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Choi, Woo, and Tarte: Informatics Competencies of Students in a Doctor of Nursing Practice Program: A Descriptive Study



Health systems that apply artificial intelligence (AI) are transforming the roles of healthcare providers, including those of Doctor of Nursing Practice (DNP) providers. These professionals are required to utilize informatics knowledge and skills to deliver quality care, necessitating a high level of informatics competencies, which should be developed through well-structured courses. The purpose of this study is to assess the informatics competency scale scores of DNP students and to provide recommendations for enhancing the informatics curriculum.


An online informatics course was offered to students enrolled in a Bachelor of Science in Nursing to DNP program, and their informatics competency, which includes three subscales, was evaluated. Online survey data were collected from Fall 2021 to Fall 2022 using the “Self-Assessment of Informatics Competency Scale for Health Professionals.”


An analysis of 127 student responses revealed that students demonstrated competence in overall informatics competency and in one subscale: “applied computer skills (clinical informatics).” They showed proficiency in the “basic computer skills” and the “role” subscales. However, they reported lower competency in managing data and integrating standard terminology into their practice.


The findings offer detailed insights into the current informatics competencies of DNP students and can inform informatics educators on how to enhance their courses. As healthcare institutions increasingly depend on AI applications, it is imperative for informatics educators to include AI-related content in their curricula.

I. Introduction

Many healthcare institutions have implemented computerized health information systems (HISs) to support healthcare providers. These institutions require providers to be proficient and comfortable with managing these systems to ensure safe and high-quality care. For Doctor of Nursing Practice (DNP) providers, a high level of informatics competency is crucial in practice [1], as they rely on informatics knowledge to monitor patient outcomes, enhance care delivery, and achieve improved clinical results. The recent surge in artificial intelligence (AI)-integrated HISs is revolutionizing the roles of healthcare providers, including DNP providers, and is influencing patient care [2].
The American Association of Colleges of Nursing acknowledged the importance of informatics and technology in DNP education and, by 2021, had advocated for their inclusion as a fundamental aspect of professional nursing education [3]. Similarly, the National Organization of Nurse Practitioner Faculties has recommended that DNP graduates possess proficiency in informatics and technology [4]. Faculty members within DNP programs recognize the critical role of informatics competency and have consequently integrated informatics into the DNP curriculum [5,6]. To attain a high level of informatics competency, DNP students require a comprehensive and well-structured informatics course.

1. DNP and Informatics

The DNP is an advanced nursing degree designed to prepare advanced-practice registered nurses—including clinical nurse specialists, nurse practitioners, nurse midwives, and nurse anesthetists—for specialized roles in clinical practice, leadership, and research [7]. DNP-prepared providers are expected to possess a comprehensive understanding of healthcare information technology and its applications within clinical settings. They are tasked with analyzing and interpreting data to discern trends and patterns that can inform clinical decisions and improve patient outcomes. This necessitates sophisticated skills in data management, analysis, and visualization. Furthermore, DNP providers are anticipated to lead and engage in quality improvement initiatives aimed at enhancing healthcare delivery. Informatics competencies are crucial for pinpointing areas in need of improvement, implementing evidence-based interventions, and tracking progress toward established objectives. Ultimately, DNP providers must demonstrate a high level of informatics competencies to effectively leverage healthcare technology, analyze data, and elevate the quality of care they provide to their patients [3,5,6,8].
Despite the critical importance of informatics competencies for DNP providers, research exploring these competencies in depth to refine informatics courses has been limited [1,9,10]. Addressing this knowledge gap is important for improving the quality of informatics education for these professionals. This study seeks to evaluate the informatics competencies acquired by students who have completed an online graduate informatics course. It focuses on two research questions: (1) what are the students’ scores on an informatics competency scale? and (2) what recommendations can be made to improve the informatics course?

II. Methods

In 2021, an online graduate informatics course was developed for students enrolled in a Bachelor of Science in Nursing (BSN) to DNP program at a university in North Carolina, the United States and subsequently refined based on student feedback. Although the course has received generally positive feedback, some concerns remain regarding its effectiveness in providing students with the requisite informatics competencies.
After receiving an exemption (No. 18-0102) from the University’s Institutional Review Board, data were collected through an online survey instrument, the Self-Assessment of Informatics Competency Scale for Health Professionals (SICS) [11]. Statistical analysis was then conducted to evaluate the informatics competencies of the students and to offer recommendations for improving the course.

1. Study Setting

The graduate-level informatics course, “Health Care Information Systems and Technology,” is accessible through a cloud-based e-learning management system known as Canvas. This course is structured into seven modules and includes five discussion forums designed to promote collaboration and the exchange of knowledge. Additionally, it features two exams aimed at assessing students’ comprehension of the informatics content, along with three assignments that evaluate their critical thinking and analytical abilities. The topics covered in the discussion forums are as follows: (1) the data-information-knowledge-wisdom framework, (2) standardized terminologies in healthcare, (3) the role of AI in healthcare, (4) interoperability within health information systems, and (5) the knowledge and skills required for effective data management. Students are tasked with the following assignments: (1) conducting usability testing, (2) evaluating health information resources available on the internet, and (3) exploring data governance within the healthcare sector. As part of their course requirements, students are expected to anonymously submit the SICS at the conclusion of the semester. They also provided consent for the use of their survey data for research purposes.

2. Study Sample

SICS data were completed by nursing students enrolled in the online graduate informatics course of the BSN-DNP program between Fall 2021 and Fall 2022.

3. Study Instrument

The SICS is an improved version of the Self-Assessment of Nursing Informatics Competencies Scale [12] that measures the informatics competencies of healthcare professionals. It has been used in multiple nursing studies [9,13,14]. The SICS is an assessment tool comprising 18 questions on three areas of informatics proficiency: “basic computer skills,” “role,” and “applied computer skills (clinical informatics).” Each question is rated on a 5-point Likert scale, with scores ranging from 1 (representing “not competent”) to 5 (indicating “expert”). Most items on the SICS pertain to healthcare professionals in diverse fields or specialties. The SICS has a high degree of reliability, as evidenced by a Cronbach’s alpha of 0.93 [11]. In this study, Cronbach’s alpha was 0.90.

4. Data Analysis

IBM SPSS version 29 (IBM, Armonk, NY, USA) was used to perform statistical analyses. Students’ informatics competencies and characteristics were summarized using descriptive statistics (mean and standard deviation [SD]). According to the Shapiro-Wilk test, the data were not normally distributed. Thus, non-parametric statistical tests—namely, the Mann-Whitney U test and the Kruskal-Wallis H test—were used to analyze the data. A p-value less than 0.05 was considered to indicate statistical significance.

III. Results

The total number of surveys analyzed was 127 (n = 127), with a response rate of 100%. The majority of the students were female (n = 115; 90.6%), identified as White, non-Hispanic (n = 89; 70.1%), and were aged between 20 and 39 years (n = 88; 69.3%). Two-thirds of the students reported having more than 6 years of nursing experience (n = 75; 59.1%). Nearly all of the students indicated that they used a computer several times a day (n = 121; 95.3%) and had more than 2 years of experience with computers (n = 122; 96.1%). Table 1 summarizes the characteristics of the DNP students.

1. Informatics Competency

The overall mean score of the SICS was 3.79 ± 0.45, falling between competent and proficient. The mean scores for the subscales—“basic computer skills,” “role,” and “applied computer skills (clinical informatics)”—were 4.07 ± 0.46, 4.40 ± 0.62, and 3.53 ± 0.54, respectively. Table 2 presents the mean and SD scores for the items of the SICS.

2. Basic Computer Skills

The students rated their ability to demonstrate basic technology skills (4.64 ± 0.51) and their use of email (4.66 ± 0.47) as above proficient. They considered their ability to conduct online literature searches (3.94 ± 0.67) as competent, and rated their use of applications to manage aggregated data (2.98 ± 0.86) as below competent.

3. Role

Students demonstrated proficiency in two key areas within the role subscale: acknowledging the significance of human functions in nursing care that cannot be replaced by computers (4.54 ± 0.63), and recognizing the importance of clinician participation in the design, selection, implementation, and evaluation of applications and systems in healthcare (4.26 ± 0.74).

4. Applied Computer Skills (Clinical Informatics)

Among the 12 items assessed, students demonstrated proficiency in two areas: using applications to document patient care (4.28 ± 0.62), and identifying, evaluating, and utilizing electronic patient education materials that are appropriate to the patient’s language and literacy level at the point of care (4.02 ± 0.66). They had a rating of below competence in two areas: extracting data from clinical data sets (2.79 ± 0.90) and incorporating structured languages into practice (2.91 ± 1.08). For the majority of the items, students rated themselves as competent, with average scores ranging from 3.34 ± 0.89 to 3.93 ± 0.69.

5. Comparisons

We further assessed whether students’ informatics competencies differed significantly according to age, sex, race, nursing experience, and computer experience (Table 3). Individuals who self-identified as Caucasian/White had a significantly higher median score on the total SICS (U = 1245.000, p = 0.03) and the “applied computer skills (clinical informatics)” subscale (U = 1246.000, p = 0.03) than those who identified as Non-Caucasian/White. Additionally, those with more than 2 years of computer experience had a higher median score on the total SICS (U = 122.000, p = 0.02) and the “applied computer skills (clinical informatics)” subscale (U = 133.500, p = 0.03) than those with 2 years or less.

IV. Discussion

The results for the “basic computer skills” subscale indicated that the students were proficient, with a mean score of 4.07 ± 0.46. This proficiency likely stems from their frequent computer usage, as 95.3% reported using a computer several times per day, and 96.1% had more than 2 years of computer experience. These findings align with those of previous studies [15,16]. Since online literature searches are a component of their academic work, the students demonstrated high competence in this area, with a mean score of 3.94 ± 0.67. However, their competency in utilizing applications for managing aggregated data was lower, with a mean score of 2.98 ± 0.86. This indicates a need for the curriculum to include training in data management software such as Excel, as well as statistical software and databases, to enhance the students’ foundational computer skills.
Students demonstrated proficiency in recognizing their roles, with an average score of 4.40 ± 0.62. This may be attributed to the fact that approximately 60% of the students reported having over 6 years of nursing experience. In the area of “applied computer skills (clinical informatics),” students were proficient in utilizing health information systems at the point of care. This proficiency likely stemmed from the frequent use of electronic health records (EHRs) and HISs in hospital settings, as well as their responsibilities as primary care providers. However, they appear to be less adept at “extracting data from clinical data sets,” with an average score of 2.79 ± 0.90. This indicates a need for the course to incorporate training on data mining from clinical data warehouses or publicly available federal databases.
The comparative analysis showed that race and years of computer experience affected informatics competency levels. This implies that curricula should incorporate hands-on computer experience to improve informatics competencies. Examples of such experiences could include practicing charting and accessing data using simulated EHRs, role-playing on a telehealth platform with classmates, reporting learning experiences after engaging with virtual reality simulations, and conducting usability testing of mobile applications. However, the influence of race on informatics competency requires further validation through studies involving a larger and more diverse cohort of students from multiple racial backgrounds.
The study’s findings have limited generalizability due to the narrow scope of data collection. The study focused on a single program at one North Carolina University with a sample size of only 127 students. Moreover, the study’s sample consisted mainly of female students (90.6%) and White, non-Hispanic students (70.1%). Furthermore, the study’s evaluation of informatics competencies relied solely on the SICS instrument, whereas using different measures could produce different outcomes. We only assessed students’ informatics competency at the end of the course, which may not accurately reflect their true level of skill. Future studies should consider a pre- and post-assessment of informatics competencies involving a larger and more diverse group of students to enhance the robustness of the findings.
In conclusion, the course effectively imparts knowledge of nursing informatics. However, our analysis has also highlighted areas where students require further development of their informatics skills, despite the comprehensive coverage provided by the course materials. As the healthcare industry increasingly relies on AI applications for data management, integration, and decision-making, it is crucial for DNP providers to master these competencies prior to graduation [2,17,18]. Furthermore, studies advocate for the early integration of AI content into the nursing curriculum to ensure that students are well-prepared before they graduate [2,1921]. Examples of this include the use of predictive machine learning models for the early detection of falls or sepsis in inpatient settings, the application of virtual reality and augmented reality in education, and the employment of AI tools such as natural language processing or chatbots in telehealth.


Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Table 1
Characteristics of students (n = 127)
Characteristic n (%)
 Female 115 (90.6)
 Male 12 (9.4)

Age (yr)
 20–29 42 (33.1)
 30–39 46 (36.2)
 40–49 24 (18.9)
 ≥50 15 (11.8)

 Black, not Hispanic 24 (18.9)
 Hispanic/Latino 6 (4.7)
 White, not Hispanic 89 (70.1)
 Other 8 (6.3)

Nursing experience (yr)
 <2 4 (3.1)
 2–5 48 (37.8)
 6–10 33 (26.0)
 >10 42 (33.1)

Frequency of computer use
 Several times per day 121 (95.3)
 Once per day or less 4 (3.1)

Computer experience (yr)
 ≤2 5 (3.9)
 >2 122 (96.1)
Table 2
Self-Assessment of Informatics Competency Scale for Health Professionals (SICS)
Items Mean score Subscales Subscale mean score
1. Demonstrate basic technology skills 4.64 ± 0.51 Basic computer skills 4.07 ± 0.46
2. Use e-mail 4.66 ± 0.47
3. Conduct on-line literature searches 3.94 ± 0.67
4. Use applications to manage aggregated data 2.98 ± 0.86

5. Recognize that the computer is only a tool to provide better nursing care and that there are human functions that cannot be performed by computer 4.54 ± 0.63 Role 4.40 ± 0.62
6. Recognize the value of clinician involvement in the design, selection, implementation, and evaluation of applications, systems in health care 4.26 ± 0.74

7. Extract data from clinical data sets 2.79 ± 0.90 Applied computer skills (clinical informatics) 3.53 ± 0.54
8. Incorporate structured languages into practice 2.91 ± 1.08
9. Describe ways to protect data 3.58 ± 0.85
10. Assess accuracy of health information on the internet 3.84 ± 0.63
11. Identify, evaluate, and apply the most relevant information 3.93 ± 0.69
12. Use application to document patient care 4.28 ± 0.62
13. Identify, evaluate, and use electronic patient education materials appropriate to language and literacy level at the point of care 4.02 ± 0.66
14. Use decision support systems, expert systems, and aids for differential diagnosis 3.49 ± 0.79
15. Act as an advocate of system users including patients and colleagues 3.87 ± 0.79
16. Participate as a content expert to evaluate information and assist others in developing information structures and systems to promote their area of nursing practice 3.34 ± 0.89
17. Applies monitoring system appropriately according to the data needed 3.39 ± 0.83
18. Describe general applications/systems to support clinical care 3.63 ± 0.81

SICS total 3.79 ± 0.45

Values are presented as mean ± standard deviation.

A 5-point Likert scale was used: 1 = not competent, 2 = somewhat competent, 3 = competent, 4 = proficient, and 5 = expert.

Table 3
Comparisons of the total SICS and three subscale scores among groups (n = 126)
n (%) Mean rank

Total SICS Basic computer skills Role Applied computer skills (clinical informatics)
Age (yr)
 20–29 42 (33.3) 65.18 58.74 65.25 67.36
 30–39 46 (36.5) 59.35 58.24 61.57 61.18
 40–49 24 (19.0) 72.88 74.25 67.65 70.10
 ≥50 14 (11.1) 56.04 76.64 57.50 48.21
 Kruskal-Wallis H 2.855 5.679 0.998 3.900
p-value 0.42 0.13 0.80 0.27

 Female 114 (90.5) 62.22 61.75 63.73 62.62
 Male 12 (9.5) 75.67 80.08 61.33 71.88
 Mann-Whitney U 538.000 485.000 658.000 583.500
p-value 0.23 0.10 0.82 0.40

 Non-White 37 (29.4) 52.65 57.58 60.99 52.68
 White, non-Hispanic 89 (70.6) 68.01 65.96 64.54 68.00
 Mann-Whitney U 1245.000 1427.500 1553.500 1246.000
p-value 0.031* 0.236 0.602 0.032*

Nursing experience (yr)
 ≤5 52 (41.3) 64.75 58.88 60.97 67.39
 5–10 33 (26.2) 54.36 58.76 60.65 55.58
 >10 41 (32.5) 69.27 73.18 69.00 64.94
 Kruskal-Wallis H 3.155 4.363 1.509 2.214
p-value 0.21 0.11 0.47 0.33

Computer experience (yr)
 ≤2 5 (4) 27.40 41.90 41.00 29.7
 >2 121 (96) 64.99 64.39 64.43 64.90
 Mann-Whitney U 122.000 194.500 190.000 133.500
p-value 0.024* 0.173 0.142 0.034*

SICS: Self-Assessment of Informatics Competency Scale for Health Professionals.

* p < 0.05.


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