significant number of users. In the first case, this data allowsprofessionals to re-define and customize the intervention strategy, while, in the secondcase,theyprovideinsightsforstatisticalandresearchpurposes.

Suchan interaction is subject touser’smonitoringand thus the involvementofusers inagiveninterventionwillbereportedaswell.Thedegreeofparticipationwillbeexpressedasa percentage of the actual participation to the expected participation, and from thoseinterventions which can report participants’ performance (e.g. the playful interactiveinterventionsperformedintheC-MMDplatformasadditionalC-MMDapps).

Additionalinformationlikethetimeneededtocompletetasksandthesuccessratewillbereported for statistical purposes and for customisation of the personalised interventionstrategy.

Overall, the non-pharmacological interventions will be part of the SR by adding theinformation presented in the following table. None of the following data types ismandatory;theavailabledatawillbereportedwheretheyareavailable.

Table2.Datafromthenon-pharmaceuticalinterventionstobereportedintheSummaryReport

A/A Name Description TypeofData

1 Participation Numeric descriptor for the degreeparticipants followed instructions on thefrequencyofuse

Percentage (%) calculated asthe actual participation to theexpectedparticipation.

2 Duration The time needed to complete theintervention in seconds. For very longinterventions(e.g.musictherapy)daysorhoursmaybereported.

Integer number andmeasurementunit

3 Score Thetotalnumberofpointsearnedbytheparticipation in the intervention(gamification) in relation to the level ofdifficulty.

Integernumber(points)

4 Averageresponsetime

Each response in subtasks will berecordedandfinallytheaverageresponsetime will be reported for statisticalreasons

Floatnumber(inmilliseconds)

5 SuccessRate Numeric descriptor for the success rate Percentage (%) calculated as




(i.e.satisfactionindicator) the points earned by theactivity to the maximumpossiblepoints

Thefollowingfigureaimstodescribetheprocessbywhichtherawdatawill fill in theSR;then it explains how the Report will allow professionals to have a view of the usersconditionsfromtheclinicalaswellasthesocialpointsofview,andconsequentlyprovide,viatheplatform,theirprofessional interventions,afterthedueconsultation(third leveloftheC-MMDScreeningStrategy,asdescribedinD1.3);thereport,thereforeistheproductofthescreeningoftheusersstatusandtheresultsoftheusers’reactiontothetreatments:soitprovidesprofessionalswithdatathattheycanreadandmanageinordertodecideaboutthefurtherprovisionofinterventions;accordingtothereport,professionalsmaybeabletodecideifthetreatmenthastobereplicated,modifiedorchanged.

Atthesametime,theReportaimstobemeaningfulandcompatiblewithdifferentsystemsofelectronicmedical/healthrecords;itmeansthatithastorespectsomeformat,languageand security criteria, in order to contribute to improve the quantity and quality ofinformationaboutapersondigitallysharedamongintegratedsystems,withthefinalscopeofamorepersonalisedandtailoredprovisionofcareservices.

Figure1.DataflowtocreatetheSummaryReport




3.1.5TreatmentPharmacologicalAdherence

PLWD.TherapyAdherenceRate.

Caregiver.TherapyAdherenceRate.

Aspartofthegamificationstrategy,theplatformallowsthemonitoringofusers’adherencetotherapytreatments.AsfromD1.1,adherencetotreatmentistheextenttowhichauserfollowsaprescribedtherapyintermsoftimeplanandrecommendations(oftheprescriber).The raw data that CCMMD platform can generate about this aspect are related to theAdherence Rate, valid both for PLWD and Caregivers. Clinically and socially relevantinformationaboutadherencecanbetheidentificationsofgapsintherapy:suchinformationmaybeusefultobereportedintheSR.

3.2Expectedresults:Interviewswithhealthandsocialprofessionals

TodefinewhattheC-MMDSRshouldcontaininordertobemeaningfulandinteroperable,the viewpoints of health and social professionals have been collected during face-to-faceinterviews.Apsychologistand twoneuro-cognitivespecialistshavebeen interviewed.ThethreeladieswillbeinvolvedintheincomingpilotstudiesinItaly.

According to theopinionof thePsychologist (meton17thMarchatCOOSSpremises), thescopeof theSR is tobeaworking tool thatcanguide theperiodicvisits shehaswithherusers. For thesepurposes, thedocument shall containpersonal information, inparticular,the living conditions and if any changes happened in this domain, as well as the initialdiagnosis.

Then,asapsychologist,sheaskedtohaveaviewaboutthelevelofDepression(oranxiety,orwell-being), as another relevant item to be included in the SR, both from a social andclinicalpointofview.Theuser’smoodadds further informationabouttheusercondition:the feelings, the attitude toward coping with the illness, the attitude towards the carereceivedarekeyaspectsthatmayaffecttheproposalofinterventions.

Informationabout interactionswithC-MMDfunctionsmaydescribetheacceptanceoftheinterventionsandthesatisfactiontowardstheproposedcontents.Itallowsexpertstoknowhowoften theuserperformed the tests/exercises/scales, if theyhavebeen completedornot.Scoresshouldbereported,aswellastheuser’sappreciationandattitudetowardthem.Rejected interventionshave tobe reported too.A registerofmissed clinical appointmentcanbealsohelpful.

A Social Report integrating this data can trigger interventions aimed at stimulating thecognitivedomain,proposingcontentsaimedto:

- enhancememory,concentration,spatialandtemporalorientation,self-control;




- improve mood through positive communication, manage anxiety, reducedepressionthroughpositiveandjoyfulcontents;

- improve/maintainadherence,whichmeanstokeepmonitoringtheprogressoftheillness and adequate interventions to the users’ changed conditions. Scales, testsand exercises shall be adapted to the new users’ conditions or confirmed if thescoresobtainedremainconstant.

Thetwoneuro-cognitivespecialists(meton21stMarchattheAnconaHospital)suggestthattheSRshouldbeaccessiblefromeachuser’sprofile,anditshouldreporttwomainareasofcontents,thattheycalled““Activities”and“Cognitivecapabilities”.

Area called “Activities”: this area, they suggested, should report aboutonline activities; itshouldlistactivitiesperdates;foreachdatethenumberofactivitiesperformedshouldbeshown,thenthedurationofeachaccess,andthenumberoftaskscompleted.

Hereisanexampleofthe“Activities”AreaoftheSR.

Name:

MarioRossi4

Category:

PLWD

Age:

73

Gender:

Male

1stContact:

01/01/2017

Activities

DatesN°ofaccess Duration

Taskscompleted

Timeneeded

01/01/2017 3 60min 3 20min

02.. 5

03… 4

… …

31/01/2017

ThesecondArea,called“Cognitivecapabilities”shouldreportthescoresofthescalesthattheusersreached inagivenperiod.Accordingtotheclinicalexperts’expectations,scoresshallbe reported inabsolutevalues,aswellas inameaningfulway fornon-clinicians: forexample, the GDS scale scores shall be indicate in absolute value (i.e. 14) and also theinterpretation of the number shall appear (i.e. 14 = “Mild Depression”). This approachshouldberepeatedforeachscaleusedonline.

TheclinicalexpertsdraftedthissecondpartoftheSRasfollows:

Name: Category: Age: Gender: 1stContact:

4Allnamesusedintheexamplesarefictitious.




MarioRossi PLWD 73 Male 01/01/2017

Cognitivecapabilities

Dates ACE-III GDS EQ5D PHQ9 Etc.

01/01/201784/100

Memoryproblems

14

MildDepression

85

Goodgenerichealth

19/27

Anxietyovertheaverage

…

02..

03…

…

31/01/2017

Scores and results may be also represented graphically. Graphics may support theidentification of symptoms, as well as allowing the evaluation of tasks performances,visuallyrepresentinganypositiveornegative“peak”,whichmayalsosuggestwhethertheuserisactingaloneorbeinghelpedbyothers(forexample,ifauserhasrecurrentscoresinperformingataskbutsuddenlyapeakofperformanceisevidenced,thenitmaymeanthatheorsheletsomeoneelsecompletingthetask,forinstanceanephew,i.e.forgames).

The SR, shall also compare resultswith scores obtained in themonth before, or, at leastwith the previous SR downloaded. This comparable data may be very significant fromclinicalpointofview,toevaluateifparametersarestableortheyarechanging.

Clinicalexperts,statedthatthereisadditionalinformationthatmayhaveclinicalimpactandtherefore theywould be useful to be reported in the SR.Namely, they suggest to reportaboutthe“UsualNetwork”whichmeansthenumberofonlinecontacteachuserhave,andthenumberofpersonsavailablearound theperson (offline contacts). ThesedatamaybereportedwithintheProfileareaoftheSR.

Also, ifpossible,smallamountsof informationaboutthephysicalactivities(suchaswalks)maybemeaningful for them(even if it isnotclear ifandhow theplatformcouldregisterdataaboutit).

Clinical experts also went through the Pharmacological Treatment issue: from theirperspective, it is not relevant to knowwhichmedicinesusers are consuming,butmaybeusefultoknowthenatureofthepharmacologicaltreatment,whichmeans,forinstance,toknowiftheusersarereceivingan“anti-Depression”treatment,or“anxiolytic”treatment,or




“memory” treatment. They confirmed that the SRmight be enriched by information likethis.

SRshallreportcomorbiditiestoo.




4 C-MMDUserSummaryReportFollowingthepreviousdescriptionofdatacollectedandprocessedbyC-MMDplatform,andintheperspectivetomatchtheexperts’expectations,thepresentsectionprovidesthemainfeatures and requirements of a proposal of the C-MMD SR, as a way of returning andreportinghealthandsocial informationaboutPLWDandcaregivers thathealthandsocialprofessionals can manage and process, within an integrated care system. The C-MMDproposalof SR is aimedat integrating theexisting standardsofhealth reports inorder toimprovethedecision-makingprocessaboutfurtherandmorecustomisedinterventions.

The main goal of the C-MMD SR is to improve the user’s support and treatment, bysupplying relevant, specific, targeted and customised information to be used by theplatformitselffortheoptimisationofthepersonalisationprocess,aswellasbyHealthandCare Professionals for the implementation of a more effective and integrated Care Plan.WithintheframeworkofC-MMDplatform,theSRoffersanintegratedandcomprehensiveviewofhealthandsocialinformationrelatedtoMMDandMCIofthePLWDandrelatedtoburden and quality of life of the caregiver, including information that they generatethemselvesthroughtheinteractionwiththeC-MMDplatformandinformationfromHealthandSocialprofessionalsrelatedtodiagnosesandtestresults.Ittakestheformofaspecificinformative tool, based on user-centred approach, gathering a set of relevant andmeaningfulinformationaboutMMDandMCIrelatedissues,aswellaswellbeingandqualityoflifeingeneral,fromarangeofsources.

TheaimoftheC-MMDSRistoprovidenotjustastaticrepositoryofdata,buttocombineinformation, knowledgeandplatform feedbacks, inorder to facilitate the integration, thecoordinationandthecontinuityofhealthandsocialsupporttoPLWDandcaregivers,atthepointofcare.ItisconceivedasatooltobeintegratedwiththeEHRsystem,thusprovidinggreaterbenefitsthanstand-alonesystems.

4.1 Structure

C-MMDSRaimstoprovidetheHealthandSocialProfessionalswithadatasetofessential,understandable,customisedandtargetedsocio-medical information,availableatthepointofcare.Namely,C-MMDSRisasetofessentialuser’sdatawithanimpactinrelationtoMCIandMMD (when dealing with the PLWD) or to burden and psychological distress (whendealingwiththecaregivers),abletoprovidetheHealthandSocialProfessionalswith:

- User’sgeneralinformation(fromprofiling)

- User’sclinicalandsocialinformation(fromscreeningandinterventionstrategy)

- User’s attitudes and preferences (from on-line interaction and recommendersystem)

- User’smedicationinformation(fromprofiling/Treatmentadherenceservice)

TheCC-MDDSRispresentedinastructuredway,throughstructuralmodulardatagroupsorsections, each of them containing a related set of information, in order to facilitate the




understanding of the whole picture, to integrate a holistic picture in the planned andintegratedcareprocessandtomanageseparatelyanysubset.

ActorsinvolvedintheC-MMDSRservicesarethefollowing:

- users (as conceived in the framework of the EHR or PS/User Summary): those are thePLWDandthecaregivers,receiversofthesupportingservicesofC-MMDplatform;

- Health and Social Professionals: those are the supporting professionals from the clinicaland social side, accessing the platform and contributing to the implementation of the C-MMDservicestowardsPLWDandcaregivers;

-HealthandSocialSystem:itrepresentstheinstitutionalactor,generallythepublicentityinchargeof thegovernanceof thehealthand social care in a specific areaor territory (e.g.localhealthagency,socialdistrict,etc.);itdoesnotaccessdirectlytheC-MMDplatformorservicesorSR,butitiscomplementaryasfortheinteroperabilitywithEHR.

4.2 FunctionalandNon-functionalrequirements

ThepotentialofexploitationofC-MMDplatformreliesalsoonthepossibilityoftheC-MMDSR to complete, integrate and add value to thepotential of informationof EHR, coveringdifferent types of EHR (as defined by the Commission Recommendation of 2 July 2008),especiallythosedesignedforasharedaccessandanintegratedsystemofhealthandsocialcare.

Therefore, based on Commission Recommendation, on “Guidelines on minimum/non-exhaustiveUserSummarydatasetforElectronicExchange”andonDirective95/46/EC,thefollowingfunctionalandnon-functionalrequirementsoftheC-MMDSRareoutlined.

Table3.FunctionalandNon-FunctionalrequirementsofC-MMDSR

FunctionalRequirements Non-functionalRequirementsThe users must be unequivocally anduniquely identified in a trustworthy way toallow the Health and Social Professionals toconsult the information related to them(followinginformedconsent).

The servicemust be accessible and usablewhen needed and requested, so technicalunavailabilitymustbedetectedandsolved.

TheHealth and Social Professionalsmust beunequivocallyidentifiedandauthenticatedintheC-MMDplatform,accordingto their roleandprofile.

The communication (passage/exchange ofinformation via the platform) must besecure and protected, and the integrity ofinformationmustbeguaranteed.

The users must provide informed, specificand independent (freely) consent andconsent lifecyclemustprovetheevidenceofitslegitimacy.

Theinformationmustbemeaningfultotheinformationneedsof theHealthandSocialProfessionals, to be appropriatelyinterpreted, treated and processed forfurthercaresteps.

The information in the C-MMD SR must bestructured through modular data groups tofacilitatetheunderstandingandoptimisethetreatment/management.

Theinformationmustbemeaningfultothecustomisation process of the C-MMDplatform, allowing the Health and SocialProfessionals to adopt more consistent




decisionsandfollowup.

4.3 UserConsentandAccess

As concerning the user consent to the creation/sharing/extracting/elaborating of C-MMDSRsinformation,thefollowingpossibilities/optionsshouldbeconsidered:

- To ask for explicit consent or ‘opt-in’: where the SR can be created and dataincludedonlywiththeexpressedconsentoftheuser;

- Toaskforimpliedconsentor‘opt-out’:wheretheconsentispresumed,unlesstheuserexplicitlyrefusesit.

Through the informative consent process outlined by the whole services of C-MMDplatform,theplatformusersreceiveallappropriateinformation(seeWP4methodologyforPilotspreparationformoredetails),enteringinthe‘opt-out’option;fortheimplementationoftheC-MMDSR,andnamelyforthepotential integrationwithEHR,furtherevidencesof“informed consent” (information, understanding, awareness, competence, independence)areneeded,namelyabout:

-Thekindsofinformationthatarebeingrecordedandretained

-Thepurposesforwhichtheinformationisbeingrecordedandretained

-Theprotectionsthatareinplacetoensurethenon-disclosureoftheirinformation

-Thekindsofinformationsharingthatwillusuallyoccur

-Thechoicesavailabletothemabouthowtheirinformationmaybeusedanddisclosed

-Theirrightstoaccessandwherenecessarytocorrecttheinformationheldaboutthem

Directive 95/46/EC requires that data processed must be adequate, relevant and notexcessiveinrelationtothepurposesforwhichtheyarecollectedand/orfurtherprocessed.Theapproach is thereforeoriented to the“need-to-know”and theaccess shouldbe role-basedandlimitedtopersonsneedingtheaccess,uptothedefinitionofdifferentcategoriesof access for different health and social professionals. This can be ensured by assigningdifferent rules for different types of health and social professionals, (health data for theclinicians and social data for the social) or assigning to the platform users (PLWD andcaregivers)thetaskofdecidingwhichprofessionalshaveaccesstowhichdata.

Thedefinitionoftheaccessrulesalsoentailstheusers’rightsoverthedataandthereforetheir consent, in terms of: access the data, to erase and correct data; know who haveaccessed to their data. And the possibility for the health and social professionals to benotified that somedata ismissing, in order to ask the users to provide themissing data.Furthermore, information harmful to the users should not be directly available to them,leaving to the health and social professionals the decision aboutwhen, how and towho(PLWDand/orcaregiver)communicatethedelicateinformation.




4.4 Contents

Determining what information should be included in the C-MMD SR requires balancingcompeting interest. On the one hand, having in mind the interoperability andcomplementarity with EHRs system, full health data should be provided, allowing healthprofessionalstoprovideabetteroverviewoftheusers’health;ontheotherhand,someofthemedicalinformationcanbeparticularlysensitive.

TheprimarydriverfordecidingonSRcontentmustbeUserCare,thatistheimplementationofatailored,personalisedanduser-centredapproach.TheC-MMDshouldbeabletocollectdataandinformation,tobeusedformanypurposesunderamulti-disciplinaryapproach:toadapt intervention strategies, to monitor performance, to adjust treatment plans, torecommendcontents,toprovidesupportingevidenceandtocompareresults.Beingatooldevotedtoamulti-disciplinaryapproachtowardsMCIandMMD,theC-MMDSRalsoshouldbeabletocollect,elaborateandthenreportinformationabout:

- Judgementsabouttheuser’sneedsandproblems

- Careplannedandprovided

- Resultsofassessments

- Views,expectationsandpreferences

- Decisionsmade

- Communications(withusersandcarerandotherprofessionals)

The framework of contents for the C-MMD SR is limited to the set of data gathered andcollected by the platform itself (profiling/screening), thus elaborated and processed toprovide adequate, relevant and meaningful information related to the treatment andmonitoringofMCIandMMD.

4.5 Evaluation

The evaluation of the C-MMD SR service has to be foreseen, in order to ensure themonitoring of its functionality by PLWD and caregivers, and especially the relatedinteroperabilityprovisionsbyHealthandSocialProfessionals;intheevaluationprocess,itisnecessary to review progress achieved through the C-MMD SR on organisational andtechnicalaspects.

Table4.DimensionforevaluationoftheC-MMDSR

Dimension DescriptionService GeneralusefulnessoftheserviceAcceptance Degreeofacceptanceoftheservicebyactors(see4.1)Usability Usabilityofthedesignedprocess(maturityofEHRsystems)Infrastructure Coverageofinfrastructurefortheserviceattheactorssite

(interoperabilitydesignevaluation)Content Completenessandusefulnessofdata(usefulnessofspecific




and tailored views on the whole data set compared tospecific datasets,within themulti-disciplinary approach ofMCIandMMD)

SecurityandPrivacy PerceivedsecurityoftheserviceandprivacyofdataConsent Willingnesstogiveconsent




5 TechnicalRequirements:TheClinicalandSocialreportingservice

There are semantic and technical issues (and a process to be standardized) in order totransform this report and its information into digital data that will be meaningful andinteroperable.Ideally,C-MMDplatformisexpectedtobeabletoprovideinformationaboutusers’healthandsocialconditions.Suchdatatobecollectedandsharedshallberesumedinaninteroperableandmeaningfulway,inordertobeintegratedinexistinghealthrecords.ItmeansthatC-MMDplatformshallcomplywithrecognisedstandards,whichrepresenttheonlyconditiontoallowthedataexchangefromagivensystemAtoaSystemB.InD3.3,APIsfor integration of gamification service, treatment adherence service and clinical reportservice, inthedescriptionofthetreatmentadherenceserviceAPI it isstatedthatHL7andespeciallyFHIRstandardsaregoingtobefollowed.FHIR5isastandarddevelopedbytheHL7consortium.

The followingsectiondescribes themain functionalitiesand requirements for theC-MMDSRtool,conceivedfromthetechnologicalpointofviewasareportcomposedby2sections:the proposed solutions deal with a Clinical Reporting Service (CRS), a Social ReportingService (SRS) and a Personal Reporting Service (PRS); these can be proposed as differentsectionswithintheSR,visibletoexpertswhowillcanopttohideasectionandjustopenthemostinterestingforthem.TheambitionistomaketheSRasatoolabletoprovidecomplexsetofdataineasy,comprehensibleandmeaningfulwayforexpertswithdifferentexpertiseandcompetences.

Theinitiallayoutofthereportingtemplates(SRS,CRSandPRS)maydiffertobetterfittheneedsofthetwogroupsofprofessionals,butitwillbeeasyforbothgroupsofprofessionalsto create their own integratedapproachesby combining social andhealth/clinical data inhighly personalized views. In this way, personalization will be performed in both thecontentsofthereportandthestructureofthereport.Considerthefollowingtwokindsofadaptation.

Contentadaptation:Eachprofessionalwillbeabletoaccessonlytheuserprofilesthatareconnected with his/her professional profile. After a request for accessing personal andmedical data, professionalswill be able to select fromwhich users theywish to see data(selectallusers,specificusersoronlyoneuser).Figure3.Designexampleofanewsensitivedata access request presents a design example of how a professional (either medical orsocial)canselecttheusersbasedonwhichthecontentofvisualanalyticscomponentwillbeadjustedto.Itshouldbenotedthatprofessionalsshouldaskforpermissiontoaccessuser’ssensitivedata,ifnotagreedearlier.Theprocessofuserselectionispresentedintheupperpart of theFigure 3.Design example of a new sensitive data access request,while in thelowerpartthelistofpendingaccessrequestscanbeseen.Thebuttonwiththeplussign‘+‘triggers thecreationofanewdataaccess requestasseen inError!Referencesourcenotfound..Asearchenginebasedontestentriesisofferedtoprofessionalstohelpthemselecttherightusersfromalonglistofavailableusers.

5https://www.hl7.org/fhir/




Figure2.Designexampleofthecontentadaptation(userselection)

Figure3.Designexampleofanewsensitivedataaccessrequest




Structure adaptation: Professionals will be able to adjust the structure of the reportdependingontheirneedsandprofessionalobligations.Professionalprofileswillbeabletoselectanyoftheavailablesocialandmedicalvariablestoincludeintheirreportingservice.Theconceptofstructureadaptationisexplainedinmoredetailinthefollowingsectionsastwo separate viewsof theClinicalReporting Service (one formedical andone for socialreporting).Thiskindofadaptationonreportingwillallowprofessionalstoselectthetypesof diagrams and the types of variables theywish to view. The list of the available data(derived from the data model) appears as a list of select boxes. This way the viewsoriginallydesignedforsocialprofessionalscanbeexchangedwithviewscomingfromthemedical professionals and vice versa. Another aspect of the structure adaptation is theway the information isdisplayed.On theexamplespresentedup tonowtheuser’sdataappear in chartsandother similar formsof visualpresentation.Error!Reference sourcenot found. is an example of timeline used to present in time-dependent order theactivities of the selected user(s). Each record presents a timestamp (date and time theinterventionorotheractivity tookplace), a title todescribe the typeof theactivity andotherdatarelatedtothenumberofsteps,thescoreoftheactivity,etc.

Figure4.Designexampleofstructureadaptation

Figure5.Designexampleofstructureadaptation




5.1 TheClinicalReportingServicesofC-MMDSR

TheClinicalReportingService(CRS)willbeofferedtomedicalandsocialprofessionalswhowill maintain a regular professional account in the C-MMD platform and will access itsfunctionalitybyusingtheverysamecredentialsforaccessingtheplatform.TheCRSwillbeavailable only to C-MMD platform users who have been authorized as professionals andhave under their professional responsibility the duty to monitor the user’s medical andsocialstatus.

Based on the need of the C-MMD platform and the international literature on medicalreporting (Di Croce et al., 2012; Larsson et al., 2003; Simon et al., 2005), the followingprincipleswillbeapplied:

1) There will be two similar, but separate clinical reporting services, one focusing onhealthandclinicalissuesandonemorefocusingonsocialissues;

2) Theclinicalreportingwillbebasedondatacollectedbytheplatform,thescalesandbytheinformationalreadyavailableinthemedicalprofile

3) Professionals will have access to personal dyad’s information and also access to thedataproducedbyallPLWDandtheCaregiversconnectedtotheprofessional’saccount

4) The principles of Visual Analytics (Keim et al., 2008;Wong & Thomas, 2004) will beappliedinbothapproachesinordertooffer:

- Machineinformationvisualization

- Analyticalreasoning

- Interactivevisualinterfaces

5) Itwilldealwithcomplexityofthedataandtheheterogeneousdataresources

6) Itwillnotrequireanyprevioustechnicalknowledgebyprofessionals

7) Itwillbebasedonabstractdatastructuressuchasgraphsinordertohandle:




- High-levelcomplexactivitieslikeuser’ssocialinteractions

- Medicalinformationcomingfromthesensinglayer(validatedscales)

8) Itwillallowcomparisonsbetween:

- Auserandagroupof(similar)users.

- Thecurrentuserstatusandapreviousmedicalstateofthesameuser.

9) Itwillusestatisticalprocesses-performedautomatically-topresentfuturetrendsandsenserisks(e.g.valuesoutofrange).

10) Showing respect to professional’s time availability, the clinical reporting will allowprofessionalstohaveinshorttimeawidepictureofallthepeopletheysupport

11) Itwillamplifyuser’scognitivecapabilitiesinthefollowingways:

- Reducesearchneedsbydepictinglargeamountsofinformationinlimitedspace.

- Represent the time-relationships of the data (e.g. by time series of time-relatedmedicalandsocialphenomena).

- Allowperceptualmonitoringofpotentialevents.

- Enableexplorationofthedatabychangingparametervalues(liketime).

12) It will support the decision making in everyday user monitoring or in times ofemergencybycombiningothersourcesandformsofmedicalreporting(externaltotheC-MMDplatform)likenarrativereportproducedbylocalin-housereportingsystems.

Medicalandsocialreportingbypersonnelwillbeprovidedasahighlyeffectivemechanismfor informingPLWDand their caregiverson theirpersonalprogressandat the same timekeep evidence of this progress for future use. According to the results, an evaluationprocessmaybetriggered,restrictionsmaybeapplied,anewinterventionmaybeproposedornoactionmaybetaken.Accordingtothis,theCRSshouldpayeffortsto:

1) Avoidanyformofsensationalismintermsandgraphics.

2) Becautiouswithincompletemedicalandsocialprofilesandinactiveperiods.

3) Avoidforecastsofphenomenawhichcannotbefullydescribedbythecollecteddata.

4) Avoidmakingdecisionsonlybasedonexperimentaldata.

5) Considertheemotionalimpactofthemedicalandsocialreportingitemsonlaypublic(likethedyads)whensharedwiththem.

6) Takeintoaccountlocalmedicalandsocialcriteriaandregulations.

7) Keep clinical reporting confidential and restrict the dissemination of health-relatedinformationthroughmainstreammedia(medicaljournalism).




Functionalitydescriptions

TheCRSwillusecustomizable report templatesspecific to themedicalandsocialpracticeareatoenhancereportingefficiency.ThiswillallowauniformwayofclinicalreportingtoalltheC-MMDprofessionalusers.

DescriptionoftheAvailableData

HavingalistofscalestobeusedinC-MMDplatform(asderivedfromtheWP1),weneedtodefinehowthescaleresultswillbesavedintheusermodelandinthemedicalrecords,nomatter if the particular scaleswill be part of the C-MMDplatformor not. Thus, both forscales implemented in to the C-MMD platform and for external resources that will bereportedinthemedicalrecords inplatformweneedtoindicateabasicsetofdescriptors.More specifically, from the technical point of view we need to know for each scoringvariablethefollowing:

1) Thefullnameofthetest,anabbreviationandareferencetoinitialauthors

2) Thetypeofscoringvariable(s)(nominal,scale,ordinal,etc.)

3) Theminandmaxvaluesofeachvariableorthecategories

4) The thresholds or the acceptance range for each one scoring variable (e.g. 28 andaboveis‘normal’fortheBostonNamingTest.BNTisusedhereonlyasanexample.)

5) Averagetimeneededtocompletethescale(administrationtime)

6) ThefrequencyoftheiruseintheC-MMDplatformofinrealworldclinicalsettings(e.g.oncepermonth,twicepersemester,etc.).

7) Thenumberofquestionsand/orpartsofthetestthatshouldbereportedseparately.Someprofessionalspayattentiontospecificpartialresults,liketheTMT-Bpart,ortheBNTresultswithphonemicandsemantichelp.

8) The direction of the expected clinical status orientation (e.g. smaller test resultindicatesmorepositivetest,ortheopposite).

9) Theordertogivethosescales(ifany).Forexample,someonemayneedtotaketheAscale first and then depending on the results to give the B test. Ordering may beappliedonpartofthetestaswell(e.g.givefirsttheXpartandthentheYpartofthetest).

10) Fromamedicalpointofview,theneedtokeeprecordsorthedependenciesbetweenscreening data (Does an accurate diagnosis require to know the historical values aswell?)

Themetadata required for scales will be used inmaking a plan for statistical analysis inmatchmakersandtopreparesomevisuallayoutsformedicalreportinginterfacedesign.

ValueDependenciesandTypesofGraphs

The last requirement form the previous list (No. 10) should be explained in some moredetails before proceeding to visual layouts design. It is highly possible that there are




dependencies between scale results and other arithmetic values ofmedical interest. Themainquestionhere is:doweneedto lookatpreviousorothermeasurements inordertomakesenseoftheresults?Dependenciesforscreeningdataareveryimportantformedicalreporting and we care about the interface design for social and medical professionals.According to the reporteddependencies,we candefine the following formsoforganizingandpresentingtheinformation:

- for self-dependencies (one value of the scale depends on previous values of the samescale), we need to present time series ofmeasures to doctors. No other graph type cancreatethesamevalue;

-forstand-alonemeasuresweonlyneedtopresentcurrentstatus(e.g.linebars);

-forgroupsofscalemeasureswemayneedtousea'spider-graph'(variableswhichcanbegroupedtogether).

MedicalReporting

TheMedicalReportingService(MRS)isdesignedforreportingtothemedicalprofessionalsthestatusofthemonitoredusersregarding:

- TheTreatmentAdherenceprogress

- ScalesResultsperscalevariable

- Expectedresultsofselectedvariablesofhighmedicalvalue(likeperformanceintheinteractiveinterventions)

- Additionalinformationliketheperformanceingamification

Error!Referencesourcenotfound.isanexampleoftheproposedvisualanalyticsinterfaceformedicalreporting.Itcontainsthreemainareas:1.thescalesperuser(upper-left),2.Thescales resulting heatmap (upper-right) and3. the time series of the variable under study.The Depression scale is considered in this example. It is expected that a selector will beavailableforthemedicalprofessionaltochooseascalefromthelistoftheavailablescales.Thetreatmentadherenceisincludedinthelistoftheavailablescales.

Figure6.Screenshotfromademomedicalreportingtemplate

Thescalesperuserperweekdayareausefultablechart thatcangiveanoverviewofthescaleresultspertest-taker.Thenumericaldescriptor(arithmeticscaleresults)mayappearinboxes,butthecolouroftheboxindicateshowtherecordedresultsarecomparedtotheexpectedresults.Thehigherthecolourvalue,thehigherthescoreresult.




Timeseriesisagraphpresentingseriesofdatapointsindexedintimeorder.AllscaleresultswillbestoredintheC-MMDdatabasealongwiththeirtimestampsatthetimeofthetest.Based on the time information, the time series of high interestmedical variables will bedrawnasseeninthelowerpartoftheFigure6(dummydataexample).Thepinkzoneinthemiddlerepresentsthezoneoftheexpectedornormalvalues.Allvaluesthatlieoutsidethiszone can be highlighted for professionals’ interpretation. Additional interactionrequirementsfortimeseriesare:

1.chooseapartialofthedepictedtimezonebyusingthepointingdeviceselector

2.drawvaluesovermovingcursor(

)

3.doubleclick(orrightclick)toreturntothenormalviewofthetimeseries

4. Synchronizemultiple time series on user’s demand (like on the variable A & B of theFigure6example)

Forallcharts,giveuserstheoptiontoprint,downloadascreenshotofanyofthepresentedcharts,ordownloadapdffile (printaspdf) forreferenceandfutureuse inreports.Thoseoptionsmaybeaccessedthroughshortinteractivemenusnexttoeachgraph.

Figure7.Screenshotfromademosocialreportingtemplate

5.2 TheSocialReportingServicesofC-MMDSR

TheSocialReportingService(SRS) isdesignedforreportingtothesocialprofessionalsthestatusofthemonitoredusersregarding:




- Thecurrentsocialstatusandtheprogress insocial interactionperformed in theC-MMDplatform

- ScalesResultsperscalevariablerelatedtothesocialstatus(socialscales)

- Expectedresultsofselectedvariablesofhighsocialvalue(e.g.datacollectedbyin-housevisits)

- Additionalinformationliketheperformanceingamification

isaproposedvisualanalyticsinterfaceformedicalreporting.Itcontainsfivemainareas:1.Overalluser-profile(upper-leftofError!Referencesourcenotfound.),2.Shortsocialprofileofselectedusers(middle-leftpartofError!Referencesourcenotfound.),3.Thetimeseriesofthevariableunderstudy(lower-leftpartofFigure8),4.Treatmentadherencestatusofallusers under study (upper-right part of Error! Reference source not found.) and 10.Comparisonofthesocialinteractionofselectedusers(lower-rightpartofError!Referencesourcenotfound.).

Figure8.Screenshotfromademosocialreportingtemplate

The short social profile presents in a ring-diagram the current status of all interventionsundertaken by a user or a group of users, their social activity and their personaldevelopment.Thosethreeareasdefinethedatamodeloftheshortsocialreportingserviceaspresentedinthemind-mapofFigure9.




Figure9.Mind-mapofthedatamodelbehindtheshortsocialreportingservice

The Stacked Bars (middle-left part of Error! Reference source not found.) can give anoverview on how specific users have gained their points. Assuming a standardized pointsystemtorewarduser’sactivityintheplatform,wemaydefinethreekindsofpointsources:Treatmentadherence,scalesandsocialization.Thisvisualelementis importanttogivethepercentageofsocialactivityoverallotheractivitiesperformedintheplatformperuser.Inaddition, social professionals can compare user’s records in order to conclude on theirrelationalpersonaldevelopmentprogress(e.g.Peterhasgainedmorepointsbysocializationactivitiesincomparisontoothers).

Last, but not least, the spider-graph (or radar-chart) is a two-dimensional chart used tographically displaying multivariate data of three or more quantitative variables. Thosevariablesarerepresentedonaxesstartingfromthesamepointanddevelopingradiallytoalldirections.Inthecurrentexample,seven(N=7)variableshavebeensupported,namelytheparticipation (loyaltyof theuser), thenumberof contacts in thepersonal social network,thenumberofpostsmadeintheplatform,thenumberoflikes,thegamificationpoints,thecurrentleveloftreatmentadherenceandtheperformanceonrequestedscales(lower-rightpartofFigure4).

5.3 ThePersonalReportingService

Although the clinical or social reporting services can present the current status and theprogressmadeinagroupofparticipants,thereisstilltheneedtohavepersonalreportsforspecific individuals in order to identify/highlight changes in their health conditions andpersonalprogresswhenfollowingatreatmentplan.




It isexpectedthatapersonalreportwouldincludeseriesoftimelines(eachonerelatedtosocial and medical variables) which will be based on recent clinical or social events andprofilestatus.Thecomparisonwiththehistoricaldata(orbaseline)willbepossiblethroughthe use of visual interactive elements which will render both the historical data and thecurrent user status (consider the example in Figure 10) in a personal reporting templatewithselfservicecapabilities(Josefioketal.,2015).

The personal reporting service will be accessed through the PLWD themselves or theircaregivers and professionals who look after the PLWD. It is expected that the templatedesignshouldincludethefollowingelements:

• PersonalInformationincludingtheonlineuserprofile• Namesofcaregiversandprofessionalswholookafterthisperson• Symptomsanddiagnosisinformation• Listofpersonalizedinterventions(eitherpharmacologicalornon-pharmacological)• Monitoringdata likeplotsofvariousmedicalandsocialvariables (performanceon

scales,interactiveinterventions,etc.).• Listofrecentalerts(ifavailable)• Asummaryofthepersonalsocialnetwork(optional)

ThepersonalreportingservicepresentedabovewillbeavailableonlinethroughtheCMMDplatformatanytime,butwillalsobeavailableinaprinter-friendlyformat.Thosepersonalreportsmay be used: 1. by doctors and social professionals during every day clinical andsocial processes, or could be stored in the local file system of the clinic (external to theCMMD)and2.byPLWDandtheircaregivers inordertokeeprecordsof theirownhealthandtreatmentmanagementefforts.OneexamplecanbefoundontheClinicalAssessmenttemplate of the Pearson (http://www.pearsonclinical.com) in the address (last access 28March,2017):http://images.pearsonclinical.com/images/pa/pdfs/16pf5karson.pdf.

Figure10.Exampleofriskdetectionusingout-of-rangedataplotoverhistoricaldatainthesocial,medicaland/orpersonalreporting

Inoverallthisreportingserviceshouldnotbeascomplicatedanddifficulttouseasmarkettools like SAP Crystal Reports(https://www.sap.com/product/analytics/crystal-reports.html) or EasyRiter (Dentrix, http://dentrixmarketplace.com/easyriter). It will bebased on ready-made printer-friendly templates to export the available information of auser personal profile, scales and interaction history. To be noted thatmedical and social




professionals will be responsible for selecting which data and visual elements will beavailabletobeincludedinthepersonalreporttemplate.




6 RecommendationsandconsiderationsC-MMDSRismeanttobeusedindigitalenvironmentsoutsidetheplatform,withintheNHSsystems. It is expected to provide additional information, which enriches the medicalrecordsofauser,andtobeinteroperablewiththeEHR.Inthisperspective,theaddedvalueof the C-MMD SR relies on the capability to consider the social dimension as part of ascreening report, with specific and meaningful information that affect the choice of atreatment.

In this way, the C-MMD SR gives the opportunity to facilitate the implementation of aholistic, integrated and multidisciplinary approach to dementia, having the dyad andallowingthedecision-makingprocessatthepointofcare;therefore,itwidenstherangeofinformation available in EHR,widening the sense and the possibility of the application ofsuch a tool, allowing integrated care solutions and an integrated interpretation of theillness.

Inordertofulfilthisassumption, it isrecommendedtoimplementaSRprovidingnotonlymeaningful,butalsosmartdata.“Smart”meansrich,intermsoforganicandholisticviewofthe illness, and it means interoperable, in terms of language technically adopted for thereport.Smart,alsomeanssafe:asecuritysystemtoprotectthedatacollectedinthereportisarecommendedpointinordertomaketheSRinteroperable.

TheamountofSmartDataproducedby theC-MMDplatformandcollected inC-MMDSRmightprovide insightsindifferentfields; intheclinicalenvironments,theycanbeusedtoevaluate the efficacy of treatments, they can improve the quality (and quantity) ofinformationaboutusers’reactionstocareinordertoimprovethedecisionmakingprocesstowardmorepersonalisedandmoreintegratedcare;insocialenvironments,suchdatamaybe adopted to monitor users and better understand their care needs: the single casemanagement canbe facilitatedby theprovisionof integrated information, combining theclinicaldatatogetherwiththetrendsofthemood,thefeelings,thesocialisationcapabilitiesandtheawarenessaboutthediseaseandtheneedtodealwithit.

It is important to clarify that it is a basic principle of C-MMD platform that the solutionproposedfortheSRwillbuildinteroperabilityoncurrentnationalsolutionsofEHRaswellasonnationalsystemsof integratedhealthandsocialcare.Thismeansthattheaccessto,the exchangeof and theprocessingon informationof the SRmust take into account theexistingandunderconstructiontechnologicalsolutionswithineHealthframeworkandmustrespectthelawsandregulationsaswellatEUandnationallevel;theinteroperability,withinthescopeofC-MMD,isthereforetheintegrationinthehealthandcaresystems.FortheC-MMDSR,therecommendationtoretainisaboutaminimumlevelofinteroperability,aimedatachievingessential requirementswith regard to semantic, technical,organisational andlegal interoperability. In the framework of C-MMD platform, the interoperability is a keyaspectforadoublepointofview:intermsofintegrationwithEHRssystemsinEUcountriesandintermsofmulti-disciplinarypurposeofthecontents.

Also theresearchspherecanbenefit fromthissmartdata; it is, somehowamatterofBigData. There is no lackofdata fordementia research,but theneed toexploit further this




data: the possibility to produce sharable data produced by a continuousmonitoringmaysignificantlyimprovetheresearchinthefield,andtheycanbeexploitedindifferentways.Tofullycaptureitspotential,C-MMDSRmaybeconsideredasatooltoproduceroutinelybig data whichwill allow a better understanding of the behaviours and environments ofpeoplelivingwithdementianotonlyafterdiagnosis,butforprevention,earlyidentificationanddiagnosis,oreventoretrospectivelyanalysetheyearsleadinguptodiagnosis.




ReferencesAgarwal S. et alia (2016). Guidelines for reporting of health interventions using mobilephones: mobile health (mHealth) evidence reporting and assessment (mERA) checklist.BMJ2016;352:i1174doi:10.1136/bmj.i1174

Di Croce M., Vercellesi L., Laccisaglia M., Bruno F. (2012). Medical reportingrecommendations:agapbetweenpracticalandtheoreticalapproachofjournalistsinItaly,AnnIstSuperSanita,48(2),pp.198-204.doi:10.4415/ANN_12_02_13.

EPSOS (2012). Smart Open Services for European Patients. Open eHealth initiative for aEuropean large-scalepilotofpatientsummaryandelectronicprescription.FinalDefinitionandFunctionalRequirements.D3.2.2

European Commission (2013). Guidelines on minimum/non exhaustive Patient SummarydatasetforElectronicExchangeinaccordancewiththeCross-BorderDirective2011/24/EU,Release1,eHealthNetwork,November2013.

European Commission (2016). Study on Big Data in Public Health, Telemedicine andHealthcare.FinalReport.

EuropeanCommission (2010). Interoperable eHealth isWorth it – Securing Benefits fromElectronicHealthRecordsandePrescribing.StudyReport2010.

EysenbachG.,(2011).CONSORT-EHEALTH:ImprovingandStandardizingEvaluationReportsofWeb-based andMobileHealth Interventions. JMed Internet Res. “011Oct-Dec; 13(4):e126.

Guss R. et alia, Clinical Psychology in the Early Stage of Dementia Care Pathway (2015).FacultyofPsychologyofOlderPeople,Ireland.

JosefiokM.,NorkusO.,SauerJ.(2015).AnApproachforaWeb-basedDiagnosisCockpitforthe Field of Neurology, WEB 2015: The Third International Conference on Building andExploringWebBasedEnvironments,pp.19-23.

Irving K., McGarrigle L., Expert Policy Paper 2012 (2012). Integrated Care Pathways forPeople with Dementia. Exploring the Potential for Ireland and the forthcoming NationalDementiaStrategy.TheAlzheimerSocietyIreland.

Larsson A,OxmanAD, Carling C, Herrin J (2003).Medicalmessages in themedia-barriersand solutions to improving medical journalism,Health Expect,6(4), pp. 323-31.doi:10.1046/j.1369-7625.2003.00228.x.

MilieuLtd– time.lex (2014).Overviewof thenational lawsonelectronichealthrecords inEUMember States and their interactionwith the previous cross-border eHealth services,July2014/7.

Philips A. C. et alia, (2016). Development and validation of the guideline for reportingevidence-based practice educational interventions and teaching (GREET). BMC MedicalEducation(2016)16:237DOI10.1186/s12909-016-0759-1




RinaldiG.(2015).BriefSummaryofthedifferenttypesofmedicalrecordsusedforthecareofpatients.ReportfromprojectADRIHEALTHMOB–1stStr./0009/0

SimonA., LeeR.C.,CookeD.L., LorenzettiD. (2005). InstitutionalMedical IncidentMedicalReportingSystems:AReview,AlbertaHeritageFoundationforMedicalResearch,17.ISBN1-894927-20-6.

ThorpeJ.,SmetD.,GessnerC. (2016).Guidelineontheelectronicexchangeofhealthdataunder Cross-Border Directive 2011/24/EU. Release 2, Patient Summary for unscheduledcare.JASEHNProject.

Wilkinson L.; Friendly M. (2009). The History of the Cluster Heat Map,The AmericanStatistician,63(2),pp.179–184.doi:10.1198/tas.2009.0033.

Keim D., Andrienko G., Fekete JD., Görg C., Kohlhammer J., Melançon G. (2008). VisualAnalytics: Definition, Process and Challenges. Information Visualization, LNCS 4950, pp.154–175.

Wong PC., J. Thomas (2004). Visual Analytics, IEEE Computer Graphics and Applications,24(5),pp.20–21.

(http://www.ehgi.eu/)

Customisation guidance document for CAREGIVERSPROMMD … · 2017-04-27 · D1.5 Customisation...

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