The article for the review is titled “Impact of remote patient monitoring on clinical outcomes: an updated meta-analysis of randomized controlled trials”. The research was done by B. Noah, M. S. Keller, S. Mosadeghi, L. Stein, S. Johl, S. Delshad, V. C. Tashjian, D. Lew, J. T. Kwan, A. Jusufagic, and B. M. R. Spiegel. The article was published in 2018 in NPJ Digital Medicine. The purpose of the study was to assess randomized control trials (RCTs) and define the impact of remote patient monitoring (RPM) on clinical outcomes. The researchers applied a mixed approach involving a combination of quantitative and qualitative methods.
Other researchers investigating the effects of digital products on clinical outcomes used systematic review for sample and data collection. For instance, Han et al. (2019) examined 3 databases and 24 articles to evaluate patient portal interventions and synthesize current evidence (p.1). Hoque et al. (2016) researched MEDLINE, EMBASE, CENTRAL, and CINAHL electronic databases to assess clinical registries’ impact on the quality of care. The article for the critique examines prior knowledge of the topic and applies the quantitative data to evaluate RPM’s effectiveness. The method might be considered feasible as the research was based on a systematic review of existing reliable sources from the PubMed database to identify RCTs. The abstracted data was analyzed by two reviewers who utilized a standardized form to ensure the information’s accuracy and validity.
The method involved minor limitations related to the broad scope of sources, the use of a single database for article search, and limited data on non-invasive monitoring devices. The researchers managed to overcome the limitations by finding additional references in the reviewed articles. The limitations affected the research process and did not impact the use of data to answer a research question. The article utilized the studies published in peer-reviewed journals and selected 27 articles for final quantitative analysis out of 4348 titles considered (Noah et al., 2018, p. 2). Moreover, 16 high-quality articles were selected for qualitative review to determine RPM’s effects on outcomes. Such an approach helped to establish the validity of the results obtained from heterogeneous sources. The interpretation of the results via statistical analysis of data indicated that behavior models along with personalized coaching approach were the most effective RPM interventions. The results referring to the original problem of RPM impact on clinical outcomes were objective findings registered in a standardized form.
The authors answered the study’s main question as they discovered the effects of various RPM methods. The research systemized the existing data to provide a new understanding of the impact of different RPM techniques on patient outcomes. Thus, the work is significant for further research as it indicated the lack of evidence and the drawbacks of specific RPM tools. The article supports the conclusions of Vegesna et al. (2017), who demonstrated the impact of RPM on different patient populations and recommended further research before its “large-scale implementation” (p. 3). However, Hummel et al. (2019) indicated a definitely positive impact of RPM on cost-effectiveness and longer life expectancies. The researchers made a significant contribution to human knowledge since they determined the gaps existing in the studies of RPM interventions and emphasized the need for further RCTs.
The research did not produce any practical applications, but it provided valuable guidelines for future studies and exposed the potential barriers to RPM utilization. The article discovered several nursing implications related to the introduction of RPM devices. For instance, as a part of hypertension treatment, RPM proved to be effective only in patients over 55 years of age, so nurses may consider other methods to monitor younger patients. Additionally, the evidence on the impact of RPM in the clinical setting is insufficient, so digital health products should be implemented with caution before proper research is done. Overall, the article might be useful for medical researchers and practicing nurses as it offers a comprehensive systematic review of clinical data and the results of several RCTs. Moreover, it provides meaningful feedback and precautions for the future use of RPM and its clinical outcomes.
Han, H. R., Gleason, K. T., Sun, C. A., Miller, H. N., Kang, S. J., Chow, S., Anderson, R., Nagy, P., & Bauer, T. (2019). Using patient portals to improve patient outcomes: Systematic review. JMIR, 6(4). Web.
Hoque, D. E., Kumari, V., Ruseckaite, R., Romero, L., & Evans, S. M. (2016). Impact of clinical registries on quality of patient care and health outcomes: Protocol for a systematic review. BMJ Open. Web.
Hummel, J., P., Leipold, R. J., Amorosi, M. A., Bao, H., Deger, K. A., Jones, P. W., Kansal, A. R., Ott, L. S., Stern, S., Stein, K., Curtis, J. P., & Akar, J. G. (2019). Outcomes and costs of remote patient monitoring among patients with implanted cardiac defibrillators: An economic model based on the PREDICT RM database. Journal of Cardiovascular Electrophysiology, 30(7). Web.
Noah, B., Keller, M. S., Mosadeghi, S., Stein, L., Johl, S., Delshad, S., Tashjian, V. C., Lew, D., Kwan, J. T., Jusufagic, A., & Spiegel, B. M. R. (2018). Impact of remote patient monitoring on clinical outcomes: An updated meta-analysis of randomized controlled trials. NPJ Digital Med, 1. Web.
Vegesna, A., Tran, M., Angelaccio, M., & Arcona. S. (2017). Remote patient monitoring via non-invasive digital technologies: A systematic review. Telemedicine and e-Health, 23(1), 3–17. Web.