digitization scope and experience the impacts of it on
TRANSCRIPT
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DIGITIZATION SCOPE AND EXPERIENCE:THE IMPACTS OF IT ON
PERFORMANCE IN HEALTHCARE ORGANIZATION
Pankaj Setia
Information Technology Management
Eli Broad College of Management
Michigan State University
And
Monika Setia, Ranjani Krishnan and V. Sambamurthy
Please do not cite or distribute without permission
ABSTRACT
Advances in the use of information technologies (IT) have led to the creation of digitized activity
systems in organizations. Though previous research has assessed the value impacts of specific
technologies or overall IT investments, we propose to examine how patterns in the use of
technologies impact performance outcomes. Specifically, we examine how the degree to whichinformation technologies is used within key activity systems creates value in the clinical and
business systems in the healthcare industry. We offer two constructs to capture the degree of ITuse: digitization scope, which refers to the number of technologies applied toward the
digitization of activity systems, and digitization experience, which refers to the amount of
experience with using information technologies within the activity systems. We propose and testhypotheses about the impacts of digitization scope and experience on performance across the
clinical and business activity systems in hospitals. Utilizing archival data on 292 hospitals in
California, our results demonstrate how the use of IT can have significantly distinct effects onperformance in the clinical and business activities in hospitals. More importantly, our research
points to how constructs related to the use of IT can explain distinct pathways in the impacts of
IT on firm performance, particularly in the healthcare sector.
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INTRODUCTION
Though prior research suggests that information technology (IT) can enhance operational and
financial performance in firms, the dynamics of these impacts is more complex than was initially
perceived (Barua and Mukhopadhayay, 2000; Tanriverdi, 2006). Recent research has utilized the
theoretical lens of complementarities as way of explaining how and why firms could utilize
information technologies in shaping superior performance (Sambamurthy et al., 2003; Barua and
Mukhopadhyay, 2000). Many empirical studies have examined complementary effects as the
integration of IT applications with specific organizational processes (Pavlou and Sawy, 2006,
Rai et al., 2006, Banker et al., 2006, Ray et al., 2004). Other research has studied
complementarities at the level of the enterprise (Aral and Weill, 2007). However,
complementarities could also be viewed in terms of the integration of information technologies
within a cumulative set of business processes, which are referred to as activity systems (Porter,
2001). Most contemporary firms seek to digitize entire activity systems, spanning customer
relationships, operations, financial management, and human resource management (Kalakota and
Robinson, 2003) through a portfolio of information technologies. Therefore, the performance
effects of IT should also be evaluated not just within specific business processes, but also in the
context of entire activity systems. In their seminal analysis, studying the shift from mass
manufacturing to flexible manufacturing systems, Milgrom and Roberts (1990) argue that
complementarities are also generated in firms due to numerous interactions between multiple
factors. They state,
we use the term complements not only in traditional sense of a relation between pairs of
inputs, but also in a broader sense as a relation among groups of activities. The definingcharacteristic of these groups of complements is that if the levels of any subset of the
activities are increased, then the marginal return to increases in any or all of the remaining
activities rises (p. 514).
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Consistent with their line of analysis, our research examines the performance impacts of
complementarities between portfolios of information technologies (i.e., a group of inter-related
digitized business processes) in firms.
Researchers also acknowledge that the nature and level of use of information technologies
plays a key role in the extent to which their impacts on performance are captured (Devaraj and
Kohli, 2003). The digitization of activity systems refers to the level of use of information
technologies within the activity system. Firms encounter two challenges in digitizing their
activity systems. First, a wide range of information technologies are available for digitization and
firms must explore which of these technologies are appropriate for their digitization efforts.
Digitization scope is defined as the variety of information technologies used in the digitization of
activity systems. Second, firms must also develop deep experience with the specific
technologies so that they can implement the needed complementary systems (e.g., business
process adaptations, rewards and incentives) and assimilate the technologies into their activity
systems. Digitization experience is defined as the amount of experience with using information
technologies within the activity systems. Our research examines the extent to which digitization
scope and experience influence the performance benefits gained from the use of information
technologies.
Our research is specifically conducted in the context of the healthcare sector. As a dominant
sector of the economy, the healthcare industry faces major institutional and regulatory pressures,
such as managed care, increasing numbers of uninsured patients, and continual pressures to
reduce costs and enhance the safety and quality of care. Information technologies are viewed as
one of the levers through which hospitals could enhance their financial and operational viability.
In fact, on April 27, 2004, President Bush signed an Executive Order establishing the position of
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National Coordinator for Health Information Technology, charged with the responsibility for
development, maintenance, and oversight of a strategic plan for nationwide adoption of health
information technologies. Research has found that investments in information technology are
associated with increased financial performance (Menon, Lee, and Eldenburg, 2000) and that
hospitals are investing considerably on business IT systems such as patient billing and credit and
collection systems to help enhance their revenues (Eldenburg and Krishnan, 2007). Other
research has focused on the impacts of two different types of information technologies in
hospitals: business and clinical technologies (Cezar, Menon, Yaylacicegi, 2007). Clinical IT
systems such as cardiology information systems, pharmacy management systems, and laboratory
information systems are valuable tools that assist physicians in patient treatment. Physicians
view clinical IT systems as critical factors that drive better quality health outcomes (Robinson
and Luft, 1988). Business IT systems such as costing systems, patient billing, nursing staff
scheduling, and credit collections are critical tools that are used by hospital managers to ensure
smooth administration and drive down costs, while enhancing customer satisfaction with
services. Thus, clinical and business activities represent two distinct activity systems in
healthcare organizations.
Our research examines the impacts of digitization scope and experience within the business
and clinical activity systems on the performance of hospitals. We use data from 292 California
hospitals to reveal that digitization scope alone is not sufficient to increase hospital performance
in their business and clinical activity systems. However, digitization experience shows
significant positive performance effects for business activity systems, whereas both digitization
scope and experience together impact the performance of clinical activity systems.
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The rest of the paper is organized as follows. The next section discusses the theoretical
development and research hypotheses. Next, we describe our data, research methods, and
analyses. Finally, we present our results and discuss their implications.
THEORETICAL BACKGROUND AND RESEARCH MODEL
Organization theory conceptualizes the firm as a set of adaptive routines that evolve with the
exploration of new possibilities and exploitation of old certainties (Schumpeter, 1934;
March, 1991; Eisenhardt and Martin, 2000). According to March (1991), organizational
exploration is associated with experimentation and variation, whereas exploitation is related with
refinement, production, efficiency, implementation, and execution.
Although they have very different impacts on performance, exploration and exploitation are
viewed as complementary, i.e., in the absence of one, the other has no effect (or might even have
adverse effects). For example, exclusive emphasis on exploitation, due to inherent short-term
improvements and the self-reinforcing nature of involved learning, often leads the organization
to ignore newer innovations (Leonard-Burton, 1995; March, 1991). As a consequence, the firm is
trapped in a sub-optimal local maximization strategy and loses its ability to find, evaluate, adopt,
and implement newer innovations (Rosenkopf and Nerkar, 2001). This hurts the firms ability to
thrive in a changing business and technological environment which offers opportunities for
newer adaptations and also threatens the basis for past performance (DAveni, 1994). Further, a
limited and exclusive focus on the exploitation of existing technologies creates an organizational
myopia that limits competencies (Levitt and March, 1988). The concept of exploration and
exploitation has been widely tested in the fields of organizational theory (Holmqvist, 2004; He
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and Wong, 2004), strategy (Winter and Szulanski, 2001), and managerial economics (Ghemawat
and Ricart i Costa, 1993).
Digitization of Activity Systems
As defined earlier, digitization is the level of use of information technologies within the
activity system. We focus on two dimensions of digitization, viz., digitization scope and
experience. Digitization scope refers to the exploration and adoption of a variety of information
technology solutions for the processes within an activity system. Digitization scope varies
according to the ongoing organizational actions in exploring the type of information technology
solutions that might be appropriate for digitizing activity systems, examining their potential
relevance and value, and adopting them for use within the activity systems. Information
technology solutions are developed both by the information systems departments as well as
vendors. As healthcare firms look for information technologies to enhance their performance, a
wide range of information technology solutions are becoming available for digitizing specific
processes and activity systems. Digitization scope is the number of information technology
solutions adopted within an activity system.
The second dimension of digitization is digitization experience. Prior research establishes
that the mere adoption of information systems is not enough (Fichman and Kemerer, 1999). The
adopting organizations must muster knowledge about which specific features of the
technological solution are appropriate (DeSanctis and Poole, 1994), how to mutually adapt the
technological solution and the activity system (Leonard-Barton, 1995), and how to trigger the
needed institutional efforts to routinize the use of the technological solution within the activity
system (Jasperson, Carter, and Zmud, 2005). All of these organizational efforts to exploit the
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capabilities of the technological solution require time and experience. Therefore, digitization
experience is defined as the amount of experience after the adoption of technology solutions
within the activity system.
The Effects of Digitization Scope
Two countervailing arguments are evident about how digitization scope could impact
performance. On one hand, the classical arguments about the benefits of information
technologies suggest that the exploration and adoption of a larger number of information
technology solutions will enhance performance because of their positive impacts on transaction
processing efficiency, decision-making speed and accuracy and organizational intelligence
(Huber, 1990). The ability of IT to enhance the reach and range of firms processes helps
organizations coordinate work across organizational boundaries at a much lower cost (Keen,
1991). Further, information technologies are associated with lower internal and external
coordination costs, and hence digitization should lead to overall lower costs of operations
(Gurbaxani and Whang, 1991). Within the clinical activity systems, greater digitization scope
implies that the hospital has adopted a larger number of clinical applications that cumulatively
would enhance the ability to gather, store, and disseminate clinical information across doctors
and treatment facilities. In addition, the adoption of more clinical applications could also
improve decision-making support by doctors (e.g., adverse medical interactions, prior treatment
history, etc.). Within the business activity system, greater digitization scope implies that
technological solutions to support a wide administrative and patient relationship management
activities (e.g., patient registration, billing, insurance claims) are available. They would benefit
improved efficiency and speed of business activity systems.
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However, the countervailing argument is that digitization scope simply captures the initial
adoption of a large number of information technology solutions. Regardless of the potential
benefits of the technological solutions, their benefits and impacts are not automatic. Prior
research on the assimilation gap demonstrates that there is a significant time lag between the
initial adoption and eventual use of information technologies in the firms activities (Cooper and
Zmud, 1990; Fichman and Kemerer, 1999). Thus, while firms are likely to gain from the
adoption of information technologies, mere adoption does not lead to the realization of their
superior capabilities. Exploration, due to its experimental nature, is known to be uncertain,
unless it is followed with an elongated period of exploitation. Emphasizing the opinion, March
(1991) points out returns from exploration are systematically less certain, more remote in
time, and organizationally more distant from the locus of action and adaptation (p. 73). In
addition, the introduction of new innovations is often disruptive and changes existing work
practices. In the case of a failure to assimilate the innovation, the organization is usually worse
off as it might lose its existing set of successful routines (Mitchell and Singh, 1993). Previously,
this has been documented in the health care organizations for the implementation of enterprise
resource planning (ERP) systems (Dryden, 1998). Therefore, greater experimentation and
exploration with new information systems in healthcare organizations may not be sufficient to
warrant performance improvements.
Taking these arguments into perspective, we propose that digitization scope within the
business or clinical activity systems will not have a significant link with hospital performance.
Therefore, we do not offer an explicit hypothesis.
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The Effects of Digitization Experience
Digitization experience captures the amount of time that a firm has been using any
information technology solution within its activity systems. Prior research has demonstrated that
at least three enabling factors are required in order to enhance the assimilation and use of any
information technology. First, depending upon the nature of the technological solution, users
must make sense of its features and how to apply it in the context of their work (DeSanctis and
Poole, 1994). Users experience significant knowledge barriers in making sense of the
technology and learning how to apply it effectively. With time and experience, they are able to
learn about the features and the effective ways of using them. Second, organizations should
enable assimilation by providing resources in the form of training, management support, or
rewards and incentives. Though these resources are vital, they do not guarantee high levels of
assimilation and use (Orlikowski, et al., 1995). In fact, they motivate users to invest their time
and attention toward making sense of the technology and discovering how to use it effectively.
Therefore, even in the presence of the enabling resources, users need time to develop the needed
experience and competence with the technology solutions. Finally, the effective use of the
technology requires mutual adaptations to the technology features and the work processes to
which it is being applied (Leonard-Barton, 1995). Through a recursive process, organizations
and users discover how to fit the features of the technology to the adapted tasks and
activities so that the technology features are being effectively used. As more time elapses, there
is a higher probability for the mutual adaptation to occur. Purvis, Sambamurthy, and Zmud
(1999) found that greater time since adoption enhances the organizational assimilation and use of
information technologies. Devaraj and Kohli (2003) demonstrated that higher levels of
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assimilation and use are key to the performance impacts of information technologies. Thus,
digitization experience should exhibit significant effects on performance and we propose that:
H1a: Higher levels of digitization experience in the business activity systems will be
significantly associated with the financial performance of hospitals.
H1b: Higher levels of digitization experience in the clinical activity systems will be
significantly associated with the financial performance of hospitals.
Further, we expect that the impacts of digitization experience on performance would vary
between the clinical and business activity systems in hospitals. The nature of clinical and
business activity systems is widely different. Business activity systems tend to be less complex
and more routinized than clinical activity systems. Clinical activity systems refer to the activities
of doctors and nurses in the delivery of medical care. Depending on the nature of the patient
care, different tasks and processes might be invoked in each instance. Many of the activities
might be time sensitive and require quick improvisations, or decisions by the doctors and nurses.
The various sub-processes related to these activities are often interdependent. The complex
clinical activity systems involve coordination across a wider range of processes and hence there
might be limits as to how much digitization experience alone can assist in realizing superior
performance. A well coordinated set of digitized processes would be sine-quo-non for the
realizing performance effects for these complex tasks. In contrast, business activity systems
involve well defined routines that are invoked most of the time in the same way for task
performance (e.g., patient registration, billing, insurance claims, etc.). Thus, digitization
experience alone can enhance the speed, efficiency and cost effectiveness of the performance of
business activities far more than the performance of clinical activities which require inputs from
a wide range of processes.
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each other in enhancing firm performance, and propose that these complementarities within the
business and clinical activity systems will enhance hospital performance:
H2a: Complementarities between digitization scope and experience within business activity
systems will be associated with a positive effect on financial performance of hospitals.
H2b: Complementarities between digitization scope and experience within clinical activity
systems will be associated with a positive effect on the financial performance of hospitals.
However, we also expect that the strength of the links between complementarities and
performance will be different between the clinical and business activity systems. Since they are
more complex, clinical activity systems are composed of a larger number of specific and
interdependent tasks and processes (for e.g., intensive care, radiology, medication management,
operating room, and laboratory). The greater interdependence is compounded by the fact that the
clinical professionals often work in compressed time frames. Therefore, coordination among the
digitized processes is vital. In other words, extended digitization scope will be a more vital
complement to experience in the case of clinical systems compared with business systems. If a
hospital develops digitization experience with a limited number of technology solutions, then the
other processes within the clinical activity system that are not well digitized could impair the
effectiveness of the digitized processes, because of the high levels of interdependence
(Thompson 1967). For example, if laboratory and radiology processes are not as well digitized
and assimilated with the operating room, the effectiveness of digitizing the operating room could
be impaired.
The simpler activities in the business systems call for lesser coordination. Thus,
complementarities between digitization scope and digitization experience will have an ever
greater effect in case of clinical activity systems. Beyond our hypothesized effects (H2a and
H2b), we propose that links between complementarities and performance will be stronger in the
case of clinical activity systems than business activity systems.
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DATA AND METHODS
The data for the research was collected from two different sources HIMSS Analytics and
the Healthcare Quality and Analysis Division of California Office of Statewide Health Planning and
Development (OSHPD). HIMSS collects data on information technology usage via a survey of
hospitals and maintains the data for 27,000 care delivery organizations (CDOs) including 3,989
hospitals through the U.S (Housman et al., 2007; Angst et al., 2007). They group data into two
categories of technologies according to the activity system to which they are applied. Forty
technologies are categorized as business technologies, and forty eight applications are
characterized as belonging to clinical activities (see table 1 for the details of these technologies).
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Insert Table 1 about here
--------------------------------------------
To avoid common method bias, data on financial performance of hospitals is obtained from a
different source - Healthcare Quality and Analysis Division of California Office of Statewide
Health Planning and Development (OSHPD). All acute care hospitals licensed by the State of
California are required to submit their annual financial reports to the OSHPD. These reports are
audited before generating the annual dataset. Besides financial information, OSHPD also reports
other data including information on ownership, size, and type of facility that is used in this
research.
Hospital Medicare id was used to merge the two databases together. Our final merged sample
consists of 292 observations for the year 2004.
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Operationalization
Dependent Variable. The hospital performance measure used in this research is net income
per patient day in hospitals. Due to the unique characteristic of healthcare, sales growth and
market share variables might not be appropriate for the study due to the geographic location and
a lack of profit focus that is a characteristic of a large number of hospital organizations. Further,
these variables only capture top line performance. Net income (NI) includes both the top line and
bottom line performance and hence was used to assess the overall value (Vh) for the hospital.
Further, the ratio of net income to patient days is used to remove any bias due to the number of
patients being managed by the hospital.
Independent Variables. Digitization scope and digitization experience were operationalized
through HIMSS data on the number of technological solutions adopted and used by each hospital
and number of years of experience with each of these solutions. The HIMSS database lists a
variety of tasks and processes within the business and clinical activity systems and details a list
of technological solutions for each process within those activity systems (see Table 1). Further,
for each of the hospitals, the database lists the specific technology solutions that they were using
and the year when that solution was initially adopted. We used the count of these technology
solutions as a measure of digitization scope within each activity system. Further, on the basis of
the year of adoption, we computed digitization experience as the number of years of use of each
solution till 2004.
Computation of Digitization Scope: If kih (0,1) indicates whether the information
technology i was adopted by the activity system in the hospital h, then digitization scope is
measured as the ratio:
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Exh = =
M
i 1
kih ( 1/N . ( ==
M
i
N
h 11
kih ) ) where N represents the total number of
hospitals in the sample, and M represents the total population of information technologies
available for the activity system . Since the information technologies include a wide range of
features and functionalities coded into them, Exh measures the extent to which a particular
hospital has explored its technology options to digitize work processes, relative to other
hospitals.
Computation of Digitization Experience: Digitization experience is defined as
Eph = =
M
i 1
Yih. kih ( 1/N . ( ==
M
i
N
h 11
Yih.kih) )
Where Yih represents the experience, or the number of years that a hospital h has used the
information technology i in its activity system . Eph measures the overall experience of the
activity system compared to the average years of experience of an activity system across all
hospitals.
Complementarities (h) Computation: Complementarities are measured as the interaction of Exh
and Ep
i.e. ( =
M
i 1
kih.=
M
i 1
Yih.kih ) ( 1/ 2N .( ==
M
i
N
h 11
Yih.kih) ) ( ( ==
M
i
N
h 11
kih) ) .
The alternate specification involves the assessment of an inverted U-curve (Gupta et al. 2006).
However, that requires digitization scope and digitization experience to be the two ends of a
continuum. Since the two are proposed to be orthogonal (and not continuous) dimensions,
interaction is the valid operationalization to assess the complementarities between them (Gupta
et al. 2006).
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Eighty percent of the hospitals in our sample have more than one year of experience, 50%
have more than 4 years of experience, and around 20% of the hospitals have more than 8 years of
experience with business information systems. For the clinical information systems, more than
half of the hospitals have between 1-1/2 years and 3 years of digitization experience. The
average size of the hospital measured as the mean number of beds staffed is 196. A majority of
hospitals (91%) are general hospitals with the remaining 9% being childrens, psychiatric, or
other specialty types. Sixty one percent of the hospitals are non-governmental not-for-profit and
the rest 39% are either owned by investors, city/county, or district. The descriptive statistics of
all variables used in the study are reported in table 2.
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Insert Table 2 about here
--------------------------------------------
Control Variables
Since our focus in this research is to analyze the financial performance of hospitals, we
control for other healthcare related factors that might impact performance. Past research has
found that a hospitals financial performance is likely to be influenced by size, type, and
ownership. The number of staffed beds was thus used as measure to control for the size. A
dummy variable was used to control for the type of hospital, which took the value of 1 if the
hospital was a specialty hospital and zero otherwise. We used three dummy variables to control
for the three ownership types - government, non-profit and for profit. The government dummy
took the value of 1 if the hospital was a government hospital and zero otherwise. The nonprofit
and for-profit dummies were coded in a similar manner. We dropped the government dummy
from the empirical modes to prevent singularity problems. In addition, we also controlled for
product mix by including the proportion of revenue from Medicare patients and Medicaid
patients. We controlled for asset intensity by including the ratio of patient revenue to total assets
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as a control. Because the regulatory and competitive environment faced by hospitals differs
across states, our sample consists of hospitals only from the state of California.
Empirical Model
We use the hospital as the unit of analysis. After ensuring that the data did not violate the
regression assumptions, we estimated the following regression model using net income per
patient as the dependent variable:
Vh = b0h + bxbh Exbh + bpbhEpbh + bxch Exch + bpch Epch + bbhbh + bchch + b7hZh + h (1)
Where:Vh (NetIncPt)_ = Net income per patient for hospital (h).
Exb(Expr_BusIT)= Ratio of the number of business information technology applications installedin a hospital (h) to average installed for all sample hospitals (digitization scope in business
activity systems)
Exc (Expr_ClnIT)= Ratio of the number of clinical information technology applications installed
in a hospital (h) to average installed for all sample hospitals (digitization scope in clinical
activity systems)
Epb (Explt_BusIT)= Ratio of the number of years of experience of hospital (h) with business IT
applications to average experience across all hospitals in sample (digitization experience in
business activity systems).
Epc (Explt_ClnIT)= Ratio of the number of years of experience of hospital (h) with clinical IT
applications to average experience across all hospitals in sample (digitization experience inclinical activity systems).
b (ComBnBe)= Complementarities in business activity systems, defined as the multiplicative
product ofExb andEpb
c (ComCnCe)= Complementarities in clinical activity systems, defined as the multiplicative
product ofExc andEpc
Zh = Vector of other factors related to income of a hospital including bed staffing level,
ownership type and type of care provided by the hospital, proportion of traditional and managedcare Medicare revenues, and assets per patient for each hospital (h).
Coefficients bxbh, bpbh, bxch, bpch, bbh, and bch represent estimated effects of the explanatory variablesand h is the random error term.
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Complementarities Estimation
To compare the relative impacts of complementarities vis--vis the effects of digitization
scope and digitization experience, we formulated two ratios -Relative Synergistic Impact Ratio
(RSIR), and Cross System Synergistic Ratio (CSSR). These ratios are assessed to interpret
synergistic effects that have not been explored before in the context of healthcare IT.
Let Exh , Eph represent the extent of digitization scope and experience, respectively, by a
hospital h in its activity system , and h represents the degree of interaction between the two
for the activity system where (b,c), where b represents business activity system, and c
stands for clinical activity system. Thus, using the standard notation the value for hospital h,
Vh= f(Exbh, Epbh, Exch, Epch,bh, ch) is a function of two pairs of independent variables Exh and
Eph, and their joint synergistic effect h which is often conceptualized as the relative impact of
one variable in the presence of the other, or px
2
EE V (Milgrom and Roberts 1990, 1995,
Siggelkow 2002). Recently, this formulation of synergies as second order cross partial derivative
has been emphasized to be an important conceptualization that distinguishes complementarities
effect from alignment, fit and other interaction effects (Tanriverdi and Lee 2008). Our treatment
of synergies follows this notation throughout the rest of the paper.
In this research, we conduct several empirical tests to assess and compare the impact on
value of synergies in business and clinical activity systems. These empirical evaluations related
to px
2
EE V are important to improve organizational decision making which relies on the
knowledge of these interactions. Faulty managerial decisions are often a result of the
misinterpretations of these interactions effects (Siggelkow 2002). Three types of empirical
assessments of these synergistic effects are presented to interpret the results.
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greater impact on value than the direct impact of digitization scope and experience. Two types of
RSIR ratios are pertinent to each of this activity system - RSIRx and RSIRp, while the former
are related to the effects of digitization scope, the latter pertain to the effects of digitization
experience. As an illustration, the test of relative impacts in the case of business activity
systems, involves the evaluation:
i. whether RSIRxb = (pbxb
2
EE V ) (
xbE V ) 1, and
ii. whether RSIRpb = ( pbxb
2
EE V ) (
pbE V )1.
A similar evaluation is done in the case of clinical activity systems.
Combined with the first assessment, test of RSIR offers valuable managerial information
related to interactive effects. For example, px
2
EE V >0, and RSIRj >1, j (x, p), and
(b, c), imply that the nature of interaction is complementary, and necessitates a greater
managerial attention because the incremental returns to direct effects are limited and less than the
synergistic effects. px
2
EE V 1, on the other hand, implies that though the
interaction effect is still stronger than the direct effect due to the substitutive nature of the
interaction the impacts on performance is not as much in case the interaction effects are not
recognized by managers (Siggelkow 2002). Similarly, other combinations offer unique insights
that can be leveraged for optimal management of organizational complements.
Finally, the last empirical assessment is related to the comparison of synergies between
digitization scope and experience effects across the two activity systems. This relative
assessment of the synergies impacts is done by evaluating the Cross System Synergistic Ratio
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(CSSRij) defined as the ratio of synergies across the two activity systems i and j, i j. In this
study, the ratio measures the relative impact of synergies in the clinical activity systems as
compared with those in the business activity systems, and is given as CSSRbc =
(pbxb
2
EE V ) (
pcxc
2
EE V ) . A value greater than 1 for the ratio will imply that
the clinical synergies between digitization scope and experience have greater impact than
corresponding synergies in the business systems, whereas a value less than 1 will imply the
greater impact of synergies between digitization scope and experience of clinical activity
systems.
RESULTS
Table 3 contains the results of estimating equation 1. The adjusted R2 of the regression is
14%. The results for business technology systems indicate that digitization scope (Ex), with the
business IT systems does not lead to superior performance. Similarly, higher digitization scope
of clinical IT (Exc) is not associated with performance. Recall that we had not offered
hypotheses about the effects of digitization scope.
A different pattern of results emerges for digitization experience. The results in Table 3
indicate a positive and significant coefficient on digitization experience within business activity
systems. This result is consistent with H1a and indicates that experience with business IT (Epb)
yields a positive payoff to the hospital. H2b predicted that greater digitization experience within
clinical systems (Epc) will be associated with a significant positive effect on the financial
performance of hospitals. However, the results in Table 3 indicate that digitization experience
with clinical IT is negatively associated with performance. These results do not support
hypothesis H2b.
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Next we did the three empirical tests proposed for complementarities. The first test was
related to the assessment whether px
2
EE V is greater than, equal to, or less than zero.
pbxb
2
EE V is found to be insignificantly different from zero (Table 3) and hence H2a, which
predicted that complementarities between digitization scope and experience exploitation within
business systems will be associated with a positive effect on financial performance of hospitals,
is not supported. This result suggests that for business activity systems, digitization experience
itself is sufficient. The results for clinical activity systems however indicate thatpcxc
2
EE V
>0 i.e. it is positive and significant. This indicates that synergies between digitization scope and
experience within clinical systems are associated with a positive effect on the financial
performance of hospitals, as predicted by H2b. The net overall effects of digitization experience
(the total of direct and complementary effects with digitization scope) are positive, suggesting
that joint exploration and exploitation are essential to realize superior performance from more
complex clinical information systems. To summarize, the first assessment of complementarities
establishes positive interaction between digitization scope and digitization experience effects
within clinical systems, but finds these to be independent in the case of business systems. The
results of the hypotheses tests are summarized in Table 4.
--------------------------------------------
Insert Tables 3 and 4 about here
--------------------------------------------
The second empirical test of complementarities was focused at the assessment ofRelative
Synergistic Impact Ratios - RSIRx and RSIRp. In the case of business activity systems, RSIRpb
is less than one indicating that returns from joint synergistic interaction are greater than
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digitization experience alone (see Table 5). RSIRxb, on the other hand is undefined and hence this
study is not able to accomplish the relative assessment of complementarities with the digitization
scope of business IT applications since the digitization scope and complementary effects are both
found to be insignificant. Both RSIRxc andRSIRpc are found to be greater than 1 (Table 5) thus
indicating that returns from joint synergistic interaction are greater compared to the direct impact
of digitization scope and experience within the clinical activity systems. These results indicate
that the effects are different across the two activity systems. More complex clinical activity
systems have greater synergistic impacts as compared to the independent impact of digitization
scope (Exc) and experience (Epc) effects, whereas for the business activity systems, digitization
experience (Epb) effects are greater than the synergistic impacts.
Finally, we assessed the cross system complementarities effects using the ratio CSSRbc which
is found to be less than 1 (see Table 5). This indicates that the between the two activity systems,
the comparative impacts of synergistic interaction is greater for clinical systems as compared
with that for the business systems.
--------------------------------------------
Insert Tables 5 about here
--------------------------------------------
Sensitivity and Robustness analysis
We tested the various assumptions for regression analysis and statistical testing before doing
the analysis. The data was found to be normal and Breusch-Pagan test for heteroskedasticity and
the Linktest for specification errors ruled out any threat to our results due to violation of these
regression assumptions. Further, we tested the robustness of the results to the violation of
distributional assumptions by estimating a non-linear regression. In this regression, the
dependent variable was transformed by taking the square root of the dependent variable (net
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income per patient) in the original parametric model in equation 1. Because the dependent
variable had negative values for some of the observations, the largest negative value was added
to the DV before taking the square root. In addition, the number 1 was added over and above the
addition of the biggest negative value because square roots behave differently for numbers
between 0 and 0.99 (the square root of the number decreases as the number itself increases) as
compared with the numbers that are greater than or equal to 1 (the square root of the number
increases as the number itself increases). The addition of number 1 makes all observations
greater than or equal to 1. Results are robust to the transformation of the dependent variable and
are reported in table 6.
--------------------------------------------
Insert Table 6 about here
--------------------------------------------
We also re-estimated the results using absolute definitions for digitization scope and
experience. That is, digitization scope was defined as the number of information systems
adopted, while experience was defined as the sum of years of experience with information
systems. The results were qualitatively unchanged.
Test for Endogeniety. It is possible that firms which have more resources because of better
financial performance are also more likely to invest in clinical and business IT. That is, net
income and digitization scope of business and clinical activity systems may be simultaneously
determined. To rule out this possibility, we tested the robustness of our results using the two-
stage least squares (2SLS) technique and compared our OLS results to 2SLS (Greene 2000). In
the first stage of the 2SLS, we used the likely endogenous variable (number of business or
clinical IT) as the dependent variable and all the other exogenous variables as independent
variables. We extracted the predicted values of the endogenous variables (number of business or
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Digitization Scope and Experience: Performance impacts in Healthcare Organizations
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clinical IT) and used these predicted values as instrumental variables in equation 1, in the second
stage. The results from the 2SLS were similar to those reported in Table 3, which indicates that
our results are not likely to be influenced by endogeneity concerns.
Finally, although we had included the proportion of revenue from Medicare and Medicaid to
control for the patient mix, we also examined the robustness of our results to the inclusion of the
case method index as an additional control variable. The case mix index is a measure of the
average severity of illness of patients treated in the hospital. There was no change in the results
after the inclusion of the case-mix index.
DISCUSSION
Organizations face relatively long periods of incremental change punctuated by changes
driven by technology, competitors, regulatory events, or other significant changes in political and
economic conditions (Tushman and OReilly, 1996). Newer information technology solutions
are developed with functionality to monitor, manage, and incorporate these changes. This
research studies the dynamics of introducing these information technology solutions into a firms
digital activity system. To the best of our knowledge, the research is the first to empirically test
the performance effects of exploration and exploitation of information technologies and their
synergistic effects at the level of an activity system. Further, there is a paucity of research that
examines the role of IT in adding value in healthcare organizations. This research, answers the
calls from the national health IT leadership panel to bring in the theories and concepts from other
disciplines to study the role of IT on hospital performance. (Lewin Group, 2005)
Our empirical analyses use data from 292 California hospitals to examine the effect of
digitization scope and experience and their synergies in clinical and business activity systems.
Our results indicate that in the case of business activity systems, digitization scope does not
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impact performance, but digitization experience has a significant positive impact on
performance. In addition, the interaction between digitization scope and experience does not
yield positive effects, contrary to the proposed argument in the current literature that exploration
and exploitation are always complementary.
However, a different pattern of results emerge when we examine the effects of digitizing
clinical activity systems. Digitization scope does not yield positive benefits and digitization
experience results in a negative impact on profits. Thus, our results indicate that in the case of
clinical activity systems, digitization experience alone is not sufficient and in fact has negative
impacts. This suggests that limited digitization of the parts of the clinical activity system
hampers the performance of the doctors and nursing staff as they have to coordinate work across
manual and digital systems. However, the interaction between the two has positive effects on
profits indicating that digitization scope and experience are both needed for performance
improvements in the clinical systems. These results are consistent with those of Cezar et al.
(2007), who use data from Washington hospitals and find that expenditures on clinical IT
(similar to our scope variable) do not have either an immediate or a lagged positive impact on
organizational performance.
The research is not without limitations. While we use the exploration and exploitation
paradigm to assess the complementarities within the activity system, it cannot be claimed that
our measures fully capture the complete diversity of the two constructs. Many other
organizational dynamics may influence exploration and exploitation effects within the
organization. Researchers in the field of organizational theory (Holmqvist, 2004; He and Wong,
2004), strategy (Winter and Szulanski, 2001) and managerial economics (Ghemawat and Ricart i
Costa, 1993) have highlighted the differences in the firms structure, processes, strategies, and
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culture that are associated with exploration and exploitation. While exploration is usually
characterized by loosely coupled organic structures, and autonomy and chaos, exploitation often
involves tightly coupled mechanistic structures, and controlled and rigid routines (Eisenhardt and
Martin, 1998; Burns and Stalker, 1961). Indeed exploration and exploitation are complex
constructs with multiple dimensionsand their definition and connotation has been a subject of
wide debate (Gupta et al. 2006). We use proxies because of the nature of our secondary data.
While secondary data offers objectivity in measurement, it does so at the expense of the richness
that can be captured in more detailed inquiry using survey instrument. We believe that our
method of using digitization scope as a proxy to measure exploration and experience as a proxy
to measure exploitation is appropriate in the case of digitization of activity systems, and has been
extensively used in prior research (for example, Rothaermel and Deeds, 2004; Katila and Ahuja,
2002).
In spite of these limitations, our results shed interesting insights on the digitization of two
important activity systems, clinical and business, and suggest that future research is warranted in
this setting. Our research also makes important contributions to the literature on complementary
effects of IT. While synergistic interactions are often proposed to be essential for realizing
performance impacts of IT systems, our empirical findings indicate that the significance of these
impacts is contingent to the context of the study. Our results suggest that synergistic interactions
between exploration and exploitation of IT are more likely to materialize in the case of complex
activities such as clinical activities. On the other hand, in the case of relatively simpler business
IT systems, exploitation is sufficient to produce higher returns. To provide better control, we
restricted our study to the hospital industry. Future research could examine whether these results
hold in other industries.
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Empirical estimation of complementarities has added to the complementarities estimation in
three ways. The first test has established a test for differentiation of synergistic interaction to be
substitutive, complementary or independent in the independent variables. Second, test has
developed the concept ofRelative Synergistic Impact Ratios (RSIR), whichhelps determine the
impact of synergistic interaction relative to the direct impacts. Finally, the relative impact of
synergies across business units can be assessed using the proposed Cross System Synergistic
Ratio (CSSR). This three pronged approach for the assessment of complementarities offers first
structured way for empirical assessment which have gained increased traction from researchers.
Our systematic testing of these effects will help establish a framework that will guide future
empirical assessment of complementarities.
Our research has focused on interactions within the business and clinical information
systems. Hospitals are currently exploring IT systems that integrate both clinical and business
modules to provide support to clinical as well as business functions (Vernon, 2005, Serb, 2006).
Future research could examine more complex interactions such as those across business and
clinical systems and explore the pattern of results that emerge when these systems are integrated.
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Table 1: Clinical and Business Technologies included in the Analyses
Clinical Software Applications Business Software Applications
Category Application Category Application
Intensive
Care Ambulatory Clinical Accounts Accounts Payable
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Ambulatory EMR Cost Accounting
Ambulatory Laboratory General Ledger
Ambulatory PACS Billing/Insurance Contract ManagementAmbulatory Pharmacy Credit/CollectionsAmbulatory Radiology Eligibility
Cardiology Cardiology - Cath Lab Encoder
Cardiology - CT
(Computerized Tomography) Patient BillingCardiology - Echocardiology Premium/Insurance Billing
Cardiology - Intravascular
Ultrasound Financing
Data Warehousing/Mining -
FinancialCardiology - Nuclear
Cardiology Financial Modeling
Cardiology InformationSystem
Forms &
Documents
Document Management -Business Office
Home Health Home Health Clinical
Document Management -
HIM
Intensive
Care
Intensive Care/Critical Care(ICU)
Document Management -Human Resources
Intensive Care/Medical
Surgical
Electronic Forms - Business
Office
Laboratory Anatomical Pathology Electronic Forms HIM
Laboratory Information
Systems
Electronic Forms Human
Resources
Microbiology Home Health Home Health Administrative
Medication
Management
Electronic Medication
Administration Record
Patient
Information ADT/RegistrationOutpatient Pharmacy Abstracting
Pharmacy Management
System Case Mix Management
Operating
Room
Operating Room (Surgery) -
Peri-Operative Patient Scheduling
Operating Room (Surgery) -Post-Operative Operations Blood Bank
Operating Room (Surgery) -
Pre-Operative Scheduling Medical Staff Credentialing
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Table 1 (continued): Clinical and Business Technologies included in the Analyses
Patient
Medical
Information
Computerized PractitionerOrder Entry (CPOE) Nurse Staffing/Scheduling
Data Warehousing/Mining
Clinical OR SchedulingDictation Staff Scheduling
Dictation with Speech
RecognitionEmployee
Information Personnel Management
Enterprise EMR Time and Attendance
Enterprise Master Person Index
(EMPI) Benefits Administration
In-house Transcription Hospital Supplies RFID - Supply Tracking
Nursing Documentation Materials Management
Outsourced Transcription
Physician Documentation Other Clinical Data Repository
PatientSurveillance Chart Deficiency Enterprise Resource Planning
Chart Tracking/Locator Executive Information Systems
Clinical Decision Support Interface Engine
RFID - Patient Tracking Practice Management
Radiology Radiology - Angiography
Order Entry (Includes Order
communications)
Radiology - CR (Computed
Radiography)
Outcomes and Quality
Management
Radiology - CT (Computerized
Tomography) Budgeting
Radiology - DF (Digital
Fluoroscopy) Business IntelligenceRadiology - DigitalMammography
Electronic Data Interchange(EDI) - Clearing House Vendor
Radiology - DR (Digital
Radiography) Payroll
Radiology - MRI (Magnetic
Resonance Imaging)
Radiology - Nuclear Medicine
Radiology US (Ultrasound)
Radiology Information System
Telemedicine - Radiology
Others
Emergency Department
Information Systems (EDIS)Medical
Terminology/Controlled
Medical Vocabulary
Nurse Acuity
Obstetrical Systems (Labor &
Delivery)
Respiratory Care Information
Systems
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Table 2 : Descriptive Statistics for Selected Variables (n=292)
Variable Description Mean Std. Dev. Min Max
Expr_BusIT (Exb)Relative exploration of a hospital with
business Information Systems 1 0.25 .25 2.46
Explt_BusIT(Epb)
Relative exploitation of business
Information Systems by the hospital 1 0.34 .13 3.02
Expr_ClnIT(Exc)
Relative exploration of a hospital with
clinical Information Systems 1 0.75 0 2.66
Explt_ClnIT(Epc)
Relative exploitation of clinical
Information Systems by the hospital 1 0.66 0 2.77
No of Business IT
Number of information systems in business
domain 16.28 4.04 4.00 40.00
No of Clinical IT
Number of information systems in clinical
domain 15.93 5.39 2.00 48.00
Experience with
Business IT
Experience (In years) with business
information systems 54.30 40.64 0.00 144.33
Experience with
Clinical IT
Experience (in years) with clinical
information systems 14.18 9.30 0.00 39.25
Bed_Stf Number of staffed beds 196.74 139.14 2.00 875.00
AsstCtrl Total Assets Per Patient Days 2957.71 2458.20 136.65 23242.50
McrtCntr Net Patient Revenue from Medicare 2.65 2.76 -0.49 23.63
McltCntr Net Patient Revenue from Medicaid 1.96 5.05 -2.07 57.78
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Table 3: Regression Results for dependent variable Net income per patient
Variable Description
Standardized
Coefficient Standard Error t-statistics
Business Information Systems
Expr_BusIT(Exb)
Digitization scope of the
hospital within the business
activity system. 0.13 2275.24 0.90
Explt_BusIT(Epb
)
Digitization experience of the
hospital within the businessactivity system. 0.73 1926.35 2.00*
ComBnBe (b)
Complementarities measured as
interaction between
Expr_BusIT and Explt_BusIT -0.68 1573.30 -1.74
Clinical Information Systems
Expr_ClnIT(Exc)
Digitization scope of the
hospital within the clinical
activity system. -0.21 1902.92 -1.23
Explt_ClnIT(Epc)
Digitization experience of the
hospital within the clinical
activity system. -0.52 1543.47 -2.02*
ComCnCe(c)
Complementarities measured as
interaction between
Expr_ClnIT and Explt_ClnIT 0.58 1573.30 1.98*
Control Variables
Bed_Stf Number of Staffed beds -0.23 2.83 -2.33*
AsstCtrl Total Assets Per Patient Days 0.07 0.09 1.18
McrtCntr
Net Patient Revenue from
Medicare 0.22 129.92 2.41*
McltCntr
Net Patient Revenue from
Medicaid 0.35 57.17 4.75**
NPProfit_DumDummy Variable for non-profithospitals -0.21 760.52 -2.23*
FPProfit_Dum
Dummy Variable for for-profit
hospitals -0.13 853.54 -1.39
Type_Care
Type of Care Provided by
Hospital 0.11 356.10 1.94Adjusted R2 of the Regression
model (F value, and P-value in
0.15 (F=4.94, p
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parentheses)
* Coefficients significant at p
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TABLE 5: Results of Complementary Estimation
Estimated
Statistic Measure Value Test Result
Synergistic
Business
Interaction pbxb
2
EE V
Not
significantly
different from
Zero =0
Di
exp
tec
Synergistic
Clinical
Interaction pcxc
2
EE V
0.58 >0
Di
exp
tec
com
RSIRxb
(pbxb
2
EE V ) (
xbE V )
Un Defined Inconclusive
Re
dig
syn
bu
no
RSIRpb
(pbxb
2
EE V ) (
pbE V )
0 1
Co
cli
tha
eff
RSIRpc
(pccb
2
EE V ) (
pcE V )
1.12 >1
Co
cli
tha
exp
CSSRbc
(pbxb
2
EE V ) (
pcxc
2
EE V )
0
-
8/3/2019 Digitization Scope and Experience the Impacts of It On
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Digitization Scope and Experience: Performance impacts in Healthcare Organizations
** Coefficients significant at p