The Internet of Things for basic nursing care—A scoping review

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Review

The Internet of Things for basic nursing care — A scoping review

Riitta Mieronkoski

^a,

*, Iman Azimi

^b

, Amir M. Rahmani

^c,d

, Riku Aantaa

^e,f

, Virpi Terävä

^a

, Pasi Liljeberg

^b

, Sanna Salanterä

^a,f

aDepartmentofNursingScience,UniversityofTurku,FI-20014TurunYliopisto,Finland

bDepartmentofInformationTechnology,UniversityofTurku,FI-20014TurunYliopisto,Finland

cDepartmentofComputerScience,UniversityofCaliforniaIrvine,USA

dInstituteofComputerTechnology,TU,Wien,Austria

eDepartmentofAnaesthesiology,IntensiveCare,EmergencyCareandPainMedicine,20014,UniversityofTurku,Finland

fTurkuUniversityHospital,20521,Turku,Finland

ARTICLE INFO

Articlehistory:

Received7July2016

Receivedinrevisedform29December2016 Accepted23January2017

Keywords:

Basicnursingcare Hospitals InternetofThings Nursinginformatics

ABSTRACT

Background:ThenoveltechnologyoftheInternetofThings(IoT)connectsobjectstotheInternetandits mostadvanced applicationsreﬁneobtained data fortheuser.We propose thatInternetofThings technologycanbeusedtopromotebasicnursingcareinthehospitalenvironmentbyimprovingthe qualityofcareandpatientsafety.

Objectives:TointroducetheconceptofInternetofThingstonursingaudiencebyexploringthestateofthe artofInternetofThingsbasedtechnologyforbasicnursingcareinthehospitalenvironment.

Datasourcesandreviewmethods:ScopingreviewmethodologyfollowingArksey&O’Malley’sstagesfrom onetofivewereusedtoexploretheextent,range,andnatureofcurrentliterature.Wesearchedeight databasesusingpredefinedsearchterms.Atotalof5030retrievalswerefoundwhichwerescreenedfor duplicationsandrelevancy tothestudytopic.265paperswerechosenforcloserscreeningof the abstractsand93forfulltextevaluation.62paperswereselectedforthereview.Theconstructsofthe papers, theInternetof Thingsbasedinnovations and thethemesofbasicnursing careinhospital environmentwereidentified.

Results:Mostofthepapersincludedinthereviewwerepeer-reviewedproceedingsoftechnological conferencesorarticlespublishedintechnologicaljournals.TheInternetofThingsbasedinnovations werepresentedinmethodologypapersortestedincasestudiesandusabilityassessments.Innovations were identiﬁedin several topics in four basic nursing care activities: comprehensiveassessment, periodicalclinicalreassessment,activitiesofdailylivingandcaremanagement.

Conclusions:InternetofThingstechnologyisprovidinginnovationsfortheuseofbasicnursingcare althoughtheinnovationsareemergingandstillinearlystages.Internetofthingsisyetvaguelyadoptedin nursing.ThepossibilitiesoftheInternetofThingsarenotyetexploitedaswellastheycould.Nursing sciencemightbeneﬁtfromdeeperinvolvementinengineeringresearchintheareaofhealth.

Whatisalreadyknownaboutthetopic?

The Internet of Things has emerged due to the recent technologicalrevolutionindeveloping low-cost,miniaturized, andenergy-efﬁcientwirelesssensordevices,ubiquitousInternet connectivityandadvancesincloudcomputing.

InternetofThingsisanovelparadigmwhereobjectswithunique identities can be integrated into an information network to

provideintelligentservicesforremotemonitoringofhealthand wellbeing.

Thereareseveralopinionpapersthathighlightthepossibilities ofInternet of Things inthe ﬁeld of healthcare. However,the nursingcareisrarelymentionedinthesewritings.

Whatthispaperadds

NumerousInternetofThingsbasedsolutionsareproposedfor basicnursingcareinhospitalenvironmentbuttheinnovations arestillonlyemergingandtestedincasestudiesandusability assessments.

*Correspondingauthor.

E-mailaddress:ritemi@utu.ﬁ(R.Mieronkoski).

InternationalJournalofNursingStudies69(2017)78–90

ContentslistsavailableatScienceDirect

International Journal of Nursing Studies

j o u r n a lh o m e p a g e : w w w . e l s e v i e r . c o m / i j n s

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TheconceptofInternetofThingsisatpresentmainlyusedin technologicalﬁeldandisnotyetadoptedtonursingresearch.

Nursingcouldbeneﬁtfromdeeperunderstandingof concepts developedandusedbyotherdisciplines.

1.Introduction

1.1.Background

Moderntechnologycanbeexploitedtoovercomesomeofthe challengesofbasicnursingcareinhospitals.Basicnursingcareis influencedbynursingstaffshortness,work environmentissues, impracticalphysicalcareenvironmentsanddifficultiesinidenti- fying the patients’ needs (Jangland et al., 2016; Lasater and Mchugh,2016;Westetal.,2005).Ononehand,thereisaneedto reinforce nursingprocedures concerningrequirementsfor basic nursing care, and on the other hand, traditional standalone equipmentinhospitalscanbeupgradedtocollect,transferand process the data efficiently and automatically. As a novel multidisciplinary concept, Internet of Things (IoT) can connect physicaland virtual things and provides advanced solutions to combineanduseinformationfromheterogeneoussources(Atzori etal.,2010).

Themostpromising applicationof advancedtechnologiesin nursingistheirabilitytosupportpatientsafetyandqualityofcare.

Toensurequality,safetyandvalueinhealthcare,clinicaldecisions needtobesupportedbyaccurate,timely,andup-to-dateclinical information (Institute of Medicine, 2011). Nursing informatics, deﬁned as “science and practice (that) integrates nursing, its informationandknowledge,withmanagementofinformationand communication technologies to promote the health of people, families, and communities worldwide.” (IMIA Special Interest Groupon NursingInformatics, 2009)incorporates technologies such as tele-healthcare applications, electronic health records, automateddataminingandbigdatatechnologies.

In addition to the informatics and software applications, sensorsandembeddedsystemsdevelopmentcanhaveasigniﬁ- cantrolein nursingcare.Medicalequipment,wearable sensors, andimplantabledevicesareexampleswhichareproposedtoassist nursinginhospitals(Caoetal.,2012;Fraileetal.,2010).Proposed softwareandhardwareentitiescanproviderecognizableimprove- mentsinbasicnursingcarealthoughthere isa missingpartto provideconnectivitybetweendifferentpartsandtoequipnursing

withacomprehensiveintelligentsystem.InternetofThingsisable toﬁllthisgapandhaveanimportantroleinthisdomainalthough itmaypartiallycoverandoverlaptheaforementionedentities(i.e., healthinformaticsandwearabledevices).

1.2.Basicnursingcare

Already the early nursing theorists Virginia Henderson and Florence Nightingale worked todefine the role and actions of nurses.The commondefinition for nursingactionsfor thebest patientoutcomeshasbeenatopicofdebate.However,itisagreed thatbasicnursingcare,alsoknownasthe“fundamentalsofcare” referstotheessentialelementsofcarethatarerequiredbyevery patientregardlessoftheirclinicalcondition(Kitsonetal.,2010).All basic nursing care actions share three main points: thecaring actionsareneededbyallpatients;theyarenotrelatedtoaspecific healthproblem;andtheyarenotdirectedtoaspecifichealthgoal (Englebrightetal.,2014).Inthisreview,weemployEnglebright’s etal.(2014)definitionforthebasicnursingcare.Thebasiccaring actions are divided into four activities. The first activity is comprehensiveassessmentincludingbaselineassessmentcon- ductedafterpatientadmissiontothehospital.Periodicalclinical reassessmentisthesecondactivitythatincludesregularassess- mentsthroughoutthehospitalization.Thethirdoneasactivities ofdailylivingconsistsofpersonalhygiene,mealsandactivities.

Finally,thelastoneiscaremanagementincludingcoordinationof careteamactivities.

1.3.InternetofThings

TheInternetofthingsisanadvancednetworkofobjects(i.e.

things) with unique identities, each of which interconnects or connects toa remote serverto providemore efﬁcient services (Atzorietal.,2010).Theamalgamationofvariousﬁeldssuchas data acquisition, communication and data analysis offers continues connectivity for the objectsto collect, exchange and combine data. Consequently, it is possible to achieve inclusive knowledgeabouttheentiresystem.

AccordingtothespecificationandfunctionalityofanInternetof Thingsbasedsystemtocollect,transmitand processhealthcare related data,thearchitecture of thesystem canbespecified in threelayers,theperceptionlayer,thegatewaylayerandthecloud layer (Al-Fuqaha et al., 2015; Touati and Tabish, 2013). The perception layer (Fig. 1) is defined to capture comprehensive

Fig.1.ThearchitectureofInternetofThingsbasedhealthcaresystemsinahospital.

R.Mieronkoskietal./InternationalJournalofNursingStudies69(2017)78–90 79

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healthandenvironmentaldatausingheterogeneoussensors.This layeristhelowestlayerandhasthemostcontactwiththestudied or monitored entities including patients, nurses and objects.

Medical devices (e.g. heart rate monitor, pulse oximeter and electrocardiographydevice),activityandlocalizationdevices(e.g.

accelerometerandbedpresence)andemergencybuttonsareitems thatstandinthislayertocollectrelateddata.

Thegatewaylayer(Fig.1)isallocatedtoconnectthesensors to a remote server. The captured data are transmitted via wireless protocols such as Bluetooth and Wi-Fi to a local gateway.Thegatewayprovidescontinuousconnectivityforthe sensors or other perception layer inputs and manages inter- ruptions. Then, it transfers the gathered data to a remote or local server called a cloud for further analysis. Recently, the concept of bringing a processing paradigm entitled as fog computingtothevicinityofthesensorswasproposed(Bonomi et al., 2014). This smart gateway is deﬁned to improve the functionality of the system (e.g. decreasing latency and increasing consistency in case of the unavailability of an Internetconnection) (Rahmani et al., 2015).

Thecloudlayer(Fig.1)isthethirdandmostremotesectionof the Internet of Things system. All the acquired data are transferred to the cloud via the gateway. The cloud can be obtainedeither viaInternetconnectedremoteserversprovided bythirdpartiesor bylocal servers connectedtolocalhospital informationsystem(HIS)toprovidemoreprotectiveprivacyand security.Usinghighprocessingpowerinthecloudplatform,data analytics,datafusionandanalysisareusedtofurtherprocessand developthedata(serverroomintheﬁgure).Theresultsofdata processingcanthenbeusedinpatientcare.Real-time/ofﬂinedata visualizationofpatientsandtheirsurroundingsareavailablevia monitorsandinterface devices (e.g.smartphones andtablets).

Thesystem couldalso enable healthcare personnelfor instant responses,feedbackandsettingadjustmentsviaanadministration control panel. Moreover, providing more comprehensive services, such data processing could send feedback todevices usedinnursingandpatientcaretoupdatetheirconﬁgurations automatically.

Thecloudlayer(Fig.1)isthethirdandmostremotesectionof theInternetofThingssystem.Alltheacquireddataaretransferred tothecloudfromthegateway.Thecloudcanbeprovidedintwo approaches.TheﬁrstapproachisobtainedviaInternetconnected

remote servers provided by third parties. The second one is achievedbylocalserversconnectedtolocalhospitalinformation system(HIS)toprovidemoreprotectiveprivacyandsecurity.Using thehighprocessingpowerinthecloudplatform,dataanalytics, data fusion and reasoning are implemented to obtain new knowledgeandresultsregardingincomingandstoreddata(server roominthefigure).Afterward,therelatedobtainedresultsalong withcollecteddataareprovidedfornurses.Real-time/offlinedata visualizationofpatientsandtheirsurroundingsareavailablevia monitorsandinterfacedevices(e.g.smartphonesandtablets).The system could also enable healthcare personnel for instant responses,feedbackandsettingadjustmentsviaanadministration controlpanel.Moreover,providingmorecomprehensiveservices, it could sendfeedback to nursingequipment and update their configurations automatically according to the patients’ and professionals’requirements.

Consequently, the Internet of Things enabled system is a paradigm that consists of embedded technologies of sensing, connecting and processing to bring advanced applications and servicesanyplace and anytime for differentﬁelds,especially in healthcareandnursing.Therefore,theusageofInternetofThings basedsystemsasthestateoftheartinhealthsciencesandbasic nursingcare,caninﬂuenceimprovementsinthequalityandsafety ofpatientcare.

1.4.Studyobjective

In thisscoping review weintroducetheconceptof Internet of Things to nursing by exploring the current literature to identify the extent, range, and nature of the literature on the Internet of Things in basic nursing care in the hospital environment. In addition, we introduce recent innovations utilizingtheInternetofThingsconceptin basicnursingcarein the hospitalenvironment.

2.Methods

Weusedascopingreviewmethodology,whichcanbeusedfor mappingthesizeandscopeofresearchonatopic,synthesizing ﬁndings,andidentifyinggapsintheliterature(GrantandBooth, 2009).Thisisanappropriateapproachgiventhatweexpecttoﬁnd paperswithdiversemethodologiesandevidenceonlyemergingin

Table1

Thesearchtermsanddatabases.

Database Searchterms Numberofpapersfound

Pubmed ”InternetofThings”OR“IoT” 429

“Nursinginformatics” 1096

Cinalh ”InternetofThings”OR“IoT” 29

Scopus ”InternetofThings”OR“IoT” 251

GoogleScholar (“InternetofThings”OR“IoT”)AND(“Nursing”OR“Hospital”) 32

ScienceDirect (“InternetofThings”OR“IoT”)AND(“Nursing”OR“Hospital”) 15

SpringerLink (“InternetofThings”OR“IoT”)AND(“Nursing”OR“Hospital”) 7

IEEExplore (“InternetofThings”OR“IoT)”AND(“Nursing”OR“Hospital”) 77

“Hygiene”AND(“Nursing”OR“Hospital”) 26

“Incontinence”AND(“Nursing”OR“Hospital”) 27

“Sleep”AND(“Nursing”OR“Hospital”) 247

“Respiration”AND(“Nursing”OR“Hospital”) 194

“Fall”AND(“Nursing”OR“Hospital”) 437

ACMDL (“InternetofThings”OR“IoT”)AND(“Nursing”OR“Hospital”) 8

“Hygiene”AND(“Nursing”OR“Hospital”) 12

“Incontinence”AND(“Nursing”OR“Hospital”) 1

“Sleep”AND(“Nursing”OR“Hospital”) 6

“Respiration”AND(“Nursing”OR“hospital”) 0

“Fall”AND(“Nursing”OR“hospital”) 23

80 R.Mieronkoskietal./InternationalJournalofNursingStudies69(2017)78–90

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Table 2

Summary of the analysis.

Activity Topics Articles IoT Layers Data Collection Target Group Design Paper Type Year Country

Perception Gateway Cloud Patient Nurse Environment Children Adults Elderly Discussion Empirical/

Methodology Case study

Usability Journal Proceedings

Periodical clinical reassessment

Vital signs Hart et al.

(2010)

p – – p

– – – p p

– – p

– – p 2010 CAN

Hu et al. (2010) p p

– p

– – – p p

– p

– – – p 2010 USA

Andre et al.

(2010)

p p – p – – – p p – – p – – p 2010 BEL

Zito et al.

(2011)

p p – p – – p p p – – p – p – 2011 IRL, ITA

Donnelly et al.

(2012)

p – – p – – – p p – – – p – p 2012 GBR

Fang et al.

(2012)

p p – p – – – p p – p – – – p 2012 CHN

Huang et al.

(2013)

p p – p – – – – p – – – p – p 2013 TWN

Mamun et al.

(2014)

p p p p – – – p p – – – p – p 2014 FIJ,BAN,

IRL Liu and Hsu

(2013)

p – p p – – – – p – – – p – p 2014 TWN

Shi-Lin et al.

(2015)

– p

– – – p p

– p

– – p

– 2015 CHN

Liu et al. (2015) p

– p p

– – – – p

– – – p p

– 2015 TWN

Güder et al.

(2016)

p – p p

– – – p p

– – p

– p

– 2016 USA

Michard (2016)

p p p p

– – – p

– – – – – p

– 2016 SUI

Neonatal monitoring Nachabe et al.

(2015)

p – p p

– – p

– – – – – p

– p 2015 FRA

Huang et al.

(2015)

p – – p – – p – – – – p – – p 2015 CHN,

USA

Pain Martinez-

Balleste et al.

(2014)

p – p p – – p – – – p – – – p 2014 ESP

Medication Jara et al.

(2010a)

p – p p – p – p p – p – – – p 2010 ESP,

GBR Jara et al.

(2010b)

p – p p – p – p p – p – – – p 2010 ESP

Laranjo et al.

(2012)

– – p

– p p

– – p

– p

– 2012 PRT

Jara et al.

(2014)

p p p p

– p

– p p

– p

– – p

– 2014 ESP

Zhang et al.

(2015)

p – p

– – p

– p p

– p

– – – p 2015 CHN

Hua-li et al.

(2015)

– – p

– – – – p

– – – p 2015 CHN

Activities of daily living

Sleep detection Biswas et al.

(2010)

– – p p – – – – p – – – p – p 2010 SGP

Rofouei et al.

(2011)

p – p p – – – p – – – p – – p 2011 USA

Liu and Hsu (2013)^a

p – p p – – – – p – – – p – p 2013 TWN

Rotariu et al.

(2013)

p p – p – – – p p – – p – – p 2013 USA

Zhu et al.

(2015)

p – p p – – – – p – – – p – p 2014 JPN

Liu et al.

(2015)^a

p – p p – – – – p – – – p p – 2015 TWN

Secretion Ang et al.

(2008)

– p p p

– – p p p

– – p

– – p 2008 MYS

R.Mieronkoskietal./InternationalJournalofNursingStudies69(2017)78–9081

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Table 2(Continued)

Activity Topics Articles IoT Layers Data Collection Target Group Design Paper Type Year Country

Perception Gateway Cloud Patient Nurse Environment Children Adults Elderly Discussion Empirical/

Methodology Case study

Usability Journal Proceedings

Wai et al.

(2010a)

p p p p – – p p p – – – p – p 2010 SGP,

GBR, FRA Wai et al.

(2010b)

p p p p – – p p p – – – p – p 2010 SGP,

GBR, FRA Yamada et al.

(2010)

p – – p – – p p p – – p – – p 2010 JPN

Wai et al.

(2011)

– p p p – – p p p – p – – – p 2011 SGP,

GBR Nilsson et al.

(2011)

p – – p

– – p p p

– – p

– – p 2011 SWE

Fuketa et al.

(2014)

p – – p

– – p p p

– p

– – – p 2014 JPN

Fall detection Huang et al.

(2009)

– p

– – – – p

– p

– – – p 2009 TWN

Rawashdeh et al. (2012)

– – p p

– – – – p

– – – p

– p 2012 USA

Visvanathan et al. (2012)

– p p p – – – – p – – p – – p 2012 AUS

Chou et al.

(2013)

p – – p – – – – p – – p – – p 2013 TWN

Enayati et al.

(2014)

– – p p – – – – p – p – – – p 2014 USA

Catarinucci et al. (2014)

– p p p p – – – p – – p – – p 2014 ITA

Schwarzmeier et al. (2014)

p – – p – – – – p – p – – – p 2014 DEU

Sriborrirux et al. (2014)

p – p p – – – – p – – p – – p 2014 THA

Mamun et al.

(2014)^a

p p p p p p

– p p

– – – p

– p 2014 FIJ,

BGD, IRL Catarinucci

et al. (2015)

– p p p p p

– – p

– p

– 2015 ITA

Activity monitoring Hu et al., (2010)^a

p p – p – – – p p – p – – – p 2010 USA

Schwarzmeier et al., (2014)^*

p – – p – – – – p – p – – – p 2014 DEU

Sriborrirux et al. (2014)^*

p – p p – – – – p – – p – – p 2014 THA

Care management

Decision making support system

Bruballa et al.

(2014)

– – p p p p – – – – – p – – p 2014 ESP

Manate et al.

(2014)

– – p p p p – – – – p – – – p 2014 ROU,

GBR Boyi et al.

(2014)

– – p p p p – – – – – p – p – 2014 CHN

Abinaya and Swathika (2015)

– – p p p

– – – – – p

– – p

– 2015 IND

Aishwarya et al. (2015)

– – p p

– p

– – – – p

– – p

– 2015 IND

Michard (2016)^a

p p p p p p

– – – – p

– – p

– 2016 SUI

Tracking (personnel, patients, devices)

Alharbe et al.

(2013)

– p p p p p

– – – – p

– – – p 2013 SAU,

GBR Catarinucci

et al. (2015)^a

– p p p p p – – p – – p – p – 2015 ITA

82R.Mieronkoskietal./InternationalJournalofNursingStudies69(2017)78–90

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Carvalho et al.

(2015)

p – – p p p

– – – – – p

– – p 2015 BRA

Nurse calling system Galinato et al.

(2015)

– – – p p

– – p p

– – – p p

– 2015 USA

Kanan and Elhassan (2015)

p p p p p

–

– – p p

– p

– – – p 2015 ARE

Sharma and Gautam (2015)

p p – p – – – p p – p – – – p 2015 IND

Comprehensive assessment

Hygiene Herman et al.

(2009)

– p – – p p – – – – – p – – p 2009 USA

Johnson et al.

(2012)

p – p – p p – – – – – – p p – 2012 USA

Meydanci et al.

(2013)

– – p

– p p

– – – – p

– – – p 2013 TUR

Asai et al.

(2013)

p – – – – p – – – – – – p – p 2013 JPN

Shhedi et al.

(2015)

p – – – p p – – – p – – – – p 2015 ROU

Shhedi et al.

(2015)

p – – – p p – – – – p – – – p 2015 ROU

Baslyman et al.

(2015)

p – p – p p – – – – – p – p – 2015 CAN

Misra et al.

(2015)

p – – – p p – – – – p – – – p 2015 IND

Galluzzi et al.

(2015)

p – p – p p – – – – – – p – p 2015 USA

Comfort Vicini et al.

(2012)

p – – p – – p – – – – – p – p 2012 ITA

aThe article is also utilized in other sections.

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theliteratureconcerningInternetofThingsbasedinnovationsin basicnursingcaresettings(Levacetal.,2010).Wefollowedthe scopingreviewguidelinesofArkseyandO’Malley(2005)inﬁve stages:1)identifyingtheresearchquestion2)identifyingrelevant studies3)deﬁningarelevantstudyselection4)chartingthedata and5)collating,summarizingandreportingtheresults.

Weexploredthefollowingquestions:

1.HowistheInternetofThingsusedinbasicnursingcare?

2.WhatarethebeneﬁtsofusingtheInternetofThingsinbasic nursingcare?

2.1.Identifyingrelevantstudies

The literature search was conducted in eight databases:

Pubmed,Cinahl,Scopus,ScienceDirect, ACMDL(Associationfor ComputingMachineryDigitalLibrary),IEEEXploreDL(Instituteof Electrical and Electronics Engineers Digital Library), Google Scholarand SpringerLink.Thedatabaseswereselectedtocover theﬁeldsofthemultidisciplinaryresearchtopic.Thesearchwas conductedinMarchandApril2016.Moreover,anadditionalsearch inthethreenursingdatabaseswasconductedinSeptember2016 toincludethewiderangeofnursinginformaticsliteraturetothe review.Atﬁrst allthenursingrelateddatabasesweresearched usingaBooleancombinationoftheterms“InternetofThing”OR

“IoT”andthetechnologicaldatabasesweresearchedfor“Internet ofThings”AND“Nursing”OR“Hospital”.Thesecondsearchwas conducted only in technological databases replacing the term InternetofThingswiththechosenbasicnursingcaretermstoﬁnd detailed information. Theseterms were chosen todescribethe aspectsthatareobjectiveanddetectable.Becauseofthenoveltyof theconceptofInternetofThings,notimelimitwasusedinﬁrst search.However,thesearchconcerningnursinginformaticswas limited to theyears 2006 to 2016. The review was limited to Englishlanguagepublications. Thecompletesearchstrategy for eachelectronicdatabaseislistedinTable1.

2.2.Studyselection

The inclusion criteria were 1) a scientiﬁc peer-reviewed publicationdescribingan InternetofThings basedsolution for basicnursingcare2)theInternetofThings solutionis usedor proposed for hospital environment 3) the term Internet of Thingsis used in the paper 4) thepaper is a clinical study, a review,a commentary,aneditorialoraconferenceproceeding.

The exclusion criteria were 1) the paper describes only a technical design’s development 2) the Internet of Things solution is used only for patient monitoring outside the hospitalenvironment3)theInternetof Thingssolutionis only used for self-monitoring 4) the publication is a book, a book chapter,a magazineor a letter.

2.3.Chartingthedata

Information on authors, their country and publication year werecollected. The type of the article and study design were analyzed.TheInternetofThingsinnovationswereidentifiedand labelledtodescribethebasicnursingcaretopics.Thetechnical developmentstate ofthethree layersof theInternet ofThings based system architecture was identified. Alsothe main target patientgroupwasspecifiedintochildren,adultsandtheelderly, althoughifnopatientgroupwasmentionedin anarticle,adult patientswerechosen.Theresultsoftheanalysisarecollectedin Table2.

3.Results

3.1.Descriptionofprocessandﬁndings

Of the 5030 articles originally identiﬁed, 149 articles were removedasduplicates.Thetitleswerescreenedand4615papers were excluded as non-relevant to the topic. 265 papers were chosenforcloserassessmentandidentiﬁedaspotentiallyrelevant.

93full-textarticleswereassessedforeligibility,andﬁnally62were included in the qualitative synthesis (See Fig. 2 for the ﬂow diagram).Despitethelargenumberofarticlesofthesearchforthe term “nursing informatics”, only one article met the inclusion criteria.

Thevastmajorityofthearticleswerepeer-reviewedproceed- ingsoftechnologicalconferences.Theseincludeddescriptionsof InternetofThingsbasedinnovationmethodologyormethodology testedinacasestudyorusabilitytestsinthehospitalenvironment.

Onlyonearticlewaspublishedinanursingjournal,twoinmedical journals,and allother articleswere publishedin technological journals.The journalarticlesdidnot differ frompeer-reviewed proceedingpapers in studydesigns.Wefoundnoclinicaltrials with comparisons or randomized designs. The articles were publishedbetweentheyears2008–2016andtheywerefrom30 countriesacrossfourcontinents.MostoftheInternetof Things solutionsweretargetedtoadultandelderlypatientswithchronic diseases.Onlyafewweredesignedforapediatricpopulation.The datausedintheInternetofThingssolutionswerecollectedinmost casesfrompatientsand theenvironmentandmore rarelyfrom nurses.Most of theinnovations proposedwererelated tovital signsdetectionandweresetunderperiodicalclinicalreassess- mentactivitiesofbasicnursingcare.Theothertopicsinperiodical clinicalreassessmentactivitieswereneonatalmonitoring,pain managementandmedication.Comprehensiveassessmentactiv- itiesincludedtopicsofhygieneandcomfort.Physicalactivity,fall detection, sleep, and secretion monitoring were set under Activities of daily living. Finally, care management activities includedtopics ofdecision makingsupport,trackingpersonnel, patientsanddevises,andnursecallingsystem.Someofthetopics couldhave been setunder several activities,but only onewas selected.TheﬁndingsaredescribedinTable2.

3.2.InternetofThingsbasedinnovationsforbasicnursingcareinthe hospitalenvironment

3.2.1.Periodicalclinicalreassessment

With Internet of Things-based solutions vital signs can be recordedusingwirelessdevicesconnectedtoagateway(Hartetal., 2010;Shi-Linetal.,2015),bodywornwirelesssensors(Andreetal., 2010;Donnellyetal.,2012;Huangetal.,2013)orambientsensors attachedonwallsorobjects(Güderetal.,2016;Mamunetal.,2014;

Huangetal.,2015;Zitoetal.,2011).Wirelessdetectionsystems havetheadvantageofgivingpatientsreal-timedependableand continuous monitoring without causing any inconvenience to patients(Huetal.,2010).Agoodexampleisacufﬂessnoninvasive measurementofbloodpressureusingpulsewavetransittimeasa partofamultifunctionaldevice,containingcontinuousmeasure- mentofsevenleadelectrocardiography,respiration,temperature, bloodpressure,peripheralcapillaryoxygensaturation,themotion stateofapatientinrealtime(Fangetal.,2012).Theheartrateofa patientcanalsobedetectedusingawirelessringprobe(Huang etal.,2013)oraversatilesystemwhichdetectselectrocardiogra- phy,heartrate,respirationwaveformandrate,skintemperature andmotionwithasinglewearablesensor(Donnellyetal.,2012).

Thetriggeringalgorithmsaresettoalarmforearlyrecognitionof patientsrequiringurgentattention.Someoftheinnovationshave the advantage of detecting both physiological parameters and

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trackingpatientsmovementsusingthesamehardware(Donnelly etal.,2012;Huetal.,2010;Mamunetal.,2014).

Several systemsfor non-invasiveand continuous respiration monitoringhave been developed both for adults and children.

Respiratory rateand pattern can be detected contactless from chestmovements,usingultra-widebandtechnology(Huangetal., 2015;Zitoetal.,2011).Thesensorcanalsobeconnectedintoa patient’s nasal prongs (Andre et al., 2010) or attached into a breathingmask(Güderetal.,2016)todetectrespirationthrough airﬂowhumiditychanges. Humiditychanges ionic conductivity whichcanbemeasuredelectricallyand thedatacanbefurther transmitted to a smartphone or tablet computer for post- processing(Güderetal.,2016).Anintelligentcontact-freesensing pad under the patient on a hospital bed can also measure respirationbyrecordingthe changesin thecapacitive coupling betweenthetracesofthepadandcorrelatingthemtorespiration (Hartetal.,2010).

For neonatal monitoring, detection of respiration and the possibleapneaofaninfantcanbedonebyobtainingabreathing signalfromaninfant'schestvibration.Analgorithmisappliedto locatethechestoftheinfantduetopossiblemovementandtoset offanalarmincaseofapnea(Huangetal.,2015).Alsofortheuseof neonatal intensive care unit nurses, a newborn’s physiological parameters, such as heart rate and temperature, and the environmental parameters, such as humidity of the incubator, canbe detected viaa wireless sensor network (Nachabe etal., 2015).Thesensorsareconnectedtoadatahubdeviceprovided withasoftwareagentforsenseddatapreprocessingandtheserver publishes the data into the hospital information system. In additiontophysiologicalparameterdetection,Martinez-Balleste etal.(2014)haveproposedanautomatedpaindetectionsystemfor infantsusingdataacquisitionwithwearablesensors,video and audioprocessing.Thesystemautomaticallyanalysesthepainor

discomfortlevelofaninfantandraisesalarmuponpredetermined conditions.

Considering medication in hospital surroundings, Jaraet al.

(2014,2010a,b)introduceapharmaceuticalintelligentinformation systemfordrugdeliverytomitigateadversedrugreactions.Inthe system,tags,e.g.,RadioFrequencyIdentiﬁcation,areprovidedfor each medicine; then, utilizing tag readers, the medicine is detected,andrelateddataissenttothecloudlayer.Therelated dataandthepatientproﬁlearestoredandtheneedtoinformthe healthcarepersonnelaboutpossibleconsequences(e.g.,allergies) andfurtheractionsisconsidered.Inasimilarmanner,Laranjoetal.

(2012)alsoofferasolutionusingRadioFrequencyIdentiﬁcation tags for identifying hospital entities to implement medication control from the prescription to pharmaceutical drug control.

Othersystemsincludinganintelligentmedicinebox(Zhangetal., 2015)anda pharmaceuticallogisticsand supplychain management system (Hua-lietal., 2015)are proposed tomonitor and controlpatientmedicationandtoimplementtracingandsupply chain management of medicines in hospitalsfrom purchaseto provisionanddistribution.

3.2.2.Activitiesofdailyliving

Sleepdetectionisinmostcasesbasedonvitalsignsmonitoring throughout sleep. Rofouei et al. (2011) have proposed a non- invasive wearable neck-cuff sleep detection tool for the early diagnosisofsleepapneawhichprovidesa summaryofpossible apneaeventsandaquantiﬁcationoftheseverityofsleepapnea.

Alsoalongtermdetectionofpatients’skintemperatureusinga wireless sensor system provides information of the circadian rhythm ofpatients(Rotariuet al., 2013).For versatilesleep/off sleepmonitoring,basicaccelerometersensorsandmotion-sensing mattresses can be used to collect information about the sleep activitypatternsofpatients.Biswasetal.(2010)havesuccessfully Fig.2.FlowdiagramofliteraturesearchmodiﬁedfromPRISMA(Moheretal.,2010).

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doneactigraphy based onbody-worn accelerometer sensors to remotelymonitorandstudythesleep-wakecycleofpatientsata nursinghome.Asoftmotionsensingmattressorsensorslocated underamattresscanalsocollectdataaboutphysicalactivitiesina bed(Liu et al.,2015; Zhu etal., 2015; Liu and Hsu,2013).The correspondingdigitalsignalscollectedbythemattresssensorsare classiﬁedintodifferenteventssuchason/offbed,sleepposture, pressuredistribution,movementcounts,respirationandheartrate (LiuandHsu,2013).

ConsideringInternetofThingsrelatedsystems,Angetal.(2008) haveintroducedawirelessintelligentincontinencemanagement systemtomonitorsecretion andtotransmitwetnessdatatoa central system and then further to alert the nurses via SMS.

Similarly,Waietal.(2010a,b)presentasystemcomprisingthree InternetofThingslayers.Thefirstlayerisdefinedtosensediaper wetness. The second layer is specified to provide a wireless connectionforthesensorsinthehospital.Finally,thethirdlayer handlessystem operations,providesaccess topatients’inconti- nenceprofilesandsendsnotificationsincaseofdetectingsoiled diapers.Toimplementthenotificationssystemmoreefficiently,a smartphonereminderisalsointegratedintothesystem(Waietal., 2011).Varioussolutionsincludingdisposablewetsensorsplaced inside ofdiapers are alsoproposed. Theyare defined to detect diaperwetnessandtotransmitthedatatothecloudforfurther actions(Fuketaetal.,2014;Nilssonetal.,2011;Yamadaetal.,2010) Apatientalertsystemandapassivefallmonitoringsystemare proposedbyHuangetal.(2009)andSchwarzmeieretal.(2014) respectivelytoprovideinstantpositioninformationandemergen- cysituationdetection.Amotionmonitoringsystem,includingfive accelerometer sensors and a 3D avatar (an embodiment of a person) to illustrate the movements, is offered to reduce falls (Rawashdeh et al., 2012). Fall prevention systems are also introduced to notify the nurses about high risk fall activities (Visvanathan et al., 2012) and bed falling (Chou et al., 2013).

Context-awaresystemsarespeciﬁedtoimplementfalldetection usingvisualsensors(Bianetal.,2015).Inthisapproach,acamerais installed ona wall ora ceiling in a room insteadof attaching devicestopatients. Thecameraoutputs areanalyzedbyonline video processing methods instantaneously and related fall informationareextractedandtransferredtohealthcare personnel’scomputers (Enayatiet al.,2014).Also mobilesystemscan providefalldetectionforhospitalssuchasaroboticsystemoffered byMamunetal.(2014).Alongwithpatientconditionmonitoring, thesystemisenabledbyacameraanda3Dlasersensordetects falls and provides emergency notiﬁcations. In addition to fall detectionandprevention,therearesystemstocarryoutin-general activitymonitoringconsideringpatient’sactivitiescontinuously.

Real-timemonitoringusinganecklacetagisproposedtoexploit activitydata.Thisdatacanbeinformationregardingdailyactivity- level and level of functional ability (Sriborrirux et al., 2014).

Providingwirelessacutecare,anon-contactDopplersensorisalso usedtofulﬁllpatientmonitoringconsideringpatient’svitalsigns andmotions(Huetal.,2010).

3.2.3.Caremanagement

AsMichard(2016)proposes,computerswillbeabletointegrate the historical, clinical, physiologic and biological information necessarytopredictadverseevents,proposethebesttherapyand ensurethecareisdeliveredproperly.Whilethedatagetsbiggerit becomesvitaltoﬁndtherelevantinformationquicklyandeasily forefﬁcientandaccuratedecisionmaking.Ontologybaseddata modellingisusedtoclassifytherecordsstoredinonedatabase( Boyi et al., 2014) and the relationships between sensors and devicescanbedetermined(Manateetal.,2014).Withthehelpof algorithms,the systems can detectdiseases and suggest treat- mentsbasedonstatisticalcalculationsbasedonabigamountof

rawdata(Aishwaryaetal.,2015).Thismaybeparticularlyusefulin emergencycare(AbinayaandSwathika,2015;Boyietal.,2014).

AsmarthospitalsystemproposedbyCatarinuccietal.(2015, 2014)offerslocalizationforentities(e.g.,patients,personneland devices)alongwithemergencysituationmanagement;Carvalho et al. (2015) propose a model for individuals in nursing home frameworkfortrackingpurpose,andAlharbeetal.(2013)assertsa system to detect people and items in hospitals. Providing a connected networkusing theInternet ofThings and intelligent servicesinthecloud,alsothenursingcallingsystemisreinforced inhospitals.AnInternetofThingsbasedcalllightsystemusesicons andphrasestoallowpatientstospecifytheirneedswhenmakinga nursecallrequest.Thus,thenursingstaffsareinformedregarding thepurposeoftheircallupontheinitiationofthecalllightrequest (Galinatoetal.,2015).Alsotheinformationofpatientsandnurses positioningcanreinforcethenursingcallingsystemandminimize thetimebetweenthepatientassistancerequestandnursearrival (KananandElhassan,2015;SharmaandGautam,2015).

3.2.4.Comprehensiveassessment

Hand hygiene as a signiﬁcant methodto mitigate infection transmissioninhospitalsandhasbeenreinforcedbyInternetof Thingsrelatedsystems.Baslymanetal.(2015)presentareal-time handhygienemonitoring tomonitorhealthcareprofessionalsin hospitalroomsandprovideareminderwhetherhandhygieneis missed.Asaiet al.(2013)alsooffera systemusingsensorsand interface devices to encourage individuals to practice hand antisepsis. Moreover, different systems are proposed for hand hygienemonitoringusinginstalledsensorsinhospitalroomsand user-tagsforpersonnel(Misraetal.,2015;Meydancietal.,2013;

Johnsonetal.,2012;Hermanetal.,2009).Shhedietal.(Shhedi et al., 2015) alsointroduce a system to monitorindividuals in hospitalrooms.Theirsystemrecognizeswhetherapersonenters theroom,complieswithhandhygieneorleavestheroom.Using positioning sensors, their system is enabled to monitor hand movementsduringhandhygiene.Similarly,asystemisproposed by Galluzzi et al. (2015) to monitorhand washing duration in hospitals and to classify hand hygienemovements using wrist wornsensors.

Differentfromtheotherproposedsolutionsused mainlyfor patientdetectionandmanagement,Vicinietal.(2012)introduces a novel Internet of Things based device for the comfort of hospitalizedchildren.Theinteractivedeviceenablessocialization not only with the hospital personnel but with other people regardlessoftheillnessorhospitalenvironment.Byplayingactive learninggamesthechildrenaregiventheopportunityoflearning andgrowingduringtheirexperienceinhospitalandgainingastate ofwellbeing(Vicinietal.,2012).

ThemainInternetofThingssolutionsidentiﬁedinthisreview aresummarizedinFig.3.

4.Discussion

Thefactthatmostoftheincludedarticleswerefromtechnology fieldcanbeinterpretedatleastintwoways.Firstly,thetopicof InternetofThingsinnursingisatinfancyasmoreresearchand implementationisrequired.Thetechnologicalfieldhasatradition oftestingandpublishingnewmethodologiesinearlystagesincase studiesandusabilitytests.Secondly,thearticlesinnursingfield mayhaveinsufficienttechnicaldescriptionofuseddevisesoruse different terminology for similar technology. Because of the terminological issues, an additional literature search was con- ductedinSeptember2016innursinginformatics.However,itwas notveryrelevanttothetopicandonlyonemorearticlemetthe inclusioncriteriaand couldbeincludedinthereview(Galinato etal.,2015).Ourstudyrevealedthatnursinginformaticsresearch

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hasnotyetfocusedonInternetofThingsanditspossibilitiesin basicnursingcare.Nursinginformaticsmostlyconcernsintegra- tion of the nursing information and knowledge with the information management technologies. However, Internet of Thingscouldofferanewapproachtoprovidereal-timewireless healthmonitoringandcloudcomputingalsoinbasicnursingcare toenableintelligentdecision-makingsupportfornurses.

The reviewed papers target at patient centered issues to improvethequalityofnursingcarewithpersonatedhealthand functioningproﬁles,andtoimprovepatientsafetywithautomated alertsystemsandcontinuousrealtimemonitoring.Innovationsin care management provide information about the location and amountofavailableresources,themeansofmanagementanduse ofbigdata.Most innovationswerebasedonthemonitoringof patients’stategivingthenursesvitalinformationandsupporting the assessment and decision making processes. While nurses devotea greatdeal oftheirtime todocumentation, medication administration,andcarecoordinationandsomewhatlesstimeto actualpatientcareactivities (Hendrich etal.,2008), oneof the main advantages of using new Internet of Things solutions in hospitals is the automation of patient data collection and processingutilizing low cost sensors,devices and technologies.

Moreover,itenablesthehospitalsystemtoformalizetheincoming rawdataintostandardelectronichealthrecord.Thisallowsnurses tousemoretimeforpatientcareinsteadofroutinedetectionof patients’vitalsignsandtransferringpatientdatatotheelectronic patientrecords.Alsototallynewinnovationsforproblemswere

offered;automatedtrackingofpatientsandpersonnelalongwith falldetectionandnursecallingsystemsgivetheorganizationnew meansof promoting patient safety.The Internet ofThings also brings new opportunities to the still unsolved and continuous struggleagainstthehealthcareassociatedinfectionsbyproviding automatedhandhygienedetectionandreminders.

Avaluablepropertyoftheseinnovationsisthattheyaremostly inconspicuousandallowthepatienttomovemorefreelywhich leadstotheimprovementofthetraditionallypassivatinghospital environment.Wirelesssolutionspromoteafeelingcomfortforall patientsparticularlyincasesofchildrenanddisorientedpatients, andalsopromotespatientsafety.Anothervalueistheopportunity toincludefamilyinthecarebyofferingrealtimedataremotely,if thefamilyisnotabletobepresentinthehospital(Nachabeetal., 2015;Martinez-Ballesteetal.,2014).

Personalizedsmartservicescouldalsobeprovidedforpatients in hospitalsusingInternet ofThingsbasedplatforms.Acquiring andstoringvariousinformation(e.g.,medicalparameters,activities,etc.)fromapatientduringtheirhospitalstayalongwiththe patient’smedicalhistory,providesacomprehensiveunderstand- ing about the patient’sstate. Considering this knowledge,it is possible to use data analysis algorithms including machine learning (Murphy,2012)andpatternrecognition(Bishop,2006) methods to offer personalized services for each patient. For instance,patientswouldachieve anadvantagein diagnosisand treatmentproceduresbyenablingpersonalizeddecisionmaking approachesandsubsequentlyminimizingmistakes.

Fig.3. InternetofThingssolutionsfornursinginhospitalenvironment.