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1 3
Electronic Markets
https://doi.org/10.1007/s12525-021-00484-1
RESEARCH PAPER
Keeping pacewiththehealthcare transformation: aliterature review
andresearch agenda foranew decade ofhealth information systems
research
NadineOstern1 · GuidoPerscheid2· CarolineReelitz2· JürgenMoormann2
Received: 11 December 2020 / Accepted: 26 May 2021
© The Author(s) 2021
Abstract
Background Accelerated by the coronavirus disease 2019 (Covid-19) pandemic, major and lasting changes are occuring in
healthcare structures, impacting people’s experiences and value creation in all aspects of their lives. Information systems
(IS) research can support analysing and anticipating resulting effects.
Aim The purpose of this study is to examine in what areas health information systems (HIS) researchers can assess changes
in healthcare structures and, thus, be prepared to shape future developments.
Method A hermeneutic framework is applied to conduct a literature review and to identify the contributions that IS research
makes in analysing and advancing the healthcare industry.
Results We draw an complexity theory by borrowing the concept of ’zooming-in and out’, which provides us with a overview
of the current, broad body of research in the HIS field. As a result of analysing almost 500 papers, we discovered various
shortcomings of current HIS research.
Contribution We derive future pathways and develop a research agenda that realigns IS research with the transformation of
the healthcare industry alreadyunder way.
Keywords Healthcare· Health information systems research· Research agenda
JEL Classifications I0· I1
Introduction
Particularly since the last decade, IT has opened up new
opportunities for ‘ehealth’ through telemedicine and remote
patient monitoring, alongside potential improvements in the
cost-effectiveness and accessibility of health care (Chiasson
& Davidson, 2004). Accordingly, health information systems
(HIS) research has come to focus on how healthcare organiza-
tions invest in and then assimilate HIS, looking in particular
at the impact of digitalization on healthcare costs, healthcare
quality, and patient privacy (Chen etal., 2019; Park, 2016).
Less attention has been paid to issues such as mobile
health, health information interchange, digital health com-
munities, and services that change customer expectations
and may lead to major disruptions (Chen etal., 2019; Park,
2016). These topics, however, are becoming increasingly
important due to the penetration of the user and health mar-
ket by external players, especially tech companies, providing
Responsible Editor: Shengnan Han
* Nadine Ostern
nadine.ostern@wiwi.uni-marburg.de
Guido Perscheid
g.perscheid@fs.de
Caroline Reelitz
c.reelitz@fs.de
Jürgen Moormann
j.moormann@fs.de
1 Chair forDigitization andProcess Management, Philipps-
University Marburg, Universitätsstraße 24, 35037Marburg,
Germany
2 School ofFinance & Management,
32-34,60322ProcessLabFrankfurtamMain, Adickesallee,
Germany
N.Ostern et al.
1 3
services such as fitness trackers, and surveillance software
for patient monitoring in hospitals (Gantori etal., 2020).
Modern IT, thus, becomes a catalyst to provide greater
operational efficiency, offering new possibilities for tech
companies to build new health-centred business models and
services (Park, 2016).
The ways in which tech companies are entering the
healthcare industry can be seen amid the spread of corona-
virus disease 2019 (Covid-19), which is pushing healthcare
systems to the edge of their capacities (Worldbank, 2020). In
this extraordinary condition, the pandemic has provided an
additional opportunity for tech companies that were hitherto
not active or not allowed to enter the healthcare industry
(Gantori etal., 2020).
We are currently seeing how entering the healthcare
market is actually taking place, particularly in the USA,
where tech companies are increasingly offering services to
help address some of the problems associated with Covid-
19. Google’s subsidiary Verily, for instance, facilitates the
automation of coronavirus symptom screening and provides
actionable, up-to-date information that supports community-
based decision-making (Landi, 2020). Although the collabo-
ration with Verily assists the US government in tracking
cases to identify the spread of the virus, it is reasonable to
suggest that Verily probably did not launch the screening
tool out of altruism. In fact, to receive preliminary screen-
ing results via the Verily app, citizens have to log into their
personal Google account (Greenwood, 2020). This allows
Verily to gain immense value by aggregating huge, struc-
tured data sets and analyse them to come up with new health
services, such as better tools for disease detection, new data
infrastructures, and insurance offerings that – for better or
for worse – may outplay current healthcare providers and
even disrupt whole healthcare ecosystems (CB Insights,
2018). Similarly, Amazon has started to provide cloud space
through Amazon Web Services to store health surveillance
data for the Australian government’s tracing app (Tillett,
2020), and Amazon Care, a division initially responsible for
handling internal staff care needs, now cooperates with the
Bill and Melinda Gates Foundation to distribute Covid-19
testing kits to US residents (Lee & Nilsson, 2020).
Looking at information systems (IS) researchers’ previ-
ous assessments of state-of-the-art healthcare-related IS lit-
erature reveals that most scholars seem to have little or no
concern for the beginning of those potentially long-lasting
changes that are occurring in the healthcare industry (Chen
etal., 2019). This is worrying, considering that it is already
apparent that the years ahead will be marked by economic
volatility and social upheaval as well as direct and indirect
health consequences, including sweeping transformations in
many of the world’s healthcare systems.
While it is clear that recent developments and the push
of tech and platform companies into the healthcare sector
can significantly improve the quality of life for billions of
people around the world, it will be accompanied by seri-
ous challenges for healthcare industries, governments, and
individuals (Park, 2016). Technological advances are, for
instance, giving rise to a plethora of smart, connected prod-
ucts and services, combining sensors, software, data, ana-
lytics, and connectivity in all kinds of ways, which in turns
leads to a restructuring of health industry boundaries and the
empowerment of novel actors, especially tech and platform
companies such as IBM, Google, and Amazon (Park, 2016).
Observing those changes, we need to develop a general
understanding of long-term trends such as digitalization and
blurring industry boundaries. As the pandemic is only an
amplifier of longer-lasting trends, it is likely that the con-
sequences and exogenous effects on the healthcare industry
will go far beyond the time of the current pandemic. Given
these observations, we wonder whether the IS research
domain is ready to capture, understand, and accompany
these developments, which require a holistic view of the
healthcare industry, its structures, and the interdependencies
between incumbents and new entrants. Thus, we argue that
it is now time to develop a more comprehensive understand-
ing of these developments and to determine the role that
IS research can play by asking: How can we prepare HIS
research to capture and anticipate current developments in
the healthcare industry?
To find answers to this question, our paper provides a lit-
erature overview of HIS research by ‘zooming in and zoom-
ing out’ (Gaskin etal., 2014) and by drawing on complexity
theory (Benbya etal., 2020). Since a healthcare system, like
the industry as a whole, can be understood as a complex,
digital socio-technical system (Kernick & Mitchell, 2009;
Therrien etal., 2017), zooming in and zooming out is a
way to view, capture, and theorize the causes, dynamics,
and consequences of a system’s complexity. Complex sys-
tems are characterized by adaptiveness, openness (Cilliers,
2001), and the diversity of actors and their mutual depend-
ency in the system, meaning that outcomes and research
span various levels within these systems, although the
boundaries of socio-technical systems are elusive. Assuming
that HIS research is just as complex as the socio-technical
system investigated, we first zoom in, focusing on concrete
research outcomes across levels (i.e., what we can actually
observe). Zooming in is followed by zooming out, which
means abstracting from the concrete level and embracing the
strengths and disparities of overall HIS research on a higher
level in which concrete research outcomes are embedded
(Benbya etal., 2020). Using this approach, we can capture
and understand the complexity of HIS research without los-
ing sight of concrete research issues and topics that drive
research in this field.
To do this, we chose a hermeneutic framework to guide
us in a thorough review and interpretation of HIS literature
Keeping pacewiththehealthcare transformation: aliterature review andresearch agenda for…
1 3
and lead us to the following overarching observations: (i)
The literature review determines the unique contribution that
IS research plays in analysing and advancing the healthcare
industry. However, it also shows that we are hardly prepared
to take up current developments and anticipate their con-
sequences. (ii)The reason for this unpreparedness is that
we currently neglect the ecosystem perspective and thus
ignore holistic approaches to resolve the striking number
of interrelated issues in HIS research. (iii) Based on the
unique insights of this literature review, our paper provides
a research agenda in which we use complexity theory to
discuss the consequences of current developments. This
theory assists IS researchers not only to better understand
developments and implications thereof for the healthcare
industry (and thus HIS research) but also to create a mean-
ingful impact on the future of this industry. Since we have
limited our research explicitly to the IS domain, our results
may not be generally applicable to other healthcare research
domains and we do not claim to provide an overview of
the literature in the field of HIS research. However, while
IS researchers cannot solve the pandemic directly, prepar-
ing them by providing a new research agenda will support
them in developing concepts and applications, thereby help-
ing them to overcome the negative effects of the pandemic.
In our opinion, it is particularly important that IS research,
and especially HIS-related research, obtains a deeper under-
standing of the needed transformation that is caused by digi-
talization and the emergence of new players catalysed by the
current pandemic.
The remainder of this paper is structured as follows.
The next section is concerned with the hermeneutic frame-
work used to conduct the systematic literature review. After
explaining the hermeneutic approach and the research steps,
we elaborate on the key findings by zooming in; that is,
we focus on the key results that emerge from analysing and
interpreting the literature for each of the phases defined in
the course of the literature sorting process. We then con-
centrate on zooming out, emphasizing the patterns and
interdependencies across phases, which helps us determine
the state of HIS research. The results of both parts of the
literature review – i.e., zooming in and zooming out (Benbya
etal., 2020; Gaskin etal., 2014) – support us in identifying
strengths, as well as drawbacks, in HIS research. On this
basis, we develop a research agenda that provides future
directions for how HIS research can evolve to anticipate the
impending transformation of the healthcare industry.
Literature review: ahermeneutic approach
To answer our research question, we conducted a literature
review based on hermeneutic understanding. In particular,
we followed Boell and Cecez-Kecmanovic (2014). They
proposed a hermeneutic philosophy as a theoretical founda-
tion and methodological approach that focuses on the inher-
ently interpretive processes in which a reader engages in an
ever-expanding and deepening understanding of a relevant
body of literature. Adopting a comprehensive literature
review approach that addresses well-known issues result-
ing from applying structured literature review approaches
(e.g., Webster & Watson, 2002), we strive toward the dual
purpose of hermeneutic analysis – i.e., to synthesize and
critically assess the body of knowledge (Boell & Cecez-
Kecmanovic, 2014). We would like to emphasize that the
hermeneutic approach to literature reviews is not in oppo-
sition to structured approaches. Rather, it addresses the
weaknesses of structured approaches (i.e., that they view
engagement with the literature as a routine task rather than
as a process of intellectual development) and complements
them with the hermeneutic perspective to create a holistic
approach for conducting literature reviews.
Theoretical underpinning andresearch method
A methodological means for engaging in reciprocal interpre-
tation of a whole and its constituent elements is the herme-
neutic cycle (Bleicher, 2017), which consists of a mutually
intertwined search and acquisition circle (Circle 1 in Fig.1)
and the wider analysis and interpretation circle (Circle 2 in
Fig.1) (Boell & Cecez-Kecmanovic, 2014). Figure1 depicts
the steps associated with the hermeneutic literature review.
The search and acquisition circle is shown on the left of the
figure, while the analysis and interpretation circle containing
steps of meta and content analysis is depicted on the right.
The two circles should be understood as an iterative proce-
dure, the nature of which will be explained in the following.
Circle 1: Search andacquisition
The hermeneutic literature review starts with the search and
acquisition circle, which is aimed at finding, acquiring, and
sorting relevant publications. In line with holistic think-
ing, we began with the identification of a rather small set
of highly relevant literature (Boell & Cecez-Kecmanovic,
2014) and went on to identify further literature on the basis
of progressively emerging keywords. This step is central
to the hermeneutic approach and addresses a criticism on
structured literature reviews, namely that they downplay the
importance of reading and dialogical interaction between
the literature and the reader in the literature search process,
reducing it to a formalistic search, stifling academic curi-
osity, and threatening quality and critique in scholarship
and research (Boell & Cecez-Kecmanovic, 2014; MacLure,
2005). Thus, while the search process remains formalized,
as in pure structured approaches, the hermeneutic approach
allows us to acquire more information about the problem at
N.Ostern et al.
1 3
hand and to identify more relevant sources of information
(Boell & Cecez-Kecmanovic, 2014).
Given our initial research question and the scope of
the review, we began by searching for papers in the Asso-
ciation for Information System’s (AIS’s) eLibrary over a
period of 30years (1990 to 2019). We consider this data-
base to be a source of the most significant publications in
the field of HIS research with a focus on the IS research
domain. Using the keywords ‘digital health’ and ‘digital
healthcare service’, we identified an initial set of 54 papers
based on the title, abstract, and keyword search. Engaging
in a first round of the hermeneutic search and acquisition
circle, we extended and refined these keywords by iden-
tifying emerging topics within the literature, as well as
using backward and forward search (Webster & Watson,
2002). In particular, with each additional paper identi-
fied through backward and forward search, we compared
keyword references in the papers to our list of keywords
and added them if there was sufficient content delimita-
tion. The decision to add a keyword was discussed with
all authors until consensus was reached. This led us to a
set of 12 keywords, including ‘electronic health’, ‘ehealth’,
‘mobile health’, ‘mhealth’, ‘health apps’, ‘tech health’,
‘healthcare services’, ‘healthcare informatics’, ‘medical
informatics’, and ‘health data’.
The selection of publications being considered for our
research comprised all journals belonging to the AIS eLi-
brary, the Senior Scholars’ Basket of Eight Journals (e.g.,
European Journal of Information Systems, Information Sys-
tems Research, and MIS Quarterly), well-regarded journals
following the analyses of Chiasson and Davidson (2004) and
Chen etal. (2019) (e.g., Business & Information Systems
Engineering, Communications of the ACM, and Decision
Support Systems), and the proceedings of the major AIS con-
ferences (e.g., Americas Conference on Information Systems
(AMCIS), International Conference on Information Systems
(ICIS)). An overview of the selected journals and proceed-
ings is provided in Appendix 1.
Using our set of keywords, we searched for each keyword
individually in the AIS eLibrary and the databases of the
respective journals. Subsequently, we created a dataset and
filtered out the duplicates, yielding a total number of 1,789
papers to be screened in the search and acquisition circle
(Circle 1 in Fig.1). Figure2 provides an overview of this
process by listing the total number of articles identified for
each journal individually.
The resulting 1,789 papers progressively passed through
the intertwined hermeneutic circles. Because of the large
number, we divided the papers at random into four equally
sized groups and assigned them to each of the authors. Each
author then screened the paper in his or her group. In the
course of several rounds of discussion, decisions on the inclu-
sion of keywords and articles in the literature review were
made by all authors, based on the original recommendations
of the author responsible for the respective group. To ensure
rigor and transparency of the analysis and results, we kept a
logbook in which all decisions of the authors and steps of the
literature review were recorded (Humphrey, 2011).
Given the abundance of topics that were already apparent
from titles and abstracts, we began to sort the publications
Fig. 1 Hermeneutic procedure applied to the literature review
Keeping pacewiththehealthcare transformation: aliterature review andresearch agenda for…
1 3
(Boell & Cecez-Kecmanovic, 2014). The process of sort-
ing proved to be challenging, as HIS research is diverse
and tends to be eclectic (Agarwal etal., 2010). This is why
researchers have developed frameworks for clustering and
analysing HIS research (LeRouge etal., 2007). So far, how-
ever, no consent on a unified framework has emerged, and
sorting is often strongly influenced by the authors’ views on
HIS research (Agarwal etal., 2010; Fichman etal., 2011).
For instance, Agarwal etal. (2010) predetermined health IT
adoption and health IT impact as major themes associated
with health ITs, acknowledging that this pre-categorization
of research topics made a systematic review of the growing
and increasingly complex HIS literature unfeasible. Con-
sequently, we decided to sort the articles we had identified
into groups inspired by and loosely related to the phases of
design science research (DSR) (Peffers etal., 2008), which
is an essential step in hermeneutics – i.e., defining guide-
lines to facilitate interpretive explication (Cole & Avison,
2007). DSR can be understood as a cumulative endeavour
and, therefore, we understood HIS research as accumula-
tive knowledge that can be reconstructed and consolidated
using DSR phases as guidance (vom Brocke etal., 2015;
vom Brocke etal., 2009). In particular, this helped us to
sort the articles without prejudice to expected HIS research
topics and clusters (Grondin, 2016).
In the past, researchers have used the DSR process in the
context of literature reviews to identify advances in design
science-related research outcomes (Offermann etal., 2010).
In this paper, we use the DSR phases – in the sense of a
rough guideline –as a neutral lens to classify articles accord-
ing to their research outcomes. We thereby assume that HIS
literature can be seen as an overall process, where research
results and progress are built upon each other and can be
classified into phases of problem identification and research
issues, definition of research objectives and possible solution
space, design and development of solutions, demonstration
of research effectiveness, innovativeness and acceptance,
and evaluation. These phases served as a guide to achieve
an outcome-oriented, first-hand sorting of articles, while this
approach also gave us the opportunity to take a bird’s-eye
view on HIS research. Note that we intentionally omitted
the last step of DSR – i.e., communication – as we regard
communication as present in all published articles. Based
on our initial reading, we assigned all 1,789 papers to the
phases and discussed this sorting in multiple rounds until all
authors agreed on the assignments.
Simultaneously, we applied criteria for the inclusion and
exclusion of articles. We included full papers published in
the journals and conference proceedings belonging to our
selection. We excluded articles that were abstract-only
papers, research-in-progress papers, panel formats, or work-
shop formats, as well as papers without direct thematic ref-
erence to our research objective. Additionally, during the
acquisition stage we stored selected papers in a separate
database whenever they fulfilled certain quality criteria (e.g.,
for separate studies using the same dataset, such as a confer-
ence publication and a subsequent journal publication, we
only used the articles with the most comprehensive reporting
of data to avoid over-representation).
The authors read the resulting 489 papers to identify
new core terms and keywords that were used in subsequent
searches, which not only provided the link to the analysis and
interpretation circle but also informed the literature search.
For this purpose, each author read the papers and kept notes
in the logbook that supported us in systematically recording
the review process and allowed us to shift from concentrating
on particular papers to focusing on scientific concepts (Boell
& Cecez-Kecmanovic, 2014; Webster & Watson, 2002).
Fig. 2 Steps of the search process to create the data set
N.Ostern et al.
1 3
Circle 2: Analysis andinterpretation
The search and acquisition circle formed part of the itera-
tive procedure of analysis and interpretation, whereby the
reading of individual papers was the key activity linking Cir-
cle 1 to the steps of Circle 2 (Boell & Cecez-Kecmanovic,
2014). Through orientational reading we gained a general
understanding of the literature, thus laying the foundation
for the subsequent steps of analysis and interpretation (Boell
& Cecez-Kecmanovic, 2014).
Within the analysis and interpretation circle, two types
of reviews were conducted for all identified and sorted arti-
cles: in a first round a meta-review, and in a second round a
content analysis of the papers was performed. Meta-reviews
are a useful tool for capturing and analysing massive quanti-
ties of knowledge using systematic measures and metrics.
We followed Palvia etal. (2015), who proposed a structured
method that is integrated into the hermeneutic approach. In
particular, having identified and sorted the relevant research
articles, we applied proposed review features, including
methodological approach, level of observation, sample size,
and research focus (Humphrey, 2011; Palvia etal., 2015) to
map, classify, and analyse the publications (Boell & Cecez-
Kecmanovic, 2014). In doing so, we slightly adapted the
classic meta-analysis by focusing on meta-synthesis, which
is similar to meta-analysis but follows an interpretive rather
than a deductive approach. Whereas a classic meta-analysis
tries to increase certainty in cause-and-effect conclusions,
meta-synthesis seeks to understand and explain the phenom-
ena of mainly qualitative work (Walsh & Downe, 2005).
The results of the meta-synthesis provided the basis for our
subsequent critical assessment of content. Furthermore, we
created a classification matrix based on particularly salient
features of the meta-review (i.e., levels of observation and
research foci), which facilitated and standardized the content
analysis.
Within the matrix, the levels of observation comprised
infrastructure (e.g., information exchange systems, elec-
tronic health records), individuals (patients and users of digi-
tal health services), professionals (e.g., nurses and general
practitioners), organizations (hospitals and other medical
institutions), and an ecosystem level. The latter is defined
as individuals, professionals, organizations, and other stake-
holders integrated via a digital infrastructure and aiming
to create a digital environment for networked services and
organizations with common resources and expectations
(Leon etal., 2016).To identify the most important concepts
used by researchers, we discussed a variety of approaches
to the derivation of research foci – i.e., areas contain-
ing related or similar concepts that are frequently used in
research on HIS. Finally, six research focus areas emerged,
covering all relevant research areas. To describe the core
HIS research issues addressed by these foci, we used the
following questions:
HIS strategy: What are the prerequisites for configuring,
implementing, using, maintaining, and finding value in
HISs?
HIS creation: How are HISs composed or developed?
HIS implementation: How are HISs implemented and inte-
grated?
HIS use and maintenance: How can HISs be used and main-
tained once in place?
Consequences and value of HIS: What are the conse-
quences and the added value of HISs?
HIS theorization: What is the intellectual contribution of
HIS research?
We used the classification matrix as a tool for assigning
publications and finding patterns across research articles and
phases. In particular, we used open, axial, and selective coding
(Corbin & Strauss, 1990) to analyse the content of articles in
a second round of the analysis and interpretation circle. Each
author individually assigned open codes to text passages while
reading the identified research articles, noting their thoughts in
the shared digital logbook that was used for constant compara-
tive analysis. Once all authors had agreed on the open codes,
axial coding – which is the process of relating the categories
and subcategories (including their properties) to each other
(Wolfswinkel etal., 2013) – was conducted by each author
and then discussed until consent on codes was reached. Next,
we conducted selective coding and discussed the codes until
theoretical saturation was achieved (Corbin & Strauss, 1990;
Matavire & Brown, 2008). For the sake of consistent terminol-
ogy, we borrowed terms from Chen etal. (2019), who used
multimethod data analysis to investigate the intellectual struc-
ture of HIS research. In particular, they proposed 22 major
research themes, which we assigned to the initial codes when-
ever possible. In two rounds of discussion in which we com-
pared the assignment of codes, two additional codes emerged,
which left us with a total of 24 theme labels (Appendix 2). By
discussing the codes at all stages of coding, theoretical satura-
tion emerged, which is the stage at which no additional data
are being found or properties of selective codes can be devel-
oped (Glaser & Straus, 1968; Saunders etal., 2018). In fact,
independent from each other, all authors saw similar instances
occurring over and over again, resulting in the same codes,
making us confident that we had reached theoretical saturation
(Saunders etal., 2018).
Finally, we entered the codes into the classification matrix,
which allowed us to identify patterns based on the meta and
content analysis. This enabled us to provide insights into the
strengths and weaknesses of current HIS research; these are
presented in the following section.
Keeping pacewiththehealthcare transformation: aliterature review andresearch agenda for…
1 3
Zooming‑in: key findings ofthephase‑based
literature analysis
In the following, we ‘zoom in’ (Gaskin etal., 2014) by
presenting key findings of the literature review for each
phase, illustrated by means of the classification matrices.
We assigned selective codes that emerged from the content
analysis to the fields of the matrices, with the numbers in
brackets indicating the frequency with which codes emerged.
Note that, for the sake of clarity, we displayed only the most
relevant research themes in the matrices and indicated the
number of further papers using the reference ‘other themes.’
A complete list of research themes for each phase can be
found in the appendix (Appendix 2). In the following, each
table shows the classification matrix and selective codes that
resulted from the meta and content analysis of papers in
the respective phase. The shaded areas in the matrix show
focused research themes (i.e., selective codes) and charac-
teristics of research articles that gave way to clusters (i.e.,
collections of themes that appear frequently and/or charac-
teristically for the respective focus).
Phase 1: Problem identification andresearch issues
Within the first phase, a large body of literature was found
(218 articles). This phase encompasses articles that identify
problems and novel research issues as a main outcome, with
the aim of pointing out shortcomings and provoking further
research. For instance, besides behavioural issues such as
missing user acceptances or trust in certain HISs, the design
and effectiveness of national health programs and/or HIS is a
frequently mentioned topic. It should be noted, however, that
literature assigned to this phase is extremely diverse in terms
of research foci, levels of observation, and research themes,
and hardly any gaps can be identified (Table1).
The first cluster (1a) encompasses the research focus of
HIS strategy, spanning all levels of observation and total-
ling 24 publications. HIS strategy appears to be of particular
relevance to the levels of organization and infrastructure.
Content-wise, the theme of health information interchange
is of particular interest, referring, for example, to the devel-
opment of a common data infrastructure (Ure etal., 2009),
consumer-oriented health websites (Fisher etal., 2007), and
security risks of inter-organizational data sharing (Zhang &
Pang, 2019). HIS productivity and HIS security are the sec-
ond most salient themes, focusing, for example, on measur-
ing the effectiveness of fitness apps (Babar etal., 2018) and
presenting challenges with regard to the interoperability of
medical devices (Sametinger etal., 2015).
The second cluster (1b), comprising 25 publications, rep-
resents the ecosystem level and focuses mainly on national
and cross-national HIS-related issues such as the relation
between ICT penetration and access to ehealth technolo-
gies across the European Union (Currie & Seddon, 2014),
as well as on the collaboration and involvement of different
Table 1 HIS publications assigned to the phase of problem identification and research issues
N.Ostern et al.
1 3
stakeholders (Chang etal., 2009; King, 2009). Most impor-
tant here is health information interchange – e.g., the pro-
vision, sharing, and transfer of information (Bhandari &
Maheshwari, 2009; Blinn & Kühne, 2013).
Cluster 1c covers the research focus of HIS use and
maintenance, as well as the consequences of HIS. Whereas
most papers addressing the HIS acceptance theme focus
on professionals’ or patients’ acceptance of specific tech-
nological solutions, such as telemedicine (Djamsbi etal.,
2009) or electronic health records (Gabel etal., 2019),
papers assigned to health information interchange focus
on topics related to information disclosure, such as self-
tracking applications (Gimpel etal., 2013). Finally, the HIS
outsourcing and performance theme concentrates on finan-
cial aspects in organizations, including potential for quality
improvements and cost reductions (Setia etal., 2011; Singh
etal., 2011).
Finally, the fourth cluster (1d) focuses on HIS theoriz-
ing with respect to the individual and infrastructure levels
of observation. Although this cluster represents a range of
theme labels (15), those addressing HIS acceptance, HIS
patient-centred care, as well as health analytics and data
mining predominate. Papers within the theme label HIS
acceptance cover a wide range of topics, such as the accept-
ance of telehealth (Tsai etal., 2019) up to the usage inten-
tions of gamified systems (Hamari & Koivisto, 2015). The
same applies to the papers assigned to the theme labels of
health analytics and data mining. Focusing on the infra-
structure level of observation, the identified papers mostly
review academic research on data mining in healthcare in
general (Werts & Adya, 2000), through to the review of
articles on the usage of data mining with regard to dia-
betes self-management (Idrissi etal., 2019). Papers on
HIS patient-centred care mostly address the challenges
and opportunities of patient-centred ehealth applications
(Sherer, 2014).
Apart from these clusters, quite a few research articles refer
to the infrastructure level of observation, addressing informa-
tion sharing in general (Li etal., 2008), electronic medical
records (George & Kohnke, 2018; Wessel etal., 2017), and
security and privacy issues (Zafar & Sneha, 2012).
Most common in terms of research methods within this
phase are case studies (57), followed by quantitative data
analyses (50), theoretical discussions (29), and literature
studies (14). In particular, case studies dominate when refer-
ring to the ecosystem or infrastructure level of observation,
whereas quantitative analyses are conducted when individu-
als or professionals are at the centre of the discussion. How-
ever, and unsurprisingly given the considerable diversity of
research themes within this phase, the variety of research
methods is also quite large, ranging from field studies (Paul
& McDaniel, 2004), to interviews (Knight etal., 2008), to
multimethod research designs (Motamarri etal., 2014).
Phase 2: Definition ofresearch objectives
andsolution space
The second phase of HIS research yielded a lower number
of articles (45) compared to the phase of problem identifica-
tion and research issues. The second phase comprises articles
that focus on proposing possible solutions to existing prob-
lems – i.e., introducing theory-driven, conceptual designs of
health ecosystems including health information interchange,
as well as scenario analyses anticipating the consequences of
HIS implementation on an organizational level. Based on the
research foci and levels of observation, we identified three
specific thematic clusters, as shown in Table2.
The first cluster (2a) comprises the ecosystem level of
observation and encompasses eight publications. Besides a
strong tendency toward theory-driven research, health infor-
mation interchange is the most common theme. We found
that the need to enable cooperation within networks and to
ensure accurate data input was addressed in most of the lit-
erature. While a majority of studies focus on the applica-
tion of HIS in networks within specific boundaries, such as
medical emergency coordination (Sujanto etal., 2008) or
Singapore’s crisis management in the fight against the SARS
outbreak in 2003 (Devadoss & Pan, 2004), other studies,
such as that by Aanestad etal. (2019), take an overarching
perspective, addressing the need to break down silo think-
ing and to start working in networks. Following the question
of why action research fails to persist over time, Braa etal.
(2004) highlighted the role of network alignment, criticizing
action research projects for failing to move beyond the proto-
typing phase and, therefore, failing to have any real impact.
Cluster 2b, encompassing nine publications, was derived
from the observation that studies within the organizational
level concentrated strongly on HIS use and maintenance and
the consequences of HIS research. Herein, a vast array of
topics was observed, such as the potential for cost reduc-
tion through HIS (Byrd & Byrd, 2009), the impact of HIS
on product and process innovation in European hospitals
(Arvanitis & Loukis, 2014), and the perceived effective-
ness of security risk management in healthcare (Zafar etal.,
2012). Moreover, we found that practice-oriented methods,
such as mixed-method approaches, surveys, data analyses,
and case studies, are used predominantly within this cluster.
Focusing on the latter, most studies analyse particular sce-
narios by using a rather small sample of cases, for instance,
Al-Qirim (2003) analysed factors influencing telemedicine
success in psychiatry and dermatology in Norway.
The third cluster (2c) was derived from analysis of the
HIS creation research focus (nine publications). Although
health information interchange is the most represented
in this cluster, a large number of further themes can be
observed. Studies within this cluster predominantly address
design aspects of system interoperability, focusing on data
Keeping pacewiththehealthcare transformation: aliterature review andresearch agenda for…
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processing and data interchange between the actors. HISs
mostly serve as a tool for the development or enhancement
of decision support systems, such as for real-time diagnos-
tics combining knowledge management with specific patient
information (Mitsa etal., 2007) or clinical learning models
incorporating decision support systems in the dosing process
of initial drug selection (Akcura & Ozdemir, 2008).
Phase 3: Design anddevelopment
The design and development phase comprises 84 research
articles concerned with the creation of novel IS artefacts
(e.g., theories, models, instantiations). We thereby refer to
Lee etal.’s (2015) definition of the IS artefact – i.e., the
information, technology, and social artefact that forms an
IS artefact by interacting. We assigned to this phase papers
that are explicitly concerned with developing solutions for
information exchange (e.g., design of messaging systems
or knowledge systems in hospitals), technological artefacts
(e.g., hardware or software used for generating electronic
health records), and social artefacts that relate to social
objects (e.g., design of national or international institutions
and policies to control specific health settings and patient-
centred solutions). Within the design and development
phase, the analysis revealed two clusters (Table3).
The first cluster (3a) was identified in the research focus
of HIS creation (31 articles). Here, the most frequent
research theme is HIS innovation followed by HIS and
patient-centred care, HIS productivity, and health analytics
and data mining. The focus is on specific contexts, mostly
medical conditions and artefacts developed for their treat-
ment, such as in the context of mental health/psychotherapy
(Neben etal., 2016; Patel etal., 2018), diabetes (Lichtenberg
etal., 2019), or obesity (Pletikosa etal., 2014). Furthermore,
information infrastructures or architectures – for instance,
for the process of drug prescription (Rodon & Silva, 2015),
or for communication between healthcare providers and
patients (Volland etal., 2014) – are represented.
The second aggregation of research articles is found in
cluster 3b, focusing on theoretical aspects of HIS (32 arti-
cles). Again, these studies span all levels of observation
(including infrastructure, individual, professional, organi-
zation, and ecosystem). Topics in this theme are diverse,
ranging from HIS on a national level (Preko etal., 2019), to
knowledge management in healthcare (Wu & Hu, 2012) to
security of HIS (Kenny & Connolly, 2016).
Beyond both clusters, it is evident that during design
and development, researchers do not deal with the conse-
quences of HIS, nor does HIS strategy play an important
role. Furthermore, only in the research focus of theori-
zation is the ecosystem level of some relevance to other
Table 2 HIS publications assigned to the definition of research objectives and solution space
N.Ostern et al.
1 3
levels (e.g., the individual level). It should be noted that
ecosystems are mostly referred to in terms of nations or
communities, without any transnational or global perspec-
tive. Furthermore, the term ‘ecosystem’ has not been used
in research, and within the other research focus areas, the
ecosystem level is barely represented. Moreover, articles
combining different perspectives of the single levels of
observation on HIS – namely individuals (i.e., patients),
professionals (i.e., medical staff), and organizations (e.g.,
hospitals) – are rare. During design and development,
potential users are not typically integrated, whereas it is
quite common to derive requirements and an application
design from theory, only involving users afterwards – e.g.,
in the form of a field experiment (e.g., Neben etal., 2016).
Surprisingly, theoretical papers outweigh papers on
practical project work, whereby the latter mostly focus on
a description of the infrastructure or artefact (e.g., Dehling
& Sunyaev, 2012; Theobalt etal., 2013; Varshney, 2004) or
are based on (mostly single) case studies (e.g., Hafermalz
& Riemer, 2016; Klecun etal., 2019; Ryan etal., 2019).
Within the design and development phase, the generation
of frameworks, research models, or taxonomies is preva-
lent (e.g., Preko etal., 2019; Tokar etal., 2015; Yang &
Varshney, 2016).
Phase 4: Demonstration
This phase includes 35 articles related to presenting and
elaborating on proposed solutions – e.g., how HIS can be
implemented organization-wide (e.g., via integration into
existing hospital-wide information systems), proposed
strategies and health policies, as well as novel solutions that
focus on health treatment improvements. Within the demon-
stration phase, we identified two clusters that emerged from
the meta and content analyses (Table4).
Cluster 4a (10 articles) is characterized by articles that
focus on HIS issues related to the infrastructure level, span-
ning the research foci of HIS strategy, creation, and deploy-
ment. Content-wise, the cluster deals mainly with technical
feasibility and desirability of HISs, including topics such
as the configuration of modular infrastructures that support
a seamless exchange of HISs within and between hospitals
(Dünnebeil etal., 2013). Moreover, papers in this cluster
address HIS practicability by determining general criteria
that are important for the design of health information sys-
tems (Maheshwari etal., 2006) or conduct HIS applica-
tion tests by carrying out prototypical implementations of
communication infrastructures. In particular, the latter are
tested and proven to meet specific technical standards to
Table 3 HIS publications assigned to the design and development phase
Keeping pacewiththehealthcare transformation: aliterature review andresearch agenda for…
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guarantee the frictionless transmission of health informa-
tion data (Schweiger etal., 2007). In contrast, Heine etal.
(2003) upscaled existing HIS solutions and tested the infra-
structure in large, realistic scenarios.
Conversely, cluster 4b(11 articles) is mainly concerned
with HIS use and maintenance, spanning several levels of
observation – i.e., infrastructure, individuals, professionals,
and organizations. Interestingly, papers in this cluster aim at
efficiency and added value when looking at the infrastruc-
ture and organizational levels, whereas researchers are more
interested in acceptance when focusing on the individual and
professional use of HISs. Overall, cluster 4b is primarily
concerned with organizational performance (e.g., increases
in efficiency due to better communication and seamless
transfer of patient health information) as well as user accept-
ance of new HISs.
Although the two clusters constitute a diverse set of lit-
erature and themes, it is apparent that research taking an
ecosystem perspective is very rarely represented. Across the
papers, only three are concerned with issues related to the
ecosystem level. In particular, Lebcir etal. (2008) applied
computer simulations in a theoretical demonstration as a
decision support system for policy and decision-makers
in the healthcare ecosystem. Abouzahra and Tan (2014)
used a mixed-methods approach to demonstrate a model
that supports clinical health management. Findikoglu and
Watson-Manheim (2016) addressed the consequences of the
implementation of electronic health records (EHR) systems
in developing countries.
Phase 5: Evaluation
The fifth phase includes 92 publications with a focus on
assessing existing or newly introduced HIS artefacts – i.e.,
concepts, policies, applications, and programs – thereby
proving their innovativeness, effectiveness, or user accept-
ance. As Table5 shows, three clusters were identified.
The main focus of publications in the evaluation
phase is on the infrastructure level, where most papers
are related to HIS creation and HIS use and maintenance.
Therefore, together with the publications pigeonholed to
HIS deployment and consequences of HIS, these articles
were summarized as the first cluster (5a, comprising 53
articles). The assessment of national HIS programs, as
well as mobile health solutions, are a frequent focus (10
papers). Articles on HIS use and maintenance are largely
related to the professional, organizational, and ecosystem
levels and were thus grouped as cluster 5b (10 articles).
A third cluster (5c – 11 articles) emerged from research
articles in HIS theorization. Here, papers at all levels of
observation were found. Research focusing on areas such
as HIS strategy and consequences of HIS are, with a few
Table 4 HIS publications assigned to the demonstration phase
N.Ostern et al.
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exceptions, not covered in the evaluation phase. Methods
used include interviews, focus groups, and observations
(e.g., Romanow etal., 2018). Experiments and simulation
are rarely applied (e.g., Mun & Lee, 2017). The number
of interviews shows a huge spread, starting with 12 and
reaching a maximum of 150 persons interviewed.
Under the evaluation lens, the ecosystem perspective
is covered by seven articles, but only three papers look
at cases, while the others focus on theorization or conse-
quences in terms of costs. Overall, popular topics in the
evaluation phase include mobile health and the fields of
electronic medical records (EMR) and EHR, e.g., Huerta
etal. (2013); Kim and Kwon (2019). The authors cover
these themes mostly from an HIS creation perspective;
thus, they deal with concrete concepts, prototypes, or even
implemented systems. In the evaluation phase, just nine
papers deal with HIS innovation – a good example being
Bullinger etal. (2012), who investigated the adoption of
open health platforms. We may conclude that, in most
cases, evaluation is related to more established technolo-
gies of HIS. As expected, most articles in this phase rely
on practice-oriented/empirical work (as opposed to theory-
driven/conceptual work). Just two papers (Ghanvatkar &
Rajan, 2019; Lin etal., 2017) deal with health analytics
and data mining, one of the emerging topics of HIS.
Zooming out: key findings oftheliterature
analysis acrossphases
Having elaborated on the key findings within each phase
of HIS research, we now ‘zoom out’ (Benbya etal., 2020;
Gaskin etal., 2014) to recognize the bigger picture.
Thereby, we ‘black-box’ the concrete research themes
(e.g., HIS implementation, health analytics, HIS inno-
vation) to focus on clusters across phases, highlighting
the breadth that HIS research encompasses (Leroy etal.,
2013). In particular, while we focused on analysing the
main topics within the different phases of HIS research in
the zoom-in section, we now abstract from those to per-
form a comparative analysis of emerging clusters across
those phases by zooming out. We do so by comparing the
different clusters, taking into account the aspects of the
level of observation and the research foci, which gave us
the opportunity to identify areas of strong emphasis and
potential gaps.
In particular, each author first conducted this compara-
tive analysis on their own and then discussed and identi-
fied the potential weaknesses together. This was done in
two rounds of discussion. In particular, it became obvious
which areas hold immense potential for further research
in healthcare (especially the penetration of new, initially
Table 5 HIS publications assigned to the evaluation phase
Keeping pacewiththehealthcare transformation: aliterature review andresearch agenda for…
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non-healthcare actors, such as tech companies or other
providers pushing into the industry). We summarize these
potentials for research by proposing four pathways that
can help HIS research to broaden its focus so that we can
better understand and contribute to current developments.
Notably, we expect that these insights will help to assess
the state-of-the-art of HIS research and its preparedness
for dealing with the consequences of Covid-19 and further
pandemics, as well as for coping with associated exog-
enous shocks.
In zooming out, we identified discrepancies between
phase 1 (problem identification and research issues) and
the subsequent phases. In particular, the diversity of top-
ics was considerably lower when it came to how research-
ers determined strategies; created, demonstrated, used, and
maintained HISs; and coped with the consequences thereof.
We observed that researchers pointed to a diverse set of
issues that span all levels of observation, especially in HIS
theorization, focusing on topics such as trust in HIS, data
analytics, and problems associated with the carrying out
of national health programs. Surprisingly, although we can
assume that researchers recognized the multidimensionality
of issues as a motivation to conduct HIS research, they did
not seem to approach HIS research issues in a comprehen-
sive and consistent way.
To illustrate this assertion, we point to the ‘shift of clus-
ters’ that can be observed when comparing the single phases,
from problem identification to the evaluation of HIS. We
note that clusters increasingly migrate ‘downwards’ (i.e.,
from the ecosystem level down to the infrastructure level)
and become even fewer. In line with Braa etal. (2004), we
suggest that extant HIS research has identified a multitude
of interrelated issues but has faced problems in translating
these approaches into concrete and holistic solutions. This
is reflected in the lower number of, and reduced diversity
in, clusters across research themes when we move through
the HIS research phases. Thus, we conclude that future HIS
research can be broadened by taking into account the fol-
lowing pathway:
HIS research is well-prepared and able to identify and
theorize on systemic problems related to the healthcare
industry. Nonetheless, it has the potential to address
these problems more thoroughly – i.e., to find solutions
that are as diverse as the problems and, thus,suitable
for coping with issues in the healthcare industry char-
acterized by the involvement of multiple actors, such as
governments, healthcare providers, tech companies, and
their interactions in diverse ecosystems (pathway 1).
As we have seen, HIS research has tended to focus on
important but incremental improvements to existing infra-
structures, particularly in the phases of demonstration and
evaluation, with the aim of presenting new IS artefacts and
conceptual or practical solutions. For instance, Choi and
Tulu (2017) considered improvements in user interfaces to
decrease the complexity of mobile health applications using
incremental interface design changes and altering touch
techniques. Similarly, Roehrig and Knorr (2000) designed
patient-centred access controls that can be implemented in
existing infrastructures to increase the privacy and security
of EHRs and avoid malicious access and misuse of patient
health information by third parties.
While we sincerely acknowledge these contributions and
wish to emphasize the multitude of papers that are con-
cerned with enhancements to existing infrastructures, we
would like to shift the view to the major challenges in HIS
research. These challenges include combating global and
fast-spreading diseases (e.g., malaria, tuberculosis, Covid-
19) and tracking health statuses accurately and efficiently,
especially in developing countries. All of these challenges
necessitate global and comprehensive solutions, spanning
individuals, organizations, and nations, and have to be
embedded in a global ecosystem (Winter & Butler, 2011).
Such grand challenges are, by nature, not easy to cope with,
and the intention to develop a comprehensive solution from
the perspective of IS researchers seems almost misguided.
However, HIS research is currently missing the opportunity
to make an impact, despite the discipline’s natural intersec-
tion with essential aspects of the healthcare industry (i.e.,
its infrastructures, technologies, and stakeholders, and the
interdependencies between these components). Thus, we
assert that:
HIS research has often focused on necessary and
incremental improvements to existing IS artefacts and
infrastructures. We see potential in shifting this focus to
developing solutions that combine existing IS artefacts
to allow for exchange of information and the creation of
open systems, which will enhance support for and under-
standing of the emergence of ecosystems (pathway 2).
By focusing on incremental improvements, HIS research
has become extraordinarily successful in solving isolated
issues, especially in relation to the problems of patients
and health service providers (e.g., hospitals and general
practitioners). However, we observed during our analysis
that spillover effects were seldom investigated. When, for
example, a new decision support system in a hospital was
introduced, positive consequences for patients, such as more
accurate diagnoses, were rarely of interest to the research.
In fact, our meta-analysis revealed that the level of obser-
vation for the majority of papers matched the level of ana-
lysed effects. While it is valid to investigate productivity
and efficiency gains by introducing a hospital-wide deci-
sion support system, we are convinced that spillover effects
(for instance, on patients) should also be within the focus of
HIS research. Therein, we suggest that HIS research has not
focused primarily on patients and their well-being but on IS
infrastructures and artefacts. However, patient well-being is
N.Ostern et al.
1 3
the ultimate direct (or indirect) goal of any HIS research (by
increasing the accuracy and shortening the time of diagno-
sis, improving treatment success rates, etc.). Thus, we pro-
pose that:
HIS research is experienced in solving isolated issues
related to the daily processes of healthcare providers;
however, we see much potential in considering the value
that is delivered by focusing on patient-centricity (path-
way 3).
Putting the patient at the centre of HIS research implies
shifting the focus of researchers to the patient’s own pro-
cesses. The question remains as to how HIS researchers can
support patient-centricity. While this is only possible by
understanding patients’ processes, we also see the need to
understand the whole system– i.e., the ecosystem in which
patients’ processes are embedded. The ecosystem perspec-
tive needs to consider networked services and organizations,
including resources and how they interact with stakeholders
of the healthcare industry (including patients). To date, we
observe, across phases the ecosystem perspective has largely
been neglected. To be precise, although HIS research seems
to be aware of the multilevel aspects of healthcare issues in
the problem identification phase, researchers appear to stop
or are hindered from developing solutions that go beyond
the development of prototypes (Braa etal., 2004). Thus, we
find that:
HIS research is capable of theorizing on an ecosystem
level (i.e., capturing the complexity of the socio-technical
health system), but would benefit from increasing the
transfer of these insights into research so as to develop
holistic solutions (pathway 4).
Looking at the strengths of HIS research, the reviewed
papers accentuate the unique contribution that IS research-
ers can make to better understand and design IS artefacts
for the healthcare context. This has been achieved by ana-
lysing empirical data and exploring contextual influences
through the application and elaboration of IS theories
(LeRouge etal., 2007). At the same time, our literature
review shows the incredible diversity and high level of
complexity of issues related to HISs, indicating that we
need solutions characterized by holism and the inclusion of
multiple actors (i.e., an integrative ecosystem perspective).
So far, by concentrating on incremental improvements to
existing infrastructures HIS research has widely failed to
reach the necessary holistic level.
We would like to emphasize that we recognize the
value of all previous approaches. Yet, it is necessary to ask
whether we as IS researchers are in a position to identify
current developments in the healthcare industry and to
anticipate the consequences triggered by pandemics or other
waves of disease. We acknowledge that this will be difficult
unless we take a more holistic view and try to understand
connections in the health ecosystems. Regarding whether
HIS research is in a position to capture and anticipate conse-
quences of the current push of tech companies in the health-
care industry catalysed, for example, by Covid-19, we assert
that this is hardly the case, even if IS research is well-placed
to interpret the expected socio-technical changes and adap-
tations within healthcare. Given the enormous potential for
disruption caused by, for instance, pandemics and its conse-
quences, such as the intrusion of technology companies into
the market, it is now time to question and redefine the role
of HIS research so that it can generate decisive impacts on
the developments in this industry.
Research agenda
To support HIS research for the transformation of the health-
care industry, we develop a research agenda that is informed
by complexity theory. This theory implies that complex,
socio-technical systems such as the healthcare industry can
fluctuate between different states, ranging from homogenous
forms of coevolution (i.e., a state where emergent structures
and processes become similar to each other) to chaotic sys-
tems that are characterized by increasing levels of tension,
which might result in extreme outcomes such as catastrophes
or crises (Benbya etal., 2020).
While coevolution and chaos represent possible extreme
states, the current situation – i.e., the penetration of tech
companies into the healthcare industry – is best described
by the dynamic process of emergence. Emergence is charac-
terized by a disequilibrium, which implies unpredictability
of outcomes that may lead to new structures, patterns, and
properties within a system characterized by self-organization
and bursts of amplification (Benbya etal., 2020; Kozlowski
etal., 2013). Given the dynamics resulting from this, it
seems impossible to predict the future; however, it is not
impossible to prepare for it.
In particular, the current dynamics within the healthcare
industry necessitate an understanding of exponential pro-
gress, not as the ability to foresee well-defined events in
space and time, but as an anticipation of the consequences
of emerging states and dynamic adaptive behaviours within
the industry (Benbya etal., 2020). The following research
agenda for HIS research is thus structured along three key
issues: anticipating the range of actors’ behaviours, determin-
ing boundaries and fostering collaboration in the healthcare
industry, and creating sustainable knowledge ecosystems.
According to these key issues, Table6 offers guiding ques-
tions for HIS researchers. Addressing all issues will contrib-
ute to an understanding of the entire healthcare industry and
the development of holistic solutions for a multitude of health
issues by involving different actors (e.g., patients, hospitals,
professionals, governments, NGOs). However, we propose
approaching the agenda stepwise, in the order of the key issues,
Keeping pacewiththehealthcare transformation: aliterature review andresearch agenda for…
1 3
Table 6 Agenda for a comprehensive research approach for future HIS-research
Areas of improvement Guiding statements for future HIS research Exemplary research questions and exemplary studies Pathway
Anticipate the range of actor behaviours • Determine existing and emergent actors in the healthcare
industry
• Identify actors’ interests and strategies in joining or staying in
the healthcare industry
• Align interests of established and new actors to achieve
patient-centricity
• Why do companies engage in activities that lead to the
blurring of industry boundaries (Nicholls-Nixon & Jasinski,
1995)?
• Does the nature of boundary-crossing actions differ between
firms (i.e., what is the value driver that leads companies into
the healthcare industry) (Akkerman & Bakker, 2011)?
• Does the infiltration of new actors into the healthcare system
promote organizational learning for the benefit of the patient
(Rivard etal., 2006)?
Pathway 1,
Pathway 3
Determine boundaries and foster collaboration • Capture and describe the blurring boundaries of the healthcare
industry
• Harness the advantages of blurring industry boundaries by
proposing and developing appropriate ecosystem infrastruc-
tures
• Create open systems that enable radical digital innovation
• How, and to what extent, do deregulation, globalization, and
breakthroughs in science and information technology contrib-
ute to the blurring of boundaries (Rycroft & Kash, 2004)?
• How can we leverage multi-company ecosystems with varying
value propositions (Schwetschke & Durugbo, 2018)?
• How is cross- and inter-industry innovation fostered, such as
through absorptive potential or creative imitation (Enkel &
Gassmann, 2010)?
Pathway 2
Create sustainable knowledge ecosystems • Design and maintain permeable knowledge management
systems for information interchange between actors in the
healthcare industry
• Implement structures of mutual benefit while protecting intel-
lectual property rights
• Ensure patient privacy while creating systems that allow for
trustworthy predictions
• How should (knowledge and data) management systems be
designed in order to balance information provision and privacy
issues (Shahmoradi etal., 2017)?
• Can we increase technology and information transfer by intro-
ducing appropriate intellectual property rights in the health-
care industry? (Fisman etal., 2004)?
Pathway 4
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first looking at the range of behaviours and consequences of
current developments for actors, then focusing on the blurring
lines of the healthcare industry, and finally investigating the
dissemination and sharing of knowledge, which we see as the
ultimate means to connect actors and infrastructures to cre-
ate a joint ecosystem. Table6 thereby provides key guiding
statements and exemplary research questions for future HIS
research that support researchers in taking one of the afore-
mentioned pathways. We structured guiding statements along
three major areas of improvement. In addition, we offer exem-
plary research questions to these statements, as well as inspir-
ing studies from other industries that have faced similar chal-
lenges and have been studied and supported by researchers.
Area ofimprovement 1: Anticipating therange
ofactor behaviours
As healthcare systems are becoming more open – for example,
through the penetration of new market actors and the use of
increasingly comprehensive and advanced health technologies
– accurately determining the boundaries of an industry and its
key actors is becoming more difficult. To model these systems,
we must carefully model every interaction in them (Benbya
etal., 2020), which first requires HIS researchers to identify
potential actors in the ecosystem rather than predetermining
assumed industry boundaries. As actors are not always evident,
we follow Benbya etal. (2020) in proposing Salthe’s (1985)
three-level specification, assisting researchers in identifying
actors at the focal level of what is actually observed (e.g., hos-
pitals, patients, and general practitioners) and its relations with
the parts described at the lower level (e.g., administrators and
legal professionals), taking into account entities or processes at
a higher level in which actors at the focal level are embedded
(e.g., national health system structures and supporting indus-
tries, such as the pharmaceutical or tech industries). These
examples are only illustrative, and criteria for levels have to be
suggested and discussed for each research endeavour.
To anticipate future developments in the healthcare indus-
try, we also need to analyse the strategies and interests of
actors for joining or staying in the healthcare industry. This
is especially important because, like other complex socio-
technical systems, the healthcare industry is made up of
large numbers of actors that influence each other in nonlin-
ear ways, continually adapting to internal or external ten-
sions (Holland etal., 1996). If tension rises above a certain
threshold, we might expect chaos or extreme outcomes. As
these are not beneficial for the actors in the system, the even-
tual goal is to align actors’ interests and strategies across a
specific range of behaviour to foster coevolution. This allows
for multi-layered ecosystems that encourage joint business
strategies in competitive landscapes, as well as the alignment
of business processes and IT across actors (Lee etal., 2013).
Area ofimprovement 2: Determining boundaries
andfostering collaboration
Actors build the cornerstones of the healthcare industry. Thus,
if we want to understand and capture its blurring boundaries,
there is a need to understand the complex causality of inter-
actions among heterogeneous actors. In particular, scholars
have emphasized that, in complex systems, outcomes rarely
have a single cause but rather result from the interdepend-
ence of multiple conditions, implying that there exist multiple
pathways from an input to an output (Benbya etal., 2020). To
capture interaction, we follow Kozlowski etal. (2013), who
envisioned a positive feedback process including bottom-up
dynamic interaction among lower-level actors (upward causa-
tion), which over time manifests at higher, collective levels,
while higher-level actors influence interaction at lower levels
(downward causation). As these kinds of causalities shape
interaction within healthcare ecosystems as well as at their
boundaries, HIS researchers need to account for multi-direc-
tional causality in the form of upward, downward, and circular
causality (Benbya etal., 2020; Kim, 1992).
Understanding casualties among actors in the healthcare
industry is important for harnessing the advantages of the
blurring of boundaries – e.g., by making use of the emergent
ecosystem for launching innovation cycles (Hacklin, 2008).
However, first, HIS researchers increasingly need to con-
sider the ecosystem perspective by investigating interactions
among actors and the role of IS infrastructures in foster-
ing collaborative health innovations. We propose a focus on
radical innovation, which is necessary to address the diver-
sity and interdependence of issues present in the healthcare
industry by putting the patient at the core of all innovation
efforts. HIS researchers, however, need to break down the
boundaries between different innovation phases and innova-
tion agencies, including a higher level of unpredictability
and overlap in their time horizons (Nambisan etal., 2017).
Notably, this requires actors in the healthcare industry to
discover new meaning around advanced technologies and IS
infrastructures whose design needs to facilitate shared mean-
ing among a diverse set of actors, thereby fuelling radical
digital innovations (Nambisan etal., 2017).
Area ofimprovement 3: Creating sustainable
knowledge ecosystems
We define knowledge dissemination and sharing as the ulti-
mate means of connecting actors and aligning actions within
common frameworks to shape an inclusive healthcare eco-
system. Paving the way for inclusive healthcare ecosystems
is thus necessary to address the current shortcomings of HIS
research as elaborated in the previous section.
Keeping pacewiththehealthcare transformation: aliterature review andresearch agenda for…
1 3
Addressing knowledge dissemination and sharing is
thereby of the utmost importance as we look at the health-
care industry in the current phase of emergence. This means
that the industry might go through several transition phases
in which existing actors, structures, and causal relationships
dissipate and new ones emerge, resulting in a different set
of causal relationships and eventually altering knowledge
claims (Benbya etal., 2020). Creating a permeable and
sustainable knowledge management system is necessary to
ensure the transfer of knowledge for the best outcomes for
the patient while securing the intellectual property rights and
competitive advantages of diverse actors such as hospitals
and other healthcare providers.
To be precise, we argue that to design sustainable knowl-
edge management systems, HIS researchers need to imple-
ment systems with structures that create mutual benefits
– i.e., encourage knowledge dissemination and sharing (e.g.,
open innovation) by actors in the healthcare industry. In a
comprehensive and sustainable knowledge management sys-
tem, however, not only corporations but also patients should
be encouraged to share knowledge. Using this information,
researchers and health service providers will be enabled to
create optimized infrastructures, processes, and products
(e.g., for predictive algorithms that improve treatment accu-
racy, or for assessing the likelihood of the occurrence of cer-
tain diseases and even of pandemics). At the same time, the
trustworthiness of predictions and the anonymity of health
information (and thus privacy) must be ensured. Bridging
this duality of data sharing and knowledge dissemination, on
the one hand, and protection of health information, on the
other, is therefore essential for future HIS research.
Conclusion
This paper analyses the HIS literature within the IS research
domain, prompted by the question of whether IS researchers
are prepared to capture and anticipate exogenous changes
and the consequences of current developments in the health-
care industry. While this review is limited to insights into the
IS research domain and does not claim to offer insights into
the health literature in general or related publications (e.g.,
governmental publications), we disclose several shortcom-
ings and three key issues. Based on these, we provide initial
guidance on how IS research can develop so that it is pre-
pared to capture the expected large and long-lasting changes
from current and possible future pandemics as well as the
necessary adaptation of global healthcare industries affect-
ing human agencies and experiences in all dimensions. Thus,
while adaptations in the healthcare industry are already
emerging, IS researchers have yet to develop a more com-
prehensive view of the healthcare industry. For this purpose,
we provide a research agenda that is structured in terms of
three areas of improvement: anticipating the range of actors’
behaviours, determining boundaries and fostering collabora-
tions among actors in the healthcare industry, and creating
sustainable knowledge management systems. In particular,
addressing these areas will assist IS researchers in balancing
the shortcomings of current HIS research with the unique
contribution that IS research plays in analysing, advancing,
and managing the healthcare industry. We are confident that
IS research is not only capable of anticipating changes and
consequences but also of actively shaping the future of the
healthcare industry by promoting sustainable healthcare eco-
systems, cultivating structures of mutual benefit and coop-
eration between actors, and realigning IS research to face
the imminent transformation of the healthcare industry. IS
research cannot contribute directly to solving the current
pandemic problems; however, it can contribute indirectly
triggering timely adaptations of novel technologies in global
health systems, and proposing new processes, business mod-
els, and systematic changes that will prepare health systems
to cope with increasing digitalization and emerging players
whose push into the market enabled by the exogenous effects
triggered by the pandemic.
While we are confident that the proposed research agenda
based on the analysis of HIS literature provides fruitful
arrays for being prepared in anticipating the future role of
IS research for the healthcare industry, our results need to be
reflected in light of their shortcomings. First and foremost,
we recognize that the selection of literature, which is limited
to the IS research domain, excludes other contextual factors
that are not primarily considered by IS researchers. Thus,
we cannot assume completeness, providing instead a broad
overview of current issues in HIS research. In addition, pos-
sible biases may have arisen due to the qualitative analysis
approach used. By independently coding and discussing
codes to the point of theoretical saturation, we are confident
that we largely eliminated biases in the thematic analysis.
However, data saturation could not be achieved. This means
that further insights could have emerged through the addi-
tion of other database searches and journals with a broader
scope. Additionally, the initial sorting of papers into single
defined phases of DSR research restricted multiple assign-
ments that could have led to different results. However, we
consider sorting as a necessary step of abstraction, especially
given the large number of papers analysed.
We deliberately considered IS research, for which we
have developed an agenda for potential future research
avenues. For each of those avenues, researchers should go
deeper into the subject matter in order to examine the com-
plexity of the paths shown and to include them in the analy-
sis (e.g., through in-depth case studies). However, it is also
clear from the issues identified that IS researchers cannot
solve current challenges by working on the pathways alone.
In fact, the issues identified in the research agenda are only
N.Ostern et al.
1 3
the starting point for further research, which should address
the proposed issues step by step and in cooperation with
other research disciplines. The latter is likely to generate fur-
ther and deeper-rooted problems, as well as, in turn, future
paths for research. Nevertheless, we are confident that this
paper provides an important first step in opening up HIS
research to better understand current developments in the
healthcare industry. Further, by following and enhancing the
proposed research pathways, we believe that HIS research
can contribute to and support changes already taking place
in the healthcare industry.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s12525- 021- 00484-1.
Funding Open Access funding enabled and organized by Projekt
DEAL.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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