The Use of Health Information Technology to Improve Care and .docx

The Use of Health Information Technology to Improve Care and
Outcomes for Older Adults
Kathryn H. Bowles, PhD, FAAN, FACMI,
van Ameringen Professor in Nursing Excellence, Director of the
Center for Integrative Science in
Aging, University of Pennsylvania School of Nursing,
Philadelphia, PA
Patricia Dykes, PhD, FAAN, FACMI, and
Senior Nurse Scientist, Director of the Center for Patient Safety
Research and Practice; Director
of the Center for Nursing Excellence, Brigham and Women’s
Hospital, Boston, MA
George Demiris, PhD, FACMI
Alumni Endowed Professor in Nursing; Professor in Biomedical
and Health Informatics, School of
Medicine; Director, Clinical Informatics and Patient Centered
Technologies; Graduate Program
Director, Biomedical and Health Informatics University of
Washington, Seattle, Washington
Introduction
Using health information technology (HIT) to improve care and
outcomes for older adults is
a growing program of research propelled by recent
transformative policies such as the
Health Information Technology for Economic and Clinical

Health (HITECH) Act
(Blumenthal, 2010; Institute of Medicine, 2011) and the
Institute of Medicine report, "The
Future of Nursing: Leading Change, Advancing Health."
(Institute of Medicine, 2010). Both
documents call for the implementation of electronic health
records (EHR) and HIT solutions
to improve the safety, quality and efficiency of care. Several
nurse scientists are at the
forefront of advancing this work, particularly using electronic
health records, decision
support and telehealth. This commentary highlights examples of
recent research (2010–
2014) led by nurse scientists using HIT to improve patient
safety, and the quality and
efficiency of patient care. We also discuss future opportunities
for Gerontological nurse
scientists interested in blending the care of older adults and HIT
and suggest strategies to
increase our capacity to engage in such innovative research.
Using the EHR to improve outcomes for older adults
Recent incentives provided by the HITECH Act have resulted in
rapid growth in the

development and implementation of the EHR. Nurse led studies
are beginning to
demonstrate that effective use of the EHR can improve
outcomes of relevance to older
adults such as pressure ulcers and falls. Dowding and
colleagues evaluated the impact of an
integrated EHR in 29 Kaiser Permanente hospitals on process
and outcome indicators for
patient falls and hospital acquired pressure ulcers (Dowding,
Turley, & Garrido, 2012).
They found that the EHR system was associated with improved
documentation of both fall
and pressure ulcer risk assessments and statistically significant
improvements for pressure
ulcer risk assessment documentation. They demonstrated that
improved documentation
using the EHR was associated with a 13% decrease in hospital
acquired pressure ulcer rates.
HHS Public Access
Author manuscript
Res Gerontol Nurs. Author manuscript; available in PMC 2015
May 14.
Published in final edited form as:
Res Gerontol Nurs. 2015 ; 8(1): 5–10. doi:10.3928/19404921-
20121222-01.

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The patient fall rates remained unchanged after EHR
implementation. The authors reported
variation in these outcomes across hospitals and care regions.
They noted that in addition to
EHR implementation, organizational factors such as
collaboration, teamwork, and
supportive leadership are needed to achieve sustained
improvements in quality and safety
outcomes. This highlights a role for Gerontological nurses as
they can promote

improvements in nursing sensitive measures such as patient
falls and hospital acquired
pressure ulcer rates by modeling adoption and use of the EHR
and by leading quality
improvement efforts that engage both senior leadership and
front line nursing staff
(McFadden, Stock, & Gowen, 2014; Rosen et al., 2010).
Leading geriatric care
improvement programs within a healthcare organization such as
NICHE (Nurses Improving
Care for Healthsystem Elders) is an example of how
Gerontological nurses can partner with
nursing leadership and frontline staff to improve the care of
older adults. This type of
program, coupled with an integrated EHR that captures data in a
structured, coded format
and provides clinical decision support can ensure that all older
adults receive evidence-
based, personalized care and that nursing documentation is
reused to build evidence for
future practice.
Gerontological nurse experts can efficiently influence important
outcomes and standardize

the way we assess and treat older adults by providing input into
which evidence-based
assessment and decision support tools are embedded into the
EHR. For example, in a study
in long-term care, the number of malnourished residents
decreased significantly after
embedding evidence-based assessment tools into the EHR that
prompted nutritional and
pressure ulcer risk assessments and documentation (Fossum,
Alexander, Ehnfors, &
Ehrenberg, 2011). Using such tools prompts the caregivers to
assess these important
parameters, and, over time, the data generated during
standardized assessments and
documentation will enable research and knowledge generation
using large datasets across
settings and time. The IOM called for a "learning health
system" where we use EHR data to
apply what is known about a patient to generate or apply
knowledge resulting in evidence-
based, personalized care in the form of decision support
(Friedman, Wong, & Blumenthal,
2010). An integrated EHR with structured, coded data capture
provides the data

infrastructure for the learning healthcare system that will
transform the way Gerontological
nurses generate and apply knowledge. Data recorded at the
individual patient level during an
encounter can be used to personalize care for that patient and
can be simultaneously applied
to spur discovery and innovation for future care delivery for
older adults (Greene et al.,
2009). Gerontological nurses play an important role in guiding
the development of our
"learning health system."
Providing decision support interventions
Using the EHR as a tool to achieve a learning health system
affords the opportunity to build
decision support within the workflow of nurses caring for older
adults. Decision support can
take the form of alerts, reminders, or algorithms that guide
evidence-based care. Bowles and
colleagues implemented the expert discharge decision support
system (D2S2) within the
hospital nursing admission assessment to identify older adults
in need of post-acute care
such as skilled home care or skilled nursing facility care. Based
on how patients answer a

series of questions, an algorithm generates a daily report sent to
discharge planners alerting
Bowles et al. Page 2
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them of patients at risk for poor discharge outcomes and
therefore in need of a post-acute
referral. Use of the decision support achieved a 26% relative
reduction in 30 and 60-day

readmissions in one study (Bowles, Hanlon, Holland, Potashnik,
& Topaz, 2014) and 33%,
30-day and 37%, 60-day relative reductions in readmissions in a
subsequent study (under
revised review at RINAH). Study findings suggest that using
decision support to early
identify at risk patients and arranging appropriate follow-up
care is associated with
improved post-acute care outcomes.
Symptom management during cancer treatment is another
complex care challenge for many
older adults and their caregivers. A nurse led team created a
computable algorithm that
adapts research evidence for use in a clinical decision support
system providing
individualized symptom management recommendations to
clinicians at the point of care
(Cooley et al., 2013). This complex challenge required mixed
methods that involved two
large clinical sites, multiple panels of experts, a seven-step
process, and two years to
complete. These rigorously developed algorithms are available
for testing.

HIT can also provide decision support for sensitive topics like
advanced care planning.
Hickman and colleagues created a multimedia decision support
intervention that delivers
education about advanced directives to patients recovering from
critical illness (Hickman,
Lipson, Pinto, & Pignatiello, 2013). Brought to the bedside via
laptop computer, this
intervention increased the intent to sign an advanced directive
by 25 times compared to the
commonly used advanced directive educational brochure,
“Putting it in writing”.
Clinical decision support in the EHR can also facilitate
guideline adherence. Beeckman and
colleagues evaluated whether a decision support system for
pressure ulcer prevention
improves guideline adherence with pressure ulcer prevention
recommendations in a nursing
home setting (Beeckman et al., 2013). They found that nurses
who used the EHR system
with the pressure ulcer prevention decision support were more
likely to provide guideline-
based pressure ulcer prevention interventions than nurses in the
control group who received

a paper copy of the practice guidelines.
The successful work of Dykes and colleagues clearly illustrates
the value of integrating fall
risk assessment and clinical decision support into the EHR
(Dykes et al., 2010). Based on
qualitative research with professional and paraprofessional
providers (Dykes, Carroll,
Hurley, Benoit, & Middleton, 2009), patients and family
(Carroll, Dykes, & Hurley, 2010),
Dykes and team learned that patient falls were a communication
problem. Nurses routinely
conduct fall risk assessment on hospitalized patients but the
degree to which the results of
that assessment and the associated plan are communicated to
other care team members, the
patient and family was variable. In a randomized control trial of
over 10,000 patients, they
found that by using HIT to integrate fall risk assessment and
clinical decision support for
tailored fall prevention plans into the workflow (Carroll, Dykes,
& Hurley, 2012), older
patients were more likely to have personalized fall prevention
plans and were less likely to
fall during an acute hospitalization (Dykes et al., 2010).

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Remote monitoring of older adults
Telehealth, defined as the use of video and biometric devices to
monitor and provide care at
a distance is a rapidly growing intervention studied by nurses.
The body of literature in the

domain of telehealth specifically for older adults is growing in
more recent years, and
numerous studies highlight the leading role of nursing in
designing, implementing and
evaluating such systems. Published reports range from pilot
feasibility studies to large multi-
site randomized clinical trials. One such recent trial is by
Takahashi et al examining
telemonitoring in older adults with multiple chronic conditions
(Tele-ERA-Elder Risk
Assessment) as a tool to reduce hospitalizations and emergency
department visits when
compared with usual care (Takahashi et al., 2010). The
telehealth device used was a
commercially available one that has video monitoring allowing
real-time, face-to-face
interaction with the provider team. Peripheral devices were
attached to measure blood
pressure and pulse, oxygen saturation, glucose level, and
weight. The elderly study patients
found home telemonitoring to be acceptable, providing a sense
of safety in their home
(Pecina et al., 2011). However, home telemonitoring in older
adults with multiple

comorbidities did not significantly improve self-perception of
mental well-being and may
worsen self-perception of physical health. While a report on the
effectiveness for reducing
hospitalizations has not been published yet, findings from this
trial have already highlighted
the role of a registered nurse as overseeing all processes and
assessing any changes in
patient status as assessed by videoconferencing and
telemonitoring.
A nurse led study examining the effectiveness of home based
individual telehealth
intervention for stroke caregivers was conducted in South Korea
(Kim et al., 2012). This
study employed a quasi-experimental design with a repeated-
measures analysis to explore if
caregiver burden will be lower for families that receive a
telecare intervention in addition to
standard care, when compared to the control group. Seventy-
three patients from five
hospitals participate in the study. There was a statistically
significant decrease of family
caregiver burden in the experimental group and the intervention
was found to be cost-

effective.
Emme and colleagues explored the role of home telehealth in
facilitating self-efficacy in
patients with chronic obstructive pulmonary disease. She
conducted this study within a
larger initiative called the Virtual Hospital (Emme et al., 2014).
The Virtual Hospital
included patients admitted to the emergency department due to
chronic obstructive
pulmonary disease (COPD) exacerbation. Within 24 hours after
admission, participants were
randomly assigned to receive standard treatment using
telehealth equipment with an
integrated organizational support in their own home or standard
treatment in the hospital.
The results of the study suggest that there may be no difference
between self-efficacy in
COPD patients undergoing virtual admission, compared with
conventional hospital
admission.
Keeping-Burke et al conducted a randomized clinical trial to
determine whether coronary
artery bypass graft surgery patients and their caregivers who
received telehealth follow-up

had greater improvements in anxiety levels from pre-surgery to
three weeks after discharge,
than those who received standard care (Keeping-Burke et al.,
2013). No group differences
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were noted in changes in patients' anxiety and depressive
symptoms, but patients in the

telehealth group had fewer physician contacts. Furthermore,
caregivers in the telehealth
group experienced a greater decrease in depressive symptoms
than those in the standard care
group and female caregivers in the telehealth group had greater
decreases in anxiety than
those in standard care.
A single-center randomized controlled clinical trial conducted
by Wakefield and colleagues
compared two remote telehealth monitoring intensity levels
(low and high) and usual care in
patients with type 2 diabetes and hypertension being treated in
primary care (Wakefield et
al., 2012). No significant differences were found across the
groups in self-efficacy,
adherence, or patient perceptions of the intervention mode. The
study indicated that home
telehealth can enhance detection of key clinical symptoms that
occur between regular
physician visits but called for further investigation of the
mechanism of the effect of the
telehealth intervention.
In the studies described above, patients and/or their family

members have to operate specific
hardware and software applications as part of the telehealth
intervention. This often raises
the question of feasibility for older adults who may live alone
and be very frail or
inexperienced with technology or are experiencing cognitive or
functional limitations. As
technology advances, there are opportunities to utilize systems
that do not require a user to
operate them but instead the systems enable passive and
ongoing monitoring of older adults’
well-being. An extensive program of research led by Rantz and
colleagues (Rantz et al.,
2012) conducted in senior housing facilities demonstrates the
power of telehealth to predict
adverse events and support seniors to age in place. In these
studies, sensor networks were
deployed that included stove temperature, bed, chair and motion
sensors, and Microfost
Kinect sensors in order to assess behavioral and physiological
patterns over time and
identify abnormalities or emergencies. Findings so far suggest
that the sensor data can serve
as tools for early illness detection. There are other initiatives

underway exploring this
concept of a “smart home,” namely a residential setting with
technology embedded in the
residential infrastructure to enable passive monitoring of
residents with the goal to assess
overall patterns of activity, quality of life and well-being. As
part of the HEALTH-E (Home
based Environmental and Assisted Living Technologies for
Healthy Elders) initiative in the
School of Nursing at the University of Washington, researchers
have installed various sensor
technologies in apartments of older adults who live in
retirement communities in Seattle.
The sensor technologies include motion sensors to detect how
one moves inside the home,
as well as infrastructure mediated sensing, namely an electricity
sensor that can detect
electricity consumption by electricity source, and a water sensor
that detects water
consumption by each water source. These features allow the
detection of activities such as
meal preparation or bathroom visit with a level of granularity
that motion sensors alone
cannot provide. Advanced data analysis and pattern recognition

techniques allow not only
the detection of activities but also potential changes over time,
for example, if data indicate a
more sedentary behavior over time, or an irregular pattern of
activities calling for timely
interventions to prevent an adverse event (Reeder, Chung et al.,
2013). Findings so far
indicate that older adults accept these technologies if they see a
purpose and perceived
usefulness does ameliorate privacy concerns (Chung et al.,
2014) Case studies showcase the
potential of technology to identify health related trends.
However, the concept of smart
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homes is still an emerging one and we are lacking large
longitudinal studies and clinical
trials that will examine the effectiveness of such technologies
and their impact on clinical or
other outcomes (Reeder, Meyer et al., 2013)
What is in the nursing research pipeline?
A search of the National Institute of Health REPORTER
database informed us about what
nurse-led HIT studies, funded by the National Institute of
Nursing, are in the pipeline. We
can look forward to hearing the results of several innovative
studies that address the needs of
and improve outcomes for Alzheimer’s patients and their
caregivers. At least four studies
address dementia, two are RO1s, one R21 and one R15.
RO1NR014737 (Williams,

Principal Investigator) will test the effects of technology that
connects dementia caregivers
to experts for guidance in managing disruptive behaviors and
supporting care at home.
Experts will analyze video recordings of the triggers and
precursors of the disruptive
behaviors along with its features and give prevention and
management advice to the
caregivers. The second RO1NR011042 (Fick, Principal
Investigator) proposes the use of the
EHR to deliver an Early Nurse Detection of Delirium
Superimposed on Dementia
intervention. The EHR will provide decision support through
standardized delirium
assessment and management screens. The R21NR 013471
(Mahoney, Principal Investigator)
will develop an innovative bureau dresser retrofitted with
sensors and an IPAD that offers
visual cues and verbal prompting to help persons with dementia
dress. The team hopes to
advance the technology from prototype proof of concept to
ready it for large-scale
intervention trials. Finally, the R21NR013569 (Hickman,
Principal Investigator) uses

gaming technology to create an interactive, avatar-based
tailored electronic program that
will engage and prepare family members for the role of
surrogate decision maker when
caring for persons with impaired judgment.
Beyond the study of dementia, the value of large dataset
analysis is evident to meet the aims
of RO1NR010822 (Larson, Principal Investigator). In this study,
investigators are using data
within a clinical data warehouse to conduct three comparative
effectiveness studies about
hospital-acquired infections and various contributing or
preventive factors. The study will
also produce policies and procedures regarding future use of
these large datasets to make
them more widely available for future research. An
RO3NR012802 (Kim, Principal
Investigator) takes advantage of EHR data documented during
the longitudinal care of older
adults as they transitioned across multiple care settings
including their homes. The focus of
the study is care coordination and the aims are to identify
interventions used in care
coordination, identify relationships among patients’

characteristics and care coordination
interventions and outcomes.
These exciting and innovative examples give us a snapshot of
what new knowledge we have
to look forward to and provide excellent examples of our
learning health system and the use
of HIT to improve care for older adults.
How Gerontological Nurses Can Get Involved
The HIT research completed to date provides a beginning
foundation for evidence-based
nursing care of older adults and a learning health system.
Gerontological nurses can
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contribute to the learning health system in several ways. First,
nurses can adopt
standardized, evidence-based risk assessments in practice and
work with their information
technology departments or vendors to make sure that these
assessments, corresponding
interventions and patient outcomes are represented in a
structured coded fashion in the EHR.
Linking evidence-based interventions to assessment data in the
EHR will ensure that all
patients receive evidence-based care during each encounter. In
addition, submission of risk
assessment and outcome data to a national nursing outcomes
database such as the National
Database for Nursing Quality Indicators (NDNQI), the
Collaborative Alliance for Nursing
Outcomes (CALNOC), the Veterans Administration Nursing

Outcomes Database
(VANOD), or Military Nursing Outcomes Database (MilNOD)
provides a means to
contribute the types of data needed for local quality
benchmarking while contributing to a
learning health system that will improve the care of older adults
nationally.
Challenges and New Directions
As noted throughout this commentary, nurses are leading
research related to the use of
EHRs, clinical decision support, and telehealth. Many of these
efforts have resulted in
improved care and interventions for older adults. However, this
work is not without
challenges. One challenge of EHR research is often the inability
to conduct randomized
clinical trials. Most EHR studies are quasi-experimental
because the EHR is delivered to all
patients therefore negating the ability to have a simultaneous
control group. When
considering the quality of EHR research we must take note
whether confounding factors
were considered and adequate controls were instituted to
compensate for the lack of

randomization. In addition, many of these studies have multiple
components. For example,
in telehealth studies, the type of equipment used, the number of
times a patient uses the
equipment, or the quality of team communication could all
affect the study outcomes
making it difficult to know which component is responsible for
the impact. For decision
support, it is important to monitor the fidelity of the
intervention to understand the amount
of exposure to the advice and to monitor any other interventions
occurring simultaneously
that could affect the outcomes. In addition, it is important to
recognize that these
interventions are “decision support”. They are not one size fits
all and we must never lose
sight of individual patient needs and instances where the
decision support is not applicable.
To advance the science of HIT research, we suggest more
research to:
• understand how nurses use HIT systems in practice, the factors
associated with
adoption, and the effect of EHR systems on nursing practice;
• identify the organizational factors that lead to improved

quality and safety
outcomes after implementation of an EHR;
• determine how patient reported data can be captured and used
to provide clinical
decision support that is aligned with patient preferences;
• develop HIT interventions that will facilitate the engagement
of older adults in their
recovery plan within hospital, homecare, and long-term care
settings and in
maximizing self-management, wellness, and independence as
they age at home
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Finally, we need to expand the settings in which HIT research
occurs. A recent systematic
review of nursing informatics studies revealed 42.5% took place
in acute care, while only
3.75% occurred in homecare or long term care respectively
(Carrington & Tiase, 2013).
Given the concentration of older adults served in homecare and
long term care, these areas
of practice are prime sources for knowledge generation through
future studies.
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surgery patients and their caregivers. Research in Nursing &
Health. 2013; 36(6):540–553.
[PubMed: 24242195]
Kim SS, Kim EJ, Cheon JY, Chung SK, Moon S, Moon KH. The
effectiveness of home-based
individual tele-care intervention for stroke caregivers in south
korea. International Nursing
Review. 2012; 59(3):369–375. [PubMed: 22897188]
McFadden KL, Stock GN, Gowen CR. Leadership, safety
climate, and continuous quality
improvement: Impact on process quality and patient safety.
Health Care Management Review,
Feb. 2014; 21 (E-pub ahead of print).
Pecina JL, Vickers KS, Finnie DM, Hathaway JC, Hanson GJ,
Takahashi PY. Telemonitoring
increases patient awareness of health and prompts health-related

action: Initial evaluation of the
TELE-ERA study. Telemedicine Journal and E-Health. 2011;
17(6):461–466. [PubMed:
21612521]
Rantz MJ, Skubic M, Koopman RJ, Alexander GL, Phillips L,
Musterman K, Miller SJ. Automated
technology to speed recognition of signs of illness in older
adults. Journal of Gerontological
Nursing. 2012; 38(4):18–23. [PubMed: 22420519]
Reeder B, Chung J, Lazar A, Joe J, Demiris G, Thompson HJ.
Testing a theory-based mobility
monitoring protocol using in-home sensors: A feasibility study.
Research in Gerontological
Nursing. 2013; 6(4):253–263. [PubMed: 23938159]
Reeder B, Meyer E, Lazar A, Chaudhuri S, Thompson HJ,
Demiris G. Framing the evidence for health
smart homes and home-based consumer health technologies as a
public health intervention for
independent aging: A systematic review. International Journal
of Medical Informatics. 2013;
82(7):565–579. [PubMed: 23639263]
Rosen AK, Singer S, Zhao S, Shokeen P, Meterko M, Gaba D.
Hospital safety climate and safety
outcomes: Is there a relationship in the VA? Medical Care
Research Review. 2010; 67(5):590–
608. [PubMed: 20139397]
Takahashi PY, Hanson GJ, Pecina JL, Stroebel RJ, Chaudhry R,
Shah ND, Naessens JM. A
randomized controlled trial of telemonitoring in older adults
with multiple chronic conditions: The
tele-ERA study. BMC Health Services Research. 2010; 10(255)

Wakefield BJ, Holman JE, Ray A, Scherubel M, Adams MR,
Hills SL, Rosenthal GE. Outcomes of a
home telehealth intervention for patients with diabetes and
hypertension. Telemedicine Journal
and E-Health : The Official Journal of the American
Telemedicine Association. 2012; 18(8):575–
579. [PubMed: 22873700]
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EHR .rtfd/TXT.rtf
From: Esther Joseph <[email protected]>
Subject: School
Date: May 30, 2020 at 9:19:18 PM EDT
To: Whitney Joseph <[email protected]>
Sent from my iPhone
__MACOSX/EHR .rtfd/._TXT.rtf
© 2011 Menachemi and Collum, publisher and licensee Dove
Medical Press Ltd. This is an Open Access
article which permits unrestricted noncommercial use, provided
the original work is properly cited.
Risk Management and Healthcare Policy 2011:4 47–55
Risk Management and Healthcare Policy Dovepress
submit your manuscript | www.dovepress.com

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47
R e v i e w
open access to scientific and medical research
Open Access Full Text Article
DOI: 10.2147/RMHP.S12985
Benefits and drawbacks of electronic health
record systems
Nir Menachemi1
Taleah H Collum2
1Department of Health Care
Organization and Policy, University
of Alabama at Birmingham,
Birmingham, AL, USA; 2Department
of Health Services Administration,
University of Alabama at Birmingham,
Birmingham, AL, USA
Correspondence: Nir Menachemi
UAB School of Public Health, 1530 3rd
Ave, S Birmingham, AL 35294, USA
Tel +1 205 934 7192
Fax +1 205 934 3347
email [email protected]
Abstract: The Health Information Technology for Economic and
Clinical Health (HITECH)
Act of 2009 that was signed into law as part of the “stimulus

package” represents the largest
US initiative to date that is designed to encourage widespread
use of electronic health records
(EHRs). In light of the changes anticipated from this policy
initiative, the purpose of this paper
is to review and summarize the literature on the benefits and
drawbacks of EHR systems.
Much of the literature has focused on key EHR functionalities,
including clinical decision sup-
port systems, computerized order entry systems, and health
information exchange. Our paper
describes the potential benefits of EHRs that include clinical
outcomes (eg, improved quality,
reduced medical errors), organizational outcomes (eg, financial
and operational benefits), and
societal outcomes (eg, improved ability to conduct research,
improved population health, reduced
costs). Despite these benefits, studies in the literature highlight
drawbacks associated with EHRs,
which include the high upfront acquisition costs, ongoing
maintenance costs, and disruptions
to workflows that contribute to temporary losses in productivity
that are the result of learning a
new system. Moreover, EHRs are associated with potential

perceived privacy concerns among
patients, which are further addressed legislatively in the
HITECH Act. Overall, experts and
policymakers believe that significant benefits to patients and
society can be realized when EHRs
are widely adopted and used in a “meaningful” way.
Keywords: EHR, health information technology, HITECH,
computerized order entry, health
information exchange
Introduction
Over the past decade, virtually every major industry invested
heavily in computerization.
Relative to a decade ago, today more Americans buy airline
tickets and check in to
flights online, purchase goods on the Web, and even earn
degrees online in such disci-
plines as nursing,1 law,2 and business,3 among others. Yet,
despite these advances in our
society, the majority of patients are given handwritten
medication prescriptions, and
very few patients are able to email their physician4 or even
schedule an appointment
to see a provider without speaking to a live receptionist.5
Electronic health record (EHR) systems have the potential to

transform the health
care system from a mostly paper-based industry to one that
utilizes clinical and other
pieces of information to assist providers in delivering higher
quality of care to their
patients. The Health Information Technology for Economic and
Clinical Health
(HITECH) Act of 2009, which is part of the American Recovery
and Reinvestment
Act (ARRA) (aka “stimulus package”), was signed into law with
an explicit purpose
of incentivizing providers (eg, hospitals and physicians) to
adopt EHR systems.
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Menachemi and Collum

However, given that a bare-bone EHR system provides
only partial benefits to patients and society,6 the HITECH
Act requires that providers adopt EHRs and utilize them
in a “meaningful” way, which includes using certain EHR
functionalities associated with error reduction and cost
containment. How exactly do EHRs improve care? And what
is the current evidence that certain EHR “meaningful use”
functionalities will translate into benefits? Answering these
questions is the purpose of this paper. Stated explicitly, the
purpose of this study is to review the literature on the impacts
of EHR. Impacts include both benefits and drawbacks, and, as
such, we discuss the advantages and disadvantages that have
been identified by researchers and other experts. Overall, we
expect that any reader interested in understanding the current
state of the knowledge base with regard to EHR benefits will
find this paper useful.
Why we need EHRs
EHRs are defined as “a longitudinal electronic record of
patient health information generated by one or more encoun-

ters in any care delivery setting. Included in this informa-
tion are patient demographics, progress notes, problems,
medications, vital signs, past medical history, immunizations,
laboratory data, and radiology reports”.7 Some of the basic
benefits associated with EHRs include being able to easily
access computerized records and the elimination of poor
penmanship, which has historically plagued the medical
chart.8,9 EHR systems can include many potential capabili-
ties, but three particular functionalities hold great promise
in improving the quality of care and reducing costs at the
health care system level: clinical decision support (CDS)
tools, computerized physician order entry (CPOE) systems,
and health information exchange (HIE). These and other
EHR capabilities are requirements of the “meaningful use”
criteria set forth in the HITECH Act of 2009.10
A CDS system is one that assists the provider in making
decisions with regard to patient care. Some functionalities of
a CDS system include providing the latest information about

a drug, cross-referencing a patient allergy to a medication, and
alerts for drug interactions and other potential patient issues
that are flagged by the computer. With the continuous growth
of medical knowledge, each of these functionalities provides a
means for care to be delivered in a much safer and more effi-
cient manner. As more and more CDS systems are used, one
can expect certain medical errors to be averted and that, overall,
the patient will receive more efficient and safe care.11
CPOE systems allow providers to enter orders (eg, for
drugs, laboratory tests, radiology, physical therapy) into
a computer rather than doing so on paper. Computerization of
this process eliminates potentially dangerous medical errors
caused by poor penmanship of physicians. It also makes the
ordering process more efficient because nursing and phar-
macy staffs do not need to seek clarification or to solicit miss-
ing information from illegible or incomplete orders. Previous
studies suggest that serious medication errors can be reduced
by as much as 55% when a CPOE system is used alone,12

and by 83% when coupled with a CDS system that creates
alerts based on what the physician orders.13 Using a CPOE
system, especially when it is linked to a CDS, can result in
improved efficiency and effectiveness of care.
Once health data are available electronically to providers,
EHRs facilitate the sharing of patient information through
HIE. HIE is the process of sharing patient-level electronic
health information between different organizations14 and can
create many efficiencies in the delivery of health care.15 By
allowing for the secure and potentially real-time sharing of
patient information, HIE can reduce costly redundant tests
that are ordered because one provider does not have access
to the clinical information stored at another provider’s
location. Patients typically have data stored in a variety of
locations where they receive care. This can include their
primary care physician’s office, as well as other physician
specialists, one or more pharmacies, and other locations, such
as hospitals and emergency departments. Over a lifetime,

much data accumulates at a variety of different places, all
of which are stored in silos. Historically, providers rely on
faxing or mailing each other pertinent information, which
makes it difficult to access in “real time” when and where it
is needed. HIE facilitates the exchange of this information
via EHRs, which can result in much more cost-effective and
higher-quality care.
In the following section, we describe the literature that has
examined the effect of EHRs on various clinical and orga-
nizational outcomes. A large proportion of the literature has
focused on one or more computerized capabilities of EHRs,
including CDS, CPOE, and HIE. Many of these studies have
been discussed in previously published literature reviews,16–20
so we further summarize them here.
Advantages of EHRs
Researchers have examined the benefits of EHRs by con-
sidering clinical, organizational, and societal outcomes.
Clinical outcomes include improvements in the quality of

care, a reduction in medical errors, and other improvements
in patient-level measures that describe the appropriateness
of care. Organizational outcomes, on the other hand, have
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Benefits and drawbacks of EHRs
included such items as financial and operational performance,
as well as satisfaction among patients and clinicians who
use EHRs. Lastly, societal outcomes include being better
able to conduct research and achieving improved population
health.
eHRs and clinical outcomes
Many clinical outcomes that have been a focus of EHR
studies relate to quality of care and patient safety. Quality

of care has been defined as “doing the right thing at the right
time in the right way to the right person and having the best
possible results”,21 and patient safety has been defined as
“avoiding injuries to patients from the care that is intended
to help them”.11 Quality of care includes six dimensions,11
but most EHR research has focused on the following three:
patient safety, effectiveness, and efficiency. In the following
paragraphs we summarize some of the studies that examine
how EHRs or various related components impact these three
quality dimensions. More research is needed on the other
three components: patient centeredness, timeliness, and
equitable access.
EHRs, especially those with CDS tools, have been
empirically linked to an increased adherence to evidence-
based clinical guidelines and effective care. Despite the best
intention of providers, various factors may result in patient
encounters that do not adhere to best practice guidelines.
Some reasons for this nonadherence include i) clinicians

not knowing the guidelines, ii) clinicians not realizing that
a guideline applies to a given patient, and iii) lack of time
during the patient visit. EHR systems try to overcome these
issues, and researchers have focused on preventive services,
including vaccine administration, to examine how EHRs can
improve adherence rates. For example, researchers found
that computerized physician reminders increased the use of
influenza and pneumococcal vaccinations from practically
0% to 35% and 50%, respectively, for hospitalized patients.22
A similar study, but in the outpatient setting, found that
computerized reminders were associated with improved
influenza and pneumococcal vaccination rates among rheu-
matology patients taking immunosuppressant medications.23
Specifically, influenza vaccinations increased from 47% to
65% of patients, and pneumococcal vaccinations increased
from 19% to 41% of patients. Other studies on vaccination
rates found comparable results that computerized reminders
can improve adherence to immunization guidelines.24,25

From the societal public health perspective, adhering to
these guidelines keeps individuals healthy and lowers the
risk of disease outbreaks in communities. Researchers have
also focused on other preventive services and on how EHRs
can improve various outcomes and make care more effective.
Kucher et al26 hypothesized that computerized alerts, as part
of a CPOE system with CDS, directed at physicians may
increase the use of prophylactic care for hospitalized patients
at high risk for deep vein thrombosis. They found a 19%
increase in the use of anticoagulation prophylaxis when using
computer alerts, and this translated into a 41% reduced risk
of deep vein thrombosis or pulmonary embolism at 90 days
after discharge. Willson et al27 found a significant association
between computerized reminders and pressure ulcer preven-
tion in hospitalized patients. They found a 5% decrease in
the development of pressure ulcers 6 months after the imple-
mentation of computerized reminders that targeted hospital
nurses. Other similar studies found comparable results. Rossi

and Every,28 for example, found that computerized reminders
as part of a CDS have been linked to an 11.3% increase in
appropriate hypertension treatment in a primary care setting.
Other studies in the outpatient setting have also found that
an EHR and its components significantly increase adherence
to protocol-based or recommended care.29,30
Although researchers have found CDS tools to be ben-
eficial in most situations, many medical conditions do not
have scientifically based guidelines for providers to follow,
thus reducing the usefulness and effectiveness of these tools
in many clinical situations. More scientific-based guidelines
need to be developed in order to maximize the benefits associ-
ated with CDS. Similar to a focus on adherence to guidelines,
researchers have also found an association between EHRs
and efficiency in health care delivery. Efficiency refers to the
avoidance of wasting resources, including supplies, equip-
ment, ideas, and energy.11 One such form of waste involves
redundant diagnostic testing. Performing redundant tests is

costly and may lead to more false-positive results, which will
then lead to even more costs.31 Evidence indicates that there
is a significant negative (eg, desirable) association between
redundant diagnostic testing and the use of an EHR and/or its
components. For example, Nies et al32 examined the affects
of a CDS on the redundancy of blood tests in a cardiovas-
cular surgery department. They found that point-of-care
computerized reminders of previous blood tests significantly
reduced the proportion of unnecessarily repeated tests. In the
outpatient setting, Tierney et al33 found a 14.3% decrease in
the number of diagnostic tests ordered per visit and a 12.9%
decrease in diagnostic test costs per visit when using an
EHR with CDS and CPOE components. Other, unrelated
studies found an 18% decrease in tests ordered for medical
visits in the emergency department,34 a 27% decrease in
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redundant laboratory tests of antiepileptic medication levels
in hospitalized patients,35 and a 24% reduction in redundant
laboratory tests in a hospital.36
Studies focusing on patient safety have frequently exam-
ined the effect of EHR components on medical or medication
errors. In a widely cited study, experts found that a CPOE
system was associated with a 55% reduction in serious
medication errors in the hospital setting.12 A follow-up
study by the same team found that by adding a CDS system
to a CPOE system, medication errors can be reduced by as
much as 86%.13 A similar, more recent study in the outpa-
tient setting found that computerization resulted in an error
rate reduction from 18.2% to 8.2%.37 Other studies have
concluded that the number of appropriate medication orders

involving dosing levels or dosing frequency can be increased
with the use of a computerized system.38 Specifically, in
one study, the use of a CDS yielded a 32% decrease in the
number of days that antibiotics were prescribed outside the
recommended dosage range and a 59% decrease in the need
for pharmacist intervention to correct a drug dose.39 On
the other hand, a few studies have found an association
between the use of CPOE and increased medical errors.
These increases generally occur due to poorly designed
system interfaces, lack of end-user training,40 or lack of sys-
tems integration.41 Factors such as dense pull-down menus
and text entries in inappropriate areas of an EHR can have
negative consequences for patients.40 Specifically, one study
found that the use of a CPOE was associated with 22 types
of medication error risks.41
Many of the studies described have focused on clini-
cal outcomes at the patient level. Such studies have been
conducted in a clinical setting, frequently by employing a

randomized trial research design. An additional body of lit-
erature has examined, observationally, whether hospitals that
have adopted EHR or other computerized capabilities per-
form better than their counterparts that have not. For example,
Menachemi et al42 found that Florida hospitals with greater
investments in EHR technologies had more desirable rates
on a variety of commonly used quality indicators. In a simi-
lar study of hospitals, researchers found that computerized
records and order entry were associated with lower mortality
rates, and CDS was associated with fewer complications.43
Additionally, the same study found that computerized test
results, order entry, and CDS were all associated with lower
costs. However, despite the results discussed here, other
researchers have found only small positive effects from EHR
adoption44,45 or mixed results.46
eHRs and organizational and societal
outcomes
Organizational outcomes
Studies examining organizational outcomes have focused

on EHR use in both the inpatient and outpatient settings.
Such outcomes have frequently included increased revenue,
averted costs, and other benefits that are less tangible, such as
improved legal and regulatory compliance, improved ability
to conduct research, and increased job/career satisfaction
among physicians. Increased revenue comes from multiple
sources, including improved charge capture/decrease in
billing errors, improved cash flow, and enhanced revenue.
Several authors have asserted that EHRs assist providers in
accurately capturing patient charges in a timely manner.47,48
With an EHR system, many billing errors or inaccurate
coding may be eliminated, which will potentially increase a
provider’s cash flow and enhance revenue.18,49,50 Reductions
to outstanding days in accounts receivable and lost or disal-
lowable charges can potentially lead to improved cash flow.50
In addition, EHR reminders to providers and patients about
routine health visits can increase patient visits and therefore
enhance revenue.49

Many averted costs associated with EHRs are the result of
efficiencies created by having patient information electroni-
cally available. Some of these include increased utilization of
tests, reduced staff resources devoted to patient management,
reduced costs relating to supplies needed to maintain paper
files, decreased transcription costs, and the costs relating
to chart pulls. The use of EHRs can reduce the redundant
use of tests or the need to mail hard copies of test results to
different providers.35,51 By making patient information more
readily available, EHRs reduce costs related to chart pulls52
as well as supplies needed to maintain paper charts.53 Studies
have also shown that having an EHR as opposed to a paper
file can result in reduced transcription costs through point-
of-care documentation and other structured documentation
procedures.50 One author found a significant decrease in staff
resources dedicated to anemia management for hemodialysis
patients when a CDS was used for medication dosing.54
Other, less tangible benefits have been associated with

EHR use. In a study conducted by Bhattacherjee et al,55
Florida hospitals with a greater adoption of health informa-
tion technology had higher operational performance, as
measured by outcomes of Joint Commission on Accreditation
of Healthcare Organizations (JCAHO) site visits. It has also
been pointed out that EHRs can facilitate improved legal
and regulatory compliance in terms of increased security of
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data and enhanced patient confidentiality through controlled
and auditable provider access.50 In addition, researchers in
Massachusetts have found that physicians using an EHR had
fewer paid malpractice claims.56 Specifically, they found

that 6.1% of physicians with an EHR had a history of paid
malpractice claims compared with 10.8% of physicians with-
out EHRs. This reduction is potentially the result of increased
communication among caregivers, increased legibility and
completeness of patient records, and increased adherence to
clinical guidelines.
Societal benefits
Another less tangible benefit associated with EHRs is an
improved ability to conduct research. Having patient data
stored electronically increases the availability of data, which
may lead to more quantitative analyses to identify evidence-
based best practices more easily.57 Moreover, public health
researchers are actively using electronic clinical data that
are aggregated across populations to produce research that
is beneficial to society. The availability of clinical data is
limited, but as providers continue to implement EHRs, this
pool of data will grow. By combining aggregated clinical
data with other sources, such as over-the-counter medica-

tion purchases and school absenteeism rates, public health
organizations and researchers will be able to better monitor
disease outbreaks and improve surveillance of potential
biological threats.58
Researchers have also found an association between EHR
use and physician satisfaction with their current practice,59 as
well as their career satisfaction.60 According to many stud-
ies, physician satisfaction should be a priority in health care
organizations, because it is associated with better quality of
care, better prescribing behaviors, and increased retention
in medical practices, particularly those in underserved
areas.61,62
To balance the generally positive findings of the afore-
mentioned studies, Chaudhry et al16 noted that a large pro-
portion of the studies that found benefits from EHR were
conducted in a select number of academic medical centers.
This raises the question about whether or not many of the
benefits identified can be generalized to other settings of care

that do not have similar financial and human resources nor a
decades-long commitment to health information technology.
More research on the varying types and degrees of benefits
associated with EHR is warranted, especially in community
settings such as physician practices and nonacademic hospital
settings.
Potential disadvantages of EHRs
Despite the growing literature on benefits of various EHR
functionalities, some authors have identified potential dis-
advantages associated with this technology. These include
financial issues, changes in workflow, temporary loss of pro-
ductivity associated with EHR adoption, privacy and security
concerns, and several unintended consequences.
Financial issues, including adoption and implementation
costs, ongoing maintenance costs, loss of revenue associated
with temporary loss of productivity, and declines in revenue,
present a disincentive for hospitals and physicians to adopt
and implement an EHR. EHR adoption and implementation
costs include purchasing and installing hardware and soft-

ware, converting paper charts to electronic ones, and training
end-users. Many studies have documented these costs in both
the inpatient and outpatient settings.47,50 In a 2002 study con-
ducted in a 280-bed acute care hospital, the projected total cost
for a 7-year-long EHR installation project was approximately
US$19 million.47 In the outpatient setting, early researchers
estimated an average initial cost of US$50,000–US$70,000
per physician for a three-physician office.50 However, as EHR
technologies have become more commonplace over the past
decade, the initial cost of systems has come down dramatically.
One industry group estimated hardware, software, services,
and telecommunications cost of approximately US$14,000
per physician in the initial year of implementation for a six-
physician practice and US$19,000 per physician with three or
fewer physicians.63 Similarly, a recent study estimates initial
costs of software, training, and installation of US$22,038 and
hardware costs of US$13,000 per full-time-equivalent (FTE)
provider in a solo or small-group primary care practice.64

Lastly, another study estimated costs during the first 60 days
of launch of US$162,047 (or US$32,409 per physician) for a
five-physician practice to implement an EHR system.65
The maintenance cost of an EHR can also be costly.
Hardware must be replaced and software must be upgraded
on a regular basis. In addition, providers must have ongoing
training and support for the end-users of an EHR. According
to one study conducted on 14 solo or small-group primary
care practices, estimated ongoing EHR maintenance costs
averaged US$8412 per FTE provider per year. A total of
91% of this cost was related to hardware replacement, vendor
software maintenance and support fees, and payments for
information systems staff or external contractors.64 Other
estimates of ongoing maintenance costs for the first year
after implementation were about US$17,100 per physician
in a medical group of five.65
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The costs of EHR adoption, implementation, and ongoing
maintenance are compounded by the fact that many financial
benefits of an EHR generally do not accrue to the provider
(who is required to make the upfront investment) but rather
to the third-party payers in the form of errors averted and
improved efficiencies, which translate into reduced claims
payments. This misalignment of incentives for health care
organizations, along with the high upfront costs, creates a bar-
rier to adoption and implementation of an EHR, especially for
smaller practices. In fact, physicians frequently cite upfront
costs and ongoing maintenance costs as the largest barriers
to adoption and implementation of an EHR.66

Another disadvantage of an EHR is disruption of work-
flows for medical staff and providers, which result in tem-
porary losses in productivity. This loss of productivity stems
from end-users learning the new system and may potentially
lead to losses in revenue. One study involving several internal
medicine clinics estimated a productivity loss of 20% in the
first month, 10% in the second month, and 5% in the third
month, with productivity subsequently returning to its origi-
nal levels.52 In that study, the loss in productivity resulted in
lost revenue of US$11,200 per provider in the first year. In
a study of solo and small-group primary care practices of
one to six FTE providers, revenue losses from reduced visits
during the initial stages of an EHR averaged approximately
US$7500 per FTE provider. This depended on whether
physicians worked longer hours during this stage or reduced
patient visits.64 Lastly, researchers have estimated that EHR
end-users spent 134.2 hours on implementation activities
associated with getting and learning a new system. These

hours spent on nonclinical responsibilities had an estimated
cost of US$10,325 per physician.65
Other declines in revenue are possible following EHR
implementation. Because EHRs are often associated with
fewer redundancies, fewer errors, and shorter lengths of stay,
it is conceivable that a given provider may avert certain bill-
able transactions that, although superfluous, may have gener-
ated reimbursements from third-party payers, especially in
a fee-for-service payment system. Although reimbursement
rates may differ for each organization, these declines could
be offset by increased revenue that is generated as a result of
efficiencies achieved with the help of an EHR system.64
Another potential drawback of EHRs is the risk of
patient privacy violations, which is an increasing concern
for patients due to the increasing amount of health informa-
tion exchanged electronically.67,68 To relieve some of these
concerns, policymakers have taken measures to ensure
safety and privacy of patient data. For example, recent

legislation has imposed regulations specifically relating to
the electronic exchange of health information that strengthen
existing Health Insurance Portability and Accountability Act
privacy and security policies.69 Although few electronic data
are 100% secure, the rigorous requirements set forth by the
new legislation make it much more difficult for electronic
data to be accessed inappropriately. For example, all EHR
systems are required to have an audit function that allows
system operators to identify each individual who accessed
every aspect of a given medical record. Many hospitals and
physicians are implementing strict, no tolerance penalties for
employees who access files inappropriately. For example, a
hospital in Arizona terminated several employees after they
inappropriately accessed the records of victims who were
hospitalized after the January 2011 shooting involving a US
Congresswoman.70 Although privacy will likely continue
to be a concern for patients, many steps are being taken by
policymakers and individual organizations to ensure that

EHRs comply with the strict laws and regulations intended
to ensure the privacy of clinical information.
EHRs may cause several unintended consequences, such
as increased medical errors, negative emotions, changes
in power structure, and overdependence on technology.40
As mentioned previously, researchers have found an asso-
ciation between the use of CPOE and increased medical
errors due to poorly designed system interfaces or lack of
end-user training. Additionally, end-users of an EHR may
experience strong emotional responses as they struggle to
adapt to new technology and disruptions in their workflow.
Changes in the power structure of an organization may also
occur due to the implementation of an EHR. For example, a
physician may lose his or her autonomy in making patient
decisions because an EHR blocks the ordering of certain
tests or medications. Overdependence on technology may
also become an issue for providers as they become more
reliant upon it. Organizations should ensure that basic medi-

cal care can still be provided in the absence of technology,
especially in times when the downtime of the system may be
critical. Although there are many unintended consequences
of EHRs, when balancing the advantages and disadvan-
tages of these systems, they are beneficial, especially at
the society level.
Conclusion
In this paper we discussed several advantages and disad-
vantages associated with an EHR adoption. Many of the
benefits accrue to patients and society overall. For these
benefits to be realized, the US Government has embarked
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53

on an ambitious journey to transition a maximum number
of providers toward EHR adoption and “meaningful use”.
Without ubiquitous use of EHR technologies, experts believe
that many efficiencies in the US health care system cannot be
realized.15 The financial incentives built into the HITECH Act
are designed to defray some of the costs associated with EHR
adoption, especially for smaller organizations where these
expenses serve as a major barrier. The financial incentives
in HITECH, which are made available through the Medicare
and Medicaid programs, are also an attempt to correct some
of the misalignment of incentives associated with EHR as
discussed previously, especially because the US Government,
through the Medicare and Medicaid programs, is the largest
insurer in the country.
Incentives made available to physicians through
the HITECH Act differ among Medicaid and Medicare
physicians.71 Medicaid offers more generous incentives
than Medicare and has less stringent requirements for the

first year. Physicians with more than 30% of their patients
paying with Medicaid are eligible for up to US$63,750 in
incentives over a 6-year period. They can begin earning these
incentives as they adopt, implement, or upgrade an EHR.
The last year to begin participation in the Medicaid incentive
program is 2016, and physicians do not need to begin prov-
ing “meaningful use” until the second year of their program
participation. On the other hand, physicians accepting more
Medicare patients are eligible for up to US$44,000 over a
5-year period as long as they can meet the “meaningful
use” criteria starting the first year. Physicians not meeting
the “meaningful use” criteria by 2015 will be assessed for
penalties in the form of reduced Medicare reimbursements.
Physicians are allowed to participate in either the Medicaid
or Medicare incentive program, but not both. Those who are
eligible are expected to participate in the Medicaid program,
because its benefits are more generous. Hospitals are also
eligible for incentives under the HITECH Act. The amount

of the incentives they receive depends on a number of fac-
tors, but the base amount to each hospital that complies with
the meaningful use criteria will be more than US$2 million.
Both physician and hospital incentives are structured so that
those immediately achieving meaningful use of an EHR will
receive larger payments.
Providers are also expected to face technological and
logistical obstacles on their quest to achieve meaningful
use of EHRs.72 To help combat the technological problems
faced by providers, the federal government, through the
HITECH Act, has committed approximately US$650 mil-
lion for the establishment of a network of up to 70 regional
health information technology extension centers. The primary
purpose of these organizations is to offer advice to physi-
cians on which information technology systems they should
purchase and assistance on how to become meaningful
users of EHRs. To address some of the logistical problems
associated with EHRs, the federal government has entrusted

US$560 million under the HITECH Act to state govern-
ments for the development of infrastructure to facilitate the
exchange of health information.
Nationwide implementation of EHRs is a necessary,
although not sufficient, part in transforming the US health
care system for the better. EHR adoption must be consid-
ered one of many approaches that diversify our focus on
quality improvement and cost reduction. The current major
legislative and political support for EHRs represents the
greatest investment in health information technologies in
US history. Over time, providers and researchers will be
eager to quantify the returns that are expected from these
investments.
Disclosure
The authors report no conflicts of interest in this work.
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Publication Info 2: Nimber of times reviewed:
ORIGINAL INVESTIGATION
Electronic Health Records and Malpractice Claims
in Office Practice
Anunta Virapongse, MD, MPH; David W. Bates, MD, MSc;
Ping Shi, MA; Chelsea A. Jenter, MPH;
Lynn A. Volk, MHS; Ken Kleinman, ScD; Luke Sato, MD;
Steven R. Simon, MD, MPH
Background: Electronic health records (EHRs) may im-
prove patient safety and health care quality, but the re-
lationship between EHR adoption and settled malprac-
tice claims is unknown.
Methods: Between June 1, 2005, and November 30, 2005,
we surveyed a random sample of 1884 physicians in Mas-
sachusetts to assess availability and use of EHR func-
tions, predictors of use, and perceptions of medical prac-

tice. Information on paid malpractice claims was accessed
on the Massachusetts Board of Registration in Medicine
(BRM) Web site in April 2007. We used logistic regres-
sion to assess the relationship between the adoption and
use of EHRs and paid malpractice claims.
Results: The survey response rate was 71.4% (1345 of
1884). Among 1140 respondents with data on the pres-
ence of EHR and available BRM records, 379 (33.2%) had
EHRs. A total of 6.1% of physicians with an EHR had a
history of a paid malpractice claim compared with 10.8%
of physicians without EHRs (unadjusted odds ratio, 0.54;
95% confidence interval, 0.33-0.86; P = .01). In logistic re-
gression analysis controlling for sex, race, year of medical
school graduation, specialty, and practice size, the rela-
tionship between EHR adoption and paid malpractice settle-
ments was of smaller magnitude and no longer statisti-
cally significant (adjusted odds ratio, 0.69; 95% confidence
interval, 0.40-1.20; P = .18). Among EHR adopters, 5.7%
of physicians identified as “high users” of EHR had paid
malpractice claims compared with 12.1% of “low users”
(P = .14).
Conclusions: Although the results of this study are in-
conclusive, physicians with EHRs appear less likely to have
paid malpractice claims. Confirmatory studies are needed
before these results can have policy implications.
Arch Intern Med. 2008;168(21):2362-2367
I
N THE PAST 10 YEARS, HEALTH IN-
formation technology (HIT) has
emerged as an essential compo-
nent of a transformed health care

system that focuses on safety, qual-
ity, and efficiency.1,2 Although results of
some studies have been equivocal,3,4 the po-
tential impact of HIT on the safe practice
of medicine seems increasingly compel-
ling: if used actively by caregivers, studies
indicate that HIT can reduce adverse drug
events and improve physician perfor-
mance in areas such as diagnosis, preven-
tive care, disease management, drug dos-
ing, and drug management. 5 , 6 One
component of HIT in particular, elec-
tronic health records (EHRs), has been tar-
geted by policymakers as an essential tool
for ensuring the secure availability of pa-
tient health records across health care en-
tities and for reducing health care spend-
ing.7 Many clinicians have also recognized
the benefits of implementing an EHR de-
spite the large initial capital expenditure.
Research indicates that EHRs can improve
documentation, enhance the efficiency of
clinic visits,8 minimize medication errors,
and enable clinicians to perform popula-
tion surveillance and monitoring.2,9 As a re-
sult, EHRs are being increasingly adopted
by caregivers seeking to improve the qual-
ity of patient care.10
The potential for EHRs to prevent ad-
verse events and reduce health care costs
has also created interest in whether use of
EHRs reduces the risk of malpractice law-
suits. The Joint Commission on Accredi-

tation of Healthcare Organizations has sug-
gested that HIT can address factors that
have proved to be risk points for error and
subsequent malpractice suits by patients,
such as communication among care-
givers, availability of patient informa-
tion, medication prescribing, and adher-
ence to clinical guidelines.11 One study12
that involved 307 closed malpractice cases
claiming medical negligence found that
more than half of the cases were due to di-
agnostic errors that harmed patients. Most
of these errors occurred because of fail-
Author Affiliations: Division of
General Medicine and Primary
Care, Department of Medicine,
Brigham and Women’s Hospital
(Drs Virapongse, Bates, and
Sato and Ms Jenter),
Department of Ambulatory Care
and Prevention, Harvard
Medical School and Harvard
Pilgrim Health Care (Ms Shi
and Drs Kleinman and Simon),
Boston, Partners Health Care,
Wellesley (Dr Bates and
Ms Volk), Harvard Risk
Management Foundation,
Cambridge (Dr Sato),
Massachusetts.
(REPRINTED) ARCH INTERN MED/ VOL 168 (NO. 21), NOV
24, 2008 WWW.ARCHINTERNMED.COM
2362

©2008 American Medical Association. All rights reserved.
Downloaded From: https://jamanetwork.com/ on 05/30/2020
ure to order diagnostic tests or lack of a follow-up plan.
Because EHRs and HIT seem to mitigate reliance on cog-
nitive factors through clinical decision support and avoid-
ance of errors of omission, diagnostic errors may in turn
decrease with implementation of such systems. Further-
more, electronic documentation tends to be superior to
the paper record in legibility and completeness. Since
many lawsuits hinge on the presentation of proper docu-
mentation to the court, a thorough and accurate medi-
cal record would likely make lawsuits easier to defend
for physicians.13 Many malpractice claims also base their
allegations on the failure to adhere to the standard of care.
With the inclusion of decision support into an EHR, phy-
sicians can be presented with the relevant guidelines from
the onset of ordering treatment and may be more likely
to adhere to them.
In addition, malpractice claims due to medical errors
constitute the bulk of malpractice claim payouts and ad-
ministrative costs.14 Of all malpractice claims, 83% show
no evidence of negligence, and most of these claims with-
out injury are uncompensated or account for a small frac-
tion of overall malpractice costs.14,15 Thus, if medical er-
rors were minimized through HIT, significant health care
savings would occur through a reduction in tort-
associated costs. Conversely, some studies16,17 have shown
that HIT has the potential to increase adverse events at-
tributable to information errors and human-machine in-
terface flaws. Although these reports primarily focus on

computerized physician order entry systems in hospital
settings, the fact remains that adoption of any HIT is not
without risk, and unintended consequences may create
a new realm of litigation issues.
Despite a considerable body of evidence indicating that
HIT can prevent medical errors, little is known about the
relationship between EHR adoption in the office prac-
tice setting and medical malpractice claims. Few data are
available to evaluate the association between use level of
EHR functions and the prevalence of malpractice claims.
In the inpatient setting, use of computerized physician
order entry was correlated with a lower frequency of medi-
cation-related malpractice claims,18 but the frequency of
these claims is low enough to make such analyses diffi-
cult. To assess whether EHR use was associated with fewer
paid malpractice claims, we linked survey data about EHR
adoption and use to physician profile data from the Mas-
sachusetts Board of Registration in Medicine (BRM).
METHODS
The sampling methods, survey questionnaire development, and
survey administration have been published elsewhere19,20 and
are described briefly herein.
SAMPLE
Using a database from a private vendor (Folio Associates, Hy-
annis, Massachusetts) and information from the BRM,21 we
iden-
tified the population of practicing physicians in Massachu-
setts in 2005. After excluding physicians who were residents
in training, retired, or without direct patient-care responsibili-
ties, the total population of physicians was 20 227. These phy-
sicians practiced in 6174 unique practice sites in Massachu-

setts. Of these practices, a stratified random sample of 1921
practices was obtained, and 1 physician from each practice was
randomly selected for the survey. After excluding practices that
had closed, the final sample size was 1884 physicians.
SURVEY
We administered a survey by mail between June 1, 2005, and
November 30, 2005, to physicians in office practice in Massa-
chusetts. The 8-page questionnaire was based on a systematic
review of the literature regarding barriers to EHR adoption and
ascertained physician and practice characteristics, adoption of
EHRs and other HIT, and use of EHR functions. Initially, the
sur-
vey was sent via express mail with a $20 cash honorarium. Two
subsequent mailings to nonresponders were sent without remu-
neration. Between mailings, multiple telephone contacts were
at-
tempted to remind physicians to complete the survey.
The survey ascertained physicians’ personal demographic
and practice characteristics and their use of HIT, including
EHRs.
Physicians reported their age; race, which we dichotomized as
white vs other; year of medical school graduation; and num-
ber of physicians in their practice. We determined each phy-
sician’s specialty from the database from which we drew the
survey sample.
MALPRACTICE CLAIMS DATA COLLECTION
In April 2007, available identifying data (name, date of gradu-
ation, and zip code) were used to access each survey respon-
dent’s physician profile on the BRM Web site (http://profiles
.massmedboard.org/MA-Physician-Profile-Find-Doctor.asp).

The
BRM Web site contains information only for the previous 10
years of the physician’s practice. Two trained data extractors
(including A.V.), blinded to the physicians’ responses to the
survey questionnaire and the specialties of the physicians, in-
dependently determined the presence or absence of a paid mal-
practice claim for each study physician from the BRM Web site.
If a paid malpractice claim was present, then number of claims
and year of the settlement payment was noted.
Data collection sheets from the 2 data extractors were com-
pared for accuracy, and any discrepancies were adjudicated
using
the BRM Web site. After a master data extraction form was
com-
piled, the names and addresses of the respondents were re-
moved and pertinent measures from the survey were merged.
The study protocol was approved by the Partners HealthCare
Human Research Committee.
STATISTICAL ANALYSIS
Statistical analysis was performed using commercially avail-
able software programs (Stata Intercooled 9; StataCorp, Col-
lege Station, Texas; and SAS statistical software, version 9.1;
SAS Institute Inc, Cary, North Carolina). Baseline character-
istics between respondents who were EHR adopters and non-
adopters, as well as between physicians with and without paid
malpractice claims, were compared using the Pearson �2 test,
the Wilcoxon rank sum test, and the unpaired, 2-tailed t test.
The primary outcome, the presence or absence of paid mal-
practice claims among physicians using EHRs and those not
using EHRs, was assessed using the Pearson �2 and Fisher ex-
act test, as appropriate, and calculating unadjusted odds ratios
(ORs) with 95% confidence intervals (CIs).

We used logistic regression to adjust for the potential in-
fluence of physician characteristics on the relationship be-
tween EHR and malpractice claims. The model was run first
with all covariates and then with inclusion only of those vari-
ables found to be statistically significantly associated (P � .05)
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with paid malpractice claims in bivariate analysis. Because age
and graduation year were highly correlated, only graduation
year (a proxy for years in practice) was used in the logistic re-
gression models. In an exploratory analysis to address the po-
tential temporal relationship between EHR adoption and the
prevention of malpractice settlements, we excluded any phy-
sicians who had paid malpractice claims the date of which pre-
ceded the date of EHR adoption. In this analysis, we also ex-
cluded any physicians who had adopted EHRs after 2001 based
on the assumption that it would take a minimum of 5 years for
a malpractice event to result in a paid settlement.
A subsequent analysis limited to EHR adopters examined
the relationship between use of EHR functions and paid mal-
practice claims. Physicians with EHRs were asked to docu-
ment the availability and degree of use of 10 key functions in
their EHR. Those who used half or more of their available func-
tions all or most of the time were considered “high EHR us-
ers,” whereas the remaining physicians were classified as “low
users.”20 The rate of paid malpractice claims among high and

low users was compared using the �2 test.
To determine whether the relationship between EHR adop-
tion and paid malpractice claims was similar among physicians
in specialties considered high risk vs low risk for malpractice
claims, we first determined the percentage of physicians with
paid
malpractice claims in each specialty within our data set. The
per-
centages ranged from 0% (dermatology) to 34.6% (general sur-
gery). We dichotomized the sample at the median (10.5%) to
create a variable that indicated whether each physician prac-
ticed in a low-risk or high-risk specialty. For example, internal
medicine (7.1%) and family medicine (10.5%) were considered
in the low-risk group, whereas obstetrics and gynecology
(24.2%)
and urology (30.8%) were in the high-risk group. We then ex-
amined the relationship between the presence of EHR and paid
malpractice settlements within each stratum.
RESULTS
As reported previously,19,20 1345 physicians completed
the survey (response rate, 71.4%). We excluded 157 phy-
sicians who indicated that they did not see outpatients
and 41 physicians who did not have physician profiles
on the BRM Web site (Figure). Seven physicians did not
answer survey questions regarding use of EHRs. This re-
sulted in 1140 respondents eligible for analysis.
EHR ADOPTION
Overall, 33.2% of the sample (379 of 1140) used EHRs
in their practices (Table 1). Physicians who used EHRs
were younger than those who did not use EHRs (mean

age, 49.1 vs 52.8 years; P � .001) and had completed medi-
cal school more recently (median graduation year, 1987
vs 1983; P � .001). The EHR adopters were less likely to
be in solo practice (14.2% vs 35.9%; P � .001). Among
physicians who used EHRs, 71.8% reported implement-
ing their systems within the 10 years preceding the sur-
vey. Duration of EHR use ranged from less than 1 year
to 18 years among survey respondents who used EHRs
in their practice.
PAID MALPRACTICE CLAIMS
A total of 105 of the 1140 survey respondents (9.2%) had
a history of 1 or more malpractice payments within the
past 10 years (Table 2). Paid malpractice claims were
more common among male physicians (11.1%) than fe-
male physicians (5.6%) (P = .003). Paid malpractice claims
were more common among physicians who had been in
practice longer. For example, 15.2% of physicians who
graduated from medical school more than 20 years ago
had paid malpractice claims in the past 10 years com-
pared with 5.8% of physicians who had graduated within
the past 20 years (P � .001) (data not shown). Practice
size was also correlated with malpractice claims. Paid mal-
practice claims were more common among physicians
in solo practice (43.7%) and among those in small group
practices of 2 to 4 people (29.1%) and 5 to 9 people
(19.4%) than among physicians who practiced in groups
of 10 or more physicians (7.8%).
Respondents for matching
on BRM Web site
1188
Physicians were sent

initial survey
1884
Did not answer EHR questions
on survey
7
Excluded because of no BRM
physician profile
41
Excluded because they reported
not seeing outpatients
157
Physicians did not respond539
Respondents remaining1147
Survey respondents1345
Respondents remaining
for analysis
1140
Figure. Flow diagram of included and excluded survey
respondents. BRM
indicates Board of Registration in Medicine; EHR, electronic
health record.
Table 1. Characteristics of EHR Adopters and Nonadopters a

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