1. FÖV/SPEA Workshop 2011: Robert Piehler & Linda Mory 1
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FÖV/SPEA Workshop 2011
Robert Piehler & Linda Mory
Speyer, July 16th 2011
The Acceptance of Electronic Health
Records among Hospitals
An Intercultural Comparison between the USA and
Germany

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1. Introduction
2. Basic Terminological Principles
3. Research Question
4. Methodological Approach
Outline
5. Conclusion

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• The U.S. as well as the German health care system face challenges
on multiple fronts, including rising costs and inconsistent quality1
• Health information technology, especially electronic health records (eHR),
has the potential to improve the efficiency and effectiveness of health
care provider2 and to improve the quality of care while controlling health
care costs3
• Despite broad consensus on the potential benefits of electronic health
records and other forms of health information technology, U.S. and German
health care providers have been slow to adopt them
• Therefore, the question arises, what factors positively influence the
acceptance of the eHR in the United States and Germany
• Are there major differences between those two countries and if so, what
could be reasons for that
Current Situation in the United States and Germany I
1. Introduction
1. Smith et al. (2004); Jha et al. (2005); Pfaff/Ernstmann (2007); Ashish et al. (2009)
2. Ashish et al. (2009); Chaudhry et al. (2006); Blumenthal/Glaser (2007)
3. Ashish et al. (2006)

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A representative study from 2009:
On the basis of responses from
63.1% of hospitals surveyed, only
1.5% of U.S. hospitals have a
comprehensive electronic-
records system (i.e., present in
all clinical units), and an
additional 7.6% have a basic
system (i.e., present in at least
one clinical unit). Computerized
provider-order entry for
medications has been
implemented in only 17% of
hospitals.
United States Germany
No studies found:
Because electronic health record
in Germany is integrated in the
electronic health card.
1. Introduction
Current Situation in the United States and Germany II

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2. Basic Terminological Principles
3. Research Question
4. Methodological Approach
Outline
5. Conclusion
1. Introduction

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ISO Definiton of eHR
Although there is no universally accepted definition of eHR, consensus is emerging that
electronic documentation of providers’ notes, electronic viewing of laboratory and radiology
results, and electronic prescribing (known as computerized provider order entry, or CPOE) are
key components of an eHR – these are some of the elements identified by the Institute of
Medicine (IOM) in a report on the features of eHR systems
Synonyms that are often used in the context of eHR: electronic patient record (ePR), electronic
medial record (eMR) or computerised patient record
Basic-generic eHR Definition
EHR is a repository of information regarding the health
status of a subject of care, in computer processable
form.
This definition (to be called the “basic-generic eHR”) is
intentionally concise and generic to ensure the broadest
applicability to the widest range of existing and future
users of eHRs and eHR systems.
Integrated Care eHR Definition
The Integrated Care eHR (ICeHR) is defined as a repository
of information regarding the health status of a subject of care
in computer processable form, stored and transmitted
securely, and accessible by multiple authorised users. It has
a standardised or commonly agreed logical information
model which is independent of EHR systems. Its primary
purpose is the support of continuing, efficient and quality
integrated health care and it contains information which is
retrospective, concurrent, and prospective.
2. Basic Terminological Principles
Definition eHR

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eHR can be classified as:
• Comprehensive eHR
Systems
• Basic eHR Systems with
Clinical Notes
• Basic eHR Systems
without Clinical Notes
2. Basic Terminological Principles
eHR Classification in the United States

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3. Research Question
4. Methodological Approach
Outline
5. Conclusion
1. Introduction
2. Basic Terminological Principles

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3. Research Question
• Which factors determine the acceptance of eHR from a healthcare
provider perspective?
• How do these factors influence acceptance and use of eHR?
• Which external effects moderate the relation between factors and
acceptance?
• Which differences exist between healthcare providers from distinct
countries/national healthcare systems?
Main Research Questions

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Barriers:
• Inadequate IT Staff
• Physicians Resistance
• …
Facilitators:
• Technical Support
• Financial Incentives
• …
1. vgl. Ashish et al (2009)
Possible Barriers and Facilitators
3. Research Question

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Outline
5. Conclusion
1. Introduction
2. Basic Terminological Principles
4. Methodological Approach
3. Research Question

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1. vgl. Venkatesh et al (2003).
2. vgl. Fishbein/Ajzen (1975).
3. vgl. Davis (1986).
4. vgl. Davis/Bagozzi/Warshaw (1989).
4. Methodological Approach
Performance
Expectancy
Effort Expectancy
Behavioral
Intention
Use
Behaviour
Social Influence
Facilitating
Conditions
Voluntariness
of Use
ExperienceAgeGender
Unified Theory of Acceptance (UTAUT) I
• Individual Level
• Rational Approach
• IT-Focus
• Self-Assessment/Self-Evaluation

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1. vgl. Davis et al. (1989).
2. vgl. Bruner/James/Hensel (2001); Davis/Bagozzi/Warshaw (1989).
3. Venkatesh et al. (2003)
Performance
Expectancy
Effort Expectancy Social Influence
Facilitating
Conditions
Behavioral
Intention
Use
Behaviour
Facilitating
conditions are
defined as the
degree to which an
individual believes
that an
organizational
and technical
infrastructure exists
to support use of
the system. 3
Social influence is
defined as the
degree to which an
individual perceives
that important
others
believe he or she
should use the new
system.3
Effort expectancy is
defined as the
degree of ease
associated with the
use of the system.1
Performance
expectancy is
defined as the
degree to which an
individual believes
that using the
system will help
him or her to attain
gains in job
performance.1
Behavioral
Intention is defined
as the tendency to
behave in a certain
way.2
Use Behaviour is
defined as actual
usage of the IT
system.
4. Methodological Approach
Performance
Expectancy
Effort Expectancy
Behavioral
Intention
Use
Behaviour
Social Influence
Facilitating
Conditions
Voluntariness
of Use
ExperienceAgeGender
Unified Theory of Acceptance (UTAUT) II

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Solution:
• Identification of indicators which can be measured
explicitly to measure the latent variables indirectly
• Calculation of the correlations between the
indicators
• Decomposition of the indicator correlations to the
correlations of the latent variables
• Calculation of the correlations between the latent
variables by solving a multidimensional linear
system of equations
Empirical validation of latent construct, which was deduced from theory, and its relations to
other constructs.
Point of Departure Examples Problem
• A system of relations which
has been deduced from theory
needs to be tested by
empirical analysis
• The acceptance of eHR is
determined by reduced costs of
action.
• The interaction configuration
between the stakeholders is
relevant for the acceptance of
eHC.
• Regression analysis can be
employed for the 1st
example since all variables
can be measured directly.
However, in the 2nd
example the variables
cannot be measured directly.
They are latent.
4. Methodological Approach
1
x1
x2
1
y1
y2
Measurement model
of the latent exogenous
variables
Structural model
2
y3
y4
Measurement model
of the latent endogenous
variables
1
2
Methodology: Structural Equation Modelling

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Outline
5. Conclusion
1. Introduction
2. Basic Terminological Principles
3. Research Question
4. Methodological Approach

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5. Conclusion
• Given the increasing importance of eHealth, this research sketch
concentrates on the issue of acceptance regarding the use of electronic
health records
• Based on both the UTAUT model (Venkatesh et al. 2003) and the relevant
literature, important factors influencing the attitude towards and the
potential use of the eHR are presented in order to conceptualize and
integrate them in a research model later
• The goal is to conduct a comparative empirical examination throughout
the United States and Germany analysing the data with structural
equation modeling using AMOS statistics software
Conclusion

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Thank You