AB1232 RHEUMA-VOR: A PROOF-OF-CONCEPT NETWORK STUDY FOR THE IMPROVEMENT OF RHEUMATOLOGICAL HEALTH CARE THROUGH COORDINATED COOPERATION

Background In chronic neurological diseases, especially in multiple sclerosis (MS), clinical assessment of motor dysfunction is crucial to monitor the disease in patients. Traditional scales are not sensitive enough to detect slight changes. Video recordings of patient performance are more accurate and increase the reliability of severity ratings. When these recordings are automated, quantitative disability assessments by machine learning algorithms can be created. Creation of these algorithms involves non–health care professionals, which is a challenge for maintaining data privacy. However, autoencoders can address this issue. Objective The aim of this proof-of-concept study was to test whether coded frame vectors of autoencoders contain relevant information for analyzing videos of the motor performance of patients with MS. Methods In this study, 20 pre-rated videos of patients performing the finger-to-nose test were recorded. An autoencoder created encoded frame vectors from the original videos and decoded the videos again. The original and decoded videos were shown to 10 neurologists at an academic MS center in Basel, Switzerland. The neurologists tested whether the 200 videos were human-readable after decoding and rated the severity grade of each original and decoded video according to the Neurostatus-Expanded Disability Status Scale definitions of limb ataxia. Furthermore, the neurologists tested whether ratings were equivalent between the original and decoded videos. Results In total, 172 of 200 (86.0%) videos were of sufficient quality to be ratable. The intrarater agreement between the original and decoded videos was 0.317 (Cohen weighted kappa). The average difference in the ratings between the original and decoded videos was 0.26, in which the original videos were rated as more severe. The interrater agreement between the original videos was 0.459 and that between the decoded videos was 0.302. The agreement was higher when no deficits or very severe deficits were present. Conclusions The vast majority of videos (172/200, 86.0%) decoded by the autoencoder contained clinically relevant information and had fair intrarater agreement with the original videos. Autoencoders are a potential method for enabling the use of patient videos while preserving data privacy, especially when non–health-care professionals are involved.

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A Peer-Led Electronic Mental Health Recovery App in a Community-Based Public Mental Health Service: Pilot Trial (Preprint)

10.2196/preprints.12550 ◽

2018 ◽

Cited By ~ 1

Author(s):

Amelia Gulliver ◽

Michelle Banfield ◽

Alyssa R Morse ◽

Julia Reynolds ◽

Sarah Miller ◽

...

Keyword(s):

Mental Health ◽

Health Care ◽

Mental Health Service ◽

Health Service ◽

Public Mental Health ◽

Care Staff ◽

Mental Health Recovery ◽

Proof Of Concept ◽

Community Based ◽

Public Mental Health Service

BACKGROUND There is an increasing need for peer workers (people with lived experience of mental health problems who support others) to work alongside consumers to improve recovery and outcomes. In addition, new forms of technology (tablet or mobile apps) can deliver services in an engaging and innovative way. However, there is a need to evaluate interventions in real-world settings. OBJECTIVE This exploratory proof-of-concept study aimed to determine if a peer worker–led electronic mental health (e-mental health) recovery program is a feasible, acceptable, and effective adjunct to usual care for people with moderate-to-severe mental illness. METHODS Overall, 6 consumers and 5 health service staff participated in the evaluation of a peer-led recovery app delivered at a community-based public mental health service. The peer worker and other health professional staff invited attendees at the drop-in medication clinics to participate in the trial during June to August 2017. Following the intervention period, participants were also invited by the peer worker to complete the evaluation in a separate room with the researcher. Consumers were explicitly informed that participation in the research evaluation was entirely voluntary. Consumer evaluation measures at postintervention included recovery and views on the acceptability of the program and its delivery. Interviews with staff focused on the acceptability and feasibility of the app itself and integrating a peer worker into the health care service. RESULTS Consumer recruitment in the research component of the study (n=6) fell substantially short of the target number of participants (n=30). However, from those who participated, both staff and consumers were highly satisfied with the peer worker and somewhat satisfied with the app. Health care staff overall believed that the addition of the peer worker was highly beneficial to both the consumers and staff. CONCLUSIONS The preliminary findings from this proof-of-concept pilot study suggest that a peer-led program may be a feasible and acceptable method of working on recovery in this population. However, the e-mental health program did not appear feasible in this setting. In addition, recruitment was challenging in this particular group, and it is important to note that these study findings may not be generalizable. Despite this, ensuring familiarity of technology in the target population before implementing e-mental health interventions is likely to be of benefit.

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Faculty Opinions recommendation of Proof of concept: network and systems biology approaches aid in the discovery of potent anticancer drug combinations.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.7641956.7951058 ◽

2011 ◽

Author(s):

Jean Clairambault

Keyword(s):

Systems Biology ◽

Anticancer Drug ◽

Drug Combinations ◽

Proof Of Concept ◽

Concept Network

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Study protocol for assessing the user acceptance, safety and efficacy of a tablet-based workflow and decision support system with incorporated basal insulin algorithm for glycaemic management in participants with type 2 diabetes receiving home health care: A single-centre, open-label, uncontrolled proof-of-concept study

Contemporary Clinical Trials Communications ◽

10.1016/j.conctc.2020.100620 ◽

2020 ◽

Vol 19 ◽

pp. 100620

Author(s):

Angela Libiseller ◽

Julia Kopanz ◽

Katharina M. Lichtenegger ◽

Julia K. Mader ◽

Thomas Truskaller ◽

...

Keyword(s):

Type 2 Diabetes ◽

Health Care ◽

Home Health Care ◽

User Acceptance ◽

Home Health ◽

Proof Of Concept ◽

Single Centre ◽

Open Label ◽

Safety And Efficacy

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The feasibility, efficacy and efficiency of eHealth-supported pediatric asthma care implemented in daily clinical practice: a 6-month proof of concept study. (Preprint)

10.2196/preprints.24634 ◽

2020 ◽

Author(s):

Mattienne Kamp ◽

Pamela Hartgerink ◽

Jean MM Driessen ◽

Boony Thio ◽

Hermie Hermens ◽

...

Keyword(s):

Health Care ◽

Clinical Practice ◽

Early Detection ◽

Asthma Control ◽

Cost Efficiency ◽

Pediatric Asthma ◽

Self Management ◽

Intention To Use ◽

Proof Of Concept ◽

Asthma Care

BACKGROUND Strategies aimed at the early detection of loss of asthma control can effectively reduce the burden of the disease. However, broad implementation in clinical practice has not been accomplished so far. We are in need of research investigating the operationalization of eHealth pediatric asthma care in practice, revealing the most potential benefits in terms of adoption, efficiency and effectiveness. This may lay the foundation for targeted effectiveness studies with the lessons learned. OBJECTIVE The aim of this proof of concept study was to investigate the feasibility and explore the efficacy and cost-efficiency of an eHealth program implemented in daily clinical pediatric asthma practice. METHODS We designed an eHealth-supported pediatric asthma program facilitating early detection of loss of asthma control while increasing symptom awareness and self-management. Asthma control was monitored by objective home-measurements in the web-based Puffer-app to allow timely medical anticipation and prevent treatment delay. Children with moderate-to-severe asthma and a high medical consumption were asked to participate in the eHealth program for 6 months. The clinical feasibility was investigated by measures of participation and patient reported health and care outcomes. Moreover, the implementation experiences of the health care professionals (HCP’s) were evaluated in a focus group. Technical feasibility was investigated by measures of technology use, system usability and technology acceptance. The efficacy and cost-efficiency of the eHealth care were explored by comparing pre-post program differences in asthma outcomes (asthma control, lung function and therapy adherence) and medical consumption. RESULTS 35/41 children volunteered for participation, of which 30 finished the 6-month eHealth program. 75% of these children indicated that eHealth helped to control their asthma during the program. HCPs preferred making safe and substantiated medical decisions based on home measurements and real time communication with patients during symptoms. The Puffer-app scored highest on ease of use (77.1%) and intention to use (81.0%) and scored lowest on control over the system (64.4%) and enjoyment (65.6%). With an average patients’ time commitment of 15 minutes, eHealth care led to a 80% gross reduction in healthcare utilization, 8.6% increase (P =.40) in asthma control, 25.0% increase (P =.04) in the self-management level and a 20.4% improved (P =.02) therapy adherence. CONCLUSIONS Children and parents were eager to participate in the study, expressed a high intention to use the Puffer-app and indicated it was easy to work with. eHealth asthma care is feasible, enables safe remote care and is beneficial to the majority of asthmatic children in terms of health outcomes and health care utilization.

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AB1189 PICASO - THE PLATFORM FOR IMPROVED PERSONAL AND COORDINATED CARE OF CHRONICALLY ILL – SIX MONTHS RESULTS FROM A PROOF-OF-CONCEPT STUDY

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.1928 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 1885.1-1885

Author(s):

J. G. Richter ◽

G. Chehab ◽

M. Tomczak ◽

C. Schwartz ◽

E. Ricken ◽

...

Keyword(s):

Health Care ◽

Chronic Diseases ◽

Health Care System ◽

Health Monitoring ◽

User Satisfaction ◽

User Requirements ◽

Proof Of Concept ◽

Concept Study ◽

Management Processes ◽

Remote Health

Background:Cross-sectoral coordination of treatment plans and efficient management of patients with chronic diseases and co-morbidities are of great importance. In rheumatoid arthritis (RA) it is essential to orchestrate information available for a patient at various locations, to allow (cost) efficient data use, to optimize management processes and to avoid redundant diagnostics. The information and communication platform developed in the Horizon2020 funded PICASO project (www.picaso-project.eu) supports the management of patients and their data along the continuum of care, consisting of hospitals, outpatient departments, practices, other health service providers via remote health monitoring. The platform might empower patients to improve their self-management of their illnesses.Objectives:What technological expertise and resources do RA patients and physicians have, who are willing to participate in a proof-of-concept study using a modern ICT platform? What is the user satisfaction? What are platform`s clinical implications?Methods:PICASO pursued a user-centered design approach. Platform`s user requirements were determined through workshops and interviews with physicians from various disciplines, patients and other stakeholders in the health care system (e.g. data protection officers). The development was accompanied by so-called “expert walkthroughs” to ensure a user-friendly design. An evaluation concept assessing the usability of the applications, user satisfaction and clinical relevance of the platform was part of the 6-month proof-of-concept study with RA patients and their physicians (rheumatologists and family doctors). A positive ethics vote was obtained.Results:111 user requirements were identified and used to develop the platform. Conformity with the GDPR as well as national regulations were precisely adhered to. All developments are based on the new ‘Fast Healthcare Interoperability Resources’ standard enabling data exchange with other software systems in the healthcare sector. This offers many advantages, e.g. a semantic model for describing the smallest units in the health care system (e.g. medication intake times, diagnostic procedures). Thus information can be linked and made available across sectors. Data can remain with the data owner and role-specific data access is ensured.30 RA patients (80% female) participated, mean age was 58.6±10.8 years, disease duration 12.6±8.5 years, DAS28 2.6±0.9, average number of comorbidities 3.0±1.6. Patients’ IT-experience was heterogeneous. After 6 months evaluations showed a good platform acceptance with an overall rating of 2.3±1.1 (n=27, Likert scale (LS) 1-6) and evaluation of ‘ease of use’ at 2.3±1.2 (n=27, LS 1-6). Usability tests showed that for patients the presentation of (1) tasks to be performed for the management of their disease, (2) results from their remote health monitoring, and (3) patient-reported outcome instruments in a dashboard was clear and easy to understand. Time required for documentation and daily tasks was rated as appropriate by 75.9% of the patients. No major technical problems or impairments due to RA where experienced when using the dashboard. 8 physicians (37.5 % female) participated in the evaluation; overall the platform was rated at 2.2±0.5 (LS 1-6).Conclusion:The platform offers cross-sectoral orchestration of patient data and thus innovative capabilities for modern management processes (e.g. treat-to-target, tele-monitoring). The PICASO platform is available for RA patients as well as for other chronic diseases.Acknowledgments:This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 689209.Disclosure of Interests:None declared

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Development and Proof of Concept of an Audit Toolkit for the Safe Handling of Cytotoxic Drugs in Low- and Middle-Income Countries

JCO Global Oncology ◽

10.1200/go.21.00205 ◽

2021 ◽

pp. 1480-1489

Author(s):

Sandrine von Grünigen ◽

Ludivine Falaschi ◽

Nicolas Guichard ◽

Sandrine Fleury-Souverain ◽

Antoine Geissbühler ◽

...

Keyword(s):

Health Care ◽

Health Care Facilities ◽

Quality And Safety ◽

Proof Of Concept ◽

Middle Income ◽

Safe Handling ◽

Middle Income Countries ◽

Care Facilities ◽

Handling Practices ◽

Low And Middle Income

PURPOSE Chemotherapies are considered high-risk drugs for patient and staff safety. Considering the rising burden of cancer and the increasing use of chemotherapy drugs in low- and middle-income countries (LMICs), promoting continuous improvements in the safety and quality of practices in these settings is essential. This paper describes the development and proof of concept of a toolkit to audit chemotherapy handling practices in the health care facilities of LMICs. METHODS A steering committee defined the audit method and the toolkit content. Several checklists were developed to facilitate the audit and data collection. Items included in checklists were derived from key reference works on safe handling. Different tools were validated using Delphi surveys and expert reviews. Audits of pilot sites were performed to test the toolkit's applicability and relevance. RESULTS The toolkit contains a 134-item global assessment tool for the different processes at each step of the medication pathway and three step-specific observation checklists to assess different health workers' practices during the prescription, preparation, and administration of chemotherapies. The toolkit also proposes using a surface-wipe sampling method to measure any cytotoxic contamination of the immediate environment. The toolkit was tested in three teaching hospitals in Africa. CONCLUSION The toolkit developed was successfully implemented in a variety of LMIC settings, providing a comprehensive evaluation of the quality and safety of the chemotherapy drug handling practices in participating health care facilities. This toolkit can help facilities in LMICs to implement a new approach to continuously improving the quality and safety of their practices and ultimately ensure patient and staff safety.

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Performance Analysis of Healthcare data and its Implementation on NVIDIA GPU using CUDA-C

Journal of Drug Delivery and Therapeutics ◽

10.22270/jddt.v9i1-s.2447 ◽

2019 ◽

Vol 9 (1-s) ◽

pp. 361-363

Author(s):

Naseem Rao ◽

Safdar Tanweer

Keyword(s):

Data Mining ◽

Health Care ◽

Integrated Circuits ◽

Proof Of Concept ◽

Data Set ◽

Related Data ◽

Healthcare Data ◽

Application Specific Integrated Circuits ◽

Nvidia Gpu ◽

Application Specific

In this paper we show how commodity GPU based data mining can help classify various healthcare data in different groups faster than traditional CPU based systems. In addition such systems are cheaper than various ASIC (Application Specific Integrated Circuits) based solutions. Such faster clustering of data could provide useful insights for making successful decisions in case of emergency and outbreaks. Finally, we present conclusion based on our research done so far. In our work we used NVIDIA GPU for implementing an algorithm for healthcare data classification. Speech dissiliency and stuttering assessment can also be addressed through classification audio/speech samples using ANN, k-NN, SVM etc4. Such a faster and economical way to get such insights is of paramount importance. Specifically as a proof-of-concept we have implement k-means algorithm on health care related data set. Keywords: NVIDIA; GPU; ECG; CPU; ANN.

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