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Self-Assessment of Nursing Informatics Competencies for Pre-licensure Nursing Students.

Information technology (IT) has infiltrated all aspects of health care, especially nursing. Nurses utilize IT to assist with daily job functions such as medication administration, charting, information resources, reporting and measuring outcomes from databases, and clinical decision making. Blending nursing practice with IT has become known as nursing informatics, defined as "the specialty that integrates nursing science with multiple information management and analytical sciences to identify, define, manage, and communicate data, information, knowledge, and wisdom in nursing practice" (American Nurses Association, 2015). The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 provided incentives to incorporate health care technology into health care facilities, promoted the use of electronic health records (EHRs), and enabled the electronic exchange and use of health information among providers and health care facilities. Thus, informatics has become an everyday reality mandating that nurses have the opportunity for exposure and knowledge to effectively function as an interdisciplinary health care team member to deliver high quality, safe care. In order to prepare nurse graduates for competence in electronic health care delivery, it is crucial that schools of nursing integrate informatics into the curriculum. In fact, influential organizational bodies such as the American Association of Colleges of Nursing (AACN, 2011), National League for Nursing (NLN, 2008), Quality and Safety Education for Nurses (QSEN, 2007), and the Institute of Medicine (IOM, 2010) have placed an emphasis on incorporating health care informatics in nursing education. Although numerous studies assess nursing informatics competencies across all levels of nursing education (Choi, 2012; Choi & DeMartinis, 2013; Choi & Zucker, 2013; Staggers, Gassert, & Curran, 2001, 2002), none assess the effect of an informatics course on nursing informatics competencies among pre-licensure nursing students (Table 1).

Therefore, the purpose of this article is to: (a) provide a general background related to technology, health care, and nursing education, (b) describe implementation and results of an informatics course in a pre-licensure nursing program, and (c) discuss suggestions for future research regarding informatics and nursing education.

Background and Significance

The useful integration of technology and health care has become a focused area of improvement in nursing curricula at all levels. Over the past five to 10 years, there has been an increased emphasis on informatics education due to the demand for technological proficiency in the clinical setting. With the passage of the HITECH Act (2009), monetary incentives were offered to health care providers who comply with the adoption and meaningful use of EHRs, and it broadened the privacy protection of health information. The meaningful use of EHRs has changed the landscape of the clinical setting in all areas of nursing, and its usage has risen from 9.4% to 83.8% from 2008 to 2015 (Henry, Pylypchuk, Searcy, & Patel, 2016). This increased usage of a new media and the heightened level of security of patient health information necessitates a more educated workforce in dealing with informatics. Practicing clinicians will encounter EHRs on a daily basis and will be responsible for the electronic use and transmission of patient information across the medium. Although informatics implementation and usage has skyrocketed, barriers exist to fully integrate meaningful use as intended by the HITECH Act. For example, Jones and Donelle (2011) identified barriers to implementation that included a lack of working knowledge with the new technology and its interruption of normal workflow. While the demands of nursing informatics continue to evolve, education must be tailored to match the needs of the workforce to prepare graduates to implement informatics in their practice.

Research has demonstrated that students at all levels of nursing education are not adequately prepared in nursing informatics competencies. Informatics competencies in the area of applied computer skills and clinical informatics roles are the weakest among both graduate and undergraduate nursing students (Choi & De Martinis, 2013; Choi & Zucker, 2013). In a comparison among three different tracks in an undergraduate program (pre-licensure, RN-BSN, and accelerated BSN), RN-BSN students scored significantly higher in overall informatics competencies than pre-licensure students, which may be a result of clinical nursing experience and the online delivery format of the RN-BSN program track (Choi, 2012). Regardless of program track, all students lacked competence in applied computer skills and clinical informatics role.

Effective integration of informatics competencies into nursing curricula is an ideal solution but one that remains elusive for most nursing programs. Dixon and Newlon (2010) examined how future nurse educators, doctor of philosophy nursing students, perceive informatics and its core elements, and how these future educators might integrate informatics into undergraduate nursing curriculum. Results demonstrated that these doctoral students do not fully understand what informatics is nor competencies needed in an undergraduate program to prepare future nurses. Computer literacy (basic computer skills) and information literacy (using the library) were the only competencies identified by the students as important in an undergraduate curriculum. None of the participants recognized informatics literacy (system selection) as an important competency for undergraduate nursing students.

Similarly, Jette, Tribble, Gagnon, and Mathieu (2010) discovered nursing students in Canada self-reported high competencies with basic computer skills yet lacked knowledge in informatics literacy; specifically, system selection as it relates to evidence-based practice, health care, and security of patient electronic data. Thus, nursing education across all levels must place a greater emphasis on informatics literacy to educate and prepare the nursing workforce to meet the demands of health care.


Utilizing a descriptive study design, pre-licensure nursing students enrolled in the second semester of a four-semester program at a state university in Florida, USA, were surveyed during the spring 2015 term. After the university's institutional review board approval, students were surveyed on the first and final day of class for the Health Care Informatics course.

The Self-Assessment of Nursing Informatics Competencies Scale (SANICS) was used to assess informatics competencies (Yoon, Yen, & Bakken, 2009). The 30-item survey was developed using a set of informatics competency statements for novice and expert nurses, evidence-based practice, wireless technologies, and related standardized terms (Staggers, et al., 2001, 2002). Five factors were extracted using an exploratory principal component analysis with oblique promax rotation that explained 63.7% of the variance: clinical informatics role ([alpha] = .91), basic computer knowledge and skills ([alpha] = .94), applied computer skills: clinical informatics ([alpha] = .89), nursing informatics attitudes ([alpha] = .94), and wireless device skills ([alpha] = .90) (Yoon et al., 2009). Each item of SANICS is rated on a 5-point Likert scale (1 = not competent and 5 = expert) with scores ranging from 30 to 150. Psychometric properties demonstrate high internal consistency reliabilities (Choi, 2012; Yoon et al., 2009).

Students were asked to voluntarily participate in the survey at the beginning of the second semester of the pre-licensure program. Informed consent was obtained, and demographic data collected with information de-identified. Students were also informed that participation and study results were collected for curriculum and evaluation purposes and that responses to the survey would have no effect on their course grade or program progression. Students were enrolled in the Health Care Informatics course that was delivered over the traditional 16-week semester. The course was delivered hybrid with face-to-face classroom times and online asynchronous times at a ratio of 1:3 each month of the semester. The SANICS was provided to the students on the first and final day of class in a hard-copy format.

Data Analysis

Data were analyzed using SPSS, Version 22 (Chicago, IL) and summarized using descriptive statistics (means and standard deviations). Differences in informatics competencies before and after the Health Care Informatics course were analyzed using paired samples t-tests.


The sample population consists of 53 second-semester junior nursing students. Table 2 describes the characteristics of participants and computer usage. One student did not complete the demographic survey. The mean age range of participants was 18-24 years (69.2%) and most students were female (84.6%). The majority of the students reported ethnicity/race as white/non-Hispanic (75%), followed by black/non-Hispanic (9.6%), biracial (5.8%), Asian/Pacific Islander (3.8%), and Hispanic/Latino (3.8%).

Informatics Competencies

Competency scores before and after the Health Care Informatics Course are summarized in Table 3. SANICS reports competence as a minimum score of 3. The initial mean competency score for students was 3.20 (SD = .84) demonstrating that students reported minimal competence in informatics. When assessing the initial subscales, the students reported competency in only two of five subscales: basic computer knowledge (M = 3.39, SD = .78) and wireless device skills (M = 3.78, SD = .12). After the semester-long informatics course, students' informatics competency scores increased and were statistically significant (M = 3.74, SD = .09, p < .001). Subscale scores demonstrated that students were competent in four of the five scales: basic computer knowledge (M = 3.83, SD = .45), applied computer skills (M = 3.15, SD = .35), clinical informatics attitudes (M = 3.30, SD = .62), and wireless devices (M = 4.07, SD = .05).


The study findings indicate that students are most competent in wireless devices and basic computer knowledge and skills prior to an informatics course. Operations such as internet use, multimedia presentations, cell phone use to locate and download resources for patient safety, quality care, and data entry were processes that students believed to be competent in performing. These findings are somewhat similar to those by Choi and De Martinis (2013), who reported that undergraduate and graduate students were competent in basic computer knowledge and skills but not in wireless device skills. One explanation for this study reporting competence in wireless device skills prior to an informatics course may be that these students are millennials who are familiar with wireless devices such as smart-phones and tablets. Interestingly, Choi (2012) reported that students in three undergraduate program tracks (pre-licensure, RN-BSN, and accelerated BSN) were competent in basic computer knowledge and skills and wireless device skills with the exception of pre-licensure students, who did not report competency in wireless device skills.

After the informatics course, the students reported competency in four of the five subscales: basic computer knowledge and skills, applied computer skills, clinical informatics attitude, and wireless device skills. Students perceived that they lacked competence in clinical informatics role even after the course. They were not confident in participating in the selection process, design, implementation, and evaluation of systems, marketing themselves, a system or application to others, promoting the integrity of and access to information. Examples of activities for skills mentioned include limited confidentiality, legal, ethical, and security issues, seeking resources to formulate ethical decision making in computing, and acting as an advocate of leaders for incorporating innovations and informatics concepts into practice. Although the students' scores in clinical informatics roles did improve, the findings were not significant and may be due to limited exposure to clinical nursing practice. Even so, it remains concerning since students completed the informatics course.


Non-response bias is an inherent limitation of the study due to participants volunteering. Additionally, competencies were reported via self-report, not actual assessment of informatics knowledge or skills. These findings may also indicate inflated competency scores due to over-reporting of desirable informatics attributes. Finally, the generalizability of the findings may be limited due to limited number of participants at one state institution.


In order to adequately prepare students to provide safe and efficient evidence-based quality care, they must be exposed to informatics during their nursing program. Accrediting bodies, professional organizations, QSEN, IOM, and research (Hebda & Calderone 2010) report that an informatics baseline must be established to implement informatics into nursing curricula and prepare students for the workforce. This study demonstrates that students' informatics competencies improved in all subscales after an informatics course. However, students remain incompetent in clinical informatics roles. Nurse educators designing an informatics course may want to focus on the selection process, design, implementation, and evaluation of systems; marketing self, a system, or application to others; promoting the integrity of and access to information such as limited confidentiality; legal, ethical, and security issues; seeking resources to formulate ethical decision making in computing, and acting as an advocate of leaders. This will lead to innovations and incorporation of informatics concepts into practice, thereby preparing students to meet the demands of the health care environment. Future research should include similar studies with more participants in both undergraduate and graduate students since many programs are incorporating informatics courses into the curricula, as well as follow-up studies that assess new graduates' informatics workforce preparation.

While this study yields promising results of an informatics course improving informatics competencies, nurse educators must collaborate with other nurse educators (Flood, Gasiewicz, & Delpier, 2010) and continue to attend faculty development workshops and training related to informatics in order to prepare our future workforce. Nurse educators must also design curricula and assignments that are meaningful in achieving learning outcomes that improve informatics competencies. One approach may be collaboration with institutional librarians who are familiar with databases, searches, and information retrieval. Finally, nursing informatics cannot remain in one course to prepare students and improve competencies. Students need exposure in clinical and didactic courses such as professional roles to meet the demands of the ever-evolving health care environment and technology.


American Association of Colleges of Nursing, (2011). The Essentials of Baccalaureate Education for Professional Nursing Practice. Retrieved from

Choi, J. (2012). Comparative assessment of informatics competencies in three undergraduate programs. Online Journal of Nursing Informatics (ONJI), 16(2), 1700-1707.

Choi, J., & De Martinis, J. (2013). Nursing informatics competencies: Assessment of undergraduate and graduate nursing students. Journal of Clinical Nursing, 22, 1970-1976.

Choi, J., & Zucker, D. (2013). Self-assessment of nursing informatics competencies for Doctor of Nursing Practice students. Journal of Professional Nursing, 29(6), 381-387.

Cronenwett, L., Sherwood, G., Barnsteiner, J., Disch, J., Johnson, J., Mitchell, P., Sullivan, D., & Warren, J. (2007). Quality and safety education for nurses. Nursing Outlook, 55(3), 122-131.

Dixon, B., & Newlon, C. (2010). How do future nursing educators perceive informatics? Advancing the nursing informatics agenda through dialogue. Journal of Professional Nursing, 26(2), 82-89.

Flood, L., Gasiewicz, N., & Delpier, T. (2010). Integrating information literacy across a BSN curriculum. The Journal of Nursing Education, 49, 101-104.

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Hebda, T., & Calderone, T. (2010). What nurse educators need to know about the TIGER initiative. Nurse Educator, 35, 56-60.

Henry, J., Pylypchuk, Y., Searcy, T., & Patel, V. (2016). Adoption of electronic health record systems among U.S. non-federal acute care hospitals: 2008-2015 (ONC Data Brief, 35). Washington, DC: U.S. Government, Office of the National Coordinator for Health Information Technology.

Institute of Medicine. (2010). The future of nursing: Leading change, advancing health. Washington, DC: The National Academies Press.

Jones, S., & Donnelle, L. (2011). Assessment of electronic health record usability with undergraduate nursing students. International Journal of Nursing Education Scholarship, 8(1), doi: 10.2202/1548-923X.2123

National League of Nursing Board of Governors. (2008). Preparing the next generation of nurses to practice in a technology-rich environment: An informatics agenda. Retrieved from

Staggers, N., Gassert, C.A., & Curran, C. (2001). Informatics competencies for nurses at four levels of practice. Journal of Nursing Education, 40, 303-316.

Staggers, N., Gassert, C.A., & Curran, C. (2002). A Delphi study to determine informatics competencies for nurses at four levels of practice. Nursing Research, 51, 383-390.

Yoon, S., Yen, P., & Bakken, S. (2010). Psychometric properties of the self-assessment of nursing informatics competencies scale. Student Health Technology Information, 146, 546-550.

Brandy Strahan, PhD, RN, is the Undergraduate Program Director for the University of West Florida School of Nursing and Assistant Professor. She may be contacted at
Table 1.
Nursing Informatics Competencies

Competency Scale           Number of Items  Cronbach's [alpha]

Basic computer
knowledge and skills       15               0.94
Applied computer skills     4               0.90
Clinical informatics role   4               0.89
Clinical informatics        4               0.90
Wireless device skills      2               0.87

Table 2.
Participant Characteristics

Variable                      Students n (%)

  Female                      44 (84.6)
  Male                         8 (15.4)
                              52 (100)
  Asian/Pacific Islander       2 (3.8)
  Biracial  3 (5.8)
  Black/Non-Hispanic           5 (9.6)
  Hispanic/Latino              2 (3.8)
  Native American              1 (1.9)
  White, Non-Hispanic         39 (75)
                              52 (100)
Age Range (years)
  18-24                       36 (69.2)
  25-29                        6 (11.5)
  30-39                        8 (15.4)
  40-49                        2 (3.8)
                              52 (100)
Computer Usage
  Several times/day           49 (94.2)
  Once/day                     1 (1.9)
  Several times/week           2 (3.8)
                              52 (100)

Table 3.
Summary of Competency Scores

Competency scale                      Means        Paired
                                      (SD)         t-tests
                                      Pre          Post          t

Total (30 items,                      3.20         3.74         -6.84
Cronbach's [alpha] = 0.94)           (0.84)       (0.47)
Clinical informatics role             2.28 (.40)   3.31 (.31)  -15.75
(5 items, Cronbach's [alpha] = .91)
Basic computer knowledge
and skills (15 items,                 3.39 (.78)   3.83 (.45)   -5.52
Cronbach's [alpha] = 0.94)
Applied computer skills               2.15 (.63)   3.15 (.18)   -6.51
(4 items, Cronbach's [alpha] = .89)
Clinical informatics attitudes        2.27 (.88)   3.30 (.62)   -7.78
(4 items, Cronbach's [alpha] = .94)
Wireless device skills                3.78 (.12)   4.07 (.05)   -5.97
(2 items, Cronbach's [alpha] = .90)

Competency scale


Total (30 items,                      <.001 (*)
Cronbach's [alpha] = 0.94)           (
Clinical informatics role             <.001 (*)
(5 items, Cronbach's [alpha] = .91)
Basic computer knowledge
and skills (15 items,                 <.001 (*)
Cronbach's [alpha] = 0.94)
Applied computer skills                .007 (*)
(4 items, Cronbach's [alpha] = .89)
Clinical informatics attitudes         .004 (*)
(4 items, Cronbach's [alpha] = .94)
Wireless device skills                 .106
(2 items, Cronbach's [alpha] = .90)

(*)Statistically significant
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Author:Strahan, Brandy
Publication:Journal of Informatics Nursing
Date:Sep 22, 2017
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