1. Electronic Medical Records and Emergency Department Efficiency:
An Annotated Bibliography
Gregory Hayden
Over the past ten years in response to government financial incentives and increased reporting
needs there been a substantial increase in the use of Electrical Medical Records (EMR) by
hospital emergency departments (ED). While the EMR has the potential for a significant
positive impact on ED operations, questions remain regarding its contribution to the overall
efficiency of the ED both in terms of patient care delivery as well as financially. A hindrance to
understanding the issues is the limited information available on the subject. The purpose of this
bibliography looks at what literature is available regarding the impact of the EMR on ED
efficiency.
Ayatollahi, H., Bath, P. A., & Goodacre, S. (2010). Factors influencing the use of IT in the
emergency department: A qualitative study. Health Informatics Journal, 16(3), 189-200.
doi:10.1177/1460458210377480
In this qualitative study Ayatollahi, Bath and Goodacre use structured interviews to collect staff
responses to a series of questions and then use framework analysis to exam possible factors
influencing staff acceptance or resistance to the use of EMR or other clinical information
systems. The theories and models discussed include the technology acceptance model, the theory
of planned behavior, and the unified theory of acceptance and use of technology. Methods and
findings were discussed. The reference list includes 29 citations including many regarding the
behavioral components of implementing IT.

2. The behavioral component to IT acceptance by ED workers is related to my topic. A limitation
of the study is its small size and that it was conducted at a single (English) hospital, so
transferability may be limited. However, employees questioned included nurses, physician, and
clerical staff so there was a broad cross section of users’ views which showed differences in
acceptance based on role. While the article is older, the theories of behavior remain relevant. I
was able to identify multiple similar papers for two of the authors. No bias was noted and the
different theories, method and findings where adequately discussed. Of interest was the
discussion on how to address the various concerns raised by the study. Per Ulrich the journal is
peer reviewed and academic/scholarly in content. Web of Science (WOS) indicates there are 7
resources citing it. The Impact Factor (IF) is 0.565.
Chustz, M. H. (2011). The economic impact of electronic medical records in rural hospital
emergency departments (Doctoral Dissertation). Available from ProQuest Dissertations
& Theses database. (UMI No. 3487292). Retrieved from:
http://search.proquest.com.proxy.cc.uic.edu/dissertations/docview/913532073/20C24BB2
229740EAPQ/1?accountid=14552
Rural hospitals often have small operating margins and are hesitant to implement an EMR
because it might adversely affect there profitability. Chustz analyzed the Evaluation and
Management Codes (E/M) for ED visits at rural hospitals for the 12 month time period prior to
implementation of an EMR, the month of the implementation, and then for the 12 month
following implementation. Using an Interrupted Time Series Analysis to analyze the data Chustz
found that there was a significant increase in E/M codes following the implementation of the
EMR at the hospitals related to improved documentation and testing attributable to the EMR

3. functionality. And that after costs were factored in there was a significant net increase in revenue
sufficient to justify the financial outlay for the system.
This resource is a dissertation, so is grey literature. The study is older, but is still current
regarding the costs associated with implementing an EMR. The topic is directly relevant to my
topic. The intended audience is academics and hospital managers, especially at small hospitals
(or possibly free standing clinics). The studies use of E/M was elegant in that it is a simple
number that is readily available for others (such as hospital administrators) wishing to replicate
the study for their own facility. Limitations on the study was the small number of hospitals and
that it is a convenience sample. It also used the Medicare reimbursement as a proxy for all
reimbursement, which as noted by Chutz may introduce some bias. However, reimbursement
managers would have a good handle on what their true reimbursement schedule is, and could
adjust their numbers as needed.
Conn, J. (June 24, 2013). EHR systems pose serious concerns, report says. Modern Healthcare.
Retrieved June 3, 2015, from
http://www.modernhealthcare.com/article/20130624/NEWS/306249952?CSFlag=337304
5119
Conn briefly summarizes current “popular” concerns regarding performance of EMR used in the
ED, then goes on to list a series of reports from organization that include the American College
of Emergency Physicians, the New England Journal of Medicine, and the National Institute of
Medicine that document those same concerns. These include a host of issues including poor data
display, endless alerts and warnings, and the possibility of a growing number of incorrect patient
and/or orders being generated. The “best of breed” and “big data” approaches to EMR is

4. explained. Of especial interest is the effect of “learned intermediary” and “gag” clauses that shift
responsibility for issues from the manufacturer to the clinicians and block public reporting of
issue respectively.
Per Ulrich this resource is not refereed and is a trade resource, so it is grey literature. The
targeted audience is senior health care management. Conn has written many articles on similar
subjects going back 10 years. The article is consistent with my understanding of the subject.
There is the possibility of bias in part of the reporting where Conn discusses “best of breed”
verses “big data” enterprise systems – while the usefulness of “best of breed” is discussed, the
rational for “big data” is not.
Furukawa, M. F (2010). Electronic Medical Records and the Efficiency of Hospital Emergency
Departments. Medical Care Research and Review, 68(1), 75–95. doe:
10.1177/1077558710372108
Furukawa analyzed the effect that the level of EMR sophistication had on ED operating
efficiency using data from the 2006 National Hospital Ambulatory Medical Care Survey which
has several hundred hospitals reporting. The EMR were ranked as minimal, basic, or fully
functional. ED efficiency was measured in terms of length of stay and the number of patient
leaving without being seen. The author found that minimal EMR system had no impact on
efficiency; basic systems had mixed results, but tended to show improvement as the systems
became more sophisticated; and ED with fully functional EMR had substantial improvements in
efficiency.
The article is directly related to my topic. While older, published in 2010 and based on 2006
survey data, it serves as a baseline for the growth in EMR that started around that time, and the

5. literature search indicated that 3-5 plus years is not uncommon for similar types of papers in the
field. Per Ulrich this is a peer reviewed academic/scholar journal. The author has published
other similar material. Graphics and tables are included to help explain the data. I found the
statistics to be complex, however along with the concept, method and findings they were
discussed in detail, as were the limitations of the survey data and areas for future study. The
presentation is objected and no bias was noted. The intended audience was academics and policy
makers. The IF is 2.410 and the article has been cited 7 times (WOS).
Ward, M. J., Landman, A. B., Case, K., Berthelot, J., Pilgrim, R. L., & Pines, J. M. (2014). The
effect of electronic health record implementation on community emergency department
operational measures of performance. Annals of Emergency Medicine, 63(6), 723-730.
doi:10.1016/j.annemergmed.2013.12.019
Ward, et al. studied the impact of implementing an EMR at 23 hospitals EDs in a large national
chain (160 hospitals based EDs). Prior to installing and EMR the hospitals had already been
scanning paper documents to a central records facility where data was extracted using a
“standardized process and standardized fields” and stored to an enterprise system. Using monthly
averages, the authors compare multiple operational and patient care parameters for the year prior
to, and the year following the implementation of an EMR at a given hospital. The findings
indicated that there was no meaningful difference on the operations measures of interest between
the base line, and after one year. A caveat noted by Ward, et al. is that this did not look at
clinical care, but given this the finding supports the use of an EMR since the hospital receives the
full benefits of the EMR with no change in the measured operational parameters. Detailed table
and graphs are provided. The analysis, methods and findings are adequately discussed, as is the

6. high degree of variability between hospitals and the limits imposed by using monthly averages.
The authors suggest that possible factors affecting the variability could be variables such
different EMR systems, training, support personal and implementation schedule not captured by
the study data and which and would be good areas for future research.
The paper was published in 2014 and the data is from 2013, so this is very current. This is
directly relevant to my topic. The intended audience is academics and senior health care
managers interested in the impact of an EMR on ED operations. The authors have academic and
emergency medicine affiliations and have multiple publications in related areas. Per Ulrich the
journal is peer reviewed with academic/scholarly content. A limitation is that this is convenience
sample which limits generalizations. However, the data collection process already in place
provided a unique before and after picture of the impact of new EMR system. WOS lists one
citation of the article. The current IF for the journal is 4.676.