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Report on ETIH 2017
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Emerging technology in nursing – my journey

Sally Britnell, Nursing, Auckland University of Technology
An edited / concise version of this was first published in Kai Tiaki Nursing New Zealand, July 2017


One of my passions is computing and technology, and I have often asked myself - how can technology improve what I do?


In nursing, my goal has always been to provide the best patient care. As a new graduate nurse, I was time-poor and believed that learning about new technology stopped me from providing appropriate patient care. Today this opinion has taken a 180-degree turn, and I believe that appropriate emerging technology can assist us to become more time-rich and allow us to work smarter with a small investment of time up front to learn.


New technology in healthcare is emerging daily. Our national health strategy calls for innovation related to technology in health care and the development of a “smart system” (New Zealand Ministry of Health, 2016). With this in mind, I spend a proportion of my time developing ideas, systems, strategies and currently software to make the work that I do “smarter”. Some projects succeed, and others do not but what drives me to continue is, learning about what is possible and how this could make a difference in providing optimal patient care.


Throughout my career, I have heard colleagues or friends expressing fear of "big brother" computer systems which store and sometimes release personal staff or patient information. Often these types of privacy breach in are related the actions of a person who is interacting with health information rather than the system itself. For example, a New Zealand Nurses Organisation staff member accidentally released email addresses of members by replying to spam email (Thomas, 2016). While ownership and security of information are important, I believe that at times this overshadows the positive impact of technology in enhancing nursing care.


With this in mind, I would like to share some themes from the Emerging Technology in Healthcare (ETiH) Symposium run by Health Informatics New Zealand, 24th May 2017.


Sharing and analysing health data to predict healthcare needs


The notion of using data to anticipate needs, trends and outcomes in individual patient care has been a fundamental component in nursing for many years. The nursing process is an example of how we achieve this on a daily basis through assessment, diagnosis, analysis, planning, implementation and evaluation with the analysis of data traditionally the role of the healthcare professional (Lewis & Foley, 2014). One of the overarching themes during the Emerging Technology in Healthcare Symposium was automation of sharing, manipulating and analysing data from multiple sources to provide optimal patient outcomes.


I first became interested in streamlining health data to improve patient care when working in Infection Prevention and Control, where speed and accuracy in information collation, analysis and sharing had a visible impact on patient outcomes. I recall a patient who was transferred from an ED at another hospital; she arrived by car with a letter stating she had a non-communicable medical diagnosis and was assigned to a four-bed room with three other patients where she stayed for 36 hours. What was not evident at this time, was that during her time in the ED she shared a room for 72 hours with a person who had active Tuberculosis (TB). This information was received by phone 36 hours after she admitted and had contact with numerous patients and staff, she was immediately moved to a single negative pressure room, TB testing began and airborne precautions put in place.


The information required to manage this situation quickly ballooned with identification of links between demographics, family, social and health history, microbiology, admission dates, times, movements within rooms, departments and hospitals. A common stumbling block was that the information required was in silos and it took time, knowledge and perseverance to obtain this across patients, sources and modalities. Noticing that this data was fragmented highlighted the need for improvement in sharing, aggregation and analysis of data, while evident in literature this was also key concept discussed during ETiH (Asri, Mousannif, Moatassime, & Noel, 2015).


Data mining is a technique used to gather data for analysis and results of this can directly impact patient outcomes. A recent US study showed that an analysis of symptoms, procedures and treatment of patients (n = 4222) admitted to the Emergency Department (ED) with sepsis using a random forest machine learning algorithm to predict in-hospital mortality of patients outperformed traditional methods of predictions such as clinical decision rules (Taylor et al., 2016).


Dr David Dembo, the General Manager of Orion Healthcare, discussed a solution for management of hospital flow and patient tracking. While building overseas hospitals, the new trend is to include a control centre where patient and operational data is combined to allow real-time prediction of needs such as hospital capacity, staffing levels, types of illness and ultimately individual patient needs and outcomes. My immediate thought at this suggestion was of Star Trek and the bridge of the Enterprise. A quick Google search for "hospital command centre" revealed a YouTube video from John Hopkins in the United States (https://youtu.be/kBqKjlPGE6I) that shows how this type of system could improve patient care (John Hopkins Medicine, 2016).


Taking Healthcare to the People of New Zealand


A predominant theme of the New Zealand Health Strategy is providing healthcare that is closer to home (New Zealand Ministry of Health, 2016). Dr Lance O'Sullivan, a General Practitioner in Northland, presented his intuitive at ETiH which uses online mobile technology to bring healthcare to the children of Northland. He described an online a system using phone and tablet apps implemented in Northland schools where parents and school staff identify a need for healthcare and collect data such as health history and photographs and initiate an online GP consultation and any medications required couriered to their home. He reported that the Northland community using this service responded exceptionally well and he sees health outcomes for is patients improving daily.


Closer to home does not solely focus on geographical location, Amanda Malu (Chief Executive Officer) and Lois van Waardenburg (Chief Operating Officer) explained that Plunket has embraced mobile technology to provide accessible consultation using Facebook (Plunket NZ, 2017b). My immediate reaction was to think of Skype consultations shown on the “Embarrassing Bodies” TV show which made me feel very uncomfortable. However, Plunket used research to inform their decision. Modernising of their service began with a shift in focus by adopting an outside (family) in (Plunket) approach to ensure their consumer needs were met. During the consultation phase, they realised that social media was a common meeting place for their consumers and this has led to Plunket pioneering is the use of Facebook by offering individualised advice in real-time via Facebook personal messenger and live streaming of seminars.


I consider myself forward thinking and very open to change when it comes to technology in nursing, yet when social media and medical advice are in the same sentence, my immediate response is to fear the harm that misuse of social media could cause our consumers. Although recent research suggests that healthcare professionals use social media professionally by forming virtual communities of practice, interaction with consumers online is less predominant (Rolls, Hansen, Jackson, & Elliott, 2016). When I first heard about Plunket providing online consultation, I wondered if this service would stop people from getting seeking face-to-face healthcare. On investigation, the Plunket website displays a disclaimer explaining that advice via social media does not replace a consultation. However I needed to actively look for this and it was less evident on the Facebook Page (Plunket NZ, 2017a). While, Plunket has set guidelines around the online nurse-client relationship all nurses have a responsibility to work within policy such as Nursing Council Code of Conduct for nurses, Guidelines on Social Media and Electronic Communication and Professional Boundaries and the Health and Disability Commissioners Code of Rights when using social media (Health and Disability Commissioner, 1996; New Zealand Nursing Council, 2012a; 2012b; 2012c). I set a challenge for nurses who use the internet in both personal and professional situations to become familiar with these documents and your responsibility around social media.


Another advance to bring healthcare closer to home is technology that automates and streamlines preparation, packaging and checking pharmaceuticals. Greg Garratt, Founder and CEO, Medi-Point presented several solutions to minimise risk medication errors that were automated. One concept that stood out was vending machines for dispensing of over the counter medications emerging internationally. After some thought, both benefits and risks of this are apparent, however, I believe that accessible, accurate, consistent and timely information are required at purchase and would like to see more research around the safety of vending machines for OTC medications.


Changing our interaction with online health information


Information is power, the ease of access and plethora of general health information via the internet impacts healthcare delivery. The use of mobile technology and online information has led to positive changes in health behaviour and has increased patients ability to manage their own health needs in several studies (Dale et al., 2014; Dearnley, Haigh, & Fairhall, 2008; Kutzle, 2014). However, this has also had the opposite effect with patients reporting a lack of consistency and validation of online advice (Akerkar & Bichile, 2004; Pandey, Hasan, Dubey, & Sarangi, 2013). As a result, I believe the nurses’ role has changed as the internet has become an everyday source of health information. Historically, nurses have been isolated providers of healthcare information; we now have a role in assessing health literacy, access to information, validating sources and combining information to ensure patient understanding.


Nursing Informatics in New Zealand


After presenting at a Health Informatics New Zealand Conference several years ago and then becoming a part of both the Health and Nursing Informatics communities in New Zealand and Internationally, I now realise that nurses are a large proportion of the healthcare industry, however our voice in Health Informatics is disproportionately low. Nurses are in a unique position to influence, educate and advise on information technology in healthcare at individual, department, institution and national level and I encourage other nurses to become a part of the health informatics community and share what we achieve every day in the health informatics arena. A good place to start is through organisations conferences such as the National Nursing Informatics Conference or via Health Informatics New Zealand.


In conclusion, embracing technology in nursing care has assisted me in providing streamlined nursing care as well as engaging and educating our future nurses. I have now broadened the question I began this article with to include the healthcare and consumer with a view towards the future. Now I ask – What is possible? How can technology assist our patients to achieve optimal health?


References


Akerkar, S. M., & Bichile, L. S. (2004). Health information on the internet: patient empowerment or patient deceit? Indian Journal of Medical Sciences, 58(8), 321–326.


Asri, H., Mousannif, H., Moatassime, Al, H., & Noel, T. (2015). Big data in healthcare: Challenges and opportunities. Presented at the Proceedings of 2015 International Conference on Cloud Computing Technologies and Applications, CloudTech 2015. http://doi.org/10.1109/CloudTech.2015.7337020


Dale, L. P., Whittaker, R., Jiang, Y., Stewart, R., Rolleston, A., & Maddison, R. (2014). Improving coronary heart disease self-management using mobile technologies (Text4Heart): a randomised controlled trial protocol. Trials, 15(1), 71. http://doi.org/10.1186/1745-6215-15-71


Dearnley, C., Haigh, J., & Fairhall, J. (2008). Using mobile technologies for assessment and learning in practice settings: a case study. Nurse Education in Practice, 8(3), 197–204. http://doi.org/10.1016/j.nepr.2007.07.003


Health and Disability Commissioner. Code of Health and Disability Services Consumers' Rights (1996). Retrieved from http://www.hdc.org.nz/media/24833/leaflet%20code%20of%20rights.pdf


John Hopkins Medicine. (2016). John Hopkins Capacity Command Center (Vol. 2). Retrieved from https://www.youtube.com/watch?v=kBqKjlPGE6I&feature=youtu.be


Kutzle, J. (2014). The Use of 4G Android Tablets for Enhanced Patient Activation of Chronic Disease Self-Management in People with Heart Failure. Journal of Nursing & Care, 03(03). http://doi.org/10.4172/2167-1168.1000158


Lewis, P., & Foley, D. (2014). Health Assessment in Nursing.


New Zealand Ministry of Health. New Zealand Health Strategy. Wellintgon: Ministry of Health. Retrieved from http://www.health.govt.nz/system/files/documents/publications/new-zealand-health-strategy-futuredirection-2016-apr16.pdf


New Zealand Nursing Council. (2012a). Code of conduct for nurses. Wellington [N.Z.]: Nursing Council of New Zealand. Retrieved from http://www.nursingcouncil.org.nz/Nurses/Code-of-Conduct


New Zealand Nursing Council. (2012b). Guidelines: Professional Boundries. Retrieved May 29, 2017, from http://www.nursingcouncil.org.nz/Nurses/Code-of-Conduct


New Zealand Nursing Council. (2012c). Guidelines: Social Media and Electronic Communication. Retrieved May 29, 2017, from http://www.nursingcouncil.org.nz/Nurses/Code-of-Conduct


Pandey, A., Hasan, S., Dubey, D., & Sarangi, S. (2013). Smartphone apps as a source of cancer information: changing trends in health information-seeking behavior. Journal of Cancer Education : the Official Journal of the American Association for Cancer Education, 28(1), 138–142. http://doi.org/10.1007/s13187-012-0446-9


Plunket NZ. (2017a). Disclaimer. Retrieved May 26, 2017, from https://www.plunket.org.nz/footer-nav/disclaimer/


Plunket NZ. (2017b). Plunket Facebook Page. Retrieved May 26, 2017, from https://www.facebook.com/PlunketNZ/


Rolls, K., Hansen, M., Jackson, D., & Elliott, D. (2016). How health care professionals use social media to create virtual communities: An integrative review. Journal of Medical Internet Research, 18(6), e166. http://doi.org/10.2196/jmir.5312


Taylor, R. A., Pare, J. R., Venkatesh, A. K., Mowafi, H., Melnick, E. R., Fleischman, W., & Hall, M. K. (2016). Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach. Academic Emergency Medicine, 23(3), 269–278. http://doi.org/10.1111/acem.12876


Thomas, F. (2016, November 2). Emails of 47,000 NZNO members leaked to unknown address in info breach. NZ Doctor. Retrieved from https://www.nzdoctor.co.nz/news/2016/november-2016/02/emails-of-47,000-nzno-members-leaked-to-unknown-address-in-info-breach.aspx

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