Innovating Healthcare through Remote Monitoring

2017 ◽  
pp. 247-268
Author(s):  
Faustina Acheampong ◽  
Vivian Vimarlund
Keyword(s):  
Decision Making ◽  
Business Model ◽  
Remote Monitoring ◽  
Clinical Decision Making ◽  
Healthcare Delivery ◽  
Work Processes ◽  
Home Based ◽  
Patient Health ◽  
The Government ◽  
Remote Patient

Information technology has been suggested to improve patient health outcomes and reduce healthcare cost. This study explored the business model and effects of collaborative innovation between caregivers and patients on healthcare delivery through remote patient monitoring by interviewing caregivers and surveying atrial fibrillation patients. Findings indicate that remote monitoring enhanced early detection of potential risks and quality of clinical decision-making with patients feeling more empowered and involved in their own care. The remote monitoring system which consisted of a home-based ECG and a web-based service and was offered free to patients, brought together caregivers, patients, service provider and the government as actors. The introduction of remote monitoring increased the workload of caregivers and facilitation of timely diagnostics and decision-making were not realized. IT is an enabler of innovation in healthcare, but it must be integrated into work processes with a viable business model to realize potential benefits and sustain it.

Innovating Healthcare through Remote Monitoring

2016 ◽  
Vol 7 (1) ◽  
pp. 49-66 ◽  
Author(s):  
Faustina Acheampong ◽  
Vivian Vimarlund
Keyword(s):  
Decision Making ◽  
Business Model ◽  
Remote Monitoring ◽  
Clinical Decision Making ◽  
Healthcare Delivery ◽  
Clinical Decision ◽  
Remote Monitoring System ◽  
Home Based ◽  
The Government ◽  
Remote Patient

Information technology has been suggested to improve patient health outcomes and reduce healthcare cost. This study explored the business model and effects of collaborative innovation between caregivers and patients on healthcare delivery through remote patient monitoring by interviewing caregivers and surveying atrial fibrillation patients. Findings indicate that remote monitoring enhanced early detection of potential risks and quality of clinical decision-making with patients feeling more empowered and involved in their own care. The remote monitoring system which consisted of a home-based ECG and a web-based service and was offered free to patients, brought together caregivers, patients, service provider and the government as actors. The introduction of remote monitoring increased the workload of caregivers and facilitation of timely diagnostics and decision-making were not realized. IT is an enabler of innovation in healthcare, but it must be integrated into work processes with a viable business model to realize potential benefits and sustain it.

Effects of a Home-Based Monitoring Device on Innovation in Healthcare Delivery

2013 ◽  
pp. 316-334
Author(s):  
Faustina Acheampong ◽  
Vivian Vimarlund
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Healthcare Delivery ◽  
Clinical Decision ◽  
Home Based ◽  
Collaborative Innovation ◽  
Patient Health ◽  
Potential Benefits ◽  
Improve Patient

Information technology has been suggested to improve patient health outcomes and reduce the burden of care. In this study, we explored the effects of collaborative innovation between caregivers and patients on healthcare delivery as a consequence of the use of an IT-based device by patients with atrial fibrillation. Two cardiologists and two nurses were interviewed while questionnaires were mailed to 75 patients querying them about the use of a home-based ECG for remote monitoring. Findings indicated that the caregivers considered the device to enhance the quality of clinical decision-making. Patients found the device to be useful and felt more involved in their own care. However, the introduction of the device presented work overload for the caregivers. Thus, the facilitation of timely diagnostics and decision-making were not realized. IT is an enabler through which innovation in healthcare delivery can be realized, but it must be integrated into work practices to realize potential benefits.

scholarly journals Health Technology Assessment Development in Vietnam: A Qualitative Study of Current Progress, Barriers, Facilitators, and Future Strategies

2021 ◽  
Vol 18 (16) ◽  
pp. 8846
Author(s):  
Hwa-Young Lee ◽  
Thuy Thi-Thu Nguyen ◽  
Saeun Park ◽  
Van Minh Hoang ◽  
Woong-Han Kim
Keyword(s):  
Decision Making ◽  
Health Insurance ◽  
Health Technology Assessment ◽  
Technology Assessment ◽  
Clinical Decision Making ◽  
Policy Decision ◽  
Health Technology ◽  
Scientific Integrity ◽  
Data Repository ◽  
The Government

Introduction: To make more efficient use of limited resources, Vietnam incorporated health technology assessment (HTA) into the decision-making process for the health insurance benefit package in 2014. We evaluated progress in HTA institutionalization in Vietnam based on the theoretical framework developed by the National Institute for Health and Care Excellence and the Health Intervention and Technology Assessment Program, identified negative and conducive factors for HTA development, and finally suggested policy recommendations that fit the Vietnamese context. Methods: Semi-structured in-depth qualitative interviews were conducted between December 2017 and March and April 2018 with a purposive sample of 24 stakeholders involved in decision-making for health insurance reimbursement. We employed thematic analysis to examine themes within the data. Results: Despite a variety of activities (e.g., training and advising/mentoring) and a substantial level of output (e.g., policy statements, focal points assigned, and case studies/demonstration projects), Vietnam has not yet reached the policy decision stage based on HTA with scientific integrity and active stakeholder participation. Most respondents, except some clinicians, supported the use of HTA. The lack of capacity of human resources in the government sector and academia, the limited data infrastructure, the absence of guidelines, the government’s interest in immediate budget-saving, and public resistance were identified as barriers to the advancement of HTA. Conclusions: A structured data repository, guidelines based on the Vietnamese context for both policy decision-making at the central level and daily clinical decision-making at the micro-level, and integration of a participatory process into HTA are suggested as priorities for HTA institutionalization in Vietnam.

scholarly journals Rapid development of a Clinical Decision-Making Committee in a UK paediatric hospital during the COVID-19 pandemic

2020 ◽  
Vol 20 (2) ◽  
pp. 167-180 ◽  
Author(s):  
Rick Turnock ◽  
Will Weston ◽  
Nicki Murdock ◽  
Amel Alghrani ◽  
Conor Mallucci ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Ethical Decision Making ◽  
Rapid Development ◽  
Clinical Decision ◽  
Paediatric Hospital ◽  
Ethical Frameworks ◽  
National Guidance ◽  
The Government ◽  
Set Up

To date, the Government has not issued any national ethical guidance to support clinical decision-making in England during periods of potentially reduced healthcare resources in the context of the evolving COVID-19 1 pandemic at the time of writing. In the ensuing vacuum left by a lack of national guidance, ethical frameworks and approaches have been drafted by professional bodies, individual hospitals and trusts. It is clear that in delivering healthcare during this pandemic, more specific guidance is needed to ensure fair and consistent allocation policies, to attain public trust and confidence and to support clinicians so that decisions do not fall on them to make alone and unsupported. This article sets out how we in our institution, a UK tertiary and secondary level stand-alone paediatric provider Trust, set up a Clinical Decision-Making Committee to inform proactive clinical and ethical decision-making, to ensure that all patients are treated appropriately and fairly during these unprecedented times.

scholarly journals Clinician Preimplementation Perspectives of a Decision-Support Tool for the Prediction of Cardiac Arrhythmia Based on Machine Learning: Near-Live Feasibility and Qualitative Study (Preprint)

2021 ◽  
Author(s):  
Stina Matthiesen ◽  
Søren Zöga Diederichsen ◽  
Mikkel Klitzing Hartmann Hansen ◽  
Christina Villumsen ◽  
Mats Christian Højbjerg Lassen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Decision Support ◽  
Qualitative Study ◽  
Real World ◽  
Remote Monitoring ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Great Promise ◽  
Prediction Tool

BACKGROUND Artificial intelligence (AI), such as machine learning (ML), shows great promise for improving clinical decision-making in cardiac diseases by outperforming statistical-based models. However, few AI-based tools have been implemented in cardiology clinics because of the sociotechnical challenges during transitioning from algorithm development to real-world implementation. OBJECTIVE This study explored how an ML-based tool for predicting ventricular tachycardia and ventricular fibrillation (VT/VF) could support clinical decision-making in the remote monitoring of patients with an implantable cardioverter defibrillator (ICD). METHODS Seven experienced electrophysiologists participated in a near-live feasibility and qualitative study, which included walkthroughs of 5 blinded retrospective patient cases, use of the prediction tool, and questionnaires and interview questions. All sessions were video recorded, and sessions evaluating the prediction tool were transcribed verbatim. Data were analyzed through an inductive qualitative approach based on grounded theory. RESULTS The prediction tool was found to have potential for supporting decision-making in ICD remote monitoring by providing reassurance, increasing confidence, acting as a second opinion, reducing information search time, and enabling delegation of decisions to nurses and technicians. However, the prediction tool did not lead to changes in clinical action and was found less useful in cases where the quality of data was poor or when VT/VF predictions were found to be irrelevant for evaluating the patient. CONCLUSIONS When transitioning from AI development to testing its feasibility for clinical implementation, we need to consider the following: expectations must be aligned with the intended use of AI; trust in the prediction tool is likely to emerge from real-world use; and AI accuracy is relational and dependent on available information and local workflows. Addressing the sociotechnical gap between the development and implementation of clinical decision-support tools based on ML in cardiac care is essential for succeeding with adoption. It is suggested to include clinical end-users, clinical contexts, and workflows throughout the overall iterative approach to design, development, and implementation.

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