by June Kaminski, RN MSN PhD(c)
Editor in Chief

CJNI was initiated by June Kaminski in 2006 when she was President-Elect of CNIA.  In 2012, June was honoured to receive the CASN and Canada Health Infoway’s inaugural Nursing Faculty E-Health Award 2012 in Ottawa Canada. She offers the Nursing Informatics Learning Centre with accredited CEU informatics courses.

Citation: Kaminski, J. (2025). Editorial. Top informatics innovations of 2025. Canadian Journal of Nursing Informatics, 20(4).  https://cjni.net/journal/?p=15656

In 2025, informatics innovations continue to show promise in reshaping healthcare delivery, education, research, and system operations. From updated competencies, artificial intelligence (AI) enabled decision support to real-world evidence platforms and precision medicine, these advances have significant positive implications for nursing education, practice, and leadership.

Innovations in Nursing Education

Informatics Competencies

A significant advance for nursing informatics this year was the introduction of the second edition of the nursing informatics entry-to-practice competencies for registered nurses from the Canadian Association of Schools of Nursing (CASN, 2025). The competencies have been broadened to encompass current trends in digital health, like the inclusion of AI enabled software, programs and devices. These competencies are what is expected of any Canadian BSN student upon graduation thus are required to be integrated into nursing programs across the country.

AI integration

Another innovation that continues to evolve is  the integration of AI and Large Language Models (LLMs), such as ChatGPT, into nursing education curricula to prepare future nurses for this technological shift in healthcare delivery (Avramovic & Mobahi, 2025; Cucci, 2025; Harrington et al., 2025) and “…enhance students’ learning experiences, communication skills, and clinical preparedness” (Cucci, 2025, p. 1) by making learning “…more interactive, personalized, and data-driven” (p. 10).

Harrington et al. (2025) described how accessible LLMs such as ChatGPT, Google Gemini and Microsoft Bing are being used more by both faculty and students to enhance content, assessments, and assignments. “LLMs continue to be applied in nursing education to enhance clinical simulation scenarios, provide personalized support for assignments, assist students and educators in developing study materials, and improve learning by promoting interactive discussions, problem-solving, and critical thinking” (p. 2). Harrington et al. (2025) also identified four attributes of LLMs that made them particularly well suited for nursing education: “1) accessibility, (2) personalization, (3) interactivity, and (4) revolutionary nature” (p. 3). Educators are encouraged to find solutions to address concerns about ethics and academic integrity and find ways to include LLMs and other AI tools in teaching and learning activities to foster creativity, critical thinking and judgement, engagement, and collaboration.

Innovations in Nursing Practice

Clinical Decision Support

AI-enhanced clinical decision support systems (CDSS) have advanced rapidly in 2025, incorporating large language models (LLMs) capable of synthesizing structured and unstructured EHR data. For nurses, these tools support early risk identification (for example, for sepsis, falls, clinical deterioration), medication safety, wound care management, chronic disease monitoring, and care planning.

From a nursing informatics perspective, the emphasis remains on augmentation rather than replacement of clinical judgment. Studies highlighted the importance of transparency, explainability, and nurse involvement in AI design to ensure systems align with nursing workflows and values such as patient-centred care and equity (Wei et al., 2025; Hoelscher & Pugh, 2025). Nurses play a critical role in validating AI outputs, identifying bias, and ensuring contextual appropriateness at the point of care.

CDSS are becoming more common within Canadian EHR environments in acute care, primary care, and community settings (Giebel et al., 2025). The use of AI-powered CDSS and predictive models continues to accelerate, providing clinicians with actionable insights for early disease detection (such as cancer) and preventing hospital readmissions. Distinct benefits of using AI-empowered CDSS are that they facilitate faster, more tailored responses; they help to streamline decision-making; they support a more agile care delivery model; and, if developed well, they provide more accuracy, clinical validity, and protect patient safety, supported by upfront transparency and traceability (McNatt, 2025).

AI Scribes and Automated Documentation

A significant focus in 2025 was on scaling AI scribes nationally through a Canada Health Infoway program to reduce clinician burden (Canada Health Infoway, 2025; Canada’s Drug Agency, 2025; Kaminski, 2025). These AI tools, such as Microsoft’s Dragon Copilot (Microsoft, 2025), create written summaries of conversations and notes, potentially saving hours of administrative work per week and freeing up time for direct patient interaction. On October 16, 2025, Microsoft announced a revision of this product: “Microsoft is expanding the capabilities of its leading AI clinical assistant, Dragon Copilot, by introducing the first commercially available ambient experience created for nursing workflows and new extensibility capabilities that allow partners to unlock additional value for Dragon Copilot users. These advancements will enable secure integration of partner AI apps and agents directly into Dragon Copilot, allowing clinicians to gain efficiencies without leaving their workflow, and empower nurses with tailored AI capabilities” (p. 1). View a brief promotional video that explains how this supports nursing care (Microsoft for Healthcare, 2025):

Microsoft for Healthcare. (2025). Empowering nurses with Dragon Copilot. [Video]. YouTube.

As well, real-time analytics and AI-powered dashboards, like those from companies such as Hero AI, are becoming more common in high-traffic units such as emergency departments to optimize patient flow, reduce wait times, and enhance safety by flagging high-risk patients. 

Real-World Evidence Platforms and Nursing-Generated Data

Real-world evidence (RWE) platforms that integrate EHR data, patient-reported outcomes, and wearable data have expanded significantly in 2025. These RWE platforms have expanded across Canadian health systems, supported by pan-Canadian data strategies and provincial digital health initiatives. “Real-world evidence (RWE) is evidence about the use, safety, and effectiveness of a medical product, technology, or drug that is based on or derived from analysis of data generated in a real-world health care setting” (Canada’s Drug Agency, 2024, p. 1).

“Real-world data (RWD) includes information about the health of individuals or the delivery and/or outcomes of health care that is collected outside of traditional clinical trials and thus reflects results within the context of the particular health care system” (Canada’s Drug Agency, 2024, p. 1). Nursing documentation, care plans, patient education, observational assessments, and care coordination notes represent a substantial portion of these data sources and are an underutilized source of real-world data. Nursing informatics innovation focuses on improving the visibility and usability of nursing-generated data within RWE ecosystems. These integrated platforms enable nurses to contribute directly to quality improvement, population health monitoring, and practice-based research, strengthening the nursing voice in evidence generation (Hoelscher & Pugh, 2025).

From a Canadian nursing perspective, informatics innovation focuses on improving the visibility, standardization, and secondary use of nursing-generated data to support quality improvement, health system planning, and population health surveillance. These platforms also strengthen nursing contributions to health services research and learning health systems, particularly in community and long-term care sectors. Coupled with patient-derived data gleaned through wearables, remote monitoring, and other Internet of Things devices, nurse-led RWD and RWE can provide fertile information and data to support personalized and innovative care.

Personalized Precision Care

Remote patient monitoring (RPM) using advanced remote monitoring tools and wearable devices use continues to expand to help manage chronic illnesses, particularly in remote communities, with data seamlessly integrating into electronic health records (EHRs) to alert providers to significant changes in real-time (Bouabida et al., 2025; Canada’s Drug Agency, 2025). “AI-powered remote monitoring could use algorithms that analyze large, real-time datasets to identify patterns and trends that allow for adjustments to treatment plans as necessary, resulting in more dynamic and responsive care. Implementing AI for remote monitoring can enhance the quality of life for patients and help prevent potential adverse outcomes” (Canada’s Drug Agency, 2025, p. 20). “Leading RPM platforms, including TELUS Health, Cloud DX, and McKesson Canada, exemplify the tools designed to monitor various patient health indicators remotely” including routine assessment data like vital signs, blood glucose, mental health, and chronic symptoms (Bouabida et al., 2025, p. 1).

The development of multimodal EHR foundation models that embed genetic risk scores with clinical records illustrates a critical step toward personalized risk stratification and proactive care planning (Amar et al., 2025). The integration of genomics, social determinants of health (SDOH), and clinical data into multimodal informatics models is also advancing precision health initiatives across Canada. For nurses, this innovation supports more personalized care planning, targeted health education, and proactive prevention strategies.

In the Canadian context, nursing informatics emphasizes health equity and cultural safety, particularly when applying predictive analytics to populations historically underserved by the healthcare system. Nurses play a key role in interpreting risk information, supporting informed consent, and advocating for responsible use of sensitive data, including genetic and social data, within publicly funded systems.

Innovations in Nursing Leadership

Operational Innovations

In Canada, nursing informatics leadership emphasizes augmentation of professional judgment, not substitution. Regulatory bodies such as provincial colleges of nursing underscore nurses’ accountability for clinical decisions, regardless of AI involvement. As a result, Canadian nurse informaticists are prioritizing explainable AI, local validation, and alignment with evidence-based nursing practice to ensure patient safety and professional responsibility.

Operational informatics innovations such as AI-supported staffing tools, workload analytics, and ambient documentation are being adopted across Canadian health systems to address workforce shortages and efficiency pressures. Nurses are central to evaluating these tools to ensure they improve care quality without compromising professional autonomy or patient safety.

Canadian nursing leaders are increasingly recognized as essential contributors to informatics governance, implementation strategy, and digital health policy development. In 2025, informatics competency is viewed not as a specialized niche but as a core leadership skill for nurses across roles and settings. Thus, it is important for nursing leaders to support all nurses in developing informatics skills and using these technologies wisely and competently. One way to do this is to explore what other Canadian clinicians and health care settings are using.

A unique environmental scan repository of Canadian initiatives is available entitled AI-driven clinical initiatives in Canadian healthcare delivery. “The AI in Action: Transforming Clinical Care Across Canada Working Group, championed by Dr. Tania Tajirian, Chief Health Information Officer (CHIO) and Chief of Hospital Medicine at the Centre for Addiction and Mental Health (CAMH), has completed a first-of-its-kind environmental scan of artificial intelligence (AI)-driven clinical initiatives in Canadian healthcare delivery. This scan provides a snapshot of verifiable, publicly available activity and a baseline for ongoing monitoring” (AI in Action: Transforming Clinical Care Across Canada Working Group, 2025, p. 1). This 2025 repository offers an amazing overview of current innovations being adopted across the country.

Interoperability and Documentation Burden

A continued push for a pan-Canadian interoperability roadmap aimed to ensure seamless data exchange across different healthcare systems, is a critical component for effective digital health solutions. Interoperability remains a national priority in 2025, driven by organizations such as Canada Health Infoway (2023) and provincial digital health agencies. Advances in standardized terminologies, semantic frameworks, and shared care records are directly impacting nursing workflow which would benefit significantly from seamless interoperability between systems and devices. Interoperable data ecosystems are essential for effective informatics.

For Canadian nurses, informatics innovation is closely tied to workforce sustainability. Improved interoperability reduces duplicate documentation, supports continuity of care across settings, and enables nurses to access comprehensive patient information regardless of jurisdiction or care environment. Nursing informatics leaders are actively involved in co-designing documentation systems that balance clinical accountability with workload realities and promoting interoperability and innovation.

In 2025, informatics innovations are deeply intertwined with nursing practice. Nurses are not only end-users of new technologies but essential contributors to their design, governance, and ethical application. A nursing informatics perspective emphasizes that successful innovation must enhance clinical judgment, reduce burden, protect patient trust, and strengthen the human dimensions of care. As informatics continues to evolve, nursing leadership will remain critical to ensuring that technology serves both patients and the profession. 2025 has shown strong innovative growth, but there is still a lot of room for improvement. Here’s to an innovative 2026!

References

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Amar, J., Liu, E., Breschi, A., Zhang, L., Kheradpour, P., Li, S., Lehmann, L., Giulianelli, A., Edwards, M., Nola, D., Mani, R., Vats, P., Tetreault, J., Chen, T.J. & McLean, C. (2025). Integrating genomics into multimodal EHR foundation models. arXiv:2510.23639. https://doi.org/10.48550/arXiv.2510.23639

Avramovic, S. & Mobahi, H. (2025). Redesigning a health informatics course for nursing students through AI-driven instruction and clinically contextualized assignments. Canadian Journal of Nursing Informatics, 20(4). https://cjni.net/journal/?p=15674

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