by Mozart M. Telles, RN, BSN
April 1, 2022
According to Kilbourne et al. (2010), mental health units trail behind in performance measurements due to a lack of linked electronic health information. Advances in technologies, especially mobile and wearable devices, can significantly impact mental healthcare by collecting and analyzing data.
"Recent developments in sensor technology, online psychological therapy, and remote video consultation, mobile applications ('apps') and gaming all present real opportunities to engage and empower patients and create novel approaches to both the assessment and intervention for mental health problems" (Hollis et al., 2015).
This project aims to implement a commercial-grade, cost-efficient wearable activity tracking system, like Fitbit, StepWatch, and others, into the mental health units to improve patient activities data logging.
Instituting an activity tracker reduces the need for an individual (BRT/Nurse) to actively check patient activities, thus reducing waste of human resources, consequently improving the outcomes by improving processes. Moreover, these devices can monitor patient activities and deliver results into an electronic database accessible by psychiatrists, psychologists, nurses, social workers, mental health providers, mental health programs, payers, and other stakeholders.
Patient-care efficiencies this project is aimed at improving.
Currently, psychiatric treatment facilities use an archaic system. Patient activity tracking in mental health units is costly and ineffective. They employ a Behavioral Resource Technician (BRT), who checks a patient's activity on a paper log at 15 minutes intervals. These checks are annotated in a paper chart and usually do not get transcribed into an electronic database format (mainly, the Nurse Manager, Nurse Informaticist or IT scans the sheets as pictures or PDF format and archives them in an electronic folder for further evaluation, which stored as a picture instead of workable data). This informal and flawed feedback needs to be supplemented and improved.
How would this improvement occur?
McGonigle and Mastrian (2022, pp. 611-624) discuss in chapter 21 that the world is heading toward AIoT and robotics. The proposal of this paper is nothing short of that. These small devices are as smart as they can be. They have sensors and computational capacity to evaluate data in an effort to determine if a patient is going into cardiac arrest, dehydrated, sedentary, or having respiratory issues and transmit an alert to concerned parties, i.e., providers. These devices are precise enough to prompt providers' actions (Alharbi et al., 2016)
Managers, nursing informaticists, IT, and nurses should brainstorm the best option for integrating the system. The data should be safely transmitted to the data center while mitigating errors. A study of internet security should be developed to analyze the risk and benefit of data transmission via the internet versus manually hooking up the devices via Bluetooth or cable. Many studies show that the system is feasible, low cost, easily accessible, and effective.
A study looking into the feasibility of activity trackers to log patient activities found that using activity trackers, like Fitbit and Stepwatch, is feasible, demonstrating that consumer-grade electronics are cheap, acceptable, and comparable to the gold standards in measuring mobility (Estrada-Codecido et al., 2020).
Using simple consumer-grade electronic equipment that is reasonably priced, we can improve the efficiency of data collection resulting in patient satisfaction and improved patient quality. Currently, the price of a Fitbit on Amazon.com goes from $34.00 up to $159.00 for specific models. The equipment can be programmed to send activity information to a hub or account where the data can be recovered by a nurse informaticist or IT department.
Armstrong et al. (2021) analyzed the "Youth and Provider Perspectives on Behavior-Tracking Mobile Apps," his research found that integrating mobile health with psychotherapy can make the treatment easy and more accessible for all stakeholders.
A randomized trial study (Vandelanotte et al., 2018) examined whether a web-based computer-tailored intervention could be improved by using a Fitbit as an alternative to self-reporting activities. Two hundred forty-three patients participated in a linear-mixed analysis model for three months. The researchers found that integrating the Fitbit into the intervention has significantly increased the intervention's effectiveness. Hence, we can assert that the Fitbit effectively gathers patient activity and improves data gathering techniques using the data.
Identify the technologies required to implement this project and explain why
The primary piece of technology implemented into this project is the addition of a consumer-grade activity tracker, like Fitbit, Oura Smart Ring, or any other activity tracker, into the lives of patients currently in treatment at mental health hospitals. The electronic component of this technology is a reasonably priced piece of equipment that can be connected to existing infrastructure, like the local intranet or Bluetooth ports, and data can be recovered through those means.
Identify the project team (by roles) and explain how you would incorporate the nurse informaticist in the project team?
For the project to be successful, a team would carry out its various functions (Nelson & Staggers, 2018). At the head of the project would be nurse management, who has the power to make decisions and allocate budgets for projects (Mosier et al., 2019). They are the ones that decide if a project is feasible for the organization at the time. Second, working together with a nurse informaticist, the nurse manager can inquire about data collection, storage, and dissemination (Mosier et al., 2019). The nurse informaticist would work closely with the IT department to evaluate the system's rigor and security, working as a project manager and quality manager.
According to Sipes (2016): "Project management is one of the most important essentials identified since it impacts all areas of NI skills and provides an organizing framework for processes and projects including skills such as design, planning, implementation, follow-up, and evaluation."
The nurse informaticist would be able to assess the usefulness, errors, and improvement in the healthcare nursing informatics system (Mcgonigle & Mastrian, 2022).
The integrated nursing information system will improve healthcare flexibility by reducing mental health workers’ charting load.
Conclusion
The inclusion of a consumer-grade activity tracker in psychiatric treatment facilities will increase patient satisfaction and reduce costs related to manually tracking patients with a specialized BRT. The nurse informaticist is a key component of the management team, and they are well suited to be the project manager for an assignment of such significance.
References
Alharbi, M., Bauman, A., Neubeck, L., & Gallagher, R. (2016). Validation of Fitbit-Flex as a measure of free-living physical activity in a community-based phase III cardiac rehabilitation population. European Journal of Preventive Cardiology, 23(14), 1476–1485. https://doi.org/10.1177/2047487316634883
Armstrong, C. C., Odukoya, E. J., Sundaramurthy, K., & Darrow, S. M. (2021). Youth and Provider Perspectives on Behavior-Tracking Mobile Apps: Qualitative Analysis. JMIR Mental Health, 8(4), e24482. https://doi.org/10.2196/24482
Baystate HR. (2022, March). Pedi ED BRT. Baystate Health Careers. https://baystatehealthjobs.com/job/pedi-ed-brt-r16034/
Estrada-Codecido, J., Lee, J., Chignell, M., & Whyne, C. (2020). P107: Use of activity trackers to count steps of older emergency department patients: a feasibility and validity study. CJEM, 22(S1), S103–S103. https://doi.org/10.1017/cem.2020.313
Hollis, C., Morriss, R., Martin, J., Amani, S., Cotton, R., Denis, M., & Lewis, S. (2015). Technological innovations in mental healthcare: harnessing the digital revolution. British Journal of Psychiatry, 206(4), 263–265. https://doi.org/10.1192/bjp.bp.113.142612
Kilbourne, A. M., Keyser, D., & Pincus, H. A. (2010). Challenges and Opportunities in Measuring the Quality of Mental Health Care. The Canadian Journal of Psychiatry, 55(9), 549–557. https://doi.org/10.1177/070674371005500903
Mcgonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed., pp. 611–624). Jones & Bartlett Learning.
Mosier, S., Roberts, Wm. D., & Englebright, J. (2019). A Systems-Level Method for Developing Nursing Informatics Solutions. JONA: The Journal of Nursing Administration, 49(11), 543–548. https://doi.org/10.1097/nna.0000000000000815
Nelson, R., & Staggers, N. (2018). Health informatics: An Interprofessional Approach (2nd ed.). Elsevier.
Sipes, C. (2016). Project Management: Essential Skill of Nurse Informaticists. Studies in Health Technology and Informatics, 225, 252–256.
Vandelanotte, C., Duncan, M. J., Maher, C. A., Schoeppe, S., Rebar, A. L., Power, D. A., Short, C. E., Doran, C. M., Hayman, M. J., & Alley, S. J. (2018). The Effectiveness of a Web-Based Computer-Tailored Physical Activity Intervention Using Fitbit Activity Trackers: Randomized Trial. Journal of Medical Internet Research, 20(12), e11321. https://doi.org/10.2196/11321
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