Can Social Cognitive Theories Help Us Understand Nurses' Use of Electronic Health Records?

Correctly structured problem lists lead to better and faster clinical decision-making in electronic health records compared to non-curated problem lists: A single-blinded crossover randomized controlled trial

BACKGROUND

Correctly structured problem lists in electronic health records (EHRs) offer major benefits to patient care. Without structured lists, diagnosis information is often scatteredly documented in free text, which may contribute to errors and inefficient information retrieval. This study aims to assess whether EHRs with correctly structured problem lists result in better and faster clinical decision-making compared to non-curated problem lists.

METHODS

Two versions of two patient records (A and B) were created in an EHR training environment: one version included diagnosis information structured and coded on the problem list ("correctly structured problem list"), the other version had missing problem list diagnoses and diagnosis information partly documented in free text ("non-curated problem list"). In this single-blinded crossover randomized controlled trial, healthcare providers, who can prescribe medications, from two Dutch university medical center locations first evaluated a randomized version of patient A, then B. Participants were asked to motivate their answer to two medication prescription questions. One (test) question required information similarly presented in both record versions. The second (comparison) question required information documented on problem lists and/or in notes. The primary outcome measure was the correctness of the motivated answer to the comparison question. Secondary outcome measure was the time to answer and motivate both questions correctly.

RESULTS

As planned, 160 participants enrolled. Two were excluded for not meeting inclusion criteria. Correctly structured problem lists increased providers' ability to answer the comparison question correctly (56.3 % versus 33.5 %, McNemar odds ratio 2.80 (1.65-4.93) 95 %-CI). Median time to answer both questions correctly was significantly lower for EHRs with correctly structured problem lists (Wilcoxon-signed-rank test p = 0.00002, with incorrect answers coded equally at slowest time).

CONCLUSIONS

Correctly structured problem lists lead to better and faster clinical decision-making. Increased structured problem lists usage may be warranted for which implementation policies should be developed.

Workflow interruption and nurses' mental workload in electronic health record tasks: An observational study

BACKGROUND

Workflow interruptions are common in modern work systems. Electronic health record (EHR) tasks are typical tasks involving human-machine interactions in nursing care, but few studies have examined interruptions and nurses' mental workload in the tasks. Therefore, this study aims to investigate how frequent interruptions and multilevel factors affect nurses' mental workload and performance in EHR tasks.

METHODS

A prospective observational study was conducted in a tertiary hospital providing specialist and sub-specialist care from June 1^st to October 31^st, 2021. An observer documented nurses' EHR task interruptions, reactions and performance (errors and near errors) during one-shift observation sessions. Questionnaires were administered at the end of the electronic health record task observation to measure nurses' mental workload for the electronic health record tasks, task difficulty, system usability, professional experience, professional competency, and self-efficacy. Path analysis was used to test a hypothetical model.

RESULTS

In 145 shift observations, 2871 interruptions occurred, and the mean task duration was 84.69 (SD 56.68) minutes per shift. The incidence of error or near error was 158, while 68.35% of errors were self-corrected. The total mean mental workload level was 44.57 (SD 14.08). A path analysis model with adequate fit indices is presented. There was a relationship among concurrent multitasking, task switching and task time. Task time, task difficulty and system usability had direct effects on mental workload. Task performance was influenced by mental workload and professional title. Negative affect mediated the path from task performance to mental workload.

CONCLUSIONS

Nursing interruptions occur frequently in EHR tasks, come from different sources and may lead to elevated mental workload and negative outcomes. By exploring the variables related to mental workload and performance, we offer a new perspective on quality improvement strategies. Reducing harmful interruptions to decrease task time can avoid negative outcomes. Training nurses to cope with interruptions and improve competency in EHR implementation and task operation has the potential to decrease nurses' mental workload and improve task performance. Moreover, improving system usability is beneficial to nurses to mitigate mental workload.

Medical Students' Intention to Change After Receiving Formative Feedback: Employing Social Cognitive Theories of Behavior

Introduction

We applied Azjen's theory of planned behavior (TPB) and Triandis' theory of interpersonal behavior (TIB) to understand medical students' intention to change behavior based on feedback received during an obstetrics and gynecology clerkship. Both models presume that behavioral intention is strongly related to actual behavior.

Materials and Methods

We collected free-text responses from students during a year-long Feedback Focused initiative on the obstetrics and gynecology clerkship at Harvard Medical School. Students reported feedback daily and what they would change based on that feedback. We applied TPB and TIB to identify students' motivation to change. We analyzed data using directed content analysis.

Results

We reviewed 1,443 feedback entries from 122 students between July 2, 2018, and May 31, 2019. Self-efficacy was the most commonly represented component, related to a student expressing their own role, ability, or skill integrating the feedback (85%). Some entries (11%) focused on students' attitudes or beliefs about the outcome of the implemented feedback, usually patient focused but sometimes about the learner's outcome. Intentions motivated by social norms and expectations focused on the perceived or stated expectations of others, usually a superior or a team (11%). A small number of entries (1.7%) indicated that students had an emotional response to challenging or meaningful feedback.

Conclusions

While self-efficacy is an important change motivator, faculty development geared toward improving the provision of meaningful feedback that bridges a desired behavior change to an outcome of interest, framed through the attitudes and beliefs or social norms lens, may improve trainee performance.

Not another box to check! Using the UTAUT to explore nurses' psychological adaptation to electronic health record usability

BACKGROUND

As the integration of electronic health records (EHRs) continues to expand throughout healthcare organizations worldwide, nurses are faced with the challenge to acclimate to a dynamic technology-based environment of patient care. As technology advances, EHR usability may influence nurses' clinical performance and require nurses to adapt to a wide range of situations associated with electronic documentation. While perceived benefits of EHRs include improvements in healthcare delivery and patient outcomes, there are also unintended consequences associated with EHR usability.

AIMS

The aim of this article is to explore dimensions of EHR usability that may influence nurses' psychological adaptation to the use of EHRs in daily practice.

MATERIALS AND METHODS

The unified theory of acceptance and use of technology (UTAUT) consists of four constructs theorized to have a direct influence on end-user behavior and acceptance of technology: performance expectancy, effort expectancy, social influence, and facilitating conditions. The UTAUT provides the framework to explore EHR usability as found in literature and describe the positive and negative psychological responses of nurses related to the use of EHRs in daily practice.

RESULTS

Integration of EHRs into daily nursing practice can result in positive experiences or have a negative impact on nurses ability to perform their role as patient caregivers.

DISCUSSION

While integration of EHRs into healthcare systems can facilitate improvements in patient outcomes, the delivery of patient care and nurses' daily practices can simultaneously be complicated by EHR usability issues.

CONCLUSION

Although positive and negative experiences of nurses in relationship to EHR usability can be found in literature, there is limited evidence on nurses' psychological adaptation to use of EHRs. Further research on EHR usability is needed based on nursing perspectives and feedback to determine the psychological impact EHRs exert on nurses, discover effective methods for resolving issues, and promote positive trends associated with EHR usability.

Exploring healthcare professionals' perceptions of artificial intelligence: Validating a questionnaire using the e-Delphi method

Objective

The aim of this study was to draw upon the collective knowledge of experts in the fields of health and technology to develop a questionnaire that measured healthcare professionals' perceptions of Artificial Intelligence (AI).

Methods

The panel for this study were carefully selected participants who demonstrated an interest and/or involvement in AI from the fields of health or information technology. Recruitment was accomplished via email which invited the panel member to participate and included study and consent information. Data were collected from three rounds in the form of an online survey, an online group meeting and email communication. A 75% median threshold was used to define consensus.

Results

Between January and March 2019, five healthcare professionals and three IT experts participated in three rounds of study to reach consensus on the structure and content of the questionnaire. In Round 1 panel members identified issues about general understanding of AI and achieved consensus on nine draft questionnaire items. In Round 2 the panel achieved consensus on demographic questions and comprehensive group discussion resulted in the development of two further questionnaire items for inclusion. In a final e-Delphi round, a draft of the final questionnaire was distributed via email to the panel members for comment. No further amendments were put forward and 100% consensus was achieved.

Conclusion

A modified e-Delphi method was used to validate and develop a questionnaire to explore healthcare professionals' perceptions of AI. The e-Delphi method was successful in achieving consensus from an interdisciplinary panel of experts from health and IT. Further research is recommended to test the reliability of this questionnaire.

Determinants of the behavioral intention to use a mobile nursing application by nurses in China

BACKGROUND

Although a mobile nursing application has began to adopt in nursing, few studies have focused on nurses' behavioral intention of it. The objective of this study is to gain insight into the behavioral intention of nurses, i.e. chinese nurses of the future, to use a mobile nursing application. This study adopted an extension of the Unified Theory of Acceptance and Use of Technology to examine Chinese nurses' acceptance of a mobile nursing application.

METHODS

A total of 1207 nurses participated in the cross-sectional survey. The majority of nurses were female (96.2%). The mean age of the participants was 34.18 (SD 7.39). The hypothesized relationships were tested using AMOS structural equation model.

RESULTS

All constructs exhibited an acceptable level of reliability and validity with Cα and CR > 0.7 and AVE > 0.5. An extension of the Unified Theory of Acceptance and Use of Technology Model had good explanatory power for nurses' behavioral intention of a mobile nursing application. Although effort expectancy and perceived risks had a surprisingly insignificant effect on nurses' behavioral intention to use a mobile nursing application, performance expectancy, social influence, facilitating conditions, self-efficacy, and perceived incentives demonstrated significant influence with β = .259, p < .001, β = .296, p < .001, β = .063, p = .037, β = .344, p < .001, β = .091, p = .001, respectively.

CONCLUSION

With 70.2% of the variance in behavioral intention to use a mobile nursing app explained by this model, it could be helpful for potential adopters, and further investigation should test the actual usage behavior for a mobile nursing app and investigate the related factors.

A Systematic Review of the Technology Acceptance Model in Health Informatics

BACKGROUND

One common model utilized to understand clinical staff and patients' technology adoption is the technology acceptance model (TAM).

OBJECTIVE

This article reviews published research on TAM use in health information systems development and implementation with regard to application areas and model extensions after its initial introduction.

METHOD

An electronic literature search supplemented by citation searching was conducted on February 2017 of the Web of Science, PubMed, and Scopus databases, yielding a total of 492 references. Upon eliminating duplicates and applying inclusion and exclusion criteria, 134 articles were retained. These articles were appraised and divided into three categories according to research topic: studies using the original TAM, studies using an extended TAM, and acceptance model comparisons including the TAM.

RESULTS

The review identified three main information and communication technology (ICT) application areas for the TAM in health services: telemedicine, electronic health records, and mobile applications. The original TAM was found to have been extended to fit dynamic health service environments by integration of components from theoretical frameworks such as the theory of planned behavior and unified theory of acceptance and use of technology, as well as by adding variables in specific contextual settings. These variables frequently reflected the concepts subjective norm and self-efficacy, but also compatibility, experience, training, anxiety, habit, and facilitators were considered.

CONCLUSION

Telemedicine applications were between 1999 and 2017, the ICT application area most frequently studied using the TAM, implying that acceptance of this technology was a major challenge when exploiting ICT to develop health service organizations during this period. A majority of the reviewed articles reported extensions of the original TAM, suggesting that no optimal TAM version for use in health services has been established. Although the review results indicate a continuous progress, there are still areas that can be expanded and improved to increase the predictive performance of the TAM.

Empirical Study of Nova Scotia Nurses' Adoption of Healthcare Information Systems: Implications for Management and Policy-Making

Background: This paper used the Theory of Planned Behavior (TPB), which was extended, to investigate nurses’ adoption of healthcare information systems (HIS) in Nova Scotia, Canada.

Methods: Data was collected from 197 nurses in a survey and data analysis was carried out using the partial least squares (PLS) technique.

Results: In contrast to findings in prior studies that used TPB to investigate clinicians’ adoption of technologies in Canada and elsewhere, this study found no statistical significance for the relationships between attitude and subjective norm in relation to nurses’ intention to use HIS. Rather, facilitating organizational conditions was the only TPB variable that explained sampled nurses’ intention to use HIS at work. In particular, effects of computer habit and computer anxiety among older nurses were signified.

Conclusion: To encourage nurses’ adoption of HIS, healthcare administrators need to pay attention to facilitating organization conditions at work. Enhancing computer knowledge or competence is important for acceptance. Information presented in the study can be used by administrators of healthcare facilities in the research location and comparable parts of the world to further improve HIS adoption among nurses. The management of nursing professionals, especially in certain contexts (eg, prevalence of older nursing professionals), can make use of this study’s insights.