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Nurses’ Attitudes Toward Meaningful Use Technologies: An Integrative Review

Kaye, Scott P. MS, RN-BC, CEN, CPEN, CCRN-K, NEA-BC, FACHE

CIN: Computers, Informatics, Nursing: May 2017 - Volume 35 - Issue 5 - p 237–247
doi: 10.1097/CIN.0000000000000310
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Nurses comprise the largest segment of the healthcare workforce. As such, their perceptions of any new technology are important to understand, as it may ultimately mean the difference between acceptance and rejection of a product. The three-stage meaningful use program is intended to help improve and standardize data capture and advance clinical processes to improve patient and population outcomes in the US. With more than 471 000 healthcare providers having already received meaningful use incentive payments totaling more than $20 billion as of June 2015, it is critical to understand how these technologies are being viewed and utilized in practice. Understanding nurses’ attitudes toward healthcare technology may help drive acceptance, as well as maximize the inherent potential of the new technologies toward improving patient care. Thus, the purpose of this integrative review is to highlight what is known about nurses’ attitudes toward meaningful use technologies.

Author Affiliations: Nursing Education and Special Projects, NewYork-Presbyterian/Queens Hospital in Flushing, New York.

The author has disclosed that he has no significant relationships with, or financial interest in, any commercial companies pertaining to this article.

Corresponding author: Scott P. Kaye, MS, RN-BC, CEN, CPEN, CCRN-K, NEA-BC, FACHE, 45-45 Clearview Expressway, Bayside, NY 11361 (scottpaulkaye@hotmail.com).

Changes in technology are a constant in nursing. Every technological innovation from the creation of the disposable catheter in 1944 to the first heart transplant in 1967, through the human genome project on the 2000s,1 has had an impact on nursing care, with current advances in technology having the potential to alter completely the way nursing will be practiced in the future.2 Technology is often presented as having a positive impact on the quality and efficiency of nursing care. Information technology, for example, can enhance the nursing process by improving the collection, interpretation, management, and dissemination of important patient information, as well as automate processes to reduce nursing workload.3,4 However, studies utilizing models and tools such as the Nurses’ Attitudes Toward Computerization questionnaire, the Information Technology Attitude Scales for Health, and the Technology Acceptance Model suggest that nurses’ attitudes toward healthcare technologies may vary significantly.5–7

One of the largest nurses’ union in the US, National Nurses United, recently launched a campaign to alert the public to what it describes as the dangers of “unproven medical technologies” such as the clinical decision support (CDS) systems built into many electronic health records (EHRs).8,9 Healthcare technology has at times been implicated as dehumanizing, or the antitheses of caring.10,11 In contrast, the theory of technological competency as caring in nursing suggests that technology should be seen as a way to enhance caring in nursing, by helping to understand the patient as a whole and complete individual, not as a replacement for the human skills of caring.12,13

The rapid growth of technology in healthcare shows no signs of slowing down, as the Health Information Technology for Economic and Clinical Health (HITECH) Act, part of the 2009 American Recovery and Reinvestment Act, has budgeted more than $20 billion toward improving health information technology.5,14 Facilities or individuals are eligible for incentive payments from this budget by complying with standards that demonstrate “meaningful use.” Meaningful use covers implementation and use of electronic medical records (EMRs) and associated technologies to help improve healthcare quality, safety, and care coordination, as well as health information privacy and security across the US.15–17 The three-stage program is intended to help improve and standardize data capture and advance clinical processes to ultimately improve patient and population outcomes.18,19 With more than 471 000 healthcare providers having already received meaningful use incentive payments totaling more than $20 billion as of June 2015,20 it is critical to understand how these technologies are being viewed and utilized in practice.

Healthcare leaders should understand nurses’ attitudes toward healthcare technology in order to help drive acceptance and maximize the inherent potential of the new technologies toward improving patient care.5,7,21 In the context of mandatory usage of meaningful use technologies (which many institutions require), measures such as perception and acceptance are more important than data usage statistics.22 Therefore, the purpose of this integrative review is to highlight what is known about nurses’ attitudes toward meaningful use technologies.

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METHODS

The five-stage methodology of Whittemore and Knafl23 was used to conduct this integrative review. The five defined stages of problem identification, literature search, data evaluation, data analysis, and presentation are intended to ensure methodological rigor. This systematic process helps to minimize bias while allowing for multiple types (eg, experimental, nonexperimental, theoretical, empirical) of primary research to be independently evaluated. For purposes of clarity and exclusion criteria applicability, the review purpose was framed as the following research question: “What are nurses’ attitudes toward meaningful use technologies?”

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Problem Identification Stage

The phenomenon of nurses’ attitudes was purposely chosen to give a broad conceptual view of the problem. Attitudes refer to “a complex combination of things we tend to call personality, beliefs, values, behaviors, and motivations” and “include feelings, thoughts and actions.”24(p44) For the purpose of this review, meaningful use technologies are used to refer to EMRs, EHRs, electronic medical administration records (eMARs), barcode medication administration (BCMA), and nursing CDS. These specific technologies were chosen because they were judged by this author to have the greatest impact on nursing processes and workflows.

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Literature Search Stage

Inclusion criteria for this review were identified as primary source material, such as books, dissertations, research articles, and concept analyses, and studies involving nurses’ perceptions of technology. Sources were excluded from this review if the relevant technology was not one of the three identified meaningful use technologies, if the primary population group was not registered nurses, if the source was not primary (eg, editorials or discussion papers), if the study was not conducted in the US, and if the study did not answer the research question.

Structured searches were conducted within five electronic databases: CINAHL Complete, MEDLINE Complete, ScienceDirect, PsycINFO, and Proquest Dissertations and Theses Global. All sources published between January 2010 and July 2015 were included in the search. The selected period for studies beginning from 2010 was deliberately chosen as most likely to reflect meaningful use technologies, based on the meaningful use EHR incentive program, which allowed hospitals to receive incentive payments as early as 2011.18 Varied search terms (Table 1) were used to broaden the depth and scope of the search. Using the identified terms as well as the limiters of English language and US studies (as the meaningful use program is limited to the US), 496 articles were retrieved. The retrieved sources were first screened for inclusion criteria by title. If the source could not be excluded by title alone, the abstract (or book summary) was read. If the abstract met the inclusion criteria, the full text of the source was obtained. This approach led to 26 studies. In addition, manual searching was performed on all reference lists and of all articles from January 2010 to present of CIN: Computers, Informatics, Nursing, the American Journal of Nursing, and Nursing Management, because these journals were noted to feature relevant content. After removal of duplicate studies and application of exclusion criteria, 17 relevant studies were identified. A diagram of the decision-making process for inclusion in the integrative review is provided in Figure 1.

Table 1

Table 1

FIGURE 1

FIGURE 1

Of the studies included, seven were doctoral dissertations, and the remainder research articles. Twelve studies were quantitative research, two were qualitative research, and three were of mixed-methods design. Of the nine full text articles that were excluded, two did not have nurses as the focus of the study, one examined attitudes toward technology that was not identified as meaningful use by this review, one study was not conducted in the US, and four were excluded because they did not answer the research question. Three additional sources25–27 were later removed in the analysis stage because the studies referenced were performed several years before the meaningful use program was introduced. Thus, 14 studies are included in this review (Table 2).

Table 2

Table 2

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Data Evaluation Stage

All quantitative studies were reviewed using Bowling’s40 checklist for assessment of rigorous research criteria (Table 3). All qualitative studies were reviews using Pearson’s41 qualitative findings critical appraisal scale (Table 4). The three mixed-methods studies were reviewed using the quantitative criteria because the focus of all three studies was on the quantitative results. Each of the studies was noted to have limitations when the appropriate criteria were applied. However, with the exception of Adams,28 all the studies were judged to be adequate for inclusion. Upon further review of Adams’ study, considering that “quality criteria apply mainly to experimental designs,”40(p122) despite the low sample size (N = 13) and several methodological concerns, the study was judged of sufficient rigor to be included. Thus, none of the 14 selected studies were excluded.

Table 3

Table 3

Table 4

Table 4

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Data Analysis Stage

Data analysis for the studies was performed by summarizing the studies in a data extraction matrix (Table 3). This matrix summarized research methodology, as well as study purpose and thematic findings, in table format. A descriptive summary is presented in the following section.

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PRESENTATION/DISCUSSION

This review contained quantitative, qualitative, and mixed-methods research studies from which the following major themes were identified:

  • nurses’ attitudes toward meaningful use technology implementation
  • nurses’ attitudes toward postimplementation improvement attempts
  • nurses’ overall acceptance of meaningful use technologies
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Implementation

General resistance to change is one of the primary factors that impede EHR adoption.30,34,38 Other barriers to implementation often have less to do with functionality of the technology than with changes in nursing workflow or processes.31,39 Process changes, although potentially appearing minor in implementation plans, are often what is most important to end-users (individuals who use a product once it has been fully developed) when the product is implemented.31 Changes to workflow that affect job efficiency compromised the greatest barrier to acceptance.31,39 Having nurse involvement from the inception and planning phases may help increase both acceptance and positive perceptions of the relevant technology.22,39 Other suggested methods for improving the perceptions of meaningful use technologies during the implementation phase include simulated training sessions, peer support in the form of expert peer users, increasing organizational commitment, and a focus on clinical communication immediately after implementation.28,30,33–35,38,39

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Postimplementation Improvement

A phenomenon known as the “Valley of Doom”21(p527) is used anecdotally to refer to feelings of despair or frustration after EMR implementation. This implies that satisfaction and acceptance are likely to decline immediately after implementation and rise after system improvements have been made. Nursing input into design and improvement of technologies was cited as a significant factor in improving perceptions of usability and usefulness over time.22,31 In contrast, the one longitudinal study that showed a decrease in satisfaction 18 months after implementation indicated that nursing input was largely ignored,21 leading to negative perceptions of an EHR. Changes suggested by nursing that resulted in improved perceptions included decreased login times, reduced redundancy, and increased focus on nursing sensitive documentation.21,22,31,38 One study noted no significant difference in nurses’ attitudes toward technology based on stage of meaningful use implementation.37

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Acceptance

Perceived ease of use (usability), perceived usefulness, and performance expectancy (relevance) are important predictors of meaningful use technology acceptance.22,29,35,36 An awareness of the positive impact of the technology on patient care also had an impact on acceptance.22,33,34,39 Peer support, the encouragement and assistance of fellow nurses, was noted as having a significant positive effect on the perceived ease of use, perceived usefulness, and intention to use technologies.33,35 Nurses were more concerned with the perceptions of other nurses than of improved workflow or patient safety.35 Thus, the support of nursing peers in the form of superusers and system trainers is likely to increase meaningful use technology acceptance.

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Usability

The factor that most dominated the results when analyzing acceptance was usability. Usability, or ease of use, refers to the “efficiency and effectiveness of an application.”3(p123) Excessive login time was commonly cited as negatively affecting usability.21,22,31 Time required to complete tasks using the technology was another frequent negative perception.21,30,34,36,38 Intuitively, the easier a technology is used, the more likely an individual is to use it. This a priori knowledge was found to be true in several studies.21,22,31,34,36,38 The newer technologies of BCMA and CDS were not generally found to be as user-friendly as the EMR.29,32,38,39 Thus, variation in nurses’ acceptance was noted.

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Barcode Technologies

Barcode medication administration acceptance was manifested in the studies as a lack of workaround (deviations in the work process to bypass a block in workflow29) usage. Both the total number of workarounds and the amount of different workaround types were inversely related to satisfaction with the technology.29 Mixed results were seen when correlating the nurses’ age or years of experience with increased use of workarounds.29,39 Similar to obstacles to EMR implementation, obstacles to full BCMA acceptance tended to be more related to changes in nursing workflow and processes than with the barcode technology itself.39 As a result, increased satisfaction with the barcoding process resulted in a reduced number of workarounds.29 Nurses indicated that their satisfaction would be higher if they felt that the system were less prone to errors.29,39

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Clinical Decision Support

Either the CDS was ignored as a meaningful use technology, or the functionality was overridden by the end-users in the selected studies. Mistrust of the technology, redundancy, and lack of task relevance were implicated as the main factors for the lack of acceptance.32,38 One study indicated that nurses had less confidence in the CDS system after receiving training than prior to training.38

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Age as a Factor

A negative correlation between age and technology acceptance was seen in 5 studies.21,29,32,33,38 A sixth study showed a similar correlation, but the difference was not judged to be statistically significant.37 The positive effect of peer influence on acceptance and perceptions, however, was not limited by the age of the nurse.33,35

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Computer Anxiety

Several studies examined computer anxiety as a variable in measuring acceptance. A lack of previous computer use or computer anxiety only seemed to affect nurses during the implantation period.27,30,31,33,39 Elapsed time since implementation appears to be predictive of overall technology acceptance, regardless of computer anxiety or previous experience.22

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Relationship of Findings to Other Reviews

A recent integrative review of nurses’ acceptance of healthcare technology using the technology acceptance model as an explanatory framework7 resulted in several of the same themes as those found in this review. Despite having no sources in common, themes such as organizational commitment, high-quality training, social influence, and perceived usefulness were common to both reviews. A 2010 review of factors affecting nurses’ attitudes toward healthcare information technology found that increased computer experience is the main factor leading to positive attitudes, and usability issues are the main cause of negative attitudes.5 The aforementioned study also reached a similar conclusion to this review, that nurse involvement in the implementation phase would likely lead to increased satisfaction.5

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LIMITATIONS

There are several limitations inherent to this review. Some studies combining nurses with other healthcare professionals or exploring other aspects of meaningful use may have contained relevant information, which was not included in this review. Although every effort was made to find meaningful use–specific technologies, there was no indication in any study that the technology used was implemented specifically for the meaningful use program. Because this was a difficult variable to account for, the inclusion criterion date of 2010 and forward was important in order to make it more likely that technologies were implemented to comply with meaningful use.

A large number of dissertations (seven of 14 studies) comprised the synthesis matrix. Although these represented primary sources, a possible lack of academic rigor is possible because of the lack of a peer-review process. The included dissertations, with the exception of the 2015 Adams study, all scored favorably on Bowling’s40 critical appraisal checklist, thus limiting this concern.

Publication bias may exist with regard to the published journal articles; however, as the studies presented both positive and negative attitudes toward and acceptance of meaningful use technologies, this was judged to be of minimal concern.

Finally, the number of selected studies (14 studies) and sample sizes of some quantitative studies may not have been sufficient to represent the full scope of information available. In particular, the studies of Adams,28 Crawley,30 and Culler et al31 had sample sizes ranging from 13 to 16. It is the hope of this author that the rigor in which Bowling’s40 criteria were applied mitigates the effects of this limitation.

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SUMMARY

In general, nurses’ perceptions of meaningful use technologies in this study were positive. Negative perceptions of technology during the implementation phase tended to be more associated with changes in workflow and processes. From the perspective of education, preimplementation training was the suggested intervention to improve nursing perceptions. After implementation, a combination of improving usability, reducing redundancy, and increased familiarity with systems tended to increase positive perceptions of the implemented technologies. Acceptance was affected by several factors; however, peer support played the largest role in increasing nurses’ acceptance. From a clinical practice perspective, this seems to indicate that identification and involvement of early adopters or peer champions might increase acceptance.

The relatively newer meaningful use technologies of CDS and barcode medication technologies were not as easily accepted by nurses compared with acceptance of the EMR. This was manifested by workarounds and system overrides. Analysis suggests that as the technologies become commonplace and are used more often, and usability increases, nurses’ acceptance of these technologies will increase.

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Implications for Future Research

There is a significant gap in literature regarding the long-term follow-up of the attitudes toward the investigated technologies. Most of the longitudinal studies examined the changes in attitudes and perceptions up to 6 months after implementation.21,22,31,38 Only one study34 examined nurses’ attitudes toward a technology after a longer period (5 years). This is likely due to the relatively short duration of the meaningful use program, but nonetheless, this knowledge gap exists. Acceptance of BCMA and CDS should be re-examined as the technologies become commonplace and integrated into existing nursing workflow. Several studies utilized frameworks such as the technology acceptance model29,33 to explain or predict nurses’ attitudes toward technologies, but no study identified a theoretical framework used to guide implementation. Locsin’s12,13 theory of technological competence as caring in nursing seems ideally suited for increasing nurses’ perceptions of technology relevance and perceived usefulness.

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CONCLUSION

Nurses compose the largest segment of the healthcare workforce.21 As such, their perceptions of any new technology are important to understand because they may ultimately mean the difference between acceptance and rejection of a product. The results of this review reflect the importance of involving nurses in the planning, development, implementation, training, and continuing evaluation of meaningful use technologies. It is clear from this study that nurses’ perceptions of meaningful use technologies are most influenced by peer support and the overall effect of the technology on existing processes and workflow. Meaningful use technologies are intended to improve healthcare quality, safety, and care coordination. Proactively engaging nurses as full stakeholders in implementing and improving these technologies is the surest way to increase acceptance and positive perceptions and thus ensure improvements in patient care.

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References

1. Milestones in medical technology. New York Times. http://www.nytimes.com/interactive/2012/10/05/health/digital-doctor.html#/#time15_363. Published October 12, 2012. Accessed June 28, 2015.
2. Huston C. The impact of emerging technology on nursing care: warp speed ahead. Online J Issues Nurs. 2013;18(2): 1.
3. American Nurses Association. Nursing Informatics: Scope and Standards of Practice. 2nd ed. American Nurses Association; 2015.
4. Bolton LB, Gassert CA, Cipriano PF. Smart technology, enduring solutions. J Health Inf Manag. 2008;22(4): 24–30.
5. Huryk L. Factors influencing nurses’ attitudes towards healthcare information technology. J Nurs Manag. 2010;18(5): 606–612.
6. Lee JJ, Clarke CL. Nursing students’ attitudes towards information and communication technology: an exploratory and confirmatory factor analytic approach. J Adv Nurs. 2015;71(5): 1181–1193.
7. Strudwick G. Predicting nurses’ use of healthcare technology using the technology acceptance model. Comput Inform Nurs. 2015;33(5): 189–198.
8. Jacobson J. Health information technology: bane or boon? Am J Nurs. 2014;114(12): 18–19.
9. National Nurses United. Nurses launch new campaign to alert public to dangers of medical technology and more. http://www.nationalnursesunited.org/press/entry/nurses-launch-new-campaign-to-alert-public-to-dangers-of-medical-technology/. Published May 13, 2014. Accessed August 2, 2015.
10. Dillon TW, Blankenship R, Crews T. Nursing attitudes and images of electronic patient record systems. Comput Inform Nurs. 2005;23(3): 139–145.
11. Kossman SP, Scheidenhelm SL. Nurses’ perceptions of the impact of electronic health records on work and patient outcomes. Comput Inform Nurs CIN. 2008;26(2): 69–77.
12. Locsin RC. Technological Competency as Caring in Nursing: A Model for Practice. 1st ed. Indianapolis, IN: Sigma Theta Tau Intl; 2005.
13. Locsin RC. Technological competency as caring in nursing: maintaining humanity in a high-tech world of nursing. J Nurs Health Sci. 2013;7(1): 1–6.
14. Moreno L, Peikes DN, Krilla A. Necessary but not sufficient: the HITECH Act and health information technology’s potential to build medical homes. 2010. http://www.academyhealth.org/files/pdf/HITECH%2520White%2520Paper--jpFINAL.pdf. Accessed June 28, 2015.
15. Gardner LA, Sparnon EM. Work-arounds slow electronic health record use. Am J Nurs. 2014;114(4): 64–67.
16. HealthIT.gov. Meaningful use definition & objectives. EHR Incentives & Certification. http://www.healthit.gov/providers-professionals/meaningful-use-definition-objectives. Published February 6, 2015. Accessed July 25, 2015.
17. Smith JB. What is meaningful use? Nurse Lead. 2013;11(2): 19–21.
18. Centers for Medicare & Medicaid Services. Eligible hospital information. http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Eligible_Hospital_Information.html. Published August 27, 2014. Accessed July 28, 2015.
19. Silverman RD. EHRs, EMRs, and health information technology: to meaningful use and beyond: a symposium introduction and overview. J Leg Med. 2013;34(1): 1–6.
20. Centers for Medicare & Medicaid Services. June 2015 Payment and Registration Summary Report.; 2013: 1–5. https://www.cms.gov/Regulations-andGuidance/Legislation/EHRIncentivePrograms/Downloads/June2015_SummaryReport.pdf. Accessed October 26, 2016.
21. Laramee AS, Bosek M, Shaner-McRae H, Powers-Phaneuf T. A comparison of nurse attitudes before implementation and 6 and 18 months after implementation of an electronic health record. Comput Inform Nurs. 2012;30(10): 521–530.
22. Carayon P, Cartmill R, Blosky M, et al. ICU nurses’ acceptance of electronic health records. J Am Med Inform Assoc. 2011;18(6): 812–819.
23. Whittemore R, Knafl K. The integrative review: updated methodology. J Adv Nurs. 2005;52(5): 546–553.
24. Borkowski N. Organizational Behavior in Health Care. Sudbury, MA: Jones and Bartlett Publishers; 2005.
25. Holden R, Brown R, Scanlon M, Karsh B. Modeling nurses’ acceptance of bar coded medication administration technology at a pediatric hospital. J Am Med Inform Assoc. 2012;19(6): 1050–1058.
26. Kutney-Lee A, Kelly D. The effect of hospital electronic health record adoption on nurse-assessed quality of care and patient safety. J Nurs Adm. 2011;41(11): 466–472.
27. Smith D, Morris A, Janke J. Nursing satisfaction and attitudes with computerized software implementation: a quasi-experimental study. Comput Inform Nurs. 2011;29(4): 245–250.
28. Adams S. Nurses Knowledge, Skills, and Attitude toward Electronic Health Records (EHR) [dissertation]. Minnesota: Walden University; 2015.
29. Bennett SF. The Relationship between Barcode Medication Administration Satisfaction and the Use of Workarounds among Registered Nurses [dissertation]. Pennsylvania: Duquesne University; 2012.
30. Crawley RD. Nurses’ Perceptions of the Electronic Health Record [dissertation]. Arizona: University of Phoenix; 2013.
31. Culler SD, Jose J, Kohler S, Rask K. Nurses’ perceptions and experiences with the implementation of a medication administration system. Comput Inform Nurs. 2011;29(5): 280–288.
32. DesRoches CM, Miralles P, Buerhaus P, Hess R, Donelan K. Health information technology in the workplace: findings from a 2010 national survey of registered nurses. J Nurs Adm. 2011;41(9): 357–364.
33. Fiato KA. Enhancing Electronic Medical Records (EMR) Implementation: Peer Support Interventions Influencing Nurses’ Acceptance and Use [dissertation]. Minnesota: Capella University; 2012.
34. Harmon CS, Fogle M, Roussel LI. Then and now: nurses’ perceptions of the electronic health record. Online J Nurs Inform. 2015;19(1). http://www.himss.org/then-and-now-nurses-perceptions-electronic-health-record. Accessed November 2, 2016.
35. Holtz B, Krein S. Understanding nurse perceptions of a newly implemented electronic medical record system. J Technol Hum Serv. 2011;29(4): 247–262.
36. Jensen TA. Nurses’ Perceptions of Nursing Care Documentation in the Electronic Health Record [dissertation]. Minnesota: Capella University; 2013.
37. Styron JL. The Impact of Technology Attitudes and Skills of Rural Health Clinic Nurses on the Level of Adoption of Electronic Health Records in Mississippi [dissertation]. Mississippi: The University of Southern Mississippi; 2014.
38. Ward MM, Vartak S, Schwichtenberg T, Wakefield DS. Nurses’ perceptions of how clinical information system implementation affects workflow and patient care. Comput Inform Nurs. 2011;29(9): 502–511.
39. Williams W. Factors That Affect Bar Code Medication Administration Technology Acceptance [dissertation]. New York: Adelphi University; 2014.
40. Bowling A. Research Methods in Health: Investigating Health and Health Services. Maidenhead, England: Open University Press, McGraw-Hill Education; 2014.
41. Joanna Briggs Institute. Checklist for qualitative research. 2016. http://joannabriggs.org/assets/docs/critical-appraisal-tools/JBI_Critical_Appraisal-Checklist_for_Qualitative_Research.pdf. Accessed October 28, 2016.
42. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339: b2535. doi:10.1136/bmj.b2535.
Keywords:

Bar Code Medication Administration; Electronic Health Record; Electronic Medical Record; Technology acceptance

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