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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Patient Saf. Author manuscript; available in PMC 2012 December 1.
Published in final edited form as:
PMCID: PMC3220192

What stands in the way of technology-mediated patient safety improvements? A study of facilitators and barriers to physicians' use of electronic health records



For electronic health records (EHR) systems to have a positive impact on patient safety, clinicians must be able to use these systems effectively after they are made available. This study's objective is to identify and describe facilitators and barriers to physicians' use of EHR systems.


Twenty research interviews were conducted with attending physicians who were using EHR at one of two Midwest community hospitals and/or at their respective outpatient clinics.


Analyses yielded over 200 perceived facilitators and barriers, comprising 19 distinct categories. Categories of facilitators/barriers related to user attributes included learning, typing proficiency, understanding the EHR system, motivation/initiative, and strategies/workarounds. Categories related to system attributes were supporting hardware/software and system speed, functionality, and usability. Categories related to support from others were formal technical support, formal training, and informal support from colleagues. Categories of organizational facilitators/barriers were time allowance and inter-institutional integration. Categories of environmental facilitators/barriers were physical space, electricity, wireless connectivity, and the social environment.


Together, the broad set of discovered facilitators and barriers confirms and expands prior research on the facilitators and barriers to health information technology use. The depth of reported information on each facilitator and barrier made possible by qualitative interview methods contributes to the theoretical understanding of facilitators and barriers to EHR use. Equally as important, this study provides an information base from which relevant policy and design interventions can be launched in order to improve the use of EHR systems and, thus, patient safety.


Electronic health records (EHR) systems are a prevailing intervention for improving quality and safety of care in the US[13] and abroad.[4] However, mixed evidence regarding the actual quality and safety benefits of EHR [510] supports the idea that it is not the mere presence of EHR that determines improvement, but rather how and to what extent clinicians use EHR systems post-adoption (i.e., once purchased and implemented).[1113] When EHR systems are available, making safe and appropriate diagnostic and treatment decisions entails actually accessing information (e.g., problem lists, prior notes, test results) in the EHR rather than relying on memory or outdated handwritten notes. Information must not only be accessed, but also processed, which is facilitated by certain EHR use behaviors (e.g., putting information side by side, using sorting and graphing features, looking up additional reference information). To effectively, securely, and quickly communicate safety-relevant information to patients and fellow providers, clinicians must actually use built-in features. To take advantage of the improved legibility, completeness, direct transmission, and forcing functions afforded by an electronic system, providers must actually enter documentation and orders into the system and must do so in a clear and complete way. To intercept potential prescribing errors, physicians must appropriately respond to alerts issued by built-in decision support. In short, the safety benefits of EHR do not come through the mere presence of these systems but rather through their appropriate use. (Of course, there are other factors besides use that affect EHR's safety benefits, for example EHR design and implementation,[14, 15] the degree to which EHR supports cognition,[1618] and the fit between the EHR and the clinical work system.[19, 20])

Several studies have identified facilitators and barriers to EHR adoption such as cost and difficulty procuring the system, physician resistance, and organizational characteristics (e.g., hospital size, ownership, and teaching status).[3, 2125] However, those studies do not reveal what facilitates or impedes EHR use once EHR has been made available at a hospital or clinic. Given that limitation and the recent focus on “meaningful use” (rather than mere acquisition) of EHR,[26, 27] this study aimed to identify and describe the perceived facilitators of and barriers to physicians' EHR use.

Figure 1 depicts the conceptual framework for the study. It shows that the post-adoption stage is important in determining EHR outcomes such as patient safety.[2830] Clinicians' post-adoption attitudes (i.e., acceptance/rejection) and behavior (i.e., use/non-use) are in part determined by facilitators and barriers, or factors that affect clinicians' ability to use the system in an meaningful way.[31, 32] Those facilitators and barriers are aspects of the work system [33, 34] such as user attributes, system attributes, support from others, organizational support, environmental factors, and control over behavior.[35] Although there are facilitators and barriers to adoption and achieving improved outcomes, this study focuses on post-adoption facilitators and barriers.

Figure 1
After an organization adopts electronic health records (EHR), clinicians accept or reject and use or do not use EHR and these post-adoption attitudes and behavior determine outcomes of interest such as quality of care, patient safety, and return on investment. ...


Study design

Perceived facilitators and barriers were elicited using semi-structured qualitative research interviews called belief elicitation interviews.[36] An assumption of this method is that subjective beliefs, though they can be incongruent with reality, are important to assess because people's behavior is based on their beliefs or perceptions of reality.[37] A human factors engineer/psychologist trained in qualitative interviewing conducted all interviews. The study was approved by institutional review boards (IRBs) at the University of Wisconsin-Madison and at both research sites.

Sample and setting

Participants were attending physicians recruited from two 400+ bed Midwest US community hospitals. Twenty physicians participated, eleven from Hospital 1 and nine from Hospital 2. Respondents represented general medicine and a diversity of specialties and were practicing an average of 15 years at the time of interviews. The same, top-ranked national vendor of inpatient hospital EHR provided system for both hospitals. Hospital 1 was using EHR for data retrieval only for three years at the time of the interviews (June–September 2007). Hospital 2 was using EHR with data retrieval and electronic documentation for nine months and computerized order entry for seven months at the time of the interviews (January–February 2009). (See Appendices for more information on hospitals, participants, and their EHR systems.)

Interview instrument

Interviews lasted one hour. Participants were asked the following questions intended to elicit perceived facilitators/barriers:

  • “What factors or circumstances would enable you to use [EHR system]?”
  • “What factors or circumstances would make it difficult or impossible for you to use [EHR system]?”
  • “Are there any other issues that come to mind when you think about being able to or not being able to use [EHR system]?

Question wording was based on wording specifically designed for psychological studies on facilitators and barriers to planned behavior.[38, 39] Scripted variations of these questions were asked if a participant had difficulty answering (e.g., “How would you fill in the blank: If not for `blank,' I would not be able to use the technology like I want to”). Unscripted prompts were used to encourage further information and to keep responses focused on interview topics (e.g., “Anything else that helps you be able to use it?”). The interviewer provided encouragement, both non-verbal (e.g., a nod, taking notes) and spoken (usually, “Mm-hum” or “Okay”), following responses and was careful to not endorse responses in a biased way (e.g., favoring barriers over facilitators). Participants were also asked about the advantages and disadvantages of using EHR, social pressure to use EHR, and opinions about EHR implementation.[40]


Transcribed interview passages were analyzed for references to facilitators and barriers, or factors, circumstances, or conditions enabling or prohibiting, respectively, intended EHR use. Identified facilitators and barriers were organized into six groups: four based on Mathieson et al[35]—“user attributes,” “system attributes,” “support from others,” and “general control-related”—and two additional groups needed to account for all the data—“organizational support” and “environmental factors” (see Figure 1). Analysis was guided by definitions of facilitators and barriers taken from social-cognitive theories of behavior.[4144] QSR NVivo 8 (Cambridge, MA) software was used for storing and coding data.


Over 200 interview statements were coded as mentioning facilitators (127) or barriers (82) to the use of EHR and specific EHR functions (e.g., order entry, clinical documentation). On average, individual physicians reported about 10 facilitators/barriers (M = 10.5, SD = 2.8, range = 6 – 16), and were more likely to mention a facilitator than a barrier (average facilitator to barrier ratio = 2.1:1, range = 3:8 – 9:1).

Below, specific facilitators and barriers to EHR use are described, and illustrative passages (chosen based on clarity and representativeness) are presented in Tables 1 through through55.

Table 1
User attributes identified as facilitators and barriers to EHR use and example passages.
Table 5
Identified facilitators and barriers related to the physical and social work environment and example passages.

User attributes

Six categories of facilitators/barriers were related to individual users, described below, ordered from most to least frequently mentioned (Table 1).

  • Learning. Learning was often mentioned as a necessary and inevitable condition for efficient use of EHR. Physicians believed learning required time, repetition, and effort, and could not be avoided through design; instead, as one physician explained, one must adjust one's behavior over time to fit the design of the EHR (“The machine has taught me to accept that”). Physicians often spoke of learning through experience (“I figured it out myself”), for example, constructing a set of six clinical note templates that “evolved … because that wasn't really part of the formal training.”
  • Typing proficiency. One physician identified fast typing as a facilitator; others perceived slow typing as a barrier and contrasted their difficulty acquiring “keyboarding skills … on the fly” with the facility of younger colleagues. Faster typing permitted more substance in clinical notes.
  • Understanding the EHR system. Lack of understanding of the system, e.g., how to navigate it, was attributed to unintuitive design. Conversely, a good mental model of the EHR's information structure facilitated use. Unfamiliarity with specific features, e.g., secure remote access, was a barrier to using EHR fully.
  • Motivation/initiative. Some attributed use of EHR beyond their basic training to personal initiative (“I put that on myself”) and adventurousness, noting that personal initiative was important because initial training was insufficient, additional formal training required extra time, and the hospital did not promote certain types of use (e.g., electronic signatures).
  • Strategies/workarounds. In addition to mastering built-in shortcuts, physicians reported developing routines (e.g., documenting the entire outpatient encounter in between patient visits vs. pre-typing notes during visit, finishing them later) that facilitated EHR use. Strategies sometimes involved working around standard protocol (e.g., entering a scheduled Saturday outpatient visit as a walk-in the day of the visit; entering freetext orders for nurses to put in using structured order entry interface) when physicians perceived the standard protocol to be problematic (e.g., caused awkward workflow, double entry, or time inefficiencies).
  • Other. Remembering/forgetting the password, forgetting how to use EHR with the passage of time, and having unimpaired physical function were additional user-related facilitators/barriers mentioned.

System attributes

Four categories of facilitators/barriers were related to the EHR system and the software and hardware supporting it (Table 2).

  • Supporting hardware/software. Almost every physician identified availability of computer stations and remote access software as facilitators of EHR use. Conversely, computers being busy (e.g., when “you hit the rush hour”), too few, or too slow were common perceived barriers. Remote access was sometimes hindered by lack of connectivity, not having the encryption card needed to log in, visiting patients in a place without Internet (e.g., nursing home), or needing Windows software.
  • Speed. System slowness in some units, but not in others, was perceived as a barrier to use as was the slow, multiple-step log-in process. Log-in was complicated by the need to remember multiple passwords.
  • Functionality. Physicians named multiple functionalities in the EHR system that facilitated its use, including order sets and pathways, customizable templates allowing information to be pulled from the EHR into clinical notes, an option to “copy and paste” (replicate) previous notes, keyboard shortcuts, and voice recognition-enabled documentation. One physician noted a functional barrier: only three patient profiles could be open concurrently.
  • Usability. Half of those interviewed identified usability as a barrier whereas only three physicians, all at Hospital 1, described the system as easy to use, mainly because of the system's consistent format. Specifically mentioned were the system's lack of simplicity (the “broad, almost infinite way that you can do things … makes it harder”), unintuitiveness, overly structured notes, fragmented information, and cumbersome outpatient scheduling feature.
Table 2
System attributes identified as facilitators and barriers to EHR use and example passages.

Support from others

Three categories of facilitators/barriers were related to support received from others (Table 3).

  • Formal technical support. Technical support facilitated use both in the initial days and weeks of EHR and afterwards. Support staff were generally perceived as knowledgeable and helpful, although some physicians noted that support staff were unavailable sometimes (off hours; holidays). Physicians were most appreciative of one-on-one, on-demand support during actual care scenarios.
  • Formal training. Although initial formal training was depicted favorably by some, insufficient training was often identified as a barrier, either because there was not enough training or because classroom training was ill-suited to physicians' clinical needs and learning styles. Additionally, self-initiated continued training opportunities were perceived to improve one's use of EHR.
  • Informal support from colleagues. In addition to formal support and training, many physicians said they were better able to use EHR from talking to and observing colleagues using EHR. Physicians borrowed tips and strategies from colleagues and also asked colleagues for specific help (e.g., troubleshooting; writing orders; discharging patients).
Table 3
Identified facilitators and barriers related to support from others and example passages.

Comments about receiving support from others shared a theme: that physicians benefited most from support that was hands-on, in-person, and provided in practice rather than from formal classroom training. Similarly, some physicians preferred learning on one's own with an expert or colleague on hand to assist. Comments from a family physician at Hospital 2 illustrate this assisted-experiential-learning theme:

“Well, it, I think we need to see somebody who's using it. You know, using it live with a patient and walking through it and see how they do it. It would be great to have training staff there. You could even get more information or examples, but to sit in a separate room and to try to go through examples is good in the initial training, but I think once we've been on it, we need to see how people do it … in real life. And that's why I think working with a doc who's good at it would be a good way to do it.”

Organizational support

Two categories of facilitators/barriers were related to organizational factors such as management and compensation (Table 4).

  • Time allowance. Having extra time and a light patient load were perceived facilitators of use, whereas taking extra time to use EHR and not being compensated for taking a lighter load were perceived barriers. Physicians reported that they needed but did not always have time to use the system fully, to participate in further training, or to learn new features (“I don't have time to kind of be digging around and playing with things to figure that stuff out”).
  • Inter-institutional integration. Physicians could not use patient data from EHRs to which they had no access, having to instead rely on printed documents. Physicians with care responsibilities across disparate health systems still needed separate log-ins for each system's EHR and commented that having a single, universal log-on would facilitate EHR use. At Hospital 2 inpatient and outpatient EHRs were integrated; at Hospital 1 physicians identified having to log in separately to inpatient and outpatient EHR systems as a barrier to “seamless access.
Table 4
Identified facilitators and barriers related to organizational support and example passages.

Environmental factors

Four categories of facilitators/barriers were related to the physical or social work environment (Table 5).

  • Physical space. Barriers included cluttered workspaces, insufficient space for a paper chart when using EHR, not enough private rooms for computer use, computer stations ill-suited to tall users, and physicians not being physically located at a computer station (e.g., when commuting).
  • Electricity. Power outages, although very infrequent, did occur and were a barrier to EHR use.
  • Wireless connectivity. A broadband connection and wireless connectivity facilitated use but these were not always available (e.g., at nursing home; in some outpatient clinics that a specialist might visit).
  • Social environment. One physician described difficulty using EHR when a patient or family member could see others' private information on the screen. Another physician noted the need for privacy when using EHR but a lack of dedicated computer rooms. A third described discomfort typing and talking to the patient at the same time.

General control-related

Control-related facilitators/barriers were those that left physicians no other choice but to use (or not use) EHR in some way. By mandating the general use of EHR and removing alternative options (“they don't keep paper backup copies”), physicians' hospitals and clinics “facilitated” EHR use. In contrast, the unavailability of specific features (e.g., clinical notes and order entry at Hospital 1) was a barrier to using EHR for certain tasks.


The mere presence of EHR does not guarantee successful use of the system or of its specific functions.[11, 4547] EHR use requires the presence of certain user and system attributes, support from others, and numerous organizational and environment facilitators. Additionally, difficulty using EHR and the non-use of specific functions result from the presence of barriers. The present study identified and described 19 categories of facilitators and barriers based on the perceptions of attending physicians using EHR systems.

Other studies have formally identified similar facilitators and barriers to use of health information technology (IT). Linder et al's[48] survey of 225 primary care clinicians revealed barriers to EHR use during patient visits, including user attributes (typing speed), systems attributes (computer slowness; usability), organizational factors (falling behind schedule), and social factors (loss of eye contact; rudeness to patient). Saleem et al's[49] ethnographic study of 90 primary care clinicians using computerized clinical reminders at four Veterans Administration (VA) medical centers identified five barriers (provider coordination; not using system in patient's presence; workload and workarounds; system flexibility; usability and slowness) and four facilitators (number of reminders; computer workstation location; workflow integration; reporting/remediation of system problems). Patterson's outpatient VA studies also reported training, knowledge of the system, and computer availability as additional barriers to the use of computerized clinical reminders.[50, 51] Finally, several of the barriers identified here, such as usability problems and system slowness, appear in work that describes the unintended consequences of EHR.[5258]

In general, the findings from this study accord with previous findings, despite the more specific definition of facilitators/barriers (centering on ability) used here. However, compared with observational studies, interviews with physicians uncovered more user-centered facilitators/barriers (learning; usability; training) and fewer externally observable ones (clinician-clinician or clinician-patient interaction; workflow). The exploratory and “naturalistic” rather than laboratory nature of the present study permitted the discovery of more facilitators and barriers than previously reported, spanning levels of analysis from “the larger organization down through … the computer interface level.”[49]

Several study limitations must be noted. The study's small, non-random sample of only attending physicians limits the generalizability of the findings. The restricted sample may also have limited the breadth of facilitators and barriers that could be identified. Thus, it will be important to extend this study's methods to other organizations, professional groups besides physicians, and other technologies in order to broaden the knowledge base on facilitators and barriers to health IT use. The use of interviews permitted this study to capture perceptions, both a limitation and strength. Although perceptions are sometimes inaccurate interpretations of reality, they are key determinants of IT acceptance and use behavior and shed light on how individuals respond differently to the same IT.[59] Although user-reported barriers are subjective, they cannot be dismissed as simply complaints. Participants were able to clearly describe how barriers operationally affected EHR use, for example, how poor typing proficiency limited the volume and content of clinical documentation or how slow computers in patients' rooms rendered those computers nonfunctional, forcing physicians to document information outside the room and not in the presence of the patient. Nevertheless, the effects of reported perceptions on behavior and performance remain to be objectively assessed. Only a single method, interviews, was used. This limited the scope of data and precluded an analysis of the strength of reported facilitators and barriers. Future studies should simultaneously “bootstrap” multiple methods to permit triangulation.[51] Finally, this study focused on facilitators and barriers, but other factors surely influence EHR use, including additional barriers not identified here,[51] the perceived effect of EHR on performance,[18] social and personal normative influence,[60] and other cognitive and implementation factors.[13, 14, 20, 40, 61, 62]


In conclusion, this study identified and described facilitators and barriers to using EHR. Research interviews permitted both a good breadth of facilitators/barriers and often in-depth descriptions of each. Such level of detail both supports the theoretical understanding of each facilitator/barrier and helps inform design, policy, and organizational decision making. Indeed, by considering the factors identified in this study and accordingly designing the sociotechnical microsystem, it should be possible to improve the ability of clinicians to easily and effectively use EHR. That, in turn, will increase the probability of quality and safety improvements through EHR.

Supplementary Material


The author thanks study participants and Geoffrey Priest, Christine Baker, and Bradley Schmidt. Anonymous reviewers provided helpful feedback. This research was completed as part of a doctoral dissertation under the supervision of Ben-Tzion Karsh. RJH was supported by a pre-doctoral training grant from the National Institutes of Health (1 TL1 RR025013-01) and a post-doctoral training grant from the Agency for Healthcare Research and Quality (5 T32 HS000083-11).

SUPPORT: RJH was supported by a pre-doctoral training grant from the National Institutes of Health (1 TL1 RR025013-01) and a post-doctoral training grant from the Agency for Healthcare Research and Quality (5 T32 HS000083-11).


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1. Institute of Medicine . Crossing the Quality Chasm: A New Health System for the 21st Century. National Academies Press; Washington, DC: 2001. [PubMed]
2. Henriksen K, Battles JB, Keyes MA, et al., editors. Advances in Patient Safety: New Directions and Alternative Approaches. AHRQ Publication No. 08-0034. Agency for Healthcare Research and Quality; Rockville, MD: 2008.
3. Blumenthal D, et al. Health Information Technology in the United States: The Information Base for Progress. Robert Wood Johnson Foundation; Washington, DC: 2006.
4. Øvretveit J, Scott T, Rundall TG, et al. Improving quality through effective implementation of information technology in healthcare. Int J Qual Health Care. 2007;19:259–66. [PubMed]
5. Linder JA, Ma J, Bates DW, et al. Electronic health record use and the quality of ambulatory care in the United States. Arch Intern Med. 2007;167:1400–5. [PubMed]
6. Chaudhry B, Wu S, Maglione M, et al. Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144:E12–E22. [PubMed]
7. Garrido T, Jamieson L, Zhou Y, et al. Effect of electronic health records in ambulatory care: Retrospective, serial, cross sectional study. BMJ. 2005;330:581. [PMC free article] [PubMed]
8. Shekelle PG, Morton SC, Keeler EB. Evidence Report/Technology Assessment No. 132. Agency for Healthcare Research and Quality; Rockville, MD: 2006. Costs and Benefits of Health Information Technology. [PubMed]
9. Zhou L, Soran CS, Jenter CA, et al. The relationship between electronic health record use and quality of care over time. J Am Med Inform Assoc. 2009;16:457–64. [PMC free article] [PubMed]
10. Parente ST, McCullough JS. Health information technology and patient safety: Evidence from panel data. Health Aff. 2009;2:357–60. [PubMed]
11. Simon SR, Soran CS, Kaushal R, et al. Physicians' use of key functions in electronic health records from 2005 to 2007: A statewide survey. J Am Med Inform Assoc. 2009;16:465–70. [PMC free article] [PubMed]
12. Poon EG, Wright A, Simon SR, et al. Relationship between use of electronic health record features and health care quality: Results of a statewide survey. Med Care. 2010;48:203–9. [PubMed]
13. Holden RJ, Karsh B. The Technology Acceptance Model: Its past and its future in health care. J Biomed Inform. 2010;43:159–72. [PMC free article] [PubMed]
14. Karsh B. Beyond usability for patient safety: designing effective technology implementation systems. Qual Saf Health Care. 2004;13:388–94. [PMC free article] [PubMed]
15. Armijo D, McDonnell C, Werner K. Electronic Health Record Usability: Interface Design Considerations. Agency for Healthcare Research and Quality; Rockville, MD: Oct, 2009. Report No.: 09(10)-0091-2-EF.
16. Stead WW, Lin HS, editors. Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions. National Academies Press; Washington, D.C.: 2009. [PubMed]
17. Karsh B. Clinical practice improvement and redesign: How change in workflow can be supported by clinical decision support. Agency for Healthcare Research and Quality; Rockville, MD: Jun, 2009. AHRQ Publication No. 09-0054-EF.
18. Holden RJ. Cognitive performance-altering effects of electronic medical records: An application of the human factors paradigm for patient safety. Cognition, Technology & Work. 2011;13:11–29. [PMC free article] [PubMed]
19. Ammenwerth E, Iller C, Mahler C. IT-adoption and the interaction of task, technology and individuals: A fit framework and a case study. BMC Med Inform Decis Mak. 2006:6. [PMC free article] [PubMed]
20. Holden RJ, Karsh B. A theoretical model of health information technology usage behaviour with implications for patient safety. Behav Inf Technol. 2009;28:21–38.
21. DesRoches CM, Campbell EG, Rao SR, et al. Electronic health records in ambulatory care: A national survey of physicians. N Engl J Med. 2008;359:50–60. [PubMed]
22. Furukawa MF, Raghu TS, Spaulding TJ, et al. Adoption of health information technology for medication safety in U.S. hospitals, 2006. Health Aff. 2008;27:865–75. [PubMed]
23. Ash JS, Bates DW. Factors and forces affecting EHR system adoption: Report of a 2004 ACMI discussion. J Am Med Inform Assoc. 2005;12:8–12. [PMC free article] [PubMed]
24. Poon EG, Blumenthal D, Jaggi T, et al. Overcoming barriers to adopting and implementing computerized physician order entry systems in U.S. hospitals. Health Aff. 2004;23:184–90. [PubMed]
25. Jha AK, DesRoches CM, Campbell EG, et al. Use of electronic health records in U.S. hospitals. N Engl J Med. 2009;360:1628–38. [PubMed]
26. Blumenthal D, Tavenner M. The “Meaningful Use” Regulation for Electronic Health Records. [(accessed 4 Aug 2010)];N Engl J Med. 2010 [PubMed]
27. Hogan SO, Kissam SM. Measuring meaningful use. Health Aff. 2010;29:601–6. [PubMed]
28. DeLone WH, McLean ER. The DeLone and McLean model of information systems success: A ten-year update. J MIS. 2003;19(4):9–30.
29. Leonard-Barton D. Implementation characteristics of organizational innovations. Communic Res. 1988;15:603–31.
30. Frambach RT, Schillewaert N. Organizational innovation adoption: A multi-level framework of determinants and opportunities for future research. J Bus Res. 2002;55:163–76.
31. Venkatesh V, Morris MG, Davis GB, et al. User acceptance of information technology: Toward a unified view. MIS Quart. 2003;27:425–78.
32. Taylor S, Todd P. Assessing IT usage: A test of competing models. Information Systems Research. 1995;6:144–76.
33. Carayon P, Schoofs Hundt A, Karsh B, et al. Work system design for patient safety: the SEIPS model. Qual Saf Health Care. 2006;15:i50–i8. [PMC free article] [PubMed]
34. Karsh B, Holden RJ, Alper SJ, et al. A human factors engineering paradigm for patient safety – designing to support the performance of the health care professional. Qual Saf Health Care. 2006;15:i59–i65. [PMC free article] [PubMed]
35. Mathieson K, Peacock E, Chin WW. Extending the technology acceptance model: The influence of perceived user resources. DATA BASE for Advances in Information Systems. 2001;32:86–112.
36. Ajzen I, Fishbein M. Understanding Attitudes and Predicting Social Behavior. Prentice-Hall; Englewood Cliffs, NJ: 1980.
37. Ajzen I. The Theory of Planned Behavior. Organ Behav Hum Decis Process. 1991;50:179–211.
38. Ajzen I. [(accessed 27 May 2005)];Constructing a TPB Questionnaire: Conceptual and Methodological Considerations. 2002
39. Francis JJ, Eccles MP, Johnston M, et al. Constructing questionnaires based on the Theory of Planned Behaviour: A manual for health services researchers. Centre for Health Services Research, University of Newcastle; Newcastle upon Tyne, UK: 2004.
40. Holden RJ. Physicians' beliefs about using EMR and CPOE: In pursuit of a contextualized understanding of health IT use behavior. Int J Med Inform. 2010;79:71–80. [PMC free article] [PubMed]
41. Dibonaventura MD, Chapman GB. Moderators of the intention-behavior relationship in influenza vaccinations: Intention stability and unforeseen barriers. Psychol Health. 2005;20:761–74.
42. Ajzen I. Perceived behavioral control, self-efficacy, locus of control, and the Theory of Planned Behavior. J Appl Soc Psychol. 2002;32:665–83.
43. Bandura A. Self-efficacy: Toward a unifying theory of behavioral change. Psychol Rev. 1977;84:191–215. [PubMed]
44. Becker MH. The health belief model and personal health behavior. Health Educ Monogr. 1974;2:324–508.
45. Simon SR, Kaushal R, Cleary PD, et al. Physicians and electronic health records: A statewide survey. Arch Intern Med. 2007;167:507–12. [PubMed]
46. Lærum H, Karlsen TH, Faxvaag A. Use of and attitudes to a hospital information system by medical secretaries, nurses and physicians deprived of the paper-based medical record: A case report. [(accessed 4 Aug 2010)];BMC Med Inform Decis Mak. 2004 4(18) [PMC free article] [PubMed]
47. Lærum H, Ellingsen G, Faxvaag A. Doctors' use of electronic medical records systems in hospitals: Cross sectional survey. Br Med J. 2001;323:1344–8. [PMC free article] [PubMed]
48. Linder JA, Schnipper JL, Tsurikova R, et al. Barriers to electronic health record use during patient visits. Proceedings of the American Medical Informatics Association Symposium. 2006:499–503. [PMC free article] [PubMed]
49. Saleem JJ, Patterson ES, Militello L, et al. Exploring barriers and facilitators to the use of computerized clinical reminders. J Am Med Inform Assoc. 2005;12:438–47. [PMC free article] [PubMed]
50. Patterson ES, Nguyen AD, Halloran JP, et al. Human factors barriers to the effective use of ten HIV clinical reminders. J Am Med Inform Assoc. 2004;11:50–9. [PMC free article] [PubMed]
51. Patterson ES, Doebbeling BN, Fung CH, et al. Identifying barriers to the effective use of clinical reminders: Bootstrapping multiple methods. J Biomed Inform. 2005;38:189–99. [PubMed]
52. Nebeker JR, Hoffman JM, Weir CR, et al. High rates of adverse drug events in a highly computerized hospital. Arch Intern Med. 2005;165:1111–6. [PubMed]
53. Campbell EM, Sittig DF, Ash JS, et al. Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2006;13:547–56. [PMC free article] [PubMed]
54. Harrison MI, Koppel R, Bar-Lev S. Unintended consequences of information technologies in health care--An interactive sociotechnical analysis. J Am Med Inform Assoc. 2007;14:542–9. [PMC free article] [PubMed]
55. Han YY, Carcillo JA, Venkataraman ST, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics. 2005;116:1506–12. [PubMed]
56. Koppel R, Metlay JP, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA. 2005;293:1197–203. [PubMed]
57. Aarts J, Doorewaard H, Berg M. Understanding implementation: The case of a computerized physician order entry system in a large Dutch university medical center. J Am Med Inform Assoc. 2004;11:207–16. [PMC free article] [PubMed]
58. Beuscart-Zephir MC, Pelayo S, Anceaux F, et al. Impact of CPOE on doctor-nurse cooperation for the medication ordering and administration process. Int J Med Inform. 2005;74:629–41. [PubMed]
59. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart. 1989;13:319–39.
60. Holden RJ. Social and personal normative influences on healthcare professionals to use information technology: Towards a more robust social ergonomics. Theor Issues Ergon Sci. 2011 in press:doi:10.1080/1463922X.2010.549249. [PMC free article] [PubMed]
61. Rosenbloom ST, Crow AN, Blackford JU, et al. Cognitive factors influencing perceptions of clinical documentation tools. J Biomed Inform. 2007;40:106–13. [PubMed]
62. Karsh B, Holden RJ. New technology implementation in health care. In: Carayon P, editor. Handbook of Human Factors and Ergonomics in Patient Safety. Lawrence Erlbaum; Mahwah, NJ: 2007. pp. 393–410.