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Evolving competencies to align
electronic medical records –
a dynamic resource-based
perspective on hospitals’
co-evolutionary information
systems alignment capability
Pien Walraven, Rogier van de Wetering, Remko Helms and
Marjolein Cani€
els
Open University of the Netherlands, Heerlen, The Netherlands, and
Johan Versendaal
Open University of the Netherlands, Heerlen, The Netherlands and
HU University of Applied Sciences Utrecht, Utrecht, The Netherlands
Abstract
Purpose –Advanced Electronic Medical Records (EMR) provide many potential benefits to hospitals.
However, because of their broad scope, many stakeholders deal with the EMR and a continuous effort has to be
made to keep up with internal and external change. Therefore, hospitals need to deliberately shape their
organizational competencies considering the pursuit of alignment, i.e. making sure that the EMR remains
optimally aligned with strategies, goals and needs of the hospital and its stakeholders. This paper aims to
investigate the evolutionary paths of these alignment competencies and their drivers, from a theoretical
perspective of co-evolutionary information systems alignment (COISA).
Design/methodology/approach –This paper reports on a longitudinal multiple case study of three Dutch
hospitals which each recently implemented an advanced EMR system. The authors conducted 35 in-depth
interviews in 2 phases (before and after go-live of the EMR), and studied documentation related to the EMR
implementations.
Findings –The findings show that each hospital’s COISA capability shows a different evolutionary path.
However, two of the three case hospitals ended up coordinating part of their COISA capability to an ecosystem
level, i.e. they incorporated other hospitals using the same EMR system to coordinate their alignment efforts,
either from an operational perspective, or in terms of orchestration and strategy. The found evolutionary paths’
key drivers include “stakeholder initiative”,“accumulating experience”,“driving events”and “emerging
issues”.
Originality/value –The findings help healthcare practitioners to deliberately shape their organization’s
COISA capability in pursuit of EMR alignment. Furthermore, the authors add to the knowledge base on co-
evolutionary approaches to alignment through the longitudinal approach.
Keywords Electronic medical records, Co-evolutionary information systems alignment, Capability evolution,
Dynamic resource-based perspective, Business-IT alignment
Paper type Research paper
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© Pien Walraven, Rogier van de Wetering, Remko Helms, Marjolein Cani€
els and Johan Versendaal.
Published by Emerald Publishing Limited. This article is published under the Creative Commons
Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works
of this article (for both commercial and non-commercial purposes), subject to full attribution to the
original publication and authors. The full terms of this licence may be seen at http://creativecommons.
org/licences/by/4.0/legalcode
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1477-7266.htm
Received 8 October 2021
Revised 9 March 2022
Accepted 10 March 2022
Journal of Health Organization and
Management
Vol. 36 No. 9, 2022
pp. 112-132
Emerald Publishing Limited
1477-7266
DOI 10.1108/JHOM-10-2021-0379
1. Introduction
Electronic Medical Records (EMR) have become an increasingly important resource for
modern healthcare in Western countries, with many contemporary hospitals rapidly
implementing advanced EMR. Traditionally, these EMR involve electronic repositories of
patients’medical histories (Kohli and Tan, 2016). However, advanced EMR provide many
additional functionalities and advantages such as hospital-wide integrated information,
medical decision-support and direct patient access via patient portals (Carvalho et al., 2019).
As a consequence, EMR become interdependent with an increasing amount of processes.
Through these developments, many stakeholders deal with EMR, all having their own views
on how to apply the EMR appropriately (Davidson et al., 2018). Given these different and
sometimes contradicting interests, it is challenging to develop and maintain the EMR such
that it optimally aligns with the strategies, goals and needs of the hospital and its
stakeholders. Coping with this complexity requires hospitals to actively shape their
capabilities to reach and maintain a certain degree of alignment of their EMR (Walraven et al.,
2020). In doing so, potential benefits of the EMR such as cost savings, improved patient
experience and better decision-making can be leveraged.
The specific conditions characterizing EMR in hospitals are exemplary of complex
conditions where co-evolutionary approaches to alignment capabilities are argued to be
useful (Amarilli et al., 2017;Benbya and McKelvey, 2006). While some traditional approaches
to alignment view the concept as an end-state (Chan and Reich, 2007), this relatively new
approach involves multi-level effects, multi-directional causalities, non-linearity and
feedback loops, with a focus on the “[...] series of co-evolutionary moves that makes IS
aligned over time”(Benbya and McKelvey, 2006, p. 288). Furthermore, more recent
conceptualizations of co-evolutionary information systems alignment (COISA) expand this
dynamic approach to alignment by applying a stakeholder interaction perspective in pursuit
of alignment (Allen and Varga, 2006). Thereby, these works explicitly address earlier
criticisms on traditional alignment conceptualizations emerging as early as 1997 when
Ciborra (1997, p. 79) underlined the blurring boundaries between business and information
technology (IT) and the importance of working towards “An enlarged notion of alignment
within a hybrid network of semi-autonomous actors.”
Given the complexity faced by contemporary hospitals in search of better EMR alignment,
researchers have applied this co-evolutionary approach to alignment to EMR before
(Walraven et al., 2020). This particular work illustrates that COISA could indeed be a fruitful
way to understand the capabilities that hospitals need to effectively execute and maintain an
inclusive, two-way dialogue in pursuit of better aligned EMR (Walraven et al., 2020). Thus far,
these endeavors focus on the implementation phase of the EMR. However, given the many
different stakeholders and the continuously changing external conditions, it is unlikely that
the EMR is and will remain optimally aligned with the needs of the hospital and its
stakeholders at the point of go-live. Therefore, hospitals will also need to develop and
maintain their COISA capability after go-live to continuously align the EMR and optimally
leverage potential benefits. Still, existing empirical works on EMR-related COISA capabilities
focus on the EMR implementation phase only (Walraven et al., 2020). Therefore, it remains
unclear what drives the evolutionary paths of the COISA capability, and thus hospitals have
little guidance on how to best shape EMR alignment in the long run. We contribute to closing
this knowledge gap by giving further insight into how the evolutionary path of the COISA
capability develops before and after EMR go-live in hospitals and in the drivers behind these
evolutionary paths. Hospitals may use these insights to better shape their COISA capability
to maintain an adequate degree of alignment. Our research question is as follows:
RQ. How does the EMR-related COISA capability evolve in hospitals, and what are key
drivers for how this capability evolves?
Evolving
competencies
to align EMR
113
To address this question, we did a longitudinal multiple case study, where we examined the
EMR-related COISA capability in three hospitals using in-depth retrospective interviews
regarding two different phases, i.e. before EMR go-live and after EMR go-live. A longitudinal
approach is appropriate because our goal is to look at the COISA capability’s evolution over
time, which fits the logic of selecting a longitudinal approach (Yin, 2018).
2. Theoretical framework
This chapter outlines our research’s theoretical foundation, as illustrated in Figure 1. We will
elaborate on each of the concepts of this model, including COISA as an organizational
capability consisting of alignment competencies; describing capability evolution in terms of
capability lifecycle stages following the dynamic resource-based perspective; and finally
describing potential informative works on drivers of the COISA capability evolution in an
EMR context. In this current study, we approach the COISA capability as alignment
competencies in continuous pursuit of EMR alignment. Specifically, EMR alignment entails a
common (i.e. held across EMR stakeholders) interpretation and implementation of what it
means to apply the EMR in an appropriate and timely way, in harmony with strategies, goals
and needs of the hospital and its stakeholders (Luftman and Brier, 1999;Luftman and
Kempaiah, 2007;Walraven et al., 2020). This definition resonates with the concept of social
alignment, i.e. “[...] when groups share understanding and commitment towards an outcome,
and the means of achieving that outcome”(Gilchrist et al., 2018, p. 1), with the extension that
EMR alignment not only incorporates the common interpretation across stakeholders, but
also its practical implementation in terms of the configuration of the EMR and other hospital
resources. Furthermore, because of the continuous change present in and around the hospital,
EMR alignment is not an end-state, but a moving target, hence the need for a long-term
alignment capability to pursue it (Baker et al., 2011;Vessey and Ward, 2013).
2.1 Co-evolutionary information systems alignment
COISA is a stream of alignment research suitable for complex conditions (Allen and Varga, 2006;
Amarilli et al., 2016;Benbya and McKelvey, 2006;Walraven et al.,2020). This school of thought
focuses on the social actors comprising organizations and their co-evolutionary interactions in
Evolves over time following an…
Drivers
Shape
direction of
Founding Development
Retrenchment
Evolutionary path
consisting of Capability lifecycle stages (Table 2)
Redeployment
…
…
COISA capability
Defined in terms of Alignment competencies (Table 1)
Strategic
alignment
competency
Orchestrational
alignment
competency
Operational
alignment
competency
Figure 1.
Conceptual model of
our current study,
researching
evolutionary paths of
the COISA capability
and their drivers
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pursuit of alignment. These interactions prevail within and between individual, operational and
strategic levels of the organization (Benbya and McKelvey, 2006), which consists of several
alignment processes, including strategy formulation (Kahre et al.,2017;Liang et al.,2017;
Sabherwal and Chan, 2001), strategy implementation (Busquets, 2015;Grisot et al., 2014;Liang
et al., 2017;Montealegre et al., 2014), enterprise architecture management (Schilling et al.,2017;
Vessey and Ward, 2013;Weeger and Ulrich, 2016), IT implementation (Lyytinen and Newman,
2008;McLeod and Doolin, 2012;Wagner et al., 2010) and IT usage (Allen et al., 2013;Burton-Jones
and Gallivan, 2007;Goh et al., 2011). The theoretical foundations of COISA are in line with a
broader research area that positions alignment as a continuous process, emerging from networks
of actors in the flow of organizational practice (Ciborra, 1997).
In this current study, we conceptualize COISA as an organizational capability, consisting
of three continuously exercised alignment competencies characterized by co-evolutionary
interactions between heterogeneous information systems (IS) stakeholders, in pursuit of a
common interpretation and implementation of what it means to apply IT in an appropriate
and timely way (Walraven et al., 2021). In doing so, we distinguish three alignment
competencies that are based directly on the abovementioned alignment processes as
synthesized from the literature by Walraven et al. (2018) and the different levels of alignment
as outlined by Benbya and McKelvey (2006). These competencies include the: strategic
alignment competency, orchestrational alignment competency, and operational alignment
competency. Table 1 summarizes our definitions of each of these alignment competencies, as
defined by Walraven et al. (2021) and based on leading articles using dynamic perspectives on
alignment (e.g. Baker et al. (2011),Liang et al. (2017),Vessey and Ward (2013),Vidgen and
Wang (2009) and Weeger and Ulrich (2016)). This dynamic perspective particularly fits our
research context of EMR as it is specifically hypothesized to be better able to deal with
internal and external complexities (Merali et al., 2012;Merali and McKelvey, 2006):
2.2 COISA as an organizational capability
In line with the conceptualization as explained by Walraven et al. (2021), we view COISA as a
whole as an organizational capability, with the three above described alignment
competencies as its foundation. This stance builds upon several existing works in the field
Competency Definition
Strategic alignment
competency
An organizations’ability to formulate strategic goal, and articulate strategic
plans and structures to implement these goals in relation to IS, while
monitoring relevance and topicality of these plans, goals and structures, in line
with frequencies of internal and external changes. (Baker et al., 2011;Liang
et al., 2017;Sabherwal and Chan, 2001;Tanriverdi et al., 2010;Walraven et al.,
2021;Yeow et al., 2018)
Orchestrational alignment
competency
An organization’s ability to maintain the coherence between their information
systems, goals, processes, data, infrastructure, roles and functions, through
architectural practices such as the definition and application of architectural
principles or standards, while monitoring relevance and topicality of these
architectural practices, in line with frequencies of strategic and operational
changes (Rolland et al., 2015;Schilling et al., 2017;Vessey and Ward, 2013;
Walraven et al., 2021;Weeger and Ulrich, 2016)
Operational alignment
competency
An organization’s ability to collaboratively use IT solutions effectively in daily
operations and implement and optimize IT solutions in operational settings in
line with end-users’needs, while monitoring and leveraging improvement
possibilities during IT usage, implementations and operations. (Allen et al.,
2013;Amarilli et al., 2017;Burton-Jones and Gallivan, 2007;Goh et al., 2011;
Lyytinen and Newman, 2008;Vidgen and Wang, 2009;Walraven et al., 2021)
Table 1.
Definitions of
co-evolutionary
alignment
competencies
Evolving
competencies
to align EMR
115
of organizational capabilities, including Peppard and Ward (2004), who define organizational
capabilities as “[...] the strategic application of competencies [...], i.e. their use and
deployment to accomplish given organizational goals”. In line with this definition, the COISA
capability considers the use and deployment of the strategic, orchestrational and operational
alignment competencies. Their combination, in particular, makes for a strategic application.
Crick and Chew (2020, p. 12) argue that business processes are “[...] the basis for an
organization’s capabilities and how they “earn their living”.This also resonates with COISA:
Namely, as shown in earlier works on COISA, alignment processes form the micro-
foundations of the strategic, orchestrational and operational alignment competencies
(Walraven et al., 2020,2021), which in turn comprise the COISA capability.
Helfat and Peteraf (2003, p. 999) define an organizational capability as “[...]theabilityofan
organization to perform a coordinated set of tasks, utilizing organizational resources, for the
purpose of achieving a particular end result”. COISA fits well into this framework since a crucial
part of COISA relies on coordinating tasks not only within but particularly between the different
alignment competences. This coordination takes place through the social interactions between
stakeholders (Walraven et al., 2020). Moreover, this perspective is resonant with the insight that
the micro-foundations of capabilities consist of individuals interacting within and between
organizational and managerial processes (Harris et al., 2013). Thus, COISA as an organizational
capability considers the combination and successful application of the three different alignment
competencies to continuously align IT.
However, viewing alignment as a capability is not novel. For example, earlier research has
suggested that strategic alignment maybe conceptualized as a collection of complementary
capabilities, including (1) dynamic capabilities, (2) IT flexibility and (3) absorptive capacity (van
de Wetering and Mikalef, 2017). Still, as this study also points out, this particular
conceptualization remains quite general, and “Future work could address how managers
should deploy improvement projects done simultaneously and hence by an integrated alignment
perspective”(van de Wetering and Mikalef, 2017, p. 10). Other researchers that address the
alignment challenge using a capability perspective include Baker et al. (2011). These authors
conceptualize strategic alignment as “an enduring competency that is a source of competitive
advantage”. However, in their study, they only focus on aligning IT strategy with business
strategy, and thus do not consider individual andoperationallevels of alignment. The only study
that takes an explicit co-evolutionary stance on the conceptualization of alignment as an
organizational capability is the one by Walraven et al. (2021),whichiswhyweusethat
conceptualization as the theoretical foundation of the current study.
2.3 COISA as an evolving capability
Given our conceptualization of COISA as an organizational capability that needs
continuous attention and effort, the question arises whether, how and in what
circumstances the COISA capability evolves over time. Several researchers have looked
into the theoretical foundations of the evolution of capabilities. Helfat and Peteraf (2003)
argue that dynamic and organizational capabilities both can be described to have life
cycles, consisting of three generic stages, i.e. (1) Founding stage, (2) Development stage
and (3) the Maturity stage. A given capability can “branch”into different directions during
the development or maturity stages. Table 2 summarizes the characteristics of each of
these capability lifecycle stages. For this current study, we use the capability lifecycle
stages by Helfat and Peteraf (2003) as a starting point.
2.4 Key drivers of COISA capability evolution in an EMR context
Several studies have written about drivers of evolutionary paths of organizational
capabilities. Helfat and Peteraf (2003), whose capability lifecycle stages we use as a
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conceptual lens, argue that branching of a capability into another stage is triggered by
selection events. These consist of threats to the capability or opportunities for the capability
to grow. Furthermore, Zollo and Winter (2002) take a knowledge-based view and argue that
the micro-foundations of the evolution of dynamic capabilities lie in learning mechanisms,
including experience accumulation, knowledge articulation and knowledge codification.
Moreover, resource orchestration theory suggests that managerial actions can be seen as
potential drivers of capability evolution (Sirmon et al., 2011). This particular theory combines
insights from resource management and asset orchestration to look deeper into the role of
managers’actions in the effective structuring, bundling and leveraging of firm resources in
pursuit of competitive advantage. In other words, from this perspective, the formation and
evolution of organizational capabilities is explicitly seen as a managerial responsibility, and
managers’actions are hypothesized to shape these orchestration efforts. This premise has
been empirically demonstrated and holds for executive and operational and middle managers
(Chadwick et al., 2015;Sirmon et al., 2011). Pelletier et al. (2021) looked into social IT alignment
(SITA) through an asset orchestration lense and find that SITA is facilitated through the
allocation, structuring and coordination of IT resources and that “[...] proper management of
the SITA process is founded on the exchange and sharing of IT competencies and knowledge”
(Pelletier et al., 2021, p. 3).
In terms of specifically healthcare IT- or EMR-related capability drivers, several works
give insight into the potential drivers of related capability evolution. Sha et al. (2011) find in
their case study on the implementation success of healthcare information systems that
normative pressure, top management support, domain knowledge sharing and having a
culture of innovation drives the development of the alignment capability. Palvia et al. (2015,
p. 711) describe that the EMR vendor often has a large influence in the development of
capabilities during EMR implementations: “[...] the [EMR] vendor’s active participation in the
EHR implementation is necessary due to project management and change management
expertise that the vendor possesses and that maybe missing or insufficient in the healthcare
organization”. Additionally, Walraven et al. (2020) describe facilitators of efficacious
co-evolutionary stakeholder interactions toward alignment during EMR implementations
based on the literature on effective alignment (e.g. Amarilli et al., 2017;Zhang et al., 2019) and
efficacious dynamics in complex organizations (e.g. Burt, 1992;Grant, 2003;McKelvey, 2001)
and applied in an empirical EMR setting. These facilitators may be seen as drivers of
Capability Lifecycle
stage Characteristics
Founding A group with leadership and with the ability to take collaborative action is formed,
with a common goal to create a new capability within the organization
Development The capability building group or team makes decisions on how to best shape the
capability at hand, informed by accumulating experiences in doing so
Maturity The capability no longer changes, but is maintained by regular exercise by the
organization
Retirement The capability ceases to exist
Retrenchment The usage of the capability declines over time
Redeployment The capability is transferred to another product market
Renewal The capability returns to the development stage after having left this stage at an
earlier point in time
Replication The capability is transferred to another geographic market (but applied to the same
product or service)
Recombination The capability is combined with other capabilities to serve a different but related
market
Table 2.
Capability lifecycle
stages, based on Helfat
and Peteraf (2003)
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capability founding and development since they contribute to the growth of the COISA
capability. However, they do not explicitly give insights into the drivers of the other
capability lifecycle stages, except that maybe the absence of one or more of these facilitators
could lead to the capability’s retrenchment or retirement. The facilitators described by
Walraven et al. (2020) include alignment motivation, considering “[...] facilitators motivating
IS stakeholders to engage in co-evolutionary interactions in a specific alignment process”
(Walraven et al., 2020, p. 9); Stakeholder involvement, or “[...] facilitators related to the
selection of actors to be involved in COISA processes”(Walraven et al., 2020,p.9);
Interconnections, or “[...] the means that IS stakeholders have to engage in co-evolutionary
alignment interactions”(Walraven et al., 2020, p. 11), and finally alignment decisions,
considering “[...] specific decisions that are taken in the alignment processes themselves and
that may, in turn, benefit following COISA interactions in those same processes”(Walraven
et al., 2020, p. 11). These alignment decisions include having common guidelines, putting in
place central coordination of the COISA capability, allowing emergent decision-making, and
having the adequate technical infrastructure in place.
3. Methodology
We conducted a longitudinal multiple case study through retrospective interviews in two
phases. Our multiple case approach improves generalizability since it enables us to compare
the evolution of the COISA capability across multiple hospitals (Yin, 2018). We used a
longitudinal approach because we are interested in the evolution of the COISA capability over
time. The first interview phase focused on the EMR implementation and its preparation and
was carried out in the months right after the go-live of the EMR system in each hospital.
Herein, we studied whether and how a COISA capability was founded to align the EMR prior
to or during the implementation, and how the capability evolved in each of the studied
hospitals during this period. The second interview phase was done during the six to twelve
months after go-live of the EMR, to study and reflect on how the COISA capabilities further
evolved after the initial go-live. The two-phased approach to longitudinal research is
comparable to the longitudinal study method on stakeholder roles and perceptions in health
information systems by Pouloudi et al. (2016).
Furthermore, our approach aligns with the before-and-after logic for longitudinal research
(Yin, 2018), where data collection is done in two phases, i.e. before and after a critical event. In
our current study, this critical event entails the go-live of the EMR. We will now elaborate on
each of the three case studies.
3.1 Case studies
We selected three Dutch hospitals based on two criteria: First, they all implemented a new,
advanced EMR in the past few years, and second, that they are academic or top clinical
hospitals. The latter criterion ensured the presence of complexity that the COISA capability is
hypothesized to address. All hospitals implemented a vendor-built system: Hospital A and
Hospital C opted for a vendor (Vendor 1). This vendor originates from the United States and
implemented their EMR solution in countries across the globe including the United Stated,
Canada, England and the Netherlands. They offer an EMR solution that is standardized to a
certain degree but still has many configuration possibilities for individual hospitals. Hospital
B implemented a standardized EMR system from a different vendor (Vendor 2), which is also
standardized and to some degree configurable. However, it is much less flexible than the
system from Vendor 1. Vendor 2 is the Dutch market leader, having implemented their EMR
system at 70% of all Dutch hospitals (van Eekeren et al., 2021). Hospital A and Hospital B
both went through a merger simultaneous to the EMR implementation. These mergers were
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for both of these case hospitals, a main reason to implement a new EMR. Hospital C did not go
through a merger, but its existing EMR was soon reaching its end-of-life.
Furthermore, the hospitals all carried out some preparations before the actual
implementation program of the EMR, however, the scope and time spent on that pre-
implementation phase differed for each case: Hospital A had the most extensive pre-
implementation phase, considering an entire program focusing on process- and IT
harmonization in preparation of the upcoming merger. Hospital B was also going through
a merger and aimed to harmonize processes as much as possible before the EMR
implementation. However, they did not set up a separate program to this end. Instead, they
gave department heads the responsibility to pursue this before the implementation phase
would start. Hospital C had a minimal pre-implementation phase, because of time limits and
presumably because they did not face a simultaneous merger. The time limits were caused by
a previously failed implementation of a different EMR, leaving the hospital very limited time
before the end-of-life of their previous EMR. Furthermore, unlike Hospitals A and B, Hospital
C opted for a two-staged implementation of the EMR of Vendor 1, to make sure that the most
crucial EMR parts could go live in time. Specifically, in the first implementation stage, the
hospital implemented the essential EMR modules to enable the different departments to
administer and exchange patient information and support essential healthcare processes. In
the second implementation stage, the hospital worked on optimizing these functionalities and
added additional functionalities such as mobile apps for doctors and nurses, information
exchange possibilities with general practitioners and integrations with medical devices.
Table 3 summarizes relevant case information.
3.2 Data collection approach
We conducted in-depth interviews with key stakeholders in two phases. In doing so, we
aimed for an optimal stakeholder representation (IT; external; management and medical),
as recommended by Pouloudi et al. (2016). Furthermore, we selected respondents with
knowledge of the whole implementation program and the EMR, i.e. respondents who are
strategically responsible for the EMR and its alignment and overview all relevant aspects.
These stakeholders are most likely to have knowledge on the formation and evolution of
formal governance structures in relation to EMR alignment. Moreover, we aimed to
interview people whose primary role in relation to the EMR was to represent their
constituencies during and after the implementation. For example, in hospital C, the digital
doctors represented all doctors in the hospital in the decision-making around the EMR.
The rationale behind this particular criterion is to optimize the stakeholder representation
in our data and to get a better idea of informal influences on decisions related to EMR
alignment on lower hierarchical levels. We could not cover the patient perspective, because
we could not identify a representative of this group meeting this latter criterion. We could
not include the vendor’s perspective for hospitals A and C because this vendor was
Hospital A Hospital B Hospital C
Size 750–1,000 beds 500–750 beds >1,000 beds
EMR Vendor Vendor 1 Vendor 2 Vendor 1
Simultaneous merger? Yes Yes No
Scope EMR Hospital-wide Hospital-wide Hospital-wide
Pre-implementation phase Extensive (separate program) Limited Very limited
Implementation program approach One go-live One go-live Two-stage approach
Hospital type Top clinical Top clinical Academic
Table 3.
Case hospital
characteristics
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unwilling to participate in our study. To identify suitable respondents for the second
phase, we used the same selection criteria and first contacted our first-phase respondents.
Then, depending on whether they were still actively involved with the EMR, we
interviewed them second time or asked them to refer us to suitable respondents. Our first
data collection phase (phase I) took place between September 2018 and November 2018.
Our second data collection phase (phase II) took place between March 2019 and June 2019.
We finally interviewed at least five respondents per hospital per phase, amounting to 35
interviews in total, as summarized in Table 4.
Our questions focused on the respondent’s experience with decision-making and
stakeholder involvement on different levels during and after EMR implementation. We
aimed to cover different levels by asking about the EMR implementation operationally, but
also about the role of strategic and architectural practices (if present); in doing so, we made
sure the interview’s themes were congruent with the three alignment competencies and their
microfoundations (i.e. alignment processes). Furthermore, we asked each respondent to
elaborate on their role in relation to the EMR during implementation and/or after go-live.
Specifically, we focused on how their role related to any official governance structures and
how they played a role in any informal decision-making structures. We also asked about how
these formal and informal decision-making structures and EMR alignment related decisions
evolved during the implementation and after, and how the involvement and stance of the
different stakeholder groups evolved over time and why. This latter effort ensured that we
could analyze and compare data on how the alignment competencies and their
microfoundations evolved over time. To enable data triangulation, we also collected
documentation related to the EMR, including project plans, strategic guidelines and decision-
making structures.
3.3 Data analysis approach
All interviews were recorded, transcribed and coded. The coding process was informed by
the recommendations by Salda~
na (2015) and involved a three-step approach: First,
passages that indicated a particular capability life cycle stage were coded using a
deductive approach, based on the work by Helfat and Peteraf (2003). Then, each of the
coded passages was labeled in a second round as either considering the operational, the
orchestrational or the strategic alignment competency. Lastly, we went through the entire
dataset once more to identify and categorize the drivers of the COISA capability’s
evolutionary paths. To improve reliability, we pursued inter-coder agreement levels as
follows: The resulting analysis and corresponding coding were independently reviewed
by two other researchers, who coded the interview passages in terms of alignment
competency and capability lifecycle stage. When disagreements arose, we had substantial
discussions to come to a final analysis.
4. Results
Our results show that (parts of) the COISA capability of all three hospitals went through the
founding-, development-, retrenchment- and renewal stages. Furthermore, in Hospital B,
parts of the COISA capability went into the redeployment stage. Finally, our data analysis
revealed a stage that was not included in the original model by Helfat and Peteraf (2003),
which we named the “coordination”stage. We characterize this “coordination”stage as
follows: a capability founded within organizational boundaries is brought to a higher
network- or ecosystem-level by formally incorporating other organizations in the capability. In
two of the three case study hospitals, part of the COISA capability evolved in this direction
after go-live.
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Hospital A B C
Phase
Group I II I II I II
IT - ICT manager
- Project lead A
- Head EMR ops
- Project lead A
- Project leader training
- ICT architect - CIO
- ICT architect
- Head EMR ops
- Project lead 1
- Project lead 2
- Program manager 2
- Program manager 3
External - Project lead B N/A - Program manager
- Vendor rep
N/A - Program manager 1
- Project lead 3
- Project lead 4
N/A
Mgmt - Project lead C - Manager healthcare - Project lead - Information manager - Project lead 5 - Project lead 6
Medical - Project lead D - Project lead D
- Digital Doctor
- Digital Nurse
- CNIO - CNIO - Digital doctor 1 - CMIO
- Digital doctor 1
- Digital doctor 2
Table 4.
Interviewees for each
case hospital and phase
Evolving
competencies
to align EMR
121
In the remainder of this chapter, we will elaborate on the evolutionary paths of the COISA
capability and their drivers, highlighting similarities, differences and possible
explanations for our findings. In doing so, we will first go into the evolutionary paths of
the COISA capability during the (pre)-implementation phase of the EMR, i.e. the results
from our first data collection phase (see Figure 2). Then, we will elaborate on our findings
from our second data collection phase, considering the six to twelve months after go-live of
the EMR in our three case hospitals (see Figures 3 and 4). We will finally focus on the
particular drivers of the COISA capability evolution, both during (pre-)implementation
and after go-live.
4.1 Data collection phase I: before go-live
Figure 2 summarizes all capability lifecycle stages manifesting during (pre-)implementation
of the EMR, before go-live, i.e. the founding stage and the development stage. Each grey row
in this figure represents a particular capability lifecycle stage and its drivers that we
identified in our case studies. Furthermore, for each of these stages, the specific actions
forming the practical manifestations of that particular stage are categorized in three white
rows, one per alignment competency. For the development stage, we differentiated between
actions performed during the pre-implementation phase and during the implementation
phase of the EMR. Lastly, all actions are color-coded so that it is clear which action manifested
in which case (Hospital A is blue, Hospital B is green and Hospital C is orange).
4.1.1 Implementation: founding and development of the COISA capability. While hospital A
had already founded all alignment competencies during pre-implementation, hospitals B and
C founded their operational and orchestrational alignment competencies during the
Initiative external &
internal digital
advisors
Vendor’sintiative
Initiative
strategic
committee
Initiative ICT
directors End-of-life
EMR
Drivers Initiative
domain project
leads
Lessons learned failed
EMR implementation
Initiative
program
manager
Hospital
B
C
Formulang
implementaon
strategy
Set-up
expert
groups for
hospital-
wide issues
Set-up agile
department teams
for EMR
configuraon
Set-up domains
(clusters of EMR
modules) & defining
dependencies
Set-up core teams
and program
commiee for
hospital-wide issues
Set-up agile
department teams
for EMR
configuraon
Orchestrational
Strategic
Operational
Set-up
strategic
commiee
represenng
perspecves
Set-up hospital-
wide end-user
groups
Set-up End-user
groups per
medical
specialism
Set-up
strategic
guidelines
Set-up strategic
commiee represenng
perspecves
Set-up small strategic
commiee to
formulatestrategic
vision for EMR
selecon
Pre-implementation
Implementation
Founding
alignment
competencies
Strategic
Drivers
Developing
alignment
competencies
Further develop
implementaon
strategy aer EMR
selecon
Vendor’s
intiative
Refine
strategic
guidelines
Initiative internal
digital advisors
Maturing
role CNIO
and expert
groups
Program
experience
Orchestrational
Appoint process
owners for cross-
departmental
processes
Set-up sounding
board for impacul
decisions
Set up “Book of
conduct” to
register and
communicate
decisions and
guidelines
Increasing
awareness of
cross-
departmental
and cross-role
dependencies
Involving
emerging
stakeholder
groups
Set-up “mini
go-live” to
solve
differences
in
terminology
Replacing administrave
staff in medical
administraoncore team
with team leads
Seng up data
commiee in addion to
medical administraon
core team
Emerging
issues
Initiative
program
management
Operational
Initiative
strategic
committee
Set up applicaon
teams for technical
EMR configuraon
Appoint subject
maer experts for
specific topics
Set up paent
panel for
paent portal
Initiative
patient portal
project lead
Workingwith
test set-ups
during
implementaon
Initiative
project
employees
Add liaison role between
technical and funconal
teams
A
Figure 2.
Results of data
collection Phase I
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implementation, shaped by the EMR vendors’implementation strategy. Following, all three
hospitals’COISA capabilities evolved into the development lifecycle stage during the EMR
implementation.
Initiativehead EMR
operations
Emerging
misalignments
Initiative
digital advisor
Initiative
CIO
Drivers Initiative
digital
doctors
Initiative
strategic
committee
Hospital
B
C
Revising
strategic
guidelines
Introducing
informaon manager
role
Set-up end-user groups
for stakeho lder
representaon
Implemenng scrum
for EMR o pmizaon
Orchestrational
Strategic
Operational
Revising
strategic
guidelines
Professionalizing
IT employees
Agile opmizaon sprints
including “shadowing”
employees during EMR usage
Set-up high-
priority issues
governance
structure
Defining
governance
structure for
ICT iniaves
Revise vision
on EMR and
digitalizaon
Developing
alignment
competencies
Strategic
Drivers
Retrenching
alignment
competencies
Stop high-priority
issues governance
structure
Decline high-priority
issues
Set-up information
manager role per
cluster
Orchestrational Confusion decision-
making structures
Declining coherence
between clusters
End EMR
implementation
program
Operational Less aenon to
end user training
Confusion on how to address
operaonal alignment issues
Declining enthusiasm
and energy keyusers
A
Drivers
Renewing
alignment
competencies
Revising
“Book of
conduct”
Set-up task forces
for unexpected
issues
Defining ICT
governance
structure
InitiativeCMIO and
medicalinformation
managers
Initiativepatient
participation
program
Use regular medical
manager meengs for
input hospital-wide
decisions
Initiative
program
manager
Appoint
product
owners
Improved collaboraon
between medical and IT
employees
Program
experience
Lack of
resources
Strategic
Orchestrational
Operational
Shape governance for
“operaons strategy”
Plans
implementation
phase
Confusion on
decision-making
structures
Shape governance for
“operaons strategy”
Initiative
digital
advisor
Revive keyuser role in
user teams
Implementation
of vendor-pushed
EMR update
Posion CMIO and CNIO
as linking pins
Set up agile
department teams
Program
experience
Initiative
CMIO
Initiative
CNIO
Clarifying keyu ser rolein
relaon to informaon
managers
Emerging
workarounds
Set up task forcesto
opmize EMR
configuraon
Initiativedigital
doctors and
CMIO
Lack of resources
amongkey users
(medicalpersonnel)
Hospital
B
C
A
Drivers
Redeploying
alignment
competencies
Strategic
Orchestrational
Using strategic commiee to developbroader hospital
innovaon agenda
Using EMR governance
structure for all digitalizaon
efforts
Using expert groupsfor
general quality improvement
in hospital-wide processes
Program
experience
Initiative
CIO
Initiative
quality
manager
Strategic
Drivers
Coordinating
alignment
competencies
Orchestrational
Operational
Align EMR strategy of hospitalA
with other Vendor1 hospitals
Align integraon processesof
paent records withother
Vendor 1 hospitals
End user groups withrepresentaves of all Vendor 2
hospitals for decisions on operaonalEMR changes
Initiative national
society of Hospitals Initiative Vendor2
Figure 3.
Results of data
collection phase II
(Results manifesting in
all three cases)
Figure 4.
Results of data
collection phase II
(Results manifesting in
one or two cases)
Evolving
competencies
to align EMR
123
In hospital A, the initial implementation strategy set up during pre-implementation was
incrementally updated based on input from the vendor, as pointed out by several
interviewees (Project lead A, hospital A; Project lead D, hospital A). Based on these
incremental updates, hospital A’s strategic alignment competency developed into hybrid
between the vendor’s standardized implementation strategy and hospital A’s own experience
during the pre-implementation phase. For example, hospital A kept their process-focused
hospital-wide and specialism-specific end-user groups, even though those were not usually
part of the governance structure prescribed by the vendor: “You have to be well-prepared
because this vendor works mainly around applications, while we had deliberately set up our end-
user teams around processes. In the beginning, this really was a struggle to keep it that way. But
we believed in what we were doing: we felt like we knew why we did it that way. But we had to
justify ourselves”(Project lead D, hospital A). Furthermore, several internal actors in hospital
A initiated some additional developments of the COISA capability. For example, in terms of
hospital A’s orchestrational alignment competency, process owners were appointed for cross-
departmental processes such as outpatient clinic logistics (ICT manager, hospital A).
Moreover, the “book of conduct”was set up as a development of the hospital’s orchestrational
alignment competency: “In the book of conduct, all hospital-wide decisions were documented.
So, for example, who is authorized to order medicine, and what kind of medicine?”(Project lead
B, hospital A).
In hospitals B and C, the COISA capability’s development was influenced by their
acquired experience during the implementation. For example, in hospital B, experience
during the program caused the orchestrational alignment competency to evolve: “While
making configurational decisions while working together, people really saw through the entire
process of a patient coming in at first aid, through the entire chain of departments including the
operating room, and there really was some kind of realization. [...] We really made some big
steps there, also in terms of cross-departmental process harmonization.”(ICT architect,
hospital B). A comparable mechanism emerged in hospital C: “Most hospitals do not have
much experience with these types of implementations. So in the beginning, the vendor is very
much in the lead in the way operational decisions are being made. [...] And as the
implementation moves forward, you become more of a partner and the vendor gradually moves
to the background and you start to shape things your own way.”(Program manager 1,
hospital C).
4.2 Data collection Phase II: after go-live
In our second data collection phase, we identified three lifecycle stages in all of our case
hospitals (i.e. development, retrenchment and renewal) and two in only one or two of our case
hospitals (i.e. redeployment, and a new lifecycle stage called “orchestration”).
4.2.1 Development, retrenchment and renewal of the COISA capability. After go-live of the
EMR, the COISA capability of all case hospitals showed evolutionary paths of development,
retrenchment and renewal (see Figure 3).
In hospital A, the development of the capability consisted of two important types of
actions. Firstly, these involve actions to address urgent issues emerging after go-live of the
system. For example, in terms of its operational alignment competency, hospital A set up so-
called task forces to solve these most urgent issues (project lead D; digital nurse; head EMR
operations, hospital A). Secondly, these involve actions focused on improving existing
structures to form a solid foundation for an effective COISA capability during EMR
operations. For example, strategic guidelines were revised to further develop the strategic
alignment competency, and agile optimization sprints including personal training based on
“shadowing”were initiated as part of the operational alignment competency: “All outpatient
clinics get an agile sprint during three weeks, and then all doctors in those clinics are being
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“shadowed”[...] to be able to analyze: how can this person make better use of the EMR? And
during those same three weeks we look at, what are the department’s wishes in terms of
optimization and development of the EMR?”(project lead training, hospital A).
At some point after go-live, hospital A’s COISA capability started to show signs of
retrenchment, for example because there was less attention to end user training (digital
doctor; project lead training, hospital A) and because there was confusion about how decision-
making structures were supposed to work after the end of the implementation program
(digital doctor, hospital A). The capability was then renewed in several ways, for example,
using the momentum of a vendor-pushed EMR update to revive the key user role (digital
nurse, hospital A).
In Hospital B, the development of the COISA capability, like in Hospital A, also involved
solving urgent issues on the one hand and working towards a more mature COISA capability
during EMR operations on the other hand. For example, this hospital also set up agile teams
as part of their operational alignment competency, addressing both urgent issues and less
urgent issues focused more on optimization (information manager; ICT architect; hospital B).
Comparable to Hospital A, hospital B’s COISA capability also evolved towards retrenchment
after go-live, for example because of the confusion that emerged after the end of the
implementation program on how to address operational issues (ICT architect; CNIO, hospital
B). The operational alignment competency was in turn renewed by setting up agile
department teams to optimize EMR configurations (Head EMR operations, ICT architect,
hospital B).
In hospital C, the COISA capability’s development was visible for example in the revision
of the hospital’s vision on the EMR (digital doctor 1; digital doctor 2; hospital C). Moreover,
there was a parallel effort by the CMIO and several information managers to set up a
governance structure for EMR alignment during operations: “EMR operations are now
situated in the implementation program and not in the regular organizational structure of the
hospital. [...] What we are working on right now is the transition from the program to the
regular organizational structure, towards the department of information management.
Together with those information managers, I will be responsible for all healthcare related
information technology, including the EMR”(CMIO, hospital C). Although not as clearly
visible as in Hospitals A and B, Hospital C also showed some signs of COISA capability
rentrenchment because of the declining enthusiasm of key users: “[...] enthusiasm is
declining because many healthcare employees are back to their own work”(digital doctor,
hospital C). This particular hospital addressed this declinement by renewing the operational
alignment competency, i.e. by setting up task forces: “the optimization teams visit all
outpatient clinics in the hospitals to see what issues they face in the EMR, to be able to quickly fix
emerging issues and optimize the EMR.”(digital doctor, hospital C).
4.2.2 Redeployment and coordination of the COISA capability. We identified the
redeployment lifecycle stage in one of our case studies (hospital B) and the new
“coordination”stage in two of our case studies: hospitals B and C (see Figure 4).
In hospital B, we found that after go-live, parts of the COISA capability were redeployed to
IT-related innovations other than the EMR. For example, departments were encouraged to
“pitch”innovative IT solutions (not necessarily within the EMR), supported by the newly
founded role of information manager (present at each group). (ICT Architect; Information
manager; CNIO, hospital B). The digital strategic committee that was initially founded as part
of the EMR program was redeployed in this context because it reviewed and prioritized these
pitches. Moreover, they developed a digital strategy broader than just the EMR after go-live
(CNIO, CIO, Hospital B).
In Hospitals A and B, we identified a new lifecycle stage of the COISA capability relative to
the predefined lifecycle stages based on Helfat and Peteraf (2003). We have named this
particular stage the “coordination”stage. This capability lifecycle implies that a capability
Evolving
competencies
to align EMR
125
founded on an organizational level is extended to a broader ecosystem. This extension is done
by formally incorporating other organizations in the capability to collaboratively coordinate
alignment efforts, hence the name “coordination”. In our empirical findings, these other
organizations entailed other hospitals working with the same EMR. However, the particular
focus of coordination differed depending on the vendor’s strategy. The COISA capability of
Hospital B, working with vendor 2’s highly standardized solution, evolved toward the
coordination stage in the operational alignment competency. Namely, to ensure that the
highly standardized solution fits the hospitals that have implemented this solution as much
as possible, vendor 2 has set up their end-user groups consisting of representatives of the
different hospitals using vendor 2’s EMR (CNIO; Vendor representative, hospital B): “For this
standardized solution, we set up end-user groups. This is on the level of medical specialists, and
they periodically meet. For example, we have an end-user group cardiology, consisting of
cardiologists of all the hospitals working with our standardized solution. [...] And the
customers are in charge, so these groups’chairs are also representatives from one of the
hospitals. We [Vendor 2] facilitate these meetings [...] The benefit is that when consensus on a
specific topic emerges among the different hospitals, we can adapt our standardized solution to
their needs, and everyone is happy.”(Vendor representative, hospital B). In short, these end-
user groups make decisions on specialism-specific issues that occur on an operational level,
and can thus be considered to be a vendor-facilitated, cross-hospital execution of the
operational alignment capability.
The COISA capability of Hospital A, working with vendor 1 and its slightly less
standardized solution, evolved toward the coordination stage in the orchestrational and
strategic alignment competencies. The head of EMR operations elaborated: “There is the
directors’meeting among all hospitals working with the EMR solution of this vendor [...]So
you have all the national hospitals working with Vendor 1 there, and Vendor 1 is represented as
well. The idea is to exchange knowledge, to set up contacts and to have a strong position in
certain themes, priorities or developments in relation to vendor 1.”(Manager healthcare,
hospital A). Coordination of the orchestrational alignment competency was done across
hospitals working with vendor 1’s EMR, for the theme of data integration (project lead A,
hospital A)
4.3 Key drivers of the COISA capability evolution
Based on our literature review, we identified several potential drivers of capability evolution
including (1) Selection events (Helfat and Peteraf, 2003); (2) Managers’motivation (Chadwick
et al., 2015;Sha et al., 2011;Sirmon et al., 2011;Walraven et al., 2020)); (3) Accumulating
experience (Pelletier et al., 2021;Zollo and Winter, 2002); and (4) Vendor influence (Palvia et al.,
2015). Using these categories as a starting point, through our hybrid deductive and inductive
coding approach we finally identified four categories of capability evolution drivers in our
case studies. These categories include (1) Stakeholder initiative; (2) Driving events; (3)
Accumulating experience and (4) Emerging issues (see Table 5).
The first category entails instances where specific stakeholders take the initiative to found
or evolve the COISA capability because they feel motivated to do so. For example, this was
the case in Hospital A, where digital advisors and an external consultant took the explicit
initiative to set up end-user groups as a foundation of the operational and orchestrational
alignment competencies (project lead B; project lead D, hospital A). The second category, i.e.
driving events, considers specific events that form a concrete reason to set up, evolve or
retrench alignment competencies. A specific example includes a merger of two hospitals
(visible in case hospitals A and B), causing strategy- and process harmonization to become an
immediate issue (ICT manager, hospital A; CNIO, hospital B). In Hospital C, these driving
events include an initially failed EMR implementation and the end-of-life of their old EMR
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(project lead 1, hospital C). The third category, i.e. Accumulating experience, considers
evolutionary paths of the COISA capability caused by lessons learned through accumulated
experience over time. For example, in hospital B, the orchestrational alignment competency
developed through experience because people became more aware of the interdependencies
between their departments (ICT architect, hospital B). The fourth category is emerging
issues. This entails specific issues that emerge during the execution and usage of the
capability requiring immediate action, then causing the capability to evolve in a certain
direction. For example, in Hospital A, several high-priority issues emerged right after go-live,
causing the hospital to set up a specific decision-making structure tailored for quick, high-
priority decisions, thereby developing the strategic alignment competency (head EMR
operations; digital doctor, hospital A).
A few things stand out in our results. First, we see that stakeholder initiative is a driver
that is seen in all lifecycle stages considering a forward evolution of the capability. Only in the
retrenchment stage, which entails a decline of the capability, there are no stakeholder
initiative instances as a key driver. Second, out of the lifecycle stages where stakeholder
initiative does seem to be a key driver, this seems most so the case for founding- and
development stages. Furthermore, driving events seem to be a driver for lifecycle stages
where the capability takes an entirely new direction, i.e. at its foundation, at its retrenchment
and when part of the capability is renewed. Lastly, the abovementioned findings seem to be
valid for all three alignment competencies, and no clear differences or patterns seem to be
present, looking at the alignment competencies individually.
5. Discussion and conclusion
Our study demonstrates that each of our case hospitals has a unique evolutionary path
regarding its COISA capability in pursuit of EMR alignment. Previous work suggests that
building such a COISA capability indeed promotes creating a common interpretation and
implementation of what it means to apply EMR in an appropriate and timely way across
stakeholders, i.e. EMR alignment (Keshavee et al., 2006;Luftman, 2004;Luftman and Brier,
1999;Walraven et al., 2020). Even so, attention should still be paid to the fact that to effectively
pursue this endeavor, continuous time and effort should be spent to maintain an adequate
level of EMR alignment due to the complex and continuously changing environment that
hospitals face (Keshavee et al., 2006;Palvia et al., 2015;Walraven et al., 2019). Our theoretical
contributions are threefold: First, we add to the existing works on EMR in hospital settings.
We do so, by taking on the challenge of EMR alignment from a theoretical perspective that is
new to this particular area of expertise. Combining insights into which capabilities are
essential in EMR alignment and the key drivers of shaping and steering these capabilities
provides health researchers with concrete concepts to do rigorous empirical research in
health IT. Moreover, it provides a basis of scientific conversation to compare the value of the
COISA capability for EMR specifically to its value in relation to other health and non-health
IT solutions.
Driver Definition
Stakeholder initiative One or more stakeholder(s) (group(s)) take(s) initiative to drive capability evolution
in a certain direction
Driving events A specific event in time causes a capability to evolve in a certain direction
Accumulating
experiences
Through accumulating experience with a capability and thanks to the resulting
knowledge, the capability evolves in a certain direction
Emerging issues Specific issues emerge during the execution and usage of the capability evolution
that require immediate action, causing the capability to evolve in a certain direction
Table 5.
Definitions of key
drivers of the COISA
capability evolution
Evolving
competencies
to align EMR
127
Secondly, we identified a new capability lifecycle stage in our current study, i.e. the
coordination stage, meaning that a capability founded within organizational boundaries is
brought to a higher network- or ecosystem-level, formally incorporating other organizations
in the capability. With this particular addition, we expand on the theoretical developments in
capability evolution, especially in terms of possible lifecycle stages that a capability may
evolve towards (Helfat and Peteraf, 2003). Furthermore, this finding underlines the
importance of the healthcare ecosystem and shows the importance of internal alignment
capabilities to enable further upscaling of health information technology (HIT) innovations.
Third, we add a new perspective to viewing alignment as an organizational capability.
Specifically, we unfold the different alignment competencies that comprise this particular
capability. In addition, we incorporate not only strategic alignment challenges, like in earlier
works (van de Wetering and Mikalef, 2017), but also operational and orchestrational
competencies. We do so by providing a rich empirical, longitudinal perspective on how this
particular viewpoint on alignment resonates with practical findings. A particularly
interesting addition to the knowledge base considers our findings in terms of key drivers
of alignment: A key finding in this current study is namely the importance of stakeholders as
drivers of the COISA capability evolution, also in the long run. Namely, for all capability
lifecycle stages except for the retrenchment stage, stakeholder initiative shows to be an
essential driver of COISA capability evolution. This resonates with earlier findings on
efficacious COISA in a healthcare setting, as described by Walraven et al. (2020).
Furthermore, most (but not all) of the stakeholders that drove the forward evolution of the
COISA capability in our case studies were middle managers and thus these findings confirm
this particular aspect of resource orchestration theory, i.e. that managers can shape the
successful orchestration of organizational capabilities (Chadwick et al., 2015;Sirmon
et al., 2011).
Moreover, both driving events and emerging issues can be related to alignment
motivation. Specifically, these should be seen as external factors that motivate stakeholders
to engage in alignment competencies. Our findings also resonate with earlier work by Zollo
and Winter (2002), who argued that the key drivers of capability evolution consist of threats
and opportunities to the capability. Specifically, intrinsically or extrinsically motivated
stakeholders show to provide opportunities for the COISA capability to evolve into different
directions, while specific driving events and emerging issues can also form direct threats to
the COISA capability, eventually leading to the capability’s retrenchment.
5.1 Practical implications
Practitioners can use our findings to better build and shape their organization’s capabilities to
align EMR. A particularly interesting finding is the coordination of alignment competencies
to an inter-organizational level. This coordination potentially enables healthcare managers to
leverage the alignment competencies within organizational boundaries to work towards
cross-organizational alignment on an ecosystem level. However, the specific alignment
competencies that are coordinated to this ecosystem level all have their advantages and
disadvantages: For example, an advantage of choosing to coordinate the operational
alignment competency, as seen in case Hospital B, is that especially among healthcare
employees, less resources are needed to maintain operational alignment. Since these
resources are already scarce in primary healthcare processes, this clearly is an advantage.
Furthermore, if coordination occurs at the operational level, orchestrational issues such as
cross-organizational data integration become less challenging because they can be executed
centrally through the decisions in the coordinated operational alignment competency. This is
less so the case when just the orchestrational and strategic alignment competencies are
coordinated and operational configurations are left to individual hospitals. However,
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choosing to coordinate the operational alignment competency also causes healthcare
employees to feel less ownership of the EMR. Furthermore, fundamental changes to the EMR
are generally difficult and slow to implement because all hospitals using the EMR have to
agree to a specific change before it can actually be implemented.
For all of our case hospitals and in particular hospitals A and B, the EMR
implementation provided a substantial opportunity to found and develop an internal
COISA capability, which seems to be a sound basis to enable coordination and
collaboration on an ecosystem level. Hospitals aiming to coordinate their alignment
capabilities may consider to first found and develop such a capability in-house.
Furthermore, hospitals could pay specific attention involving suitable stakeholders in
building and evolving their COISA capability: Specifically, stakeholders’initiative shows
to be an important driver of the evolution of the COISA capability. Furthermore,
practitioners could be more conscious of potential external motivators for stakeholders to
drive COISA capability evolution. Specifically, driving events and emerging issues could
be leveraged to motivate stakeholders toward a co-evolutionary alignment dialogue,
eventually leading to better aligned HIT solutions.
5.2 Limitations and conclusion
Although we view this particular study’s added value for theory and practice to be
substantial, our study is not without limitations. First, we only studied three hospitals, all
situated in Western Europe. Especially given the seeming importance of stakeholders and
thus human factors, it would be interesting to see whether our findings hold in different
cultural contexts. Furthermore, our study was based mainly on retrospective interviews,
which may have influenced our findings (Yin, 2018). Future research could apply
ethnographic approaches and include observations as a research method to get an even
deeper insight into how alignment capabilities evolve around EMR in a hospital context.
Lastly, we did not get a comprehensive overview of all stakeholder perspectives in all
hospitals. For example, in Hospital B, we mostly interviewed people in advisory or IT-roles
and only a limited amount of healthcare employees, since these were relatively difficult to
access in this particular hospital.
Concluding, our study reveals the different ways in which the EMR-related COISA
capability evolved in three hospitals which all recently implemented a new EMR. In doing so,
we reveal a new lifecycle stage that shows how an internal COISA capability is scaled up to
multiple organizations working with the same EMR vendor. This adds to multiple existing
theoretical perspectives, including EMR alignment and capability evolution. Furthermore, we
underline the importance of stakeholders in the COISA capability’s evolution. Practitioners
can use our findings to effectively improve their EMR alignment through effective COISA
coordination and stakeholder involvement.
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Corresponding author
Pien Walraven can be contacted at: pien.walraven@ou.nl
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