Remote Monitoring for Chronic Disease Management

2018 ◽  
Vol 10 (1) ◽  
pp. 43-58 ◽  
Author(s):  
Maki Ono ◽  
Niraj Varma
2011 ◽  
Vol 37 (4) ◽  
pp. 16-20 ◽  
Author(s):  
Bonnie J. Wakefield ◽  
John E. Holman ◽  
Annette Ray ◽  
Melody Scherubel

2021 ◽  
Vol 22 (2) ◽  
pp. 403
Author(s):  
Paulino Alvarez ◽  
Alex Sianis ◽  
Jessica Brown ◽  
Abbas Ali ◽  
Alexandros Briasoulis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniele Binci ◽  
Gabriele Palozzi ◽  
Francesco Scafarto

PurposeDigital transformation (DT) is a priority for the healthcare sector. In many countries, it is still considered in the early stages with an underestimation of its benefits and potentiality. Especially in Italy, little is known about the impact of digitalization – particularly of the Internet of Things (IoT) – on the healthcare sector, for example, in terms of clinician's jobs and patient's experience. Drawing from such premises, the paper aims to focus on an overlooked healthcare area related to the chronic heart diseases field and its relationship with DT. The authors aim at exploring and framing the main variables of remote Monitoring (RM) adoption as a specific archetype of healthcare digitalization, both on patients and medical staff level, by shedding some lights on its overall implementation.Design/methodology/approachThe authors empirically inquiry the RM adoption within the context of the Cardiology Department of the Casilino General Hospital of Rome. To answer our research question, the authors reconstruct the salient information by using induction-type reasoning, direct observation and interviewees with 12 key informants, as well as secondary sources analysis related to the hospital (internal documentation, presentations and technical reports).FindingsAccording to a socio-technical framework, the authors build a model composed of five main variables related to medical staff and patients. The authors classify such variables into an input-process-output (I-P-O) model. RM adoption driver represents the input; cultural digital divide, structure flexibility and reaction to change serve the process and finally, RM outcome stands for the output. All these factors, interacting together, contribute to understanding the RM adoption process for chronic disease management.Research limitations/implicationsThe authors' research presents two main limitations. The first one is related to using a qualitative method, which is less reliable in terms of replication and the interpretive role of researchers. The second limitation, connected to the first one, is related to the study's scale level, which focuses on a mono-centric consistent level of analysis.Practical implicationsThe paper offers a clear understanding of the RM attributes and a comprehensive view for improving the overall quality management of chronic diseases by suggesting that clinicians carefully evaluate both hard and soft variables when undertaking RM adoption decisions.Social implicationsRM technologies could impact on society both in ordinary situations, by preventing patient mobility issues and transport costs, and in extraordinary times (such as a pandemic), where telemedicine contributes to supporting hospitals in swapping in-person visits with remote controls, in order to minimize the risk of coronavirus disease (COVID-19) contagion or the spread of the virus.Originality/valueThe study enriches the knowledge and understanding of RM adoption within the healthcare sector. From a theoretical perspective, the authors contribute to the healthcare DT adoption debate by focusing on the main variables contributing to the DT process by considering both medical staff and patient's role. From a managerial perspective, the authors highlight the main issues for RM of chronic disease management to enable the transition toward its adoption. Such issues range from the need for awareness of the medical staff about RM advantages to the need for adapting the organizational structure and the training and education process of the patients.


2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Xinyan Yu ◽  
Qinghong Zhang ◽  
Dong Wang ◽  
Yan Feng ◽  
Fangjie Li

Objective: To study the value of the wearable single-lead remote monitoring device with the scatterplot in chronic disease management. Methods: dmitted into 435 residents accord with the inclusion criteria of 20 primary medical institutions of Yinchuan city, and grouped voluntarily by the implementation schemes were grouped voluntarily according to the implementation schemes. According to one of the three implementation schemes selected, the general practitioner guided the subjects to take on the wearable single-lead remote monitoring device, collecting and uploading the EEG data, then diagnosed and analyzed by the synchronously generated ECG scatterplot, finally, summarized the incidence and the categories, analyzed the differences among these three groups.Results: Among 435 subjects, there were 61 normal patients and 374 arrhythmias with the detection rate of 85.98%; and among the 1672 data collected, there were 606 normal data and 1066 arrhythmia with the detection rate of 63.76%; 880 data in total 333 cases with atrial premature beat; 442 data in total 215 cases with occasional ventricular premature beat; 37 data of 22 cases with frequent atrial beat; 65 data of 28 cases with frequent ventricular premature beat; 13 data of 6 cases with atrial fibrillation; 25 data of 15 cases with excitation conduction disorder; 2 data of 2 cases with atrial flutter; 31 data of 19 cases with ventricular tachycardia; 30 data of 16 cases with conduction block; and 14 data of 8 cases with Para systolic rhythm. comparing the detection rate of arrhythmia in three groups, the difference was not statistically significant (P>0.05). Conclusion: The wearable single-lead remote monitoring device with the scatterplot has high application value in cardiovascular chronic disease management.Its effectively screening, validly diagnosing and detailed classifying are helpful to the early intervention , and the protection of the patients’ lives.


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