Introduction
Integrating digital health technologies, including electronic health records (EHRs), telemedicine platforms, and mobile health applications, has dramatically reshaped healthcare delivery [1‐6]. These technologies offer significant improvements in access to care, efficiency, and patient outcomes, but they also introduce new risks to patient safety [7‐13]. Patient safety in digital health is a broad and multifaceted concept with several concerns, from data security and privacy to system reliability and ethical considerations [14‐18]. As digital health tools become more embedded in clinical practice, developing and refining safety protocols that address these challenges is essential [19‐27]. Nurses are key stakeholders in implementing and using these technologies and are instrumental in ensuring that these safety protocols are robust and effective [28‐33].
Patient safety protocols in digital health are designed to protect patients from harm related to the use of technology [34‐37]. These protocols address several core aspects of care, where data privacy and security are among the most critical components of patient safety. Digital health technologies involve storing, transmitting, and sharing personal health data, increasing the risk of data breaches or unauthorized access [38‐41]. Effective safety protocols must ensure that patient data is securely encrypted, stored in compliance with regulations (such as HIPAA), and only accessible by authorized personnel [42‐46]. Nurses play a key role in ensuring that the systems used to manage patient data are secure and that privacy is maintained throughout the care process. They must safeguard patient information, report potential breaches, and uphold patients’ privacy rights [47‐51].
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System reliability is another critical aspect of patient safety in digital health, where telemedicine platforms, EHRs, and other digital tools must function correctly to ensure patient care is not disrupted [52‐55]. Nurses are often the first to identify technical issues, such as incorrect data entry, system downtime, or telemedicine platform glitches, that could affect patient care [30, 56, 57]. Safety protocols must include contingency plans for system failures, ensuring that procedures are in place to mitigate the impact of technical problems on patient safety (58‐59). Nurses’ role in troubleshooting, reporting issues, and ensuring that systems are used correctly is central to maintaining safety in digital health settings [47‐51].
Informed consent is essential to patient safety, mainly when patients engage in telemedicine consultations or share personal health information via digital platforms. Ensuring patients understand these technologies’ potential risks, benefits, and limitations is crucial (14, 60‐61). Nurses should follow safety protocols to educate patients about these risks and obtain consent before proceeding with digital consultations or interventions so the patients know how their information will be used and trust the digital health services they receive [38‐41]. Nurses must balance the technological efficiency of digital health tools with ethical considerations, ensuring that patients’ autonomy and decision-making power are respected [28‐33].
Nurses are also at the forefront of ensuring that patient safety protocols in digital health are supported by proper training and clinical competency [30, 56, 57]. With the rapid evolution of digital health tools, nurses must continuously update their knowledge and skills to handle new technologies effectively. Ongoing training in data security, system usage, troubleshooting, and staying informed about best practices in telemedicine is essential for maintaining high standards of care (62‐63).
The implications of implementing robust patient safety protocols in digital health are far-reaching. First, ensuring data privacy and system reliability prevents patient harm, reduces the risk of errors, and enhances patients’ trust in healthcare systems. When patients feel confident that their data is secure and their systems are reliable, they are more likely to engage with digital health technologies, leading to better health outcomes (64‐65). Second, ethical considerations—particularly informed consent—are essential for maintaining the integrity of the healthcare system. Nurses’ ability to navigate these ethical challenges ensures that patients’ rights are respected, helping to build trust between patients and providers (14, 60‐61). This trust is crucial in maintaining a positive patient experience and improving adherence to recommended treatments and interventions [38‐41].
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Furthermore, nurses are instrumental in educating patients about the proper use of digital health technologies and ensuring that technology access is unbiased [47‐51]. In regions like Egypt, where technology adoption may vary, safety protocols must account for these disparities (66‐67). Nurses play a vital role in advocating for policies that ensure all patients have access to the tools for safely engaging with digital health systems, ultimately reducing healthcare disparities [14].
Thus, patient safety protocols in digital health are essential for mitigating the risks associated with new technologies, such as concerns with data privacy, system reliability, informed consent, clinical competency, and equitable access. Nurses play a vital role in ensuring that these protocols are followed and that the unique challenges that digital health technologies present are addressed. By refining and implementing comprehensive safety protocols, healthcare systems can improve the safety and quality of care delivered through digital health tools, ultimately benefiting patients and providers. As digital health technologies evolve, ongoing training, collaboration, and adaptation of safety protocols will be necessary to meet emerging challenges and ensure patient safety in the digital age.
Aim of the study
To examine the factors influencing the successful adoption of digital health and telemedicine technologies from the perspective of nurses, focusing on ensuring patient safety and enhancing organizational readiness for digital health integration.
Hypotheses
Hypothesis 1
Nurses in outpatient settings will demonstrate a high level of awareness about telemedicine, reflecting the integration and emphasis on digital health technologies in these environments.
Hypothesis 2
Effective patient safety protocols in outpatient settings will be influenced by robust risk assessment practices, including data security and technology reliability, which will be pivotal in ensuring safe care.
Research questions
1.
How do nurses in outpatient care settings perceive the impact of digital health and telemedicine on patient safety protocols?
2.
What are the main challenges nurses face when implementing patient safety protocols in the context of telemedicine and digital health?
3.
How do digital health technologies influence nurses’ ability to maintain patient confidentiality and data security in outpatient settings?
4.
To what extent do nurses’ experiences and familiarity with telemedicine affect their adherence to patient safety protocols?
5.
What factors in outpatient care environments contribute to successfully implementing patient safety protocols amidst the rise of digital health and telemedicine?
Method
Study design and setting
This cross-sectional study was conducted in outpatient settings across healthcare centers in Egypt, specifically focusing on nurses’ involvement in patient safety protocols. Outpatient care, which includes clinics, medical offices, and community health centers, differs from inpatient care in terms of higher patient turnover and more constrained resources, such as fewer specialized staff and equipment. The decision to focus on outpatient settings was driven by their growing role in primary care and preventative health, making it essential to understand patient safety challenges unique to these environments. With shorter patient interactions and diverse health concerns, outpatient care requires tailored safety protocols to address time and resource limitations. The study highlights how nurses maintain safety standards in outpatient care by examining these settings, providing valuable insights for improving safety practices and risk management.
Sampling method and sample size calculation
A convenience sampling method was used to recruit participants from the total population of approximately 800 nurses. Sample size calculations using G*Power software, with parameters of a medium effect size (Cohen’s d = 0.5), a significance level of 0.05, and a statistical power of 0.80, indicated that approximately 246 nurse participants were required. Non-responses were addressed through follow-ups and reminders to lessen potential biases. In order to enhance analysis, missing data were handled using pair-wise deletion, multiple imputation, and full information maximum likelihood (FIML) estimation.
Participants
The study participants comprised registered nurses with at least six months of experience working in outpatient care in outpatient departments. A diverse range of nurses from various outpatient settings, including primary care, specialty clinics, and ambulatory surgery units, were sampled to ensure comprehensive representation. Nurses not directly involved in patient care, such as administrative staff and those primarily assigned to inpatient units, were excluded. The recruitment process involved obtaining approval from healthcare center administrators and distributing informational flyers and emails to nursing staff. Eligible nurses who met the inclusion criteria were invited to participate, with voluntary participation and informed consent ensured. Follow-up reminders and the availability of electronic and paper surveys facilitated broad participation and data representativeness.
Data Collection measures
Five tools were used for data collection:
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Demographic Profile
The demographic profile of the study participants, comprising 246 nurses, was developed to ensure a representative and diverse participant pool. Sampling strategies included accessing healthcare records and conducting community outreach efforts to capture a wide range of demographic characteristics. The demographic profile included variables such as age, gender, educational background, ethnicity, employment status, and awareness of telemedicine.
Patient Safety Culture Survey (PSCS)
The Patient Safety Culture Survey (PSCS) tool is designed to assess the safety culture within healthcare organizations. Developed by Sorra and Nieva, the PSCS evaluates the safety culture within healthcare organizations. The survey comprises several components, including measures of leadership support, communication openness, teamwork, and organizational learning. A Likert scale, ranging from 1 to 5, captures responses. Mean scores and standard deviations (SD) are calculated for each component to assess the overall safety culture and identify areas for improvement [68].
Telemedicine Risk Assessment and Mitigation Matrix (TRAMM)
The Telemedicine Risk Assessment and Mitigation Matrix (TRAMM) tool was created by O’Keefe and colleagues to assess the risks associated with the implementation of telemedicine. It evaluates several key areas related to the safety and efficacy of telemedicine practices, including data security, clinical decision-making, technology reliability, and communication protocols. The tool uses the Likert scale to collect responses and employs mean scores and SD as measures of the overall risk levels. The TRAMM is thus a valuable tool for identifying potential issues in telemedicine and developing strategies to enhance the safety and efficacy of telemedicine practices [69].
Digital Health Adoption Readiness Assessment (DHARA)
The Digital Health Adoption Readiness Assessment (DHARA), was developed by Greenhalgh and colleagues to assess the preparedness of healthcare organizations to adopt digital health and telemedicine solutions. The assessment collects data on organizational culture, infrastructure readiness, clinician engagement, and patient acceptance. Responses are collected using a Likert scale, with mean scores and standard deviations employed to evaluate preparedness and inform strategies for effective digital health adoption [70].
Digital Health Impact Assessment Tool (DHIA)
The Digital Health Impact Assessment Tool (DHIA) is developed by the World Health Organization (WHO) to evaluate the potential impact of digital health and telemedicine initiatives on healthcare delivery. The tool assesses factors such as stability, interoperability, data privacy, patient engagement, and clinician satisfaction. Likert scale responses are used and mean scores and standard deviations are calculated to gauge digital health initiatives’ anticipated impact and effectiveness [71].
Validity and reliability
The tools employed in this study are believed to be valid in accurately measuring the constructs they are designed to assess, providing reliable insights. The Patient Safety Culture Survey (PSCS) exhibits robust construct validity as evidenced by psychometric assessments, effectively capturing pivotal safety culture dimensions such as leadership support, communication transparency, teamwork, and organizational learning. This validity is supported by factor analysis and comparisons with external benchmarks. The Telemedicine Risk Assessment and Mitigation Matrix (TRAMM) is an effective tool for assessing risks associated with telemedicine, including data security and technology reliability. Its validity is supported by expert consensus and real-world assessments. The Digital Health Adoption Readiness Assessment (DHARA) is also a valid tool for evaluating organizational culture, infrastructure readiness, clinician engagement, and patient acceptance, as evidenced by factor analysis and successful integration outcomes. The Digital Health Impact Assessment Tool (DHIA) measures the impact of digital health initiatives, and its validity has been confirmed through factor analysis of dimensions such as stability, interoperability, and data privacy, with the results supported by expert opinions and empirical studies.
To further ensure the tools’ relevance and accuracy within Egyptian healthcare, a pilot study was conducted involving 25 participants, constituting 10% of the total sample size. The preliminary testing was conducted under the supervision of five public health and community nursing experts, who reviewed the tools and provided feedback. The pilot study revealed areas for minor improvement, which were carried out to enhance the tools’ applicability and reliability and ensure their suitability for the distinctive characteristics of the Egyptian healthcare environment. These tools are validated through construct validity, factor analysis, expert evaluations, practical applications, and contextual pilot testing, ensuring their reliability in assessing patient safety and digital health practices.
The reliability of the instruments used in this study is validated by their consistent performance across many applications. The Patient Safety Culture Survey (PSCS) demonstrates high internal consistency, as indicated by a Cronbach’s alpha coefficient of 0.89. This finding supports the reliability of measuring safety culture dimensions, including leadership support and teamwork. The Telemedicine Risk Assessment and Mitigation Matrix (TRAMM) demonstrates strong reliability, as evidenced by a Cronbach’s alpha of 0.87 for risk factors, including data security and technology reliability. The Digital Health Adoption Readiness Assessment (DHARA) demonstrates robust reliability with a Cronbach’s alpha of 0.85, ensuring consistent evaluation of readiness factors such as organizational culture and clinician engagement. Lastly, the Digital Health Impact Assessment Tool (DHIA) achieves a Cronbach’s alpha of 0.88, thereby confirming the reliability of its measurement of impact dimensions such as stability and patient engagement. These reliability metrics demonstrate the efficacy of the tools in consistently evaluating patient safety and digital health practices.
Statistical analysis
The statistical analyses were conducted using SPSS 26. Descriptive statistics, including mean and standard deviation calculations, were used to summarise the data and assess central tendencies and variability. The mean score represents the average response for each survey component and assessment tool, and the standard deviation quantifies the dispersion of responses around the mean, indicating variability within the dataset. Pearson’s correlation coefficient determines the strength and direction of linear relationships between the total mean scores of the various assessment tools, thus evaluating the associations between variables such as patient safety culture and digital health readiness. Furthermore, a multiple linear regression analysis was conducted to ascertain the influence of predictor variables, such as educational level and awareness of telemedicine, on the total scores of the assessment tools. The regression analysis yielded insights into the influence of these predictors on the study outcomes.
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Several assumptions underwent rigorous scrutiny to guarantee the reliability of the findings during the statistical analysis. The normality of the data was evaluated to determine the suitability of parametric tests. The linearity of the data was evaluated to ascertain whether the relationships between the predictors and the outcomes were indeed linear. The homogeneity of variance was verified to confirm that the residual variance remained consistent across predictor levels, and the independence of observations was evaluated to ensure that the data points were not correlated. The mean scores were calculated by summing the individual responses and dividing by the total number of responses. The standard deviations were computed as the square root of the average squared differences between each response and the mean.
Ethical considerations
The study was granted approval by the Faculty of Nursing’s Institutional Review Board (IRB) at Port Said University, with the approval code NUR (72024/4/) (36), in order to ensure the protection of participants’ rights, privacy, and confidentiality. Informed consent was obtained from all participants, and they were informed that their participation was entirely voluntary and that they could withdraw from the study without any adverse consequences. In order to ensure the protection of sensitive data collected during the research process, measures were implemented to maintain anonymity and confidentiality throughout the handling and analysis of data. All procedures performed in the study were conducted in accordance with the ethical standards of the instituational and / or national research committee and with the 1964 Declaration of Helsinki and its later amendements.
Results
A total of 246 participants were recruited for the study. As shown in Table 1, the majority of the participants (44.72%) were aged between 36 and 55 years, followed by those aged 18 to 35 years (40.65%) and those over 55 years (14.63%). The gender distribution was nearly equal, with 48.78% male and 51.22% female participants. Most participants had a college or university education (73.17%), with smaller proportions holding diplomas (6.10%) or graduate/postgraduate degrees (20.73%). Most participants were employed full-time (69.88%), with 24.39% employed part-time and 6.73% unemployed. Awareness of telemedicine was high, with 73.17% of participants reporting being aware of its use in healthcare.
Table 1
Demographic characteristics of study participants (N = 246)
Demographic Characteristic | Number of Participants | Percentage (%) |
|---|---|---|
Age Group | ||
− 18–35 years | 100 | 40.65 |
− 36–55 years | 110 | 44.72 |
- Over 55 years | 36 | 14.63 |
Gender | ||
- Male | 120 | 48.78 |
- Female | 126 | 51.22 |
Education Level | ||
- Diploma | 15 | 6.10 |
- College/University | 180 | 73.17 |
- Graduate/Postgraduate | 51 | 20.73 |
Employment status | ||
- Full-time | 170 | 69.88 |
- Part-time | 60 | 24.39 |
- Unemployed | 16 | 6.73 |
Awareness about Telemedicine | ||
- Aware | 180 | 73.17 |
- Not Aware | 66 | 26.83 |
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The evaluation of the Patient Safety Culture Survey summarized in Table 2 revealed that the mean score for communication openness was the highest (M = 4.5, SD = 0.4), followed by teamwork (M = 4.3, SD = 0.5) and leadership support for safety (M = 4.2, SD = 0.6). The lowest scoring area was organizational learning (M = 4.1, SD = 0.7). These findings suggest that while communication and teamwork are strengths within the organization, efforts to enhance continuous learning and leadership engagement in safety initiatives could further strengthen patient safety culture in nursing management practices.
Table 2
Patient Safety Culture Survey (PSCS) evaluation: Mean scores and Standard deviations
Survey Component | Mean Score | Standard Deviation |
|---|---|---|
Leadership Support for Safety | 4.2 | 0.6 |
Communication Openness | 4.5 | 0.4 |
Teamwork | 4.3 | 0.5 |
Organizational Learning | 4.1 | 0.7 |
Total Mean Score | 4.275 | 0.55 |
As seen in Table 3, risk assessment scores across the evaluated components were consistently high, with clinical decision-making receiving the highest score (M = 5.0, SD = 0.2) and technology reliability scoring slightly lower (M = 4.8, SD = 0.3). Data security and communication protocols both scored 4.9 (SD = 0.1). These results highlight the importance of maintaining robust clinical decision-making processes and secure communication in telemedicine applications within nursing practice.
Table 3
Risk Assessment Component evaluation: Mean scores and Standard deviations
Risk Assessment Component | Mean Score | Standard Deviation |
|---|---|---|
Data Security | 4.9 | 0.1 |
Clinical Decision-making | 5.0 | 0.2 |
Technology Reliability | 4.8 | 0.3 |
Communication Protocols | 4.9 | 0.1 |
Total Mean Score | 4.9 | 0.175 |
The results in Table 4 show that the Digital Health Adoption Readiness Assessment indicated strong organizational culture readiness (M = 8.2, SD = 0.6) and patient acceptance (M = 8.9, SD = 0.3). However, clinician engagement had the lowest score (M = 6.8, SD = 0.5), highlighting an area for improvement. This suggests that while patients generally accept digital health innovations, further efforts are needed to engage clinicians in these practices, which could involve targeted training and support from nursing leadership.
Table 4
Digital Health Adoption Readiness Assessment (DHARA) results: Mean scores and Standard deviations
Readiness Component | Mean Score | Standard Deviation |
|---|---|---|
Organizational Culture | 8.2 | 0.6 |
Infrastructure Readiness | 7.5 | 0.4 |
Clinician Engagement | 6.8 | 0.5 |
Patient Acceptance | 8.9 | 0.3 |
Total Mean Score | 7.85 | 0.45 |
The Digital Health Impact Assessment results presented in Table 5, revealed high levels of patient engagement (M = 9.0, SD = 0.2) and data privacy (M = 8.8, SD = 0.5). Clinician satisfaction (M = 8.5, SD = 0.4) and stability (M = 8.2, SD = 0.4) also scored highly. These findings suggest that digital health technologies positively impact patient engagement and clinician satisfaction. However, ongoing attention to maintaining data privacy and system stability is essential for successfully integrating these technologies into nursing workflows.
Table 5
Digital Health Impact Assessment Tool (DHIA) results: Mean scores and Standard deviations
Impact Assessment Component | Mean Score | Standard Deviation |
|---|---|---|
Stability | 8.2 | 0.4 |
Interoperability | 7.5 | 0.3 |
Data Privacy | 8.8 | 0.5 |
Patient Engagement | 9.0 | 0.2 |
Clinician Satisfaction | 8.5 | 0.4 |
Total Mean Score | 8.4 | 0.36 |
Table 6 shows a correlation matrix of total scores across the assessments, revealing moderate positive correlations between the different tools. Specifically, the PSCS was significantly correlated with the DHARA (r = 0.65, p < 0.01) and DHIA (r = 0.60, p < 0.01), indicating that a strong patient safety culture is associated with better digital health adoption enthusiasm and overall impact, suggesting that organizations with robust safety cultures are more likely to implement and benefit from digital health innovations successfully. Nursing managers can influence this relationship by adopting systems that support safety and technology adoption.
Table 6
Correlation Matrix of Total Mean scores
Variable | PSCS Total | TRAMM Total | DHARA Total | DHIA Total |
|---|---|---|---|---|
Patient Safety Culture Survey (PSCS) Total | 1.00 | 0.56 | 0.65** | 0.60** |
Telemedicine Risk Assessment and Mitigation Matrix (TRAMM) Total | 0.56 | 1.00 | 0.58** | 0.62** |
Digital Health Adoption Readiness Assessment (DHARA) Total | 0.65 ** | 0.58 ** | 1.00 | 0.67** |
Digital Health Impact Assessment Tool (DHIA) Total | 0.60 ** | 0.62 ** | 0.67** | 1.00 |
As detailed in Table 7, a multiple regression analysis was conducted to examine the predictors of total assessment scores, focusing on education level and telemedicine awareness. Awareness of telemedicine was found to be a significant predictor of scores on the PSCS (β = 0.25, p = 0.03) and TRAMM (β = 0.28, p = 0.02), indicating that participants who were more aware of telemedicine reported better outcomes in terms of safety culture and risk mitigation. On the other hand, education level did not emerge as a significant predictor, suggesting that raising awareness about telemedicine in nursing practice could enhance patient safety and better risk management in digital health settings.
Table 7
Regression Analysis of Predictors on total scores of Assessment Tools
Predictors | PSCS | TRAMM | DHARA | DHIA | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
B | SE | β | p-value | B | SE | β | p-value | B | SE | β | p-value | B | SE | β | p-value | |
Education Level | 0.10 | 0.09 | 0.12 | 0.28 | 0.12 | 0.09 | 0.14 | 0.22 | 0.08 | 0.09 | 0.09 | 0.39 | 0.09 | 0.09 | 0.10 | 0.35 |
Awareness about Telemedicine | 0.20 | 0.08 | 0.25 | 0.03* | 0.22 | 0.08 | 0.28 | 0.02* | 0.18 | 0.08 | 0.22 | 0.07 | 0.19 | 0.08 | 0.23 | 0.06 |
Discussion
The Patient Safety Culture Survey (PSCS) findings provide critical insights into safety culture within healthcare organizations that adopt digital health technologies and telemedicine. From the nursing practice and management perspective, these results highlight strengths and opportunities for improvement. The high mean score for communication openness signifies a positive environment where nurses and other healthcare providers feel empowered to voice safety concerns. This finding aligns with the literature emphasizing the role of transparent communication in reducing errors and improving patient outcomes, particularly within nursing teams. For instance, Hurtig et al. [72] reports that effective communication between patients and providers improves safety and prevents medical errors.
Similarly, a study by Karande et al. [73] shows that minimizing medical errors is crucial for enhancing patient safety, and communication plays a significant role in this effort. Furthermore, studies like those by Schnipper et al. [74] highlight how open communication contributes to a safety culture by encouraging reporting safety issues, ultimately improving patient care. Additionally, Sharkiya [75] demonstrates how quality communication improves patient-centered health outcomes, particularly among older patients.
The role of nurses in fostering such openness is critical, as they are often the frontline providers who detect and report safety issues. Similarly, the high score for leadership support for safety underlines the importance of strong nursing leadership in prioritizing safety initiatives. Nursing leaders are pivotal in creating environments where patient safety is central, encouraging staff engagement without fear of blame. Research has shown that supportive nursing leadership fosters a culture of safety and increases nurses’ participation in safety-related activities, which is crucial for maintaining high standards of care across all settings. Studies by Künzle et al. [76] and Ree and Wiig [77] highlight the importance of leadership behavior and transformational leadership in improving patient safety and work engagement, respectively. For example, Wang and Dewing [78] explore how nursing leadership mediates the relationship between safety culture and patient safety outcomes, emphasizing the need for person-centered approaches. Similarly, Haskins and Roets [79] emphasize that sustaining a culture of safety requires ongoing efforts from nurse leaders to engage staff and maintain a strong safety culture.
The current findings highlight the critical role of teamwork in safety and quality care, with a notable mean score for Teamwork aligning with research linking effective teamwork to improved patient safety and organizational performance. Prior studies have consistently emphasized the importance of collaboration among nursing teams and other healthcare professionals for patient safety in complex healthcare environments. For instance, Gluyas [80] underscores how effective communication and teamwork promote patient safety, particularly in high-stakes environments. Freytag et al. [81] also highlight that simulation-based debriefing can improve teamwork and patient safety outcomes.
Similarly, Dinius et al. [82] showed the association between inter-professional teamwork and hospital patient safety, highlighting the importance of collaborative efforts to improve patient outcomes across healthcare teams. Despite this, the mean score for Organisational Learning indicates a need for continuous improvement essential for nursing management. Ongoing education and training are vital for driving quality improvement and reducing adverse events. The role of organizational learning in enhancing patient safety is well-documented, with Rivard et al. [83] emphasizing that improving safety indicators is a crucial part of this learning process. Similarly, Richter et al. [84] explore how organizational factors influence safety, especially in ensuring effective transition between healthcare providers.
In summary, while the PSCS results reflect a generally positive safety culture, there are opportunities to enhance communication, leadership support, teamwork, and organizational learning to advance patient safety and quality care in digital health and telemedicine. Linnander et al. [85] demonstrate how changing hospital organizational culture can improve patient outcomes. Lu et al. [86] discuss the importance of organizational culture as a resource for patient safety and staff well-being, reinforcing the need for continuous cultural and organizational development.
Additionally, the results show a favorable evaluation of risk assessment elements in telemedicine implementations, particularly in clinical decision-making, highlighting the organization’s commitment to ensuring high standards of care. Additionally, strong data security and communication protocol scores emphasize the organization’s focus on building reliable and secure telemedicine systems, reflecting high confidence in the system’s ability to manage risks effectively. The minimal standard deviations indicate consistency in risk perceptions, reinforcing the robustness of the risk assessment framework.
These results are consistent with existing research emphasizing the importance of structured risk assessments in telemedicine. Prior studies highlight the role of teleconsultation in clinical decision-making, focusing on effective communication between nurses and patients and improving clinical decision-making [87‐89]. Kindi [90] explores factors influencing decision-making among nurses, while Tatullo et al. [91] discuss the impact of telemedicine on risk management, supporting the current study’s findings on the importance of comprehensive risk assessment in telemedicine.
The Organizational Culture and Infrastructure Readiness scores suggest a strong foundation and adequate resources to support the effective adoption of digital health initiatives. This indicates the organization’s proactive attitude in fostering an environment that encourages digital transformation. However, the somewhat lower score for Clinician Engagement suggests room for improvement in involving healthcare professionals in the adoption process. Despite the organization’s high preparedness in several areas, enhancing clinician engagement and ensuring smooth integration into clinical workflows remain critical for optimizing the implementation of digital health initiatives. The overall score reflects a high level of preparedness and alignment with the organization’s digital health adoption goals, positioning it favorably to leverage digital technologies for improved patient care and operational efficiency. These findings emphasize the commitment to embracing innovation and digital solutions to meet the evolving demands of patients and healthcare delivery systems.
Several studies emphasize the importance of organizational readiness and patient acceptance in adopting digital health. The study by Kampstra et al. [92] highlights how organizational culture supports quality improvement efforts, while Fowe [93] discusses organizational readiness for change in telehealth and mobile health interventions. Madanian et al. [94] explore patients’ perspectives on digital health tools and Carrera et al. [95] focus on factors driving patient acceptance of digital therapeutics. Additionally, Uren and Edwards [96] examine organizational readiness in the context of AI adoption. All these studies validate the current findings, emphasizing the importance of organizational culture, clinician engagement, and patient involvement in successfully implementing digital health solutions.
The Digital Health Impact Assessment Tool (DHIA) findings highlight the significant potential of digital health and telemedicine to transform healthcare delivery. Notably, high scores for patient engagement emphasize the role of digital interventions in actively involving patients in their care. The high scores seen for Usability, Interoperability, Data Privacy, and Clinician Satisfaction align with key objectives for effective digital health implementation, suggesting that digital health initiatives can improve patient outcomes, clinical workflows, and healthcare accessibility, reinforcing the transformative impact of these technologies on healthcare systems. Research by Barbosa et al. [97] and Kruszyńska-Fischbach et al. [98] reinforces these results, emphasizing the role of digital health in enhancing patient engagement, clinical efficiency, and remote care. The DHIA findings underscore digital health’s capacity to optimize healthcare delivery and patient-centered care.
The findings from the correlation analysis indicate a strong interrelationship among the assessment tools for evaluating patient safety culture, risk assessment, digital health readiness, and impact. The moderate to strong correlations between the Patient Safety Culture Survey (PSCS), Telemedicine Risk Assessment and Mitigation Matrix (TRAMM), Digital Health Adoption Readiness Assessment (DHARA), and Digital Health Impact Assessment Tool (DHIA) suggest an interconnected framework. The importance of safety culture in influencing risk management and digital health integration is consistent with several studies. For example, Singer et al. highlight that a strong safety culture is essential for effective risk management and quality improvement in healthcare settings [99]. Similarly, the alignment among these tools reflects the idea that comprehensive risk assessment and readiness for digital health are critical for enhancing patient safety and care quality, as suggested by Farokhzadian et al. [59]; Kalteh & Mokarami 100, who found that safety culture impacts organizational risk management practices and readiness for technological advancements.
Regression analysis reveals that awareness of telemedicine significantly predicts higher scores on the Patient Safety Culture Scale (PSCS) and the Telemedicine Risk and Management Model (TRAMM). This suggests that increased awareness enhances perceptions of safety and risk management, a finding supported by research indicating that heightened awareness improves safety practices and risk mitigation in telemedicine settings [101]. Interestingly, education level did not significantly impact, implying that practical experience and organizational support may play a larger role in influencing safety culture. This aligns with previous studies emphasizing that engagement and awareness, rather than formal education, are critical factors for improving healthcare safety culture and risk management [102, 103]. While the overall model’s explanatory power was modest, it underscores the importance of awareness in shaping safety practices, consistent with the literature highlighting the role of awareness and professional involvement in fostering a strong safety culture [104, 105].
Conclusion
The study shows that nurses are strongly aware of telemedicine and integrating digital health technologies in outpatient settings, enhancing their understanding of these tools. It also highlights that effective risk assessment practices, particularly concerning data security and technology reliability, contribute significantly to the success of patient safety protocols. However, challenges with clinician engagement, system reliability, organizational culture readiness, and patient acceptance still need to be addressed for optimal implementation of patient safety protocols. Despite the positive factors, clinician engagement remains a critical area requiring attention. Telemedicine awareness emerged as a key factor in ensuring nurses’ adherence to safety protocols, aligning with the research questions. These findings emphasize the importance of continuous education and support for nurses, particularly in outpatient settings, to adapt to evolving digital health tools. To fully leverage the benefits of digital health technologies, ongoing efforts are needed to engage clinicians, ensure data security, and maintain system reliability, ultimately improving patient safety and care quality.
Recommendations
Several key recommendations emerge from the study’s findings to improve the integration and use of digital health and telemedicine technologies in nursing practice. First, healthcare organizations should promote a healthy safety culture by encouraging leadership support, open communication, and teamwork and recognizing nurses’ central role in maintaining patient safety. Second, comprehensive risk assessment frameworks, such as the Telemedicine Risk Assessment and Mitigation Matrix (TRAMM), should be implemented to identify and address potential risks in telemedicine, considering the unique challenges nurses face when integrating digital health technologies. Third, enhancing nurse engagement in the decision-making process for adopting digital health tools is essential, ensuring they receive adequate education, training, and infrastructure to understand and use these technologies. Additionally, continuous training programs should be established to keep nurses updated on digital health’s technical, ethical, and privacy aspects, emphasizing operational skills and data security. Finally, using tools like the Digital Health Impact Assessment Tool (DHIA) can evaluate the effectiveness of digital health initiatives, ensuring they enhance patient care while addressing emerging barriers and safety concerns.
Future research directions
Based on the current results, future studies should focus on several key areas to advance nursing practice in digital health and telemedicine environments. Investigating the challenges to organizational learning and continuous improvement can inform strategies to strengthen the safety culture in healthcare. Studies should also explore strategies for improving nurse engagement with digital health initiatives, particularly their involvement in decision-making and implementation phases, which is crucial for successful adoption. Longitudinal research is needed to evaluate the sustained impact of nurse involvement on telemedicine patient safety protocols, providing an understanding of their long-term effectiveness and sustainability. Moreover, incorporating patient perspectives in evaluating telemedicine’s effectiveness and safety protocols can promote a more patient-centered approach to digital health strategies. Comparative studies between traditional and telemedicine-based healthcare settings would help identify unique challenges and advantages in nursing practice. Further research should also examine the impact of emerging technologies, such as artificial intelligence (AI) and machine learning, on nursing practice, focusing on how these tools can support clinical decision-making and enhance patient safety. Lastly, as digital health tools become widespread, future studies should address the importance of digital knowledge among nurses, exploring its effect on their ability to use telemedicine effectively and identifying gaps to develop targeted training programs. These research directions will help address current challenges and prepare the nursing profession for the evolving digital healthcare.
Implications of the study
The study has important implications for advancing the integration of digital health within nursing practice. While high levels of telemedicine awareness, strong communication, and teamwork are evident, a significant gap in clinician engagement may hinder the full adoption of digital health technologies. Healthcare organizations must address this by providing comprehensive training programs tailored to nurses, focusing on digital knowledge, telemedicine protocols, and data security. Additionally, nurturing a safety culture supported by leadership and continuous learning is essential for strengthening patient safety in digital health environments. By increasing clinician involvement, improving communication, and ensuring data privacy, healthcare organizations can optimize the implementation of digital health technologies, enhancing patient care and operational efficiency in the increasingly digital healthcare landscape.
Study limitations
Despite the valuable insights gained from this study, several limitations must be acknowledged. The sample size, while adequate for this research, may limit the generalizability of the findings. A larger and more diverse sample would be beneficial in ensuring that the results can be applied to a broader range of healthcare settings and populations. Moreover, the study relies on self-reported data, which introduces potential biases such as response bias and social desirability bias. Participants may have provided answers they believe are more socially acceptable or expected rather than their true opinions, potentially affecting the reliability of the results.
Additionally, the study’s cross-sectional design captures only a snapshot in time and does not allow for establishing causal relationships between the variables. Longitudinal studies could provide a more comprehensive understanding of how digital health and telemedicine initiatives impact healthcare outcomes over time. Furthermore, the focus on quantitative measures may have overlooked the depth and complexity of healthcare professionals’ experiences, particularly concerning challenges like staffing difficulties in delivering telemedicine. Future research incorporating qualitative approaches could complement these findings, offering a richer, more nuanced understanding of the issues at play. Finally, the study may not have fully explored other factors influencing the adoption of digital health technologies, such as organizational culture, financial constraints, and regulatory challenges. Exploring these factors in future research could provide a more comprehensive view of enhancing digital health implementation and its impact on healthcare delivery.
Acknowledgements
This study is supported by funding from Prince Sattam bin Abdulaziz University’s project number (PSAU/2024/R/1446). Also, the authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA, for funding this research work “through the project number “NBU-FFR-2024-190-01.”” Additionally, we would like to express our gratitude to all the participants who took part in this study.
Declarations
Ethics approval and consent to participate
The study obtained approval from the institutional review board (IRB) at the Faculty of Nursing, Port Said University, with the code number NUR (72024/4/) (36), to ensure the protection of participants’ rights, privacy, and confidentiality. Informed consent was obtained from all participants, emphasizing their voluntary participation and right to withdraw from the study at any point without repercussions. Measures were implemented to safeguard sensitive data collected during the research process, maintaining anonymity and confidentiality throughout data handling and analysis. All procedures performed in the study were conducted in accordance with the ethical standards of the instituational and / or national research committee and with the 1964 Declaration of Helsinki and its later amendements.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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