Skip to main content
The BMJ logoLink to The BMJ
. 2021 Jun 14;373:n1190. doi: 10.1136/bmj.n1190

How the nursing profession should adapt for a digital future

Richard G Booth 1 ,, Gillian Strudwick 2, Susan McBride 3, Siobhán O’Connor 4, Ana Laura Solano López 5
PMCID: PMC8201520

Abstract

Transformation into a digitally enabled profession will maximize the benefits to patient care, write Richard Booth and colleagues


Digital technologies increasingly affect nursing globally. Examples include the growing presence of artificial intelligence (AI) and robotic systems; society’s reliance on mobile, internet, and social media; and increasing dependence on telehealth and other virtual models of care, particularly in response to the covid-19 pandemic.

Despite substantial advances to date, challenges in nursing’s use of digital technology persist. A perennial concern is that nurses have generally not kept pace with rapid changes in digital technologies and their impact on society. This limits the potential benefits they bring to nursing practice and patient care. To respond to these challenges and prepare for the future, nursing must begin immediate transformation into a digitally enabled profession that can respond to the complex global challenges facing health systems and society.

Many exemplars show how digital technologies already bring benefit to nursing practice and education.1 For instance, telehealth programs where nurses provide daily monitoring, coaching, and triage of patients with several chronic diseases have helped reduce emergency department admissions.2 Mobile devices, in particular smartphones and health applications, are enabling nurses to offer remote advice on pain management to adolescent patients with cancer3 4 and supplement aspects of nursing education by providing innovative pedagogical solutions for content delivery and remote learning opportunities.5

The development and application to nursing of systems based on AI are still in their infancy. But preliminary evidence suggests virtual chatbots could play a part in streamlining communication with patients, and robots could increase the emotional and social support patients receive from nurses, while acknowledging inherent challenges such as data privacy, ethics, and cost effectiveness.6

Challenges persist

Digital technologies may, however, be viewed as a distraction from, or an unwelcome intrusion into, the hands-on caring role and therapeutic relationships that nurses have with patients and families.7 This purported incompatibility with traditional nursing ideals, such as compassionate care, may explain some nurses’ reluctance to adopt digital approaches to healthcare.8 9 In addition, nursing’s history was as structurally subordinate to other healthcare disciplines,10 and the profession is still cementing its relationship and leadership in health systems.

The specialty of nursing informatics has long advocated for the integration of technology to support the profession, but it has comparatively few practitioners globally. Nursing informaticians are predominantly based in the United States, where the discipline seems to have originated, but many other countries and regions are expanding their digital nursing workforce and involvement with informatics.11 12

Slow progress in some areas has been due to a lack of leadership and investment that supports nurses to champion and lead digital health initiatives. Globally, uncertainty remains regarding the next steps the nursing profession should take to increase and optimize its use of digital technology. This challenge is exacerbated by the global diversity of the profession, including unequal access to resources such as technological infrastructure maturity and expertise. Huge differences exist among countries and regions of the world in terms of the digitalization of healthcare processes, access to internet connectivity, and transparency of health information processes.

Selected technologies: benefits and challenges

The nursing literature contains many analyses of digital technologies used to support or extend the profession, including practice (eg, hospital information systems, electronic health records, monitoring systems, decision support, telehealth); education (eg, e-Learning, virtual reality, serious games); and, rehabilitative and personalized healthcare approaches (eg, assistive devices sensors, ambient assisted living).1 Table 1 summarizes the potential benefits, challenges, and implications of emerging innovations to practice.

Table 1.

Benefits, challenges, and implications of selected digital technologies in nursing

Digital technologies Examples of potential benefit Examples of current challenges Future implications
Artificial intelligence/big data Use in decision support systems can improve the identification of infection13
Pandemic/outbreak response using big data analytics to help in contact tracing and population health response14
Biases in current datasets can become ingrained in artificial intelligence (AI) algorithms15
Techniques are complex and may unintentionally reduce nursing involvement in the development of these systems16
Ethics and accountability of decisions generated by these systems, including transparency and privacy concerns17
AI based nursing in acute and primary care needs research
Policies needed on professional accountability
Educational and leadership competencies and opportunities related to AI and data analytics
Automation technologies (eg, robotics, drones) Robots can support people with cognitive, sensory, and motor impairments; help those who are ill or injured; support caregivers; and aid the clinical workforce18 Technologists, researchers, providers, and users must collaborate to ensure success18 Emerging innovations coupling AI and robotics will have intended and unintended changes to nursing practice and its professional culture
Nursing must assist in co-designing and developing these solutions to be complementary to practice
Cost-benefit analysis of developing complex health technologies that use planetary resources is needed
Assisted living technologies or “smart homes” technology Motion monitoring system in homes can help tailor care decisions for older adults with memory problems19 Privacy implications
Variety and turnover of different technologies makes identifying suitable devices challenging20
Technical and expense barriers21
Nurses should be involved in the design, development, and implementation of systems in collaboration with patients and carers
Clinical decision support systems Systems can detect infectious disease and trigger appropriate actions22 Over alerting clinicians results in alert fatigue and workarounds23
Owing to lack of research rigor, the impact and effectiveness in some clinical environments (eg, emergency departments) is unclear24
Nurses should be involved in design, development, and implementation
Consider usability when designing systems that improve rather than disrupt decision making and workflow
Electronic health records (EHRs) Nursing documentation is superior to paper based records in aspects of data completeness and structure, including legibility25 Weaknesses in documentation quality and quantity due to factors such as the time required or poor system or interface design25 Nurses need dedicated time and equipment and a supportive digital work culture
AI driven clinical decision support integrated into the EHRs to facilitate decision making will be important to look for intended and unintended consequences
Nursing leadership should redesign EHRs to reduce burden of documentation
Mobile health Coaching patients via applications can improve short term outcomes26 Perceived lack of affordability and reliability of mobile applications for clinical decision support27
Concerns over the professional image of nursing when using mHealth, particularly in hospital settings28
Need to develop policies and a professional culture that supports use of mobile devices in clinical practice. Where relevant, these should be integrated with EHRs and other related technologies
Telehealth/ telemedicine Beneficial in nursing homes during outbreaks of infectious disease—eg, during the covid-19 pandemic to reduce isolation and keep residents and nursing staff safe29 Nurses’ technical skills and negative attitudes towards telemedicine can be a barrier, as can their concerns around data privacy and confidentiality30 Nurses should support the co-design of telehealth systems and emerging virtual models of care with patients and carers
Personalized/ precision healthcare Treatment tailored to individual patients enables nurses to deliver more personalized care31 Pace of technological change and equity issues related to technology access could undermine precision health developments32 Nurses should advocate for patients and families to have equitable access to their genomic health data for use in personalized and precision healthcare solutions
Social media and online information (internet) Diverse pools of health information facilitate nursing processes and support patient and student education33 Quality and reliability of online health information, particularly on social media, varies, and it can be risky or unsafe34 Nurses should be educated about appropriate use of social media and online health information and support patients’ use of these technologies to improve their self-management
Virtual and augmented reality Virtual reality training can improve knowledge in nursing education35 and be used in pediatric and adult populations as a treatment tool or clinical intervention36 37 Can cause simulation sickness, including dizziness and visual disturbances38 Low cost devices and software should be developed by nurses and educators that can integrate with existing mobile, internet, and other digital technologies

The table is not exhaustive, but the diversity of topics researched shows the profession recognizes the value and challenges of digital technologies. Given the evidence, for the profession to make further progress we recommend five areas for focused and immediate action. These recommendations should be qualified in light of regional context and professional background owing to global heterogeneity in nursing and the inclusion of digital technologies into healthcare.

Reform nursing education

We must urgently create educational opportunities at undergraduate and graduate levels in informatics, digital health, co-design, implementation science, and data science.39 These should include opportunities to work with and learn from computing, engineering, and other interdisciplinary colleagues. For instance, nursing will need a critical mass of practitioners who understand how to use data science to inform the creation of nursing knowledge to support practice. 40 These practitioners will also need savviness and courage to lead the development of new models of patient care enabled by digital technologies.41 42

Determining how, where, and why technology like AI should be used to support practice is of immediate interest and a growing competency requirement in health sciences and informatics education.43 Nursing education should evolve its competencies and curriculums proactively for the increasing use of digital technologies in all areas of practice39 while incorporating novel pedagogical approaches—for example, immersive technologies such as virtual and augmented reality—to deliver aspects of simulation based education.44 45

Recently, the American Association of Colleges of Nursing released core competencies for nursing education, explicitly identifying informatics, social media, and emergent technologies and their impact on decision making and quality as critical to professional practice.46

Build nursing leadership in digital health

All levels of nursing leadership must advocate more actively for, and invest resources in, a profession that is both complemented and extended by digital technology. The profession needs to evolve its use of digital technology by continuing to champion and support nurses to become knowledgeable in, and generate new scientific knowledge on, data analytics, virtual models of care, and the co-design of digital solutions with patients, differences across contexts and regions permitting.

Advancement of leadership competencies in existing informatics technologies, such as clinical decision support systems, electronic health records, and mobile technologies, is also essential: these kinds of systems will undoubtedly come with increasing levels of AI functionality. Possessing a critical mass of nursing leaders who understand the intended and unintended consequences as well as opportunities of these kinds of technologies is vital to ensure the quality and safety of nursing.

The increasing presence and recognition of the importance of chief nursing informatics officers is a step in the right direction.47 Further, providing opportunities for nurses of all specialties to contribute to the development and implementation of digital health policies, locally and nationally, could increase future use of digital technologies in nursing.

Investigate artificial intelligence in nursing practice

The influence of AI on human decision making and labor are areas in need of immediate inquiry to support nursing practice for the next decade and beyond. AI technologies could provide the profession with huge benefits in data analytics and advanced clinical decision support.

Although many of the purported potential benefits of AI (eg, improved patient outcomes, streamlined workflow, improved efficiency) have yet to be fully shown in nursing research,6 it is inevitable that AI technologies will be used more regularly to support and extend nurses’ cognitive, decision making, and potentially labor functions.15

These opportunities bring new and dynamic practice considerations for nursing and interprofessional expertise. One example relates to the potential automation of inequity and injustice within systems and decision support tools containing AI48 49: self-evolving algorithms in systems sometimes unintentionally reinforce systemic inequities found in society.

Increased use of AI also brings novel policy, regulatory, legal, and ethical implications to the fore. The nursing profession must examine its role, processes, and knowledge against emerging ethical frameworks that explore the opportunities and risks that AI and similar innovations bring, while advocating for patient involvement in AI development and application. Floridi and colleagues offer tenets regarding AI development and the ethical considerations in using such innovations in their call to develop AI technology that “secures people’s trust, serves the public interest, and strengthens shared social responsibility.” 50 They also advocate that as guiding principles, AI should be used to enhance human agency, increase societal capacities, cultivate societal cohesion, and enable human self-realization, with an emphasis on instilling and reinforcing human dignity.50 Further research, funding, and thought leadership in this domain are needed to help support the development of new practice policy, regulatory frameworks, and ethical guidelines to guide nursing practice.

Re-envision nurse-patient relationships

The profession must reframe how nurses interact with and care for patients in a digital world. The sheer variety of “do-it-yourself” health and wellness applications (eg, personalized genetic testing services, virtual mental health support), mobile and social media applications (eg, mHealth, wearables, online communities of practice) and other virtual healthcare (eg, telemedicine, virtual consultations) options available to consumers is impressive.

All this may seem antithetical toward the traditionally espoused nursing role—therapeutic relationships in physical interactions—but patients are increasingly empowered, connected to the internet, and demanding personalized or self-management healthcare models that fit their busy and varied lifestyles.

To maximize its impact on patient care, the profession should continue to develop virtual care modalities that exploit internet and mobile technology, drawing on its experiences with telehealth and remote models of care.51 These care models might also be extended through virtual or augmented reality technologies or integrated with assisted living or “smart home” systems,52 and potentially other precision and personalized healthcare solutions that leverage genomic and other biometric data.

Care approaches, interpretations of privacy, and technological interoperability functionalities should be co-designed among the interprofessional healthcare team, patients, and carers53 and available where patients want them, ideally in both physical and digital realms. Deeper discussions and scientific research regarding access, cost, electronic resource use or wastage, and equity implications of the increasing digitalization of nurse-patient relationships will also need to be thoroughly explored.

Embrace digital practice

The profession requires a cultural shift. Its membership and leadership must demand the evolution of digital systems better to meet contemporary and emerging needs.

Too often, technology to support nursing is poorly configured, resourced, or not upgraded to respond to practice and societal trends. Nurses still commonly use practice systems that are lacking basic usability (eg, contributing to alert fatigue, reinforcing disruptive workflow processes) or generate added documentation burdens because of poor configuration and optimization.54

There is huge variation globally in access to, integration of, and sustainability of digital technology.55 56 57 Solutions vary and are context specific. Renewed awareness of digital technology’s use brought about by the covid-19 pandemic offers an impetus for change that nurses should embrace.

Tasks undertaken by nurses that do not add enough value to patient care present opportunities for partial or full divestment,58 and may be better integrated into future technology enabled processes or delivered by other care providers.

The profession should revisit cultural interpretations of how technology such as drones, robots, and other AI enabled systems can be considered complementary to nursing practice and process, rather than as competition or adversaries. Collaboration with technology developers, providers, and patients will be essential to ensure success.

Although some outdated nursing activities and processes made redundant or less relevant will likely be missed by some in the profession, digital technology provides opportunities to support new models of care and approaches to nursing practice. We must not allow cultural and historical interpretations of nursing to upend or impede progress.

How nursing can stay relevant

Nurses entering the profession today will undoubtedly witness substantive disruption and change from digital technology by the time they are mid-career.59 Without immediate action, the nursing profession stands to miss a remarkable opportunity to generate new roles, knowledge, and relationships within future health systems and societies saturated by digital technologies.

Nursing will continue to offer value and importance to healthcare systems in the coming decades. However, the profession must consider its role, knowledge, and relationships with technologies and patients to remain relevant in digitally enabled societies and healthcare systems and continue to provide compassionate care in a digital world. Without proactive strategic self-reflection, planning, and action, nursing will fail to control its trajectory across the chasm separating the past, present, and future of practice.

Key recommendations.

  • Nursing must accelerate the transformation to a digitally enabled profession by investing in informatics education, research, and practice

  • Nurses should upskill in data science and other digital health topics to ensure emerging technologies such as AI are developed appropriately and safe for nursing practice and patient care

  • Nursing must invest in and lead digital health developments and collaborate with others to develop and deliver digital tools that patients and the public need

  • Nurses should champion informatics across all areas of professional practice, create leadership opportunities in digital health, and inform health policy in this area

Competing interests: We have read and understood BMJ policy on declaration of interests and have no relevant interests to declare.

Provenance and peer review: Commissioned; not externally peer reviewed.

This article is part of a series commissioned by The BMJ for the World Innovation Summit for Health (WISH). The BMJ peer reviewed, edited, and made the decision to publish. The series, including open access fees, is funded by WISH.

References

  • 1. Krick T, Huter K, Domhoff D, Schmidt A, Rothgang H, Wolf-Ostermann K. Digital technology and nursing care: a scoping review on acceptance, effectiveness and efficiency studies of informal and formal care technologies. BMC Health Serv Res 2019;19:400. 10.1186/s12913-019-4238-3  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. van Berkel C, Almond P, Hughes C, Smith M, Horsfield D, Duckworth H. Retrospective observational study of the impact on emergency admission of telehealth at scale delivered in community care in Liverpool, UK. BMJ Open 2019;9:e028981. 10.1136/bmjopen-2019-028981  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Jibb LA, Stevens BJ, Nathan PC, et al. Implementation and preliminary effectiveness of a real-time pain management smartphone app for adolescents with cancer: A multicenter pilot clinical study. Pediatr Blood Cancer 2017;64:1-9. 10.1002/pbc.26554  [DOI] [PubMed] [Google Scholar]
  • 4. Jibb L, Nathan PC, Breakey V, et al. Pain Squad+ smartphone app to support real-time pain treatment for adolescents with cancer: protocol for a randomised controlled trial. BMJ Open 2020;10:e037251. 10.1136/bmjopen-2020-037251  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Chuang YH, Lai FC, Chang CC, Wan HT. Effects of a skill demonstration video delivered by smartphone on facilitating nursing students’ skill competencies and self-confidence: A randomized controlled trial study. Nurse Educ Today 2018;66:63-8. 10.1016/j.nedt.2018.03.027  [DOI] [PubMed] [Google Scholar]
  • 6. Buchanan C, Howitt ML, Wilson R, et al. Predicted influences of artificial intelligence on the domains of nursing: Scoping review. JMIR Nurs 2020;3:e23939. 10.2196/23939 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Robichaux C, Tietze M, Stokes F, McBride S. Reconceptualizing the electronic health record for a new decade: A caring technology? ANS Adv Nurs Sci 2019;42:193-205. 10.1097/ANS.0000000000000282  [DOI] [PubMed] [Google Scholar]
  • 8. Sandelowski M. (Ir)reconcilable differences? The debate concerning nursing and technology. Image J Nurs Sch 1997;29:169-74. 10.1111/j.1547-5069.1997.tb01552.x  [DOI] [PubMed] [Google Scholar]
  • 9. O’Keefe-McCarthy S. Technologically-mediated nursing care: the impact on moral agency. Nurs Ethics 2009;16:786-96. 10.1177/0969733009343249  [DOI] [PubMed] [Google Scholar]
  • 10. Fairman J, D’Antonio P. Reimagining nursing’s place in the history of clinical practice. J Hist Med Allied Sci 2008;63:435-46. 10.1093/jhmas/jrn018  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Hussey P, Adams E, Shaffer FA. Nursing informatics and leadership, an essential competency for a global priority: eHealth. Nurse Lead 2015;13:52-7. 10.1016/j.mnl.2015.07.002 [DOI] [Google Scholar]
  • 12. Atique S, Bautista JR, Block LJ, et al. A nursing informatics response to COVID-19: Perspectives from five regions of the world. J Adv Nurs 2020;76:2462-8. 10.1111/jan.14417  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Horng S, Sontag DA, Halpern Y, Jernite Y, Shapiro NI, Nathanson LA. Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning. PLoS One 2017;12:e0174708. 10.1371/journal.pone.0174708  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Chen C-M, Jyan H-W, Chien S-C, et al. Containing COVID-19 among 627,386 persons in contact with the Diamond Princess cruise ship passengers who disembarked in Taiwan: Big data analytics. J Med Internet Res 2020;22:e19540. 10.2196/19540  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Robert N. How artificial intelligence is changing nursing. Nurs Manage 2019;50:30-9. 10.1097/01.NUMA.0000578988.56622.21  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Topaz M, Pruinelli L. Big data and nursing: Implications for the future. Stud Health Technol Inform 2017;232:165-71. 10.3233/978-1-61499-738-2-165  [DOI] [PubMed] [Google Scholar]
  • 17. Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J 2019;6:94-8. 10.7861/futurehosp.6-2-94  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Riek LD. Healthcare robotics. Commun ACM 2017;60:68-78 10.1145/3127874 [DOI] [Google Scholar]
  • 19. Klemets J, Määttälä J, Hakala I. Integration of an in-home monitoring system into home care nurses’ workflow: A case study. Int J Med Inform 2019;123:29-36. 10.1016/j.ijmedinf.2018.12.006  [DOI] [PubMed] [Google Scholar]
  • 20. Fritz RL, Dermody G. A nurse-driven method for developing artificial intelligence in “smart” homes for aging-in-place. Nurs Outlook 2019;67:140-53. 10.1016/j.outlook.2018.11.004  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Gjestsen MT, Wiig S, Testad I. What are the key contextual factors when preparing for successful implementation of assistive living technology in primary elderly care? A case study from Norway. BMJ Open 2017;7:e015455. 10.1136/bmjopen-2016-015455  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Hoelscher D, McBride S. Usability and the rapid deployable infectious disease decision support system. Comput Inform Nurs 2020;38:490-9. 10.1097/CIN.0000000000000654  [DOI] [PubMed] [Google Scholar]
  • 23. McBride S, Tietze M, Hanley MA, Thomas L. Statewide study to assess nurses’ experiences with meaningful use-based electronic health records. CIN Comput Informatics . Comput Inform Nurs 2017;35:18-28. 10.1097/CIN.0000000000000290  [DOI] [PubMed] [Google Scholar]
  • 24. Bennett P, Hardiker NR. The use of computerized clinical decision support systems in emergency care: a substantive review of the literature. J Am Med Inform Assoc 2017;24:655-68. 10.1093/jamia/ocw151  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Akhu-Zaheya L, Al-Maaitah R, Bany Hani S. Quality of nursing documentation: Paper-based health records versus electronic-based health records. J Clin Nurs 2018;27:e578-89. 10.1111/jocn.14097  [DOI] [PubMed] [Google Scholar]
  • 26. Young HM, Miyamoto S, Dharmar M, Tang-Feldman Y. Nurse coaching and mobile health compared with usual care to improve diabetes self-efficacy for persons with type 2 diabetes: Randomized controlled trial. JMIR Mhealth Uhealth 2020;8:e16665. 10.2196/16665  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Dodson CH, Baker E, Bost K. Thematic analysis of nurse practitioners use of clinical decision support tools and clinical mobile apps for prescriptive purposes. J Am Assoc Nurse Pract 2019;31:522-6. 10.1097/JXX.0000000000000170  [DOI] [PubMed] [Google Scholar]
  • 28. O’Connor S, Chu CH, Thilo F, Lee JJ, Mather C, Topaz M. Professionalism in a digital and mobile world: A way forward for nursing. J Adv Nurs 2020;76:4-6. 10.1111/jan.14224  [DOI] [PubMed] [Google Scholar]
  • 29. Alexander GL, Powell KR, Deroche CB. An evaluation of telehealth expansion in U.S. nursing homes. J Am Med Inform Assoc 2021;28:342-8. 10.1093/jamia/ocaa253  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Koivunen M, Saranto K. Nursing professionals’ experiences of the facilitators and barriers to the use of telehealth applications: a systematic review of qualitative studies. Scand J Caring Sci 2018;32:24-44. 10.1111/scs.12445  [DOI] [PubMed] [Google Scholar]
  • 31. Fu MR, Kurnat-Thoma E, Starkweather A, et al. Precision health: A nursing perspective. Int J Nurs Sci 2019;7:5-12. 10.1016/j.ijnss.2019.12.008  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Starkweather A, Jacelon CS, Bakken S, et al. The use of technology to support precision health in nursing science. J Nurs Scholarsh 2019;51:614-23. 10.1111/jnu.12518  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. O’Connor S, Jolliffe S, Stanmore E, Renwick L, Booth R. Social media in nursing and midwifery education: A mixed study systematic review. J Adv Nurs 2018;74:2273-89. 10.1111/jan.13799  [DOI] [PubMed] [Google Scholar]
  • 34. Sun Y, Zhang Y, Gwizdka J, Trace CB. Consumer evaluation of the quality of online health information: Systematic literature review of relevant criteria and indicators. J Med Internet Res 2019;21:e12522. 10.2196/12522  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Woon APN, Mok WQ, Chieng YJS, et al. Effectiveness of virtual reality training in improving knowledge among nursing students: A systematic review, meta-analysis and meta-regression. Nurse Educ Today 2021;98:104655. 10.1016/j.nedt.2020.104655  [DOI] [PubMed] [Google Scholar]
  • 36. Eijlers R, Utens EMWJ, Staals LM, et al. Systematic review and meta-analysis of virtual reality in pediatrics. Anesth Analg 2019;129:1344-53. 10.1213/ANE.0000000000004165  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Kothgassner OD, Goreis A, Kafka JX, Van Eickels RL, Plener PL, Felnhofer A. Virtual reality exposure therapy for posttraumatic stress disorder (PTSD): a meta-analysis. Eur J Psychotraumatol 2019;10:1654782. 10.1080/20008198.2019.1654782  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Tyrrell R, Sarig-Bahat H, Williams K, et al. Simulator sickness in patients with neck pain and vestibular pathology during virtual reality tasks. Virtual Real (Walth Cross) 2018;22:211-9. 10.1007/s10055-017-0324-1 [DOI] [Google Scholar]
  • 39. Buchanan C, Howitt ML, Wilson R, et al. Predicted influences of artificial intelligence on nursing education: Scoping review. JMIR Nurs 2021;4:e23933. 10.2196/23933 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Brennan PF, Bakken S. Nursing needs big data and big data needs nursing. J Nurs Scholarsh 2015;47:477-84. 10.1111/jnu.12159  [DOI] [PubMed] [Google Scholar]
  • 41. Pepito JA, Locsin R. Can nurses remain relevant in a technologically advanced future? Int J Nurs Sci 2018;6:106-10. 10.1016/j.ijnss.2018.09.013  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. McBride SG, Tietze M, Fenton MV. Developing an applied informatics course for a doctor of nursing practice program. Nurse Educ 2013;38:37-42. 10.1097/NNE.0b013e318276df5d  [DOI] [PubMed] [Google Scholar]
  • 43. Sapci AH, Sapci HA. Artificial intelligence education and tools for medical and health informatics students: Systematic review. JMIR Med Educ 2020;6:e19285. 10.2196/19285  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. O’Connor S. Virtual reality and avatars in health care. Clin Nurs Res 2019;28:523-8. 10.1177/1054773819845824  [DOI] [PubMed] [Google Scholar]
  • 45. Chen FQ, Leng YF, Ge JF, et al. Effectiveness of virtual reality in nursing education: Meta-analysis. J Med Internet Res 2020;22:e18290. 10.2196/18290  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.The American Association of Colleges of Nursing. The essentials: Core competencies for professional nursing education. 2021. https://www.aacnnursing.org/Education-Resources/AACN-Essentials
  • 47. Kirby SB. Informatics leadership: the role of the CNIO. Nursing 2015;45:21-2. 10.1097/01.NURSE.0000462394.23939.8e  [DOI] [PubMed] [Google Scholar]
  • 48. Gianfrancesco MA, Tamang S, Yazdany J, Schmajuk G. Potential biases in machine learning algorithms using electronic health record data. JAMA Intern Med 2018;178:1544-7. 10.1001/jamainternmed.2018.3763  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science 2019;366:447-53. 10.1126/science.aax2342  [DOI] [PubMed] [Google Scholar]
  • 50. Floridi L, Cowls J, Beltrametti M, et al. AI4People—An ethical framework for a good AI Society: Opportunities, risks, principles, and recommendations. Minds Mach (Dordr) 2018;28:689-707. 10.1007/s11023-018-9482-5  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51. Choi YK, Lazar A, Demiris G, Thompson HJ. Emerging smart home technologies to facilitate engaging with aging. J Gerontol Nurs 2019;45:41-8. 10.3928/00989134-20191105-06  [DOI] [PubMed] [Google Scholar]
  • 52. Spiegel B, Fuller G, Lopez M, et al. Virtual reality for management of pain in hospitalized patients: A randomized comparative effectiveness trial. PLoS One 2019;14:e0219115. 10.1371/journal.pone.0219115  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. deBronkart D, Eysenbach G. Gimme my damn data (And let patients help!): The #gimmemydamndata manifesto. J Med Internet Res 2019;21:e17045. 10.2196/17045  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54. Yan Q, Jiang Z, Harbin Z, Tolbert PH, Davies MG. Exploring the relationship between electronic health records and provider burnout: A systematic review. J Am Med Inform Assoc 2021;28:1009-21. 10.1093/jamia/ocab009  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Konttila J, Siira H, Kyngäs H, et al. Healthcare professionals’ competence in digitalisation: A systematic review. J Clin Nurs 2019;28:745-61. 10.1111/jocn.14710  [DOI] [PubMed] [Google Scholar]
  • 56. Brown J, Pope N, Bosco AM, Mason J, Morgan A. Issues affecting nurses’ capability to use digital technology at work: An integrative review. J Clin Nurs 2020;29:2801-19. 10.1111/jocn.15321  [DOI] [PubMed] [Google Scholar]
  • 57. Ko M, Wagner L, Spetz J. Nursing home implementation of health information technology: Review of the literature finds inadequate investment in preparation, infrastructure, and training. Inquiry. J Heal Care Organ Provision 2018;55:46958018778902. 10.1177/0046958018778902  [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Booth R, Strudwick G, McMurray J, et al. The future of nursing informatics in a digitally-enabled world. In: Hussey P, Kennedy M, eds. Introduction to nursing informatics. Health informatics. Springer, 2021: 395-417. 10.1007/978-3-030-58740-6_16 [DOI] [Google Scholar]
  • 59. Coiera E. The fate of medicine in the time of AI. Lancet 2018;392:2331-2. 10.1016/S0140-6736(18)31925-1  [DOI] [PubMed] [Google Scholar]

Articles from The BMJ are provided here courtesy of BMJ Publishing Group

RESOURCES