Upload
chris-kiess
View
442
Download
2
Embed Size (px)
DESCRIPTION
This paper explores the research surrounding the unintended consequences of healthcare information technology, the types and impact.
Citation preview
IUPUI
Unintended Consequences of
Information Technology in Healthcare
A Review of the Literature
Christopher Kiess
5/4/2009
2
Table of Contents Abstract ................................................................................................................. 3
Introduction ........................................................................................................... 4
Methods ................................................................................................................ 5 Table 1: Literature Search Methods ............................................................................................... 6 Table 2: Literature Search Criteria .................................................................................................. 7
Background ........................................................................................................... 7 1.1 History of Unintended Consequences .................................................................................... 7 1.2 Unintended Consequences in Healthcare Introduction..................................................... 8 1.3 Developing a Taxonomy of Unintended Consequences .................................................. 9 Table 3: Types of Unintended Consequences .......................................................................... 12 Table 4: Extent and Importance of Unintended Consequences .......................................... 13 1.4 Increased Mortality as an Unintended Consequence ...................................................... 14 1.5 Medication Errors as an Unintended Consequence ........................................................ 15
Conclusion .......................................................................................................... 16
3
Abstract
Introduction: The unintended consequences of technology implementation
have been discussed recently in the literature with a small number of studies
representing the body of work to date. There has been no effort to compile these
results into a single body of work as of the writing of this paper. This paper will
examine unintended consequences of technology in the healthcare environment
with a review of the literature and provide recommendations for moving forward
in addressing the issues presented. Methods: An extensive literature search was
performed using both keywords and exploiting the controlled vocabulary of 5
databases to develop a body of literature representing the primary areas of
interest. Results: The search resulted in 14 articles being accepted for analysis
representing 7 studies and 4 reviews. Conclusion: The unintended
consequences of healthcare technology is a new field of exploration representing
only a small number of studies. These studies, however, are providing us with a
taxonomy of both practical examples and categories of the different types of
unintended consequences. This provides a foundation with which we can begin
to move forward in solving the problems we see in relation to technology and
humans interacting. Research must continue in this field and we must move
forward in developing systems to define and outline how we will approach the
implementation of technology from sociological, technical and sociotechnical
perspectives.
4
Introduction
The effective implementation of IT systems is a high-priority area for the nation,
as it is increasingly important in improving quality, enhancing patient safety, and
decreasing costs. The Institute of Medicine (IOM) and National Academy of
Engineering have advocated widespread adoption of information technology (IT)
to improve quality, evidence-based practice, and to reduce medical errors
(Agrawal & W. Y. Wu, 2009; Building a Better Delivery System, 2005; Institute of
Medicine (U.S.), 2001; To Err Is Human, 2000). More effective use of IT is
recommended in integrating point-of-care access to health literature and
evidence-based guidelines; computerized decision support systems;
computerized clinical data; automation of decisions to reduce errors; and
electronic communication among providers and patients into practice (Agrawal &
Mayo-Smith, 2004; Doebbeling, Chou, & Tierney, 2006; Institute of Medicine
(U.S.), 2001; Mayo-Smith & Agrawal, 2007; Morrissey, 2003; Coiera, 2003; Cors,
n.d.). IT has three major benefits for improving quality: enhanced surveillance
and monitoring, increased guideline-based adherence, and decreased
medication errors (Chaudhry et al., 2006).
The benefits of information technology have been extensively documented
in the medical literature and have been shown to decrease errors, improve
processes and workflow, increase adherence to evidence-based guidelines and
decrease cost (Agrawal & W. Y. Wu, 2009; Chaudhry et al., 2006; Einbinder & D.
W. Bates, 2007; P. G. Shekelle, S. C. Morton, & Keeler, 2006). The
implementation of information technology affects numerous hospital processes
from finance to patient care and education (Doebbeling et al., 2006; Institute of
Medicine (U.S.), 2001). The type of information technology implemented in
medical institutions varies and can include clinical decision support (CDS) tools,
computerized physician order entry (CPOE), medication reconciliation and
medication dispensing systems (Bails, Clayton, Roy, & Cantor, 2008; Hatcher &
5
Heetebry, 2004; Motulsky, Winslade, Tamblyn, & Sicotte, 2008). Much has been
written concerning specific obstacles related to the implementation of health
information technology (HIT). These include staff resistance to implementation
(Ward, Stevens, Brentnall, & Briddon, 2008), communication problems between
the physician and patient as a result of technology (Makoul, Curry, & Tang, 2001;
Teutsch, 2003) and workarounds as a result of design (Halbesleben, D. S.
Wakefield, & B. J. Wakefield, 2008). These obstacles have been referred to a
number of times in the medical literature as “unintended consequences” (Joan S
Ash, Berg, & Coiera, 2004; Joan S Ash, Sittig, Emily Campbell, Guappone, &
Dykstra, 2006; Joan S Ash, Sittig, Emily M Campbell, Guappone, & Dykstra,
2007; Joan S Ash, Sittig, Dykstra, Emily Campbell, & Guappone, 2007, 2009;
Joan S Ash, Sittig, Dykstra, et al., 2007; Joan S Ash, Sittig, Poon, et al., 2007;
Emily M Campbell, Sittig, Joan S Ash, Guappone, & Dykstra, 2006; Harrison,
Koppel, & Bar-Lev, 2007).
A recent study published in the New England Journal of Medicine cited
physician resistance as one of the top barriers to the implementation of
electronic-records systems in hospitals (Jha et al., 2009). Physician and staff
resistance are primary barriers to the implementation of technology (Ward et al.,
2008) and facilitators to unintended consequences in the form of workarounds
(Halbesleben et al., 2008). Unintended consequences and failure in the
implementation of technology in hospitals can, in part, be attributed to the lacking
of a sociotechnical approach (Coiera, 2003, 2007; Ward et al., 2008).
This paper will examine unintended consequences of technology in the
healthcare environment with a review of the literature and provide
recommendations for moving forward in addressing the issues presented.
Methods
An extensive literature search was performed using both keywords and exploiting
the controlled vocabulary of each database to develop a body of literature
6
representing the primary areas of interest. Five primary databases were chosen
and a set of keywords was developed to employ in searching (see Table 1).
Compound keywords were used as phrases and limits on fields were set to title
and abstract in all searches moving to broader search sets if satisfactory results
were not found. Compound searches were performed in which terms were
searched to develop a search set that was then coupled with a subsequent
search using Boolean logic and processing. This exploited the keyword search
for maximum results. Articles were selected and their bibliographies mined for
further resources, which were then added to the initial set. Keyword adjustment
was an iterative process through the search. The controlled vocabularies in each
database were exploited for all possible and relevant terms as well with the
subsequent mining of the bibliographies taking place with those resources.
Table 1: Literature Search Methods
Databases Searched Keywords PubMed, HAPI, PsycINFO, CINAHL, Cochrane Database of Systematic Reviews
Unintended consequences, medical errors, technology, workarounds, CPOE, Computerized Provider Order Entry, Computerized Physician Order Entry, CDS, Clinical Decision Support
The criteria for selection of articles were divided by topic and different criteria
applied for each topic (see Table 2). As the literature is relatively obscure in this
area, the criteria set were minimal to obtain maximum results and inclusion in the
review. Moreover, no criteria were set per technology. That is, there were no
stipulations made in relation to whether the literature related to any of the topics
referred to CDS, CPOE, EHR, EMR, HIS, LIS or IT in general. The interest of this
review was set to unintended consequences and the general criteria were that
the subject matter merely had to relate to healthcare settings in terms of
7
technology. The literature search for unintended consequences resulted in 14
articles being accepted for analysis representing 7 studies and 4 reviews.
Table 2: Literature Search Criteria
Topic Criteria for Selection Unintended Consequences Age – 5 years or less
Level of Study – Review or data backed Length – no less than two pages Other – Unintended Consequences must be primary topic
Background
1.1 History of Unintended Consequences Unintended Consequences has largely been a term used in economics or
sociology and refers to outcomes – positive or negative – that are not foreseen or
part of the original intent with the initial action. It may well have first been widely
discussed in concept as part of Adam Smith’s Invisible Hand Theory developed
during the Enlightenment Period (Smith, 1977). The Invisible Hand was a
concept Smith used to describe how an individual agent in an economy strives
for their own wealth having little regard for those they interact with. Their intention
is to make themselves wealthy by producing goods and services. But, their
goods and services are valued by others creating a system that is ultimately
beneficial for the entire society.
It was not until the twentieth century that the term, Unintended
Consequence, became widespread at the hands of the sociologist, Robert K.
Merton (Merton, 1936, 1996). Merton evaluated unintended consequences as a
result of what he termed “purposive action” where the action is not behavior-
8
based but rather an action taken when one or more alternatives existed. Under
Merton’s Theory there can be positive or negative unintended consequences as
a result of our actions. Merton outlined five primary causes of unintended
consequences:
• Not understanding the complexity of the problem well enough to make an
educated choice
• Being ignorant of the range or complexity of the situation
• Subjugating the long term for short term gains or interests
• Basic values (cultural values, policies or laws) may conflict with the given
change
• Self Fulfilling Prophecies often have an opposing affect to the prophecy
An example of Merton’s theory can be seen in modern society. Building projects
are often seen as a benefit to a given community. However, a new shopping mall
or superstore often can have negative consequences to include subjugation of
local (smaller) businesses, local suppliers are subjugated, congested roadways
near the site, decrease in communication in the community and
commercialization of the community.
1.2 Unintended Consequences in Healthcare Introduction
Unintended consequences can occur in a number of differing industries and
professions and they are almost always sociologic at root. The relationship
between humans and technology has been written on extensively over the past
several decades (Krug, 2005; Moggridge, 2007; Don Norman & Dunaeff, 1994;
Donald A. Norman, 2002, 2005, 2007). Most recently, there have been attempts
to understand these relationships in healthcare and an emerging inquiry into the
unintended consequences resulting from the implementation of technology and
the interaction of healthcare professionals with new technology.
9
Prior to the work of Coiera and Ash, there was relatively little discussion of
unintended consequences in the healthcare literature (Joan S Ash et al., 2009; D
W Bates et al., 1999; Patterson, Cook, & Render, 2002). The earliest article
found was a 1998 analysis of the benefits and detriments to electronic medical
records (Silverman, 1998). The article cites two primary problems with electronic
medical records – lack of privacy and costs associated with implementation and
upkeep. This latter category is reported on in later works by Ash and her
colleagues (Emily M Campbell et al., 2006; Joan S Ash et al., 2009; Joan S Ash,
Sittig, Poon, et al., 2007; Joan S Ash, Sittig, Dykstra, et al., 2007). With the
exception of the first sentence, Silverman did not specifically use the term
“unintended consequences” in his analysis or maintain a primary focus on it.
Negative consequences resulting from new technology implementation are often
reported in the literature without using the specific terminology, “unintended
consequences” or focusing on the distinct sociologies related to the
consequences. Wachter used the term “unforeseen consequences” in his
general assessment of computerization in healthcare but maintains a focus on
quality and safety in healthcare from an administrative viewpoint. McDonald
described near misses in an article outlining the potential hazards of bar-code
administration in patient misidentification. There are a number of articles
correlating adverse drug events with computerization of processes (Han et al.,
2005; McAlearney, Chisolm, Schweikhart, Medow, & Kelleher, 2007; Nebeker,
Hoffman, Weir, Bennett, & Hurdle, 2005). But, these works have not discussed
unintended consequences as a concept in and of itself.
1.3 Developing a Taxonomy of Unintended Consequences
It was Ash et al. who spearheaded the research on unintended consequences
with her studies beginning in 2003 (Joan S Ash et al., 2004) and began defining
unintended consequences as a concept. There are only a small number of
studies with which to proceed with and knowledge at this point of the problems
associated with the implementation of information technology is minimal – our
10
results largely in a set of descriptive categories. These categories are essential
for understanding the effects of technology both good and bad. But, there is even
less in the literature in terms of suggestions to avoid these consequences (Joan
S Ash, Fournier, Stavri, & Dykstra, 2003; Joan S Ash et al., 2007; Coiera, 2007).
It is imperative to continue both researching and categorizing unintended
consequences as they occur in healthcare environments and further our
explorations of suggested solutions.
Ash et al. explored unintended consequences first as part of
research including three different countries across the United States, Europe and
Australia. The results were the first attempt at categorizing the errors resulting
from the unintended consequences of implementation of technology. The original
intent of the study concerned gathering qualitative data in institutions using
Patient Care Information Systems. In gathering and analyzing the data, the
observers began to discover patterns indicating there existed possibilities of
errors occurring within these systems or attitudes reflecting this knowledge (Joan
S Ash et al., 2004). This initiated a series of related studies to both analyze the
existing data from new perspectives and obtain more data (Joan S Ash et al.,
2004; Joan S Ash et al., 2006; Joan S Ash et al., 2007; Joan S Ash et al., 2009;
Joan S Ash, Sittig, Dykstra, et al., 2007; Joan S Ash, Sittig, Poon, et al., 2007;
Emily M Campbell et al., 2006). The body of work Ash and her colleagues have
produced has provided insight into:
• The types or categories of unintended consequences
• Types of unintended consequences specific to clinical decision support
systems (CDS)
• Sociological consequences to implementation
• Quantification of the importance of the types of unintended consequences
• The extent or prevalence of unintended consequences
• Solutions and implementation recommendations
The initial publishing of the resulting analysis of qualitative data yielded two
primary categories of unintended consequences – errors involving the entry or
11
retrieval of information held in the system and errors in communication and
coordinating patient care (Joan S Ash et al., 2004). Both types of errors were
further broken down into subcategories where there were problems described
with the human-computer interface (wrong person orders, juxtaposition) that had
not been designed with a complex “interruptive” environment in mind. Hospitals
are environments where interruptions are common and thus systems must be
designed with this in mind. Cognitive overload and shifts in cognitive patterns
due to restructuring the charting process was another finding. Structuring the
information often results in forcing the physician to enter comments a certain way
and in a certain field. Physicians were found to be frustrated with pre-populated
fields allowing for no modification. Other works have shown physicians cannot
troubleshoot and diagnose in the same fashion as before since the information is
presented differently and, thus, interpreted differently (Harrison et al., 2007). Ash
et al. described the phenomenon as a “loss of overview” where the physician can
no longer get the big picture. Misunderstanding the complexity of the work was a
third subcategory and is described as seeing the work completed in linear
fashion rather than an interactive hub of activities. This can lead to problems in
the processes already in place and are exacerbated by an inflexible system. The
fourth and final subcategory refers to the change in communication patterns
among workers. Entering an order in a system is not effectively communicating
that order to anyone other than whoever receives the order on the other end.
This means a nurse working with a doctor may not know a medication was
ordered or another physician could conceivably enter a duplicate order. But, the
communication (or feedback) from the system can also prove frustrating for the
end-user. Alerts, for example, can often overwhelm the user and be ineffective in
prompting the user to new or improved behavior. These categories were
eventually fleshed out further with added analysis and data gathering to form a
taxonomy in which 9 types of unintended consequences were represented (See
Table 3).
12
Table 3: Types of Unintended Consequences
Type of Unintended Consequence Example
More/New Work Issues
Multiple Passwords Responding to alerts Entering required information or more detailed information Extra time
Workflow Issues
System “re-orders” the workflow HCI problems Inconsistencies between system and policy/procedures
Never Ending Demands
More space required for computers Persistent upgrades Screen space not large enough Perpetual training Maintenance
Paper Persistence
Paper process does not end
Communication Issues
Communication patterns change as a result of system Physicians and nurses spend more time entering information than at bedside
Emotions
Frustration and anger on the part of professionals in attempting to use systems and alter workflow
New Kinds of Errors
Juxtaposition errors Automated entry
Changes in Power Structure
IS/IT become authorities Those who know how to use system leverage that knowledge Administrators can track compliance more easily
Overdependence on Technology
System failures leave hospitals merciless
With the 9 types of consequences, Ash and colleagues later developed an 8-
question survey deigned to determine both the extent – or prevalence – of the
13
types and the overall level of importance of each type to hospitals with
implemented CPOE. 176 full interviews were conducted via telephone – the
results of which can be seen in table 4. Rated the highest in terms of importance
were system demands, communication and workflow issues. The lowest rating
went to shifts in power and new types of errors. Most interesting to note is there
did not appear to be any correlation between the length of time each hospital had
owned the CPOE system and unintended consequences. Ash et al. also noted
there were both positive and negative unintended consequences involved in
implementation of CPOE and that hospitals can either work to avoid the negative
unintended consequences or simply accept them as part of developing a new
system.
Table 4: Extent and Importance of Unintended Consequences
Category
No
Yes (Less important)
Yes (moderately
to very important)
N
More work or new work
8 40 125 173
Workflow 6 15 149 170 System Demands 10 21 143 174 Communications 8 20 146 174 Emotions 8 28 140 176 New Kinds of Errors
15 77 82 174
Power Shifts 61 50 61 172 Dependence on the Technology
14 15 138 167
As part of the same series of studies, Ash and her colleagues were also able to
compile data on Clinical Decision Support Systems and unintended
consequences therein (Joan S Ash et al., 2007). There were two primary
categories derived from this data – those consequences related to the content of
the system and those related to the presentation of the system. Those
consequences related to the content of the system were a shift in roles and
responsibilities, the currency of the content and wrong or misleading content. The
14
consequences related to the presentation of the system included rigidity of the
system (or the inability to tailor certain procedures or notifications), alert fatigue
(developed from too many alerts) and sources of potential errors such as auto-
complete fields and paper routing issues. Three primary recommendations
followed analysis in this study. To address the currency of the system and the
content it was suggested a knowledge management structure be developed with
interdisciplinary participation. In this way, a knowledge base can be developed
and can address many of the issues outlined in the problems related to content.
In relation to presentation problems, the recommendations were two: implement
a taxonomy designed to mediate the number of automated alerts determine what
fields need structure data versus those that do not. The need to capture
structured data often results in rigidity for the input of information. When this
structure is not needed, it can be removed (or not added) to the system to allow
more flexibility to the end user.
1.4 Increased Mortality as an Unintended Consequence
A study performed by Han et al. originating in the Children’s Hospital of
Pittsburgh reported an increase of 3.77% in mortality after the implementation of
a CPOE (Han et al., 2005). This study caused somewhat of a stir and generated
concern in the field of medicine. This was later commented on by Dean Sittig and
Ash in a commentary published in the same journal (Sittig, Joan S Ash, Zhang,
Osheroff, & Shabot, 2006). A study published that same year, however, showed
a significant decrease in mortality after implementation of a CPOE (Del Beccaro,
Jeffries, Eisenberg, & Harry, 2006). An expert panel was then constructed to
evaluate the two studies and develop an understanding of the differences in
results (Ammenwerth et al., 2006). The primary findings showed the two studies
were difficult to compare due to differing study designs and sampling. Also, the
Han study had implemented their CPOE in a six-day time period rather than
using a slow implementation process. The primary recommendation of this paper
was to ensure a socio-technical approach was taken in implementation that
15
would recognize the differences within organizations and to ensure future
informaticians are educated in these approaches.
1.5 Medication Errors as an Unintended Consequence
Koppel et al. also conducted a study at the Philadelphia Veteran’s Administration
using both quantitative and qualitative methods to examine the effects of CPOE
on medication errors. Their study resulted in finding of 22 different classes of
errors, which they then divided into two large categories –interface issues and
information errors due to faulty systems implementation and integration. The
information related errors largely revolved around medication and medication
reconciliation. Some of these errors clearly lacked foresight into who would use
the system and how it would (or should) be used. For example, dosing of
medications was set from a pharmacy purchasing perspective so that the
medications were listed in the system as they were ordered from suppliers. This
meant a single dose could be more or less than what was standard for the
physician or clinic. This resulted in both under and overdosing. There were
scheduling problems with the cancellation of medication orders and renewal of
medications. Within the system cancelling a medication was a different process
than medication renewal meaning the system was prone to errors if the physician
forgot to complete the entire process. An alert process for allergy medicines
failed to notify the physician until after the order was sent meaning in a highly
interruptive environment, the alert could possible never be seen. Errors with the
interface included unclear log-on and off procedures where physicians could
potentially enter orders under another physician’s id. Other errors included
contemporaneous charting as a time barrier, improper alerts, errors in which the
procedures in the institution are subjugated or ignored. The study findings
confirm what Ash et al. find and what Ammenwerth et al. recommend –
sociotechnical approaches are necessary to address these errors prior to
implementation.
16
Conclusion
The implementation of technology in a stable environment is a challenge. But,
implementing a system in an environment as complex as healthcare exacerbates
an already difficult situation. In hospitals you have:
• Systems that do not communicate with one another
• A patient who often will move from unit to unit and, thus, system to system
• An ever-changing series of guidelines, information and new treatments
• Inconsistent human nature (i.e. doctors and nurses)
• Administrators who sometimes use systems to force policy rather than
medical standards and guidelines
• Designers who often have little understanding of medicine or the workflow
challenges in a hospital
The above represents a series of moving parts that must synchronize and work
towards a common goal. In designing systems the complexity of a hospital is
often not realized and it is evident we must adjust our approach in order to build
a better system and give our physicians and nurses tools that help rather than
hinder their work. If we were to suppose a hospital is much like an ecology, we
might understand how we can best approach the problems outlined in this
writing.
Island ecology is a subject that has fascinated scientists for years and has
been the subject of science writer David Quammen on a number of occasions
(Quammen, 1998, 1997). Island ecology is often equated with the term “insular
biogeography” and islands pose certain challenges in that species (both plant
and animal) are much more vulnerable to extinction based on their insulation
from other ecologies. The dodo bird is, perhaps, the most famous example of an
island species that became extinct as a result of its island habitat. The same
concept has been explored in relation to the division of state parks in the United
States. The 20th century saw many state parks being split to allow logging
17
companies passage through or the make room for travel. A result has been the
species in those parks have gone extinct. To cite an example, the Bridge
Mountains and The Crazy Mountains both lost their species of Grizzlies once
they had been insulated through development projects (Quammen, 1999). We
have also seen this same concept occur in the Amazonian Forest in what has
been termed “ecosystem decay” as a result of fragmenting the forest (W. F.
Laurance et al., 2002). The more complex and connected an ecosystem is, the
better its chance of survival. If we were to see hospitals as complex ecosystems
where connections between humans and systems must remain (as well as
connections between humans and humans), we would begin to understand just
how complex the system is and how our interventions can harm rather than help.
Chaos Theory is a related theory and has also proved useful in evaluating the
environment of organizations (Thiétart & Forgues, 1995). It is of value in
understanding the nature of chaotic environments where change occurs rapidly.
Both the interconnectivity of hospitals and their chaotic nature must be
understood and addressed prior to interventions.
A sociotechnical approach has been discussed in the literature in relation
to unintended consequences (Harrison, Henriksen, & Hughes, 2007; Harrison et
al., 2007) and is worthy of pursuit. History has shown that a frequent response to
problems with technology have been to develop new technologies to address
existing issues (Don Norman & Dunaeff, 1994; Donald A. Norman, 2002, 2007).
However, this sort of patchwork approach ignores the social interaction between
humans and technology. In order to best develop these interactions, we must
approach the problems that are social in nature and understand how they affect
the technology we have developed through ethnographies, interviews, data
analysis and observations. We must then gain an understanding of how to build
systems in coalition with those who will use them through participatory design,
collaboration in system development and maintaining iterative processes in
design.
Unintended consequences in healthcare technology is a new field of
exploration representing only a small number of studies. These studies, however,
18
are providing us with a taxonomy of both practical examples and categories of
the different types of unintended consequences. This provides a foundation with
which we can begin to move forward in solving the problems we see in relation to
technology and humans interacting. Research must continue in this field and we
must move forward in developing systems to define and outline how we will
approach the implementation of technology from sociological, technical and
sociotechnical perspectives.
19
Agrawal, A., & Mayo-Smith, M. F. (2004). Adherence to computerized clinical
reminders in a large healthcare delivery network. Studies in Health
Technology and Informatics, 107(Pt 1), 111-4.
Agrawal, A., & Wu, W. Y. (2009). Reducing medication errors and improving
systems reliability using an electronic medication reconciliation system.
Joint Commission Journal on Quality and Patient Safety / Joint
Commission Resources, 35(2), 106-14.
Ammenwerth, E., Talmon, J., Ash, J. S., Bates, D. W., Beuscart-Zéphir, M.,
Duhamel, A., et al. (2006). Impact of CPOE on mortality rates--
contradictory findings, important messages. Methods of Information in
Medicine, 45(6), 586-593.
Ash, J. S., Berg, M., & Coiera, E. (2004). Some unintended consequences of
information technology in health care: the nature of patient care
information system-related errors. Journal of the American Medical
Informatics Association: JAMIA, 11(2), 104-112.
Ash, J. S., Fournier, L., Stavri, P. Z., & Dykstra, R. (2003). Principles for a
successful computerized physician order entry implementation. AMIA ...
Annual Symposium Proceedings / AMIA Symposium. AMIA Symposium,
36-40.
Ash, J. S., Sittig, D. F., Campbell, E., Guappone, K., & Dykstra, R. H. (2006). An
unintended consequence of CPOE implementation: shifts in power,
control, and autonomy. AMIA ... Annual Symposium Proceedings / AMIA
Symposium. AMIA Symposium, 11-15.
20
Ash, J. S., Sittig, D. F., Campbell, E. M., Guappone, K. P., & Dykstra, R. H.
(2007). Some unintended consequences of clinical decision support
systems. AMIA ... Annual Symposium Proceedings / AMIA Symposium.
AMIA Symposium, 26-30.
Ash, J. S., Sittig, D. F., Dykstra, R., Campbell, E., & Guappone, K. (2007).
Exploring the unintended consequences of computerized physician order
entry. Studies in Health Technology and Informatics, 129(Pt 1), 198-202.
Ash, J. S., Sittig, D. F., Dykstra, R., Campbell, E., & Guappone, K. (2009). The
unintended consequences of computerized provider order entry: findings
from a mixed methods exploration. International Journal of Medical
Informatics, 78 Suppl 1, S69-76.
Ash, J. S., Sittig, D. F., Dykstra, R. H., Guappone, K., Carpenter, J. D., &
Seshadri, V. (2007). Categorizing the unintended sociotechnical
consequences of computerized provider order entry. International Journal
of Medical Informatics, 76 Suppl 1, S21-27.
Ash, J. S., Sittig, D. F., Poon, E. G., Guappone, K., Campbell, E., & Dykstra, R.
H. (2007). The extent and importance of unintended consequences
related to computerized provider order entry. Journal of the American
Medical Informatics Association: JAMIA, 14(4), 415-423.
Bails, D., Clayton, K., Roy, K., & Cantor, M. N. (2008). Implementing online
medication reconciliation at a large academic medical center. Joint
Commission Journal on Quality and Patient Safety / Joint Commission
Resources, 34(9), 499-508.
21
Bates, D. W., Kuperman, G. J., Rittenberg, E., Teich, J. M., Fiskio, J., Ma'luf, N.,
et al. (1999). A randomized trial of a computer-based intervention to
reduce utilization of redundant laboratory tests. The American Journal of
Medicine, 106(2), 144-150.
Building a Better Delivery System: A New Engineering/Health Care Partnership.
(2005). (p. 262). Washington, D.C: National Academies Press.
Campbell, E. M., Sittig, D. F., Ash, J. S., Guappone, K. P., & Dykstra, R. H.
(2006). Types of unintended consequences related to computerized
provider order entry. Journal of the American Medical Informatics
Association: JAMIA, 13(5), 547-56.
Chaudhry, B., Wang, J., Wu, S., Maglione, M., Mojica, W., Roth, E., et al. (2006).
Systematic review: impact of health information technology on quality,
efficiency, and costs of medical care. Annals of Internal Medicine, 144(10),
742-52.
Coiera, E. (2003). Guide to Health Informatics (2nd ed.). A Hodder Arnold
Publication.
Coiera, E. (2007). Putting the technical back into socio-technical systems
research. International Journal of Medical Informatics, 76 Suppl 1, S98-
103.
Cors, W. K. (n.d.). Physician executives must leap with the frog. Accountability
for safety and quality ultimately lie with the doctors in charge. Physician
Executive, 27(6), 14-6.
Del Beccaro, M. A., Jeffries, H. E., Eisenberg, M. A., & Harry, E. D. (2006).
22
Computerized provider order entry implementation: no association with
increased mortality rates in an intensive care unit. Pediatrics, 118(1), 290-
295.
Doebbeling, B. N., Chou, A. F., & Tierney, W. M. (2006). Priorities and strategies
for the implementation of integrated informatics and communications
technology to improve evidence-based practice. Journal of General
Internal Medicine, 21 Suppl 2, S50-7.
Einbinder, J. S., & Bates, D. W. (2007). Leveraging information technology to
improve quality and safety. IMIA Yearbook of Medical Informatics 2007.
Methods Inf Med, 46(Suppl 1), 22-29.
Halbesleben, J. R. B., Wakefield, D. S., & Wakefield, B. J. (2008). Work-arounds
in health care settings: Literature review and research agenda. Health
Care Management Review, 33(1), 2.
Han, Y. Y., Carcillo, J. A., Venkataraman, S. T., Clark, R. S. B., Watson, R. S.,
Nguyen, T. C., et al. (2005). Unexpected increased mortality after
implementation of a commercially sold computerized physician order entry
system. Pediatrics, 116(6), 1506-1512.
Harrison, M. I., Henriksen, K., & Hughes, R. G. (2007). Improving the health care
work environment: a sociotechnical systems approach. Joint Commission
Journal on Quality and Patient Safety / Joint Commission Resources,
33(11 Suppl), 3-6, 1.
Harrison, M. I., Koppel, R., & Bar-Lev, S. (2007). Unintended consequences of
information technologies in health care--an interactive sociotechnical
23
analysis. Journal of the American Medical Informatics Association: JAMIA,
14(5), 542-549.
Hatcher, M., & Heetebry, I. (2004). Information technology in the future of health
care. Journal of Medical Systems, 28(6), 673-688.
Institute of Medicine (U.S.). (2001). Crossing the Quality Chasm: A New Health
System for the 21st Century (p. 337). Washington, D.C: National Academy
Press.
Jha, A. K., DesRoches, C. M., Campbell, E. G., Donelan, K., Rao, S. R., Ferris,
T. G., et al. (2009). Use of Electronic Health Records in U.S. Hospitals. N
Engl J Med, 360(16), 1628-1638.
Krug, S. (2005). Don't Make Me Think: A Common Sense Approach to Web
Usability, 2nd Edition (2nd ed.). New Riders Press.
Laurance, W. F., Lovejoy, T. E., Vasconcelos, H. L., Bruna, E. M., Didham, R. K.,
Stouffer, P. C., et al. (2002). Ecosystem Decay of Amazonian Forest
Fragments: a 22-Year Investigation. Conservation Biology, 16(3), 605-
618.
Makoul, G., Curry, R. H., & Tang, P. C. (2001). The use of electronic medical
records: communication patterns in outpatient encounters. Journal of the
American Medical Informatics Association: JAMIA, 8(6), 610-615.
Mayo-Smith, M. F., & Agrawal, A. (2007). Factors associated with improved
completion of computerized clinical reminders across a large healthcare
system. International Journal of Medical Informatics, 76(10), 710-6.
McAlearney, A. S., Chisolm, D. J., Schweikhart, S., Medow, M. A., & Kelleher, K.
24
(2007). The story behind the story: physician skepticism about relying on
clinical information technologies to reduce medical errors. International
Journal of Medical Informatics, 76(11-12), 836-842.
Merton, R. (1936). The Unanticipated Consequences of Purposive Social Action.
American Sociological Review, 1(6), 894-904.
Merton, R. K. (1996). On Social Structure and Science (1st ed.). University Of
Chicago Press.
Moggridge, B. (2007). Designing Interactions (1st ed.). The MIT Press.
Morrissey, J. (2003). An info-tech disconnect. Even as groups such as Leapfrog
push IT as an answer to quality issues, doctors and executives say, 'not
so fast'. Modern Healthcare, 33(6), 6-7, 36-8, 40 passim.
Motulsky, A., Winslade, N., Tamblyn, R., & Sicotte, C. (2008). The impact of
electronic prescribing on the professionalization of community
pharmacists: a qualitative study of pharmacists' perception. Journal of
Pharmacy & Pharmaceutical Sciences: A Publication of the Canadian
Society for Pharmaceutical Sciences, Société Canadienne Des Sciences
Pharmaceutiques, 11(1), 131-146.
Nebeker, J. R., Hoffman, J. M., Weir, C. R., Bennett, C. L., & Hurdle, J. F. (2005).
High rates of adverse drug events in a highly computerized hospital.
Archives of Internal Medicine, 165(10), 1111-1116.
Norman, D., & Dunaeff, T. (1994). Things That Make Us Smart: Defending
Human Attributes In The Age Of The Machine. Basic Books.
Norman, D. A. (2002). The Design of Everyday Things. Basic Books.
25
Norman, D. A. (2005). Emotional Design: Why We Love (or Hate) Everyday
Things (1st ed.). Basic Books.
Norman, D. A. (2007). The Design of Future Things: Author of The Design of
Everyday Things (illustrated edition.). Basic Books.
Patterson, E. S., Cook, R. I., & Render, M. L. (2002). Improving patient safety by
identifying side effects from introducing bar coding in medication
administration. Journal of the American Medical Informatics Association:
JAMIA, 9(5), 540-553.
Quammen, D. (1997). The song of the dodo. Scribner.
Quammen, D. (1998). The Flight of the Iguana. Scribner.
Quammen, D. (1999). Wild Thoughts from Wild Places. Scribner.
Shekelle, P. G., Morton, S. C., & Keeler, E. B. (2006). Costs and benefits of
health information technology. Evidence report/technology assessment,
(132), 1.
Silverman, D. C. (1998). The electronic medical record system: health care
marvel or morass? Physician Executive, 24(3), 26-30.
Sittig, D. F., Ash, J. S., Zhang, J., Osheroff, J. A., & Shabot, M. M. (2006).
Lessons from "Unexpected increased mortality after implementation of a
commercially sold computerized physician order entry system". Pediatrics,
118(2), 797-801.
Smith, A. (1977). An Inquiry into the Nature and Causes of the Wealth of Nations
(1904th ed.). University Of Chicago Press.
Teutsch, C. (2003). Patient-doctor communication. The Medical Clinics of North
26
America, 87(5), 1115-1145.
Thiétart, R. A., & Forgues, B. (1995). Chaos Theory and Organization.
Organization Science, 6(1), 19-31.
To Err Is Human: Building a Safer Health System. (2000). (p. 287). Washington,
D.C: National Academy Press.
Ward, R., Stevens, C., Brentnall, P., & Briddon, J. (2008). The attitudes of health
care staff to information technology: a comprehensive review of the
research literature. Health Information and Libraries Journal, 25(2), 81-97.