Connecting clinical care and research: Single-source with x4T – Process design, architecture, and use cases

AbstractClinical research and routine care documentation have traditionally been performed in a dual-source approach, where data is collected redundantly and maintained in separated systems. The generic x4T single-source process removes redundant steps and is adoptable to specific types of studies. In support of the various processes, we have designed and implemented an architecture called x4T based on CDISC ODM. The software has been deployed in three different use cases containing up to 3976 subjects until now and allows real-time access to live data from routine care documentation systems.

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Bridging the divide between clinical research and clinical care in oncology: An integrated real-world evidence generation platform

Digital Health ◽

10.1177/20552076211059975 ◽

2021 ◽

Vol 7 ◽

pp. 205520762110599

Author(s):

Ariel B. Bourla ◽

Neal J. Meropol

Keyword(s):

Clinical Research ◽

Real World ◽

Clinical Care ◽

Routine Care ◽

Trial Participation ◽

Real World Data ◽

Regulatory Decision ◽

Real World Evidence ◽

Level Data ◽

Patient Health

Real world data (RWD) are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources; real-world evidence (RWE) generated by RWD analyses can become an important component of drug development programs and, potentially, regulatory decision-making. As a RWD source, electronic health records (EHRs) can now provide patient-level data at unparalleled depth and granularity. We propose a RWE generation framework that could maximize the synergy between RWD and prospective clinical trials by capitalizing on an emerging data curation infrastructure that may be applied to both retrospective and prospective research. In this platform, centralized data collection and monitoring could be enabled via routine EHR use, and seamlessly integrated with select intentional data capture during prospective study periods. By bridging the divide between routine care and clinical research, this integrated platform aggregates retrospective and prospective data, collected both routinely and intentionally. This approach makes clinical trial participation more available to patients, increasing the potential depth of data, representativeness and efficiency of clinical research.

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Unlocking Data for Clinical Research – The German i2b2 Experience

Applied Clinical Informatics ◽

10.4338/aci-2010-09-cr-0051 ◽

2011 ◽

Vol 02 (01) ◽

pp. 116-117 ◽

Cited By ~ 21

Author(s):

S. Mate ◽

K Helbing ◽

U. Sax ◽

H.U. Prokosch ◽

T. Ganslandt

Keyword(s):

Data Protection ◽

Clinical Care ◽

Use Cases ◽

Entry Barriers ◽

Objective Data ◽

Query Performance ◽

Data Query ◽

Medical Standard ◽

Data Collections ◽

Cdisc Odm

Summary Objective: Data from clinical care is increasingly being used for research purposes. The i2b2 platform has been introduced in some US research communities as a tool for data integration and querying by clinical users. The purpose of this project was to assess the applicability of i2b2 in Germany regarding use cases, functionality and integration with privacy enhancing tools. Methods: A set of four research usage scenarios was chosen, including the transformation and import of ontology and fact data from existing clinical data collections into i2b2 v1.4 instances. Query performance was measured in comparison to native SQL queries. A setup and administration tool for i2b2 was developed. An extraction tool for CDISC ODM data was programmed. Interfaces for the TMF privacy enhancing tools (PID Generator, Pseudonymization Service) were implemented. Results: Data could be imported in all tested scenarios from various source systems, including the generation of i2b2 ontology definitions. The integration of TMF privacy enhancing tools was possible without modification of the platform. Limitations were found regarding query performance in comparison to native SQL and certain temporal queries. Conclusions: i2b2 is a viable platform for data query tasks in use cases typical for networked medical research in Germany. The integration of privacy enhancing tools facilitates the use of i2b2 within established data protection concepts. Entry barriers should be lowered by providing tools for simplified setup and import of medical standard formats like CDISC ODM.

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Real-time Voltage Stability Assessment and Enhancement: Implementation and Use Cases

2020 AEIT International Annual Conference (AEIT) ◽

10.23919/aeit50178.2020.9241133 ◽

2020 ◽

Author(s):

Gilburt Chiang ◽

Simon Wyatt ◽

Pat Causgrove ◽

Hua Li

Keyword(s):

Real Time ◽

Voltage Stability ◽

Use Cases ◽

Stability Assessment

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Patient Experience in Home Respiratory Therapies: Where We Are and Where to Go

Journal of Clinical Medicine ◽

10.3390/jcm8040555 ◽

2019 ◽

Vol 8 (4) ◽

pp. 555 ◽

Cited By ~ 5

Author(s):

Cátia Caneiras ◽

Cristina Jácome ◽

Sagrario Mayoralas-Alises ◽

José Ramon Calvo ◽

João Almeida Fonseca ◽

...

Keyword(s):

Clinical Research ◽

Patient Experience ◽

Clinical Care ◽

Research Priorities ◽

Specific Patient ◽

Quality Healthcare ◽

Body Of Knowledge ◽

Number Of Patients ◽

Patient Reported ◽

System Sustainability

The increasing number of patients receiving home respiratory therapy (HRT) is imposing a major impact on routine clinical care and healthcare system sustainability. The current challenge is to continue to guarantee access to HRT while maintaining the quality of care. The patient experience is a cornerstone of high-quality healthcare and an emergent area of clinical research. This review approaches the assessment of the patient experience in the context of HRT while highlighting the European contribution to this body of knowledge. This review demonstrates that research in this area is still limited, with no example of a prescription model that incorporates the patient experience as an outcome and no specific patient-reported experience measures (PREMs) available. This work also shows that Europe is leading the research on HRT provision. The development of a specific PREM and the integration of PREMs into the assessment of prescription models should be clinical research priorities in the next several years.

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Dose performance and image quality: Dual source CT versus single source CT in cardiac CT angiography

European Journal of Radiology ◽

10.1016/j.ejrad.2008.08.010 ◽

2009 ◽

Vol 72 (3) ◽

pp. 396-400 ◽

Cited By ~ 20

Author(s):

Min Wang ◽

Heng-Tao Qi ◽

Xi-Ming Wang ◽

Tao Wang ◽

Jiu-Hong Chen ◽

...

Keyword(s):

Image Quality ◽

Ct Angiography ◽

Cardiac Ct ◽

Dual Source Ct ◽

Single Source ◽

Cardiac Ct Angiography ◽

Dual Source

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Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases

npj Digital Medicine ◽

10.1038/s41746-021-00459-8 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Ania Syrowatka ◽

Masha Kuznetsova ◽

Ava Alsubai ◽

Adam L. Beckman ◽

Paul A. Bain ◽

...

Keyword(s):

Public Health ◽

Artificial Intelligence ◽

Real Time ◽

Scoping Review ◽

Grey Literature ◽

Use Cases ◽

Outbreak Detection ◽

Response To Treatment ◽

Pandemic Preparedness ◽

Modeling Approaches

AbstractArtificial intelligence (AI) represents a valuable tool that could be widely used to inform clinical and public health decision-making to effectively manage the impacts of a pandemic. The objective of this scoping review was to identify the key use cases for involving AI for pandemic preparedness and response from the peer-reviewed, preprint, and grey literature. The data synthesis had two parts: an in-depth review of studies that leveraged machine learning (ML) techniques and a limited review of studies that applied traditional modeling approaches. ML applications from the in-depth review were categorized into use cases related to public health and clinical practice, and narratively synthesized. One hundred eighty-three articles met the inclusion criteria for the in-depth review. Six key use cases were identified: forecasting infectious disease dynamics and effects of interventions; surveillance and outbreak detection; real-time monitoring of adherence to public health recommendations; real-time detection of influenza-like illness; triage and timely diagnosis of infections; and prognosis of illness and response to treatment. Data sources and types of ML that were useful varied by use case. The search identified 1167 articles that reported on traditional modeling approaches, which highlighted additional areas where ML could be leveraged for improving the accuracy of estimations or projections. Important ML-based solutions have been developed in response to pandemics, and particularly for COVID-19 but few were optimized for practical application early in the pandemic. These findings can support policymakers, clinicians, and other stakeholders in prioritizing research and development to support operationalization of AI for future pandemics.

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Perspectives and experiences of patients and healthcare professionals with geriatric assessment in chronic kidney disease: a qualitative study

BMC Nephrology ◽

10.1186/s12882-020-02206-9 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Carlijn G. N. Voorend ◽

Noeleen C. Berkhout-Byrne ◽

Yvette Meuleman ◽

Simon P. Mooijaart ◽

Willem Jan W. Bos ◽

...

Keyword(s):

Kidney Disease ◽

Qualitative Study ◽

Clinical Outcomes ◽

Geriatric Assessment ◽

Clinical Care ◽

Treatment Options ◽

Routine Care ◽

Treatment Team ◽

Dutch Hospital ◽

Additional Support

Abstract Background Older patients with end-stage kidney disease (ESKD) often live with unidentified frailty and multimorbidity. Despite guideline recommendations, geriatric assessment is not part of standard clinical care, resulting in a missed opportunity to enhance (clinical) outcomes including quality of life in these patients. To develop routine geriatric assessment programs for patients approaching ESKD, it is crucial to understand patients’ and professionals’ experiences with and perspectives about the benefits, facilitators and barriers for geriatric assessment. Methods In this qualitative study, semi-structured focus group discussions were conducted with ESKD patients, caregivers and professionals. Participants were purposively sampled from three Dutch hospital-based study- and routine care initiatives involving geriatric assessment for (pre-)ESKD care. Transcripts were analysed inductively using thematic analysis. Results In six focus-groups, participants (n = 47) demonstrated four major themes: (1) Perceived characteristics of the older (pre)ESKD patient group. Patients and professionals recognized increased vulnerability and (cognitive) comorbidity, which is often unrelated to calendar age. Both believed that often patients are in need of additional support in various geriatric domains. (2) Experiences with geriatric assessment. Patients regarded the content and the time spent on the geriatric assessment predominantly positive. Professionals emphasized that assessment creates awareness among the whole treatment team for cognitive and social problems, shifting the focus from mainly somatic to multidimensional problems. Outcomes of geriatric assessment were observed to enhance a dialogue on suitability of treatment options, (re)adjust treatment and provide/seek additional (social) support. (3) Barriers and facilitators for implementation of geriatric assessment in routine care. Discussed barriers included lack of communication about goals and interpretation of geriatric assessment, burden for patients, illiteracy, and organizational aspects. Major facilitators are good multidisciplinary cooperation, involvement of geriatrics and multidisciplinary team meetings. (4) Desired characteristics of a suitable geriatric assessment concerned the scope and use of tests and timing of assessment. Conclusions Patients and professionals were positive about using geriatric assessment in routine nephrology care. Implementation seems achievable, once barriers are overcome and facilitators are endorsed. Geriatric assessment in routine care appears promising to improve (clinical) outcomes in patients approaching ESKD.

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On the Impact and Mitigation of Signal Crosstalk in Ground-Based and Low Altitude Airborne GNSS-R

Remote Sensing ◽

10.3390/rs13061085 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1085

Author(s):

Corentin Lubeigt ◽

Lorenzo Ortega ◽

Jordi Vilà-Valls ◽

Laurent Lestarquit ◽

Eric Chaumette

Keyword(s):

Specular Reflection ◽

Signal Amplitude ◽

Satellite System ◽

Mitigation Strategies ◽

Variance Estimator ◽

Single Source ◽

Dual Source ◽

Reflected Signal ◽

The Impact ◽

Signal Crosstalk

Global Navigation Satellite System Reflectometry (GNSS-R) is a powerful way to retrieve information from a reflecting surface by exploiting GNSS as signals of opportunity. In dual antenna conventional GNSS-R architectures, the reflected signal is correlated with a clean replica to obtain the specular reflection point delay and Doppler estimates, which are further processed to obtain the GNSS-R product of interest. An important problem that may appear for low elevation satellites is signal crosstalk, that is the direct line-of-sight signal leaks into the antenna dedicated to the reflected signal. Such crosstalk may degrade the overall system performance if both signals are very close in time, similar to multipath in standard GNSS receivers, the reason why mitigation strategies must be accounted for. In this article: (i) we first provide a geometrical analysis to justify that the estimation performance is only affected for low height receivers; (ii) then, we analyze the impact of crosstalk if not taken into account, by comparing the single source conditional maximum likelihood estimator (CMLE) performance in a dual source context with the corresponding Cramér–Rao bound (CRB); (iii) we discuss dual source estimators as a possible mitigation strategy; and (iv) we investigate the performance of the so-called variance estimator, which is designed to eliminate the coherent signal part, compared to both the CRB and non-coherent dual source estimators. Simulation results are provided for representative GNSS signals to support the discussion. From this analysis, it is found that: (i) for low enough reflected-to-direct signal amplitude ratios (RDR), the crosstalk has no impact on standard single source CMLEs; (ii) for high enough signal-to-noise ratios (SNR), the dual source estimators are efficient irrespective of the RDR, then being a promising solution for any reflected signal scenario; (iii) non-coherent dual source estimators are also efficient at high SNR; and (iv) the variance estimator is efficient as long as the non-coherent part of the signal is dominant.

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Data-Driven Tuning of PID Controlled Piezoelectric Ultrasonic Motor

Actuators ◽

10.3390/act10070148 ◽

2021 ◽

Vol 10 (7) ◽

pp. 148

Author(s):

Sarah Makarem ◽

Bülent Delibas ◽

Burhanettin Koc

Keyword(s):

Genetic Algorithm ◽

Pid Controller ◽

Good Alternative ◽

Data Driven ◽

Grid Search ◽

Single Source ◽

Dual Frequency ◽

Dual Source ◽

Stage System ◽

Piezoelectric Ultrasonic Motor

Ultrasonic motors employ resonance to amplify the vibrations of piezoelectric actuator, offering precise positioning and relatively long travel distances and making them ideal for robotic, optical, metrology and medical applications. As operating in resonance and force transfer through friction lead to nonlinear characteristics like creep and hysteresis, it is difficult to apply model-based control, so data-driven control offers a good alternative. Data-driven techniques are used here for iterative feedback tuning of a proportional integral derivative (PID) controller parameters and comparing between different motor driving techniques, single source and dual source dual frequency (DSDF). The controller and stage system used are both produced by the company Physik Instrumente GmbH, where a PID controller is tuned with the help of four search methods: grid search, Luus–Jaakola method, genetic algorithm, and a new hybrid method developed that combines elements of grid search and Luus–Jaakola method. The latter method was found to be quick to converge and produced consistent result, similar to the Luus–Jaakola method. Genetic Algorithm was much slower and produced sub optimal results. The grid search has also proven the DSDF driving method to be robust, less parameter dependent, and produces far less integral position error than the single source driving method.

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