Improving Healthcare through Human City Interaction

Tim Woolliscroft

and Simon Polovina

Shefﬁeld Business School, Business Operation Systems, Shefﬁeld Hallam University, Shefﬁeld, U.K.

Conceptual Structures Research Group, Communication and Computing Research Centre, Cultural Communication and

Computing Research Institute (C3RI)| Department of Computing, Shefﬁeld Hallam University, Shefﬁeld, U.K.

Keywords:

Agents, Cyber-physical Systems, Healthcare, Human City Interaction, Human Computer Interaction, Internet

of Things, Smart Cities, Smart Communities, Structuration Theory.

Abstract:

The study of information technology has given insufﬁcient focus to a) the structural factors and b) the com-

munity perspective. As information systems become increasingly integrated with human systems these wider

inﬂuences are more important than ever. Human city interaction concepts including their interplay with cyber-

physical systems and social computing are appropriated to healthcare. Through Structuration Theory, insights

are given into how healthcare through the human city interaction lens can most effectively be improved.

1 INTRODUCTION

This paper explores how the concept of human com-

puter interaction and its notions of social comput-

ing and cyber-physical systems can improve the ef-

ﬁciency of healthcare. Human city interaction moves

the conceptual basis of human computer interaction

from the micro, individual user scale towards a macro,

city wide scale. As such it can also impact healthcare

practices given they are inherently community-based.

As NHS digitisation continues to meet resistance,

we argue that greater focus needs to be given to the

social aspects involved. Indeed, two-thirds of poten-

tial health information systems have not yet materi-

alised (House of Commons, 2013; Waterson, 2014).

We postulate that a greater focus on the structural fac-

tors might have had a different result.

The paper is laid out as follows: Structuration

Theory is used to appropriate human city interaction

concepts to healthcare. Based on this approach, the

human social challenges are highlighted and the re-

search gap addressed including the system design is-

sues. The paper concludes with the insights that hu-

man city interaction can bring to improving health-

care.

2 STRUCTURATION

Structuration Theory is a theory of agency and struc-

ture to help understand how people behave (Giddens,

1984). Agency and structure is the extent to which

people are free independent agents or are agents

whose behaviour is socially determined. Structuration

Theory emphasises the role of everyday social prac-

tice in consistently recreating social structure (Jones

and Karsten, 2008). Structuration Theory is often ar-

gued as relevant to dealing with ‘wicked’ unstructured

problems in the public sector (van Veenstra et al.,

2014).

Structuration Theory has frequently been applied

to information systems research to help understand

the relationship between information systems and

the people using them including the surrounding so-

cial context and social processes (Jones and Karsten,

2008; Checkland and Holwell, 1997). The need for

this approach is evident from the seismic impact that

information technology is already having on human

computer interaction by extending it beyond individ-

ual users interacting with individual computers to-

wards interaction between many people and many

computers across the internet.

3 HUMAN CITY INTERACTION

The idea of human city interaction emerges from

smart cities literature, connecting it to cyber-physical

systems and the internet of things (Naphade et al.,

2011; Jin et al., 2014). Human city interaction is

distinct from the idea of the smart city, in that the

smart city describes the urban environment whereas

172

Woolliscroft, T. and Polovina, S.

Improving Healthcare through Human City Interaction.

DOI: 10.5220/0006368401720177

In Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017) - Volume 3, pages 172-177

ISBN: 978-989-758-249-3

we deﬁne the concept of human city interaction as the

complex web of human computer interaction in the

smart city environment. Smartness is proportional to

the increased awareness that these digital technolo-

gies bring in as they extract this information from the

physical environment (Gurgen et al., 2013). Human

city interaction emphasises the complex web of hu-

man computer interaction in the smart city environ-

ment. Over the next few subsections we outline sev-

eral key important concepts the building blocks of hu-

man city interaction and its relevance to healthcare.

3.1 Smart Communities

A smart community brings together the interplay of

the cyber, physical, and social worlds; within this en-

vironment humans and physical things will interact

with each other through ubiquitous networks (Xia and

Ma, 2011). The combination of a focus on human in-

teractions and a connection with cyber-physical sys-

tems connects the concept of human city interaction

with the concept of smart community (Li et al., 2011;

Xia and Ma, 2011). These communities are also con-

nected with social computing and ﬁnding solutions to

societal problems including healthcare.

3.2 Social Computing

Social computing includes human social dynamics

connected to ICT technologies, with theoretical un-

derpinnings in both computational and social sciences

(Wang et al., 2007). Although the idea is usually as-

sociated with social media the origin of the term can

be traced back to the 1940’s to a paper by Vannevar

Bush that predicted many changes that have now be-

come reality, such as computer-supported collabora-

tion (Wang et al., 2007). There are speciﬁc exam-

ples of some of the components of social computing

including blogs, wikis, social bookmarking, peer-to-

peer networks, open source communities, photo and

video sharing communities, and online business net-

works (Parameswaran and Whinston, 2007). Social

computing is shifting computing to the edge of the

network where individuals with relatively low techni-

cal skills can apply their creativity and work collec-

tively with others (Wang et al., 2007; Parameswaran

and Whinston, 2007).

3.3 Web 2.0

Deﬁnitions of Web 2.0 are very similar to that of so-

cial computing. Both emphasise collaboration and

the ability of users to interact with each other. Web

2.0 includes features that enable collaboration includ-

ing well-known examples such as wikis and blogs

(Aghaei et al., 2012). The collaborative nature of

Web 2.0 has been emphasised by the phrase pro-

sumers, which emphasises that users of 2.0 are both

consumers of it and producers of it (Lupton, 2015).

The key difference between Web 2.0 and social com-

puting however is the emergence of terms including

Web 3.0 and Web 4.0. As such, Web 2.0 is becoming

associated with a point in time that we are moving

beyond (Aghaei et al., 2012).

3.4 Medicine 2.0 and Health 2.0

The terms Medicine 2.0 and Health 2.0 have been

coined to describe the application of Web 2.0 to the

healthcare arena. Some however have gone further

than this and suggest a movement towards a different

more equal relationship between patients and health-

care professionals (Bos et al., 2008). Given the col-

laborative nature of the Web’s evolution, information

technology will change healthcare signiﬁcantly; Web

2.0 technology in the form of Medicine 2.0 will im-

pact on all areas of medical practice (Hughes et al.,

2008). Similarly, Health 2.0 is shaping health care

with Web 2.0 tools with the result being a whole new

way of involving consumers in the health care system

including the transition towards participatory health-

care (Belt et al., 2010; Bos et al., 2008). Collabora-

tion, participation, openness and change are common

themes in the Health 2.0 literature (Belt et al., 2010;

Eysenbach, 2008). These ideas of collaboration and

change are key components of effective human city

interaction.

3.5 Collaborative Intelligence

Collaboration is a central theme in social computing,

Web 2.0 and Medicine 2.0 literature. The term collab-

orative intelligence however builds on this and sug-

gests a shift into a deeper form of collaboration that is

often referred to as collective or collaborative intelli-

gence. Collaborative intelligence has the potential to

result in positive change, extending into a claim that

mass collaboration changes everything (Tapscott and

Williams, 2008).

3.6 Collective Intelligence

There is a subtle distinction between collective or col-

laborative intelligence. Collaborative intelligence is a

system where each person or machine interacts au-

tonomously as part of decision making network. Col-

lective intelligence takes this idea a step further with

Improving Healthcare through Human City Interaction

173

a shift in power from the individual to the collec-

tive. Collective intelligence is not a new idea, but

it has received a new meaning through the emer-

gence of Web 2.0 applications (Leimeister, 2010).

This new meaning depicts the ability for people digi-

tally connected by the internet collectively to create

knowledge. There have been instances of amateur

knowledge surpassing professional knowledge, and

Wikipedia is given as the most recognised example of

this (Surowiecki, 2005; Boulos and Wheeler, 2007).

In relation to healthcare, collective intelligence

can improve evidence based medicine by drawing

on a larger knowledge base (Tapscott and Williams,

2008). Online networks enrich and contextu-

alise health information and reduce misinformation

(Aghaei et al., 2012; Boulos and Wheeler, 2007;

Hughes et al., 2008). Similarly, collective intelli-

gence might be the solution to concerns about health

information quality. As thousands of bloggers ex-

change ideas daily they are effectively acting as ﬁlters

for information-overloaded Web surfers (Boulos and

Wheeler, 2007).

Mass participation is central to the ideas of social

computing and collective intelligence. This assump-

tion is however subject to criticism. In reality only a

small proportion of users may actually be active pro-

ducers (Dijck and Nieborg, 2009). Also, mass partic-

ipation must ensure that the individual is not hypno-

tised by the crowd (Le Bon, 1897).

3.7 Web 4.0

The Web is evolving far beyond Web 2.0 to Web 4.0

(Aghaei et al., 2012; Patel, 2013; Choudhury, 2014).

Web 4.0 is described as the symbiotic Web in which

the human mind and machines can interact symbiot-

ically, including Medicine 4.0 and its links to human

city interaction (Choudhury, 2014; Naphade et al.,

2011; Roche and Rajabifard, 2012).

4 HUMAN-SOCIAL CHALLENGE

Certain social system problems are ill formulated,

have many different clients or agencies with conﬂict-

ing values, and have been referred to as ‘wicked prob-

lems’ (Churchman, 1967; Rittel and Webber, 1973).

Health services (in particular cancer services) are

such a wicked problem (Ferlie, 2013). Human city

interaction and its interplay with cyber-physical sys-

tems realises the collaborative user interactions that

are similarly of beneﬁt to healthcare (Xia and Ma,

2011; Cockerham, 2005). The wicked problems how-

ever present number of human social challenges that

can be usefully considered by referring to the theory

of structurisation that we met earlier.

4.1 Structuration and Wicked Problems

Structuration Theory connects directly to the idea

of addressing wicked problems (van Veenstra et al.,

2014). Structuation uses the term routinization to de-

scribe the idea of structure being continuously pro-

duced and reproduced through action. Through re-

peated actions a social order is established and certain

patterns of behaviour and ways of engaging in tasks

become institutionalised (Giddens, 1984). From rou-

tinization in healthcare we might conclude that there

are necessary structural constraints upon both patients

and professionals that might be preventing them from

moving towards a perfectly collaborative position.

Medicine 2.0 introduced the idea of including

patients and professionals working more closely to-

gether, but routinization may still be evident in the

cyber-physical models of healthcare. It has been as-

sumed that patients will simply behave as required for

the efﬁciency gains from healthcare cyber-physical

systems to be achieved (Broy et al., 2012). How-

ever, for the efﬁciency to be harnessed a wide variety

of complex social factors need to be considered in-

cluding psychological factors linked to human inter-

actions and lifestyle habits that have developed over

time. This assertion is supported elsewhere, as health

lifestyles are not the uncoordinated behaviours of dis-

connected individuals, but are routines linked to inter-

actions within groups (Cockerham, 2005).

After IT systems have been adopted, they need to

be assimilated to change existing work practices. Un-

til this has happened productivity may decline and if

innovation is not successfully assimilated they could

be worse off as previous successful routines will have

been lost (Setia et al., 2011). Further support arises

from social constraints, both in relation to cyber-

physical systems and IT artefacts that are shaped

by messy processes. Rather they are inﬂuenced by

the social system they are embedded in. Further-

more cyber-physical systems are particularly uncon-

trollable due to feed- back loops and the behaviour

of some parts of the system being difﬁcult to predict

(Beverungen, 2013).

Perhaps more signiﬁcant than the issue of integrat-

ing patients into a new health system based on human

city interaction are the cultural factors that impact

on the behaviour of healthcare professionals. Resis-

tance to change and conformity to routinization may

emerge from the desire to hang onto power and sta-

tus linked to current structures, reinforced by the per-

ception that change is just part of the government’s

ICEIS 2017 - 19th International Conference on Enterprise Information Systems

174

agenda to cut services or it might be based on uncon-

scious ideas about how things have always been done.

5 ADDRESSING THE GAP

Failure to consider wider structural factors in infor-

mation technology, health and health economics re-

search is far from superﬁcial oversight. This goes

right to the heart of the philosophical assumptions of

most researchers in these ﬁelds. Health economics

has remained insulated from theoretical debates that

have taken place in other areas of the social sciences

(Rickles et al., 2007; Lessard, 2007; Giddings, 2006).

Helpfully though, Structuration Theory has been in-

terrelated with other approaches, including a useful

study where this theory meets actor-network theory

(Greenhalgh and Stones, 2010).

Whatever the merits and demerits of the various

approaches, in the realm of healthcare technology

there is rarely sufﬁcient consideration of social con-

text. As we’ve previously stated, information tech-

nology has evolved far beyond a system of individ-

ual people interacting with individual computers; it

is now increasingly a complex Web of many peo-

ple interacting with a complex Web of digital devices

through the internet. Structuration Theory and hu-

man city interaction at least provides a fulcrum for

improving healthcare given its community-oriented

approach. Human agent collectives are described

as systems where people routinely collaborate with

autonomous software (Jennings et al., 2014). That

work highlights ﬂexible social interactions between

humans and the computers as they engage in synergis-

tic human computer collaboration, neatly ﬁtting with

the idea of human city interaction. This area how-

ever has also been under-researched; although some

research domains are beginning to explore aspects of

this area, none are dealing with it in its totality (Jen-

nings et al., 2014). Perhaps the time to emphasise

the community context in human-computer interac-

tion and the consequent effects on the associated tech-

nologies as we have described has arrived.

5.1 Design Issues

Human city interaction raises the challenge of inﬂu-

encing human behaviour and the use of design as a

tool (Naphade et al., 2011). Given that human city

interaction includes a complex Web of interactions

between people as well as machines, system design

in this area is not straightforward. Most current sys-

tems assume altruistic and benevolent behaviour from

users and fail to consider behavioural issues such as

the need to provide other pertinent aspects such as in-

centives in a collective context (Jennings et al., 2014).

The ethical issue of accountability also emerges from

the fact that the systems at times instruct us and at

other times are instructed by us, thus heightening the

potential tension between the human and computer

agents in the collective (Jennings et al., 2014). Enter-

prise Architecture however might be a useful frame-

work to help overcome some of these design chal-

lenges. It offers a perspective that holistically brings

together the myriad human and technological agents

needed to fulﬁl the collective purpose of the city,

including its provision of healthcare (van der Weel,

2017).

In linking the ideas of design to Structuration The-

ory for healthcare efﬁciency the process of design

needs to be applied akin to the complex web of city

structures. As people are as much the fabric of a city

as the technology, a change programme would involve

the people in designing the information technology

rather than changing peoples’ behaviour to ﬁt it. At

the same time, at a higher layer of conceptualisation

the people as well as the technology should be con-

sidered as components that need to be factored into

the system design.

Our approach is represented in Figure 1. Essen-

tially, this ﬁgure depicts the concepts and their direct

and indirect relationships from human city interaction

to improving healthcare.

6 CONCLUSION

The appropriation of human city interaction to health-

care could improve its efﬁciency. Ideally, it would

address the present healthcare information systems

failures as illustrated at the beginning of this paper

(House of Commons, 2013; Waterson, 2014). It is not

however that simple and difﬁculties can be expected

along the way. Introducing the technology that could

enable the improvements as we’ve described are as

likely to reduce efﬁciency as to increase it especially

at least in the short term. At least as much attention is

needed in creating the human conditions as the tech-

nology.

Social theory including Structuration Theory as

we have highlighted can highlight the social issues

that need to be considered to achieve the necessary

efﬁciency improvements. The ideas of routinization

and structural inﬂuences contained within Structura-

tion Theory we suggest contain insights that can make

efﬁciency improvement more likely. In short, greater

consideration of the structural factors that impact on

how people interact with each other and with the com-

Improving Healthcare through Human City Interaction

175

rely−on

Web/Medicine/Health: 2.0−4.0

presents

Smart Cities

situated−in

manifested−by

applied−by

Smart Communities

Social Computing

Cyber−Physical Systems

characterised−by

is−component−of

characterised−by

resulting−in

Insights

Routinization

appropriated−to−improving

Agency Structure

Human City Interaction

Heathcare

Structuration Theory

Human−Social Challenge

explained−by

to−address

characterised−by

Research Gap

applied−by

Figure 1: From Human City Interaction to Healthcare.

puting power that is increasingly interwoven into the

fabric akin to that of a smart city.

We have only ‘scratched the surface’ so to speak

of the complex social analysis that is required, and

we are not suggesting that Structuration Theory is

the only theory that can help understand this issue.

Rather, this theory articulates the probable challenges

and the ways to address them in the effective human-

computer interactions for improving healthcare.

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