Research Coordinators Research Articles

The factors affecting implementing shared decision-making in clinical trials: a cross-sectional survey of clinical research coordinators’ perceptions in Japan

BackgroundThe shared decision-making model has been proposed as the ideal treatment decision-making process in medical encounters. However, the decision to participate in clinical trials rarely involves shared decision-making. In this study, we investigated the perceptions of Japanese clinical research coordinators who routinely support the informed consent process.MethodsThis study aimed to (1) identify clinical research coordinators’ perceptions of the current status of shared decision-making implementation and its influencing factors, and (2) obtain suggestions to enhance the shared decision-making process in clinical trials. A cross-sectional survey was conducted using a web questionnaire based on the Theory of Planned behaviour. Invitations were sent to 1087 Japanese medical institutions, and responses from the participants were captured via the web. The shared decision-making process in clinical trials was defined according to the Shared Decision-Making Questionnaire for Doctors. The effect of the attitudes toward shared decision-making, clinical research coordinators’ subjective norms towards its implementation, perceived barriers to autonomous decision-making, and the number of difficult steps in the shared decision-making process on the shared decision-making current status as the shared decision-making intention was assessed by multiple regression analysis.ResultsIn total, 373 clinical research coordinators responded to the questionnaire. Many believed that they were already implementing shared decision-making. Attitudes toward shared decision-making (t = 3.400, p < .001), clinical research coordinators’ subjective norms towards its implementation (t = 2.239, p = .026), perceived barriers to autonomous decision-making (t = 3.957, p < .001), and the number of difficult steps in the shared decision-making process (t = 3.317, p = .001) were found to significantly influence current status (Adjusted R2 = .123). However, results on perceived barriers to autonomous decision-making and the number of difficult steps in the shared decision-making process indicate a lack of knowledge of shared decision-making and decision-support skills among clinical research coordinators.ConclusionsClinical research coordinators might positively perceive shared decision-making based on normative beliefs without sufficient knowledge of it. Therefore, providing appropriate training on shared decision-making to clinical research coordinators and increasing awareness among stakeholders could enable its improvement.Trial registrationNot applicable.

Analysis and design of control systems via parameter‐based approach

Analysis and design of control systems via parameter‐based approach

Correction to: Clinical Outcomes of Rhythm Control Strategies for Asymptomatic Atrial Fibrillation According to the Quality-of-Life Score: The CODE-AF (Comparison Study of Drugs for Symptom Control and Complication Prevention of Atrial Fibrillation) Registry.

HomeJournal of the American Heart AssociationVol. 12, No. 5Correction to: Clinical Outcomes of Rhythm Control Strategies for Asymptomatic Atrial Fibrillation According to the Quality‐of‐Life Score: The CODE‐AF (Comparison Study of Drugs for Symptom Control and Complication Prevention of Atrial Fibrillation) Registry Open AccessCorrectionPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citations ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toOpen AccessCorrectionPDF/EPUBCorrection to: Clinical Outcomes of Rhythm Control Strategies for Asymptomatic Atrial Fibrillation According to the Quality‐of‐Life Score: The CODE‐AF (Comparison Study of Drugs for Symptom Control and Complication Prevention of Atrial Fibrillation) Registry Originally published21 Feb 2023https://doi.org/10.1161/JAHA.122.027611Journal of the American Heart Association. 2023;12:e027611This article corrects the followingClinical Outcomes of Rhythm Control Strategies for Asymptomatic Atrial Fibrillation According to the Quality‐of‐Life Score: The CODE‐AF (Comparison Study of Drugs for Symptom Control and Complication Prevention of Atrial Fibrillation) RegistryOther version(s) of this articleYou are viewing the most recent version of this article. Previous versions: February 21, 2023: Ahead of Print In the article by Ju Youn Kim et al, “Clinical Outcomes of Rhythm Control Strategies for Asymptomatic Atrial Fibrillation According to the Quality‐of‐Life Score: The CODE‐AF (Comparison Study of Drugs for Symptom Control and Complication Prevention of Atrial Fibrillation) Registry,” which published online September 8, 2022 (J Am Heart Assoc. 2022;11:e025956. doi: 10.1161/JAHA.122.025956) and was included in the September 20, 2022 issue of the journal, a correction was needed.The authors mistakenly provided an incorrect grant number in their Sources of Funding statement. The correct grant number from the Ministry of Health and Welfare, Republic of Korea is HC19C0130.The Sources of Funding statement now reads:“This research was supported by a grant of the Patient‐Centered Clinical Research Coordinating Center funded by the Ministry of Health and Welfare, Republic of Korea (Grant number: HC19C0130).”The authors regret the error.The online version of the article has been updated and is available here:https://www.ahajournals.org/doi/10.1161/JAHA.122.025956. Previous Back to top Next FiguresReferencesRelatedDetailsRelated articlesClinical Outcomes of Rhythm Control Strategies for Asymptomatic Atrial Fibrillation According to the Quality‐of‐Life Score: The CODE‐AF (Comparison Study of Drugs for Symptom Control and Complication Prevention of Atrial Fibrillation) RegistryKyoung‐Min Park, et al. Journal of the American Heart Association. 2022;11 March 7, 2023Vol 12, Issue 5Article InformationMetrics Copyright © 2023 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley BlackwellThis is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.https://doi.org/10.1161/JAHA.122.027611PMID: 36802724 Originally publishedFebruary 21, 2023 PDF download

Corrigendum: Building trust, building futures: Knowledge as co-production as relationship, design, and process in transdisciplinary science

Corrigendum: Building trust, building futures: Knowledge as co-production as relationship, design, and process in transdisciplinary scienceIn the published article, there was an omission in the Funding statement. " This research was funded by the National Science Foundation: grant number SES-1639524 through the Innovations at the Nexus of Food, Energy, and Water Systems program; grant number OIA-1757324 through the NSF Idaho EPSCoR Program, and; BCS-1856059 through the EngageINFEWS Research Coordination Network."Funding for the article was provided after the article was published. The correct Funding statement appears below. The funding statement has been updated to include additional funds received to support the APC fee. "This research was funded by the National Science Foundation: grant number SES-1639524 through the Innovations at the Nexus of Food, Energy, and Water Systems program; grant number OIA-1757324 through the NSF Idaho EPSCoR Program, and; BCS-1856059 through the EngageINFEWS Research Coordination Network. Publication of this article was partially funded by the University of Idaho Open Access Publishing Fund."The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Realigning theory with evidence to understand the role of care coordination in mental health services research.

Current theoretical models intended to guide health services research and evaluation lack care coordination-its features and impacts. These aspects are critical for understanding the role of care coordination in healthcare use, quality, and outcomes. In this Focus article, we briefly review the well-known Andersen individual behavioral model (IBM) of healthcare use and the Donabedian health system and quality model (HSQM) together with recent practice-based evidence. We propose a new integrated theoretical model of healthcare and care coordination. The model can serve as a guide for future research to better understand the variation in care coordination services and delivery and its added value to improving mental health in different real-world settings.

Secondary prevention with a structured semi-interactive stroke prevention package in INDIA (SPRINT INDIA): a multicentre, randomised controlled trial

There is a high burden of stroke, including recurrent stroke, in India. We aimed to assess the effect of a structured semi-interactive stroke prevention package in patients with subacute stroke to reduce recurrent strokes, myocardial infarction, and death. This was a multicentre, randomised, clinical trial conducted in 31 centres of the Indian Stroke Clinical Trial Network (INSTRuCT). Adult patients with first stroke and access to a mobile cellular device were randomly allocated (1:1) to intervention and control groups by the research coordinators at each centre using a central, in-house, web-based randomisation system. The participants and research coordinators at each centre were not masked to group assignment. The intervention group received regular short SMS messages and videos that promoted risk factor control and medication adherence and an educational workbook, in one of 12 languages, and the control group received standard care. The primary outcome was a composite of recurrent stroke, high-risk transient ischaemic attack, acute coronary syndrome, and death at 1 year. The outcome and safety analyses were done in the intention-to-treat population. The trial is registered with ClinicalTrials.gov, NCT03228979 and Clinical Trials Registry-India (CTRI/2017/09/009600) and was stopped for futility after interim analysis. Between April 28, 2018, and Nov 30, 2021, 5640 patients were assessed for eligibility. 4298 patients were randomised to the intervention group (n=2148) or control group (n=2150). 620 patients were not followed up at 6 months and a further 595 patients were not followed up at 1 year because the trial was stopped for futility after interim analysis. 45 patients were lost to follow-up before 1 year. Acknowledgment of receipt of the SMS messages and videos by the intervention group patients was low (17%). The primary outcome occurred in 119 (5·5%) of 2148 patients in the intervention group and 106 (4·9%) of 2150 patients in the control group (adjusted odds ratio 1·12; 95% CI 0·85-1·47; p=0·370). Among the secondary outcome measures, alcohol cessation and smoking cessation were higher in the intervention group than in the control group (alcohol cessation 231 [85%] of 272 in the intervention group vs 255 [78%] of 326 in the control group; p=0·036; smoking cessation 202 [83%] vs 206 [75%]; p=0·035). Medication compliance was better in the intervention group than in the control group (1406 [93·6%] of 1502 vs 1379 [89·8%] of 1536; p<0·001). There was no significant difference between the two groups in other secondary outcome measures at 1 year: blood pressure, fasting blood sugar (mg/dL), low-density lipoprotein cholesterol (mg/dL), and triglycerides (mg/dL), BMI, modified Rankin Scale, and physical activity. A structured semi-interactive stroke prevention package did not reduce vascular events when compared with standard care. However, there was an improvement in some lifestyle behavioural factors, including adherence to medication, which might have long-term benefits. There was a possibility of type 2 error owing to reduced power since there were fewer events and a high number of patients could not be followed up. Indian Council of Medical Research.

Barriers to Using Legally Authorized Representatives in Clinical Research with Older Adults.

Older adults are at increased risk of cognitive impairments including Alzheimer's disease dementia. Legally authorized representatives (LARs) can provide informed consent when a participant is no longer able to, but little is known about barriers to incorporating them in research. Explore reasons for not asking and documenting participant decisions to appoint LARs among researchers conducting clinical intervention trials studying older adults or individuals with cognitive impairments. Mixed method design consisting of a survey (N = 1,284) and qualitative interviews (N = 40) regarding barriers to incorporating LARs. Participants were principal investigators and clinical research coordinators. 37% (N = 469) had not asked and documented participant decisions about appointing LARs in the prior year. They had significantly lower confidence in resources available to incorporate LARs and lower positive attitudes compared to their counterparts who had done so. The majority (83%) had no trials studying individuals with cognitive impairments and reported LARs were not applicable. A minority (17%) had at least one trial studying individuals with cognitive impairments and reported being unaware of LARs. Qualitative findings indicate discomfort broaching a sensitive topic especially with individuals who are not yet impaired. Resources and education to increase awareness and knowledge of LARs are needed. Researchers studying older adults should, at minimum, have the knowledge and resources to incorporate LARs when necessary. Stigma and discomfort discussing LARs will need to be overcome, as early proactive discussions before a participant loses decisional capacity could enhance participant autonomy and facilitate recruitment and retention of older adults to research.

The role of claudin 18.2 and HER-2 in pancreatic cancer outcomes.

To examine the prognostic value of claudin 18.2 (CLDN18.2) and human epidermal growth factor receptor-2 (HER-2) expression in patients with resected pancreatic ductal adenocarcinoma (PDAC). This study enrolled patients who underwent surgery and were diagnosed with PDAC at Suleyman Demirel University Hospital, Turkey between 2015 and 2019. Sixty-eight patients with resected PDAC treated at a medical oncology clinic were assessed. All patients were over the age of 18 years, underwent follow-up and treatment in our unit, and had pathology slides that we could access. Clinicopathological data were obtained from medical files, including the patients' age, sex, pathological parameters, and clinical stage according to the Eighth International Union against Cancer/American Joint Committee on Cancer. Patient survival and the period from the date of diagnosis to death were assessed in the follow-up data. There was no statistically significant difference between CLDN18.2 and HER-2 expression scores for samples and patient clinicopathological characteristics. No HER-2 expression scores of ≥2 were found in the samples. Only 25% (n = 17) of the samples had HER-2 expression scores of +1. CLDN18.2 expression was detected in 54.4% (n = 37) of the patient samples. CLDN18.2 expression scores were +1 in 30.8% (n = 21) of the patient samples, +2 in 16.2% (n = 11), and +3 in 7.4% (n = 5). When CLDN18.2 and HER-2 expression were compared, a statistically significant difference and moderate positive correlation were observed. No significant relationship between HER-2 expression and survival was observed in the survival analysis of PDAC patients; however, high CLDN18.2 expression was related to longer overall survival. Our study is the third to research CLDN18.2 expression in PDAC. HER-2 expression is low and CLDN18.2 expression is high in patients with PDAC. HER-2 expression is not related to overall survival but CLDN18.2 is related and may be used as a prognostic marker in patients with PDAC.

Examining uncertainty management in the clinical trial experiences of African American and Black Caribbean participants and the coordinators who recruit them

Clinical research studies experience low accrual rates for African American and Black Caribbean participants. These low rates could result in treatment regimens that are less effective for these groups. This study applied a communication lens to the decision-making processes that occur when the groups are being recruited for studies. Attention was paid to how participants managed their uncertainty in decision-making. Focus group discussions were conducted with 48 participants, with exclusive groups for African American, Black Caribbean, and clinical research coordinator (CRC) participants. Respondents were asked semi-structured questions. While the CRCs were asked about their practices recruiting within these groups, the patients were asked about their experiences being recruited. Three themes were derived from the data. Participants experienced uncertainty when the quality of information was lacking. Many participants realized they had little knowledge about research and struggled with understanding medical terms; therefore, they sought to manage uncertainty by asking questions. Additionally, participants experienced uncertainty because of sources of uncertainty, including family experiences and historical narratives. Participants also offered strategies for managing uncertainty. For instance, recruiters must incorporate matriarchal figures and use clear information about the purpose, process, and potential outcomes. Altogether, our findings indicate that research on the cause of the low number of African American and Black Caribbean participants in research studies needs to examine how uncertainty is experienced and managed during the research recruitment process.

Clinical research coordinators’ role in knowledge translation activities in rehabilitation: a mixed methods study

BackgroundClinical research coordinators (CRCs) facilitate the interaction between researchers and knowledge users in rehabilitation centres to promote and sustain evidence-informed practices. Despite their presence in rehabilitation settings in Quebec for over 20 years, little is known about their profiles and knowledge translation (KT) activities nor how they can best enact their role. This study explored CRCs’ roles and perspectives on the barriers, enablers, and strategies for improving KT activities in rehabilitation settings.MethodsWe conducted a multi-centre, participatory sequential mixed methods study. In the descriptive quantitative phase, we collected data via an online survey to determine CRCs’ role in research and KT. In the subsequent qualitative phase, we conducted an in-person focus group to elicit CRCs’ perspectives regarding factors influencing their work in KT, and potential solutions for overcoming these challenges. We used a descriptive and an inductive content analysis approach for the data analysis. The data synthesis was inspired by the Promoting Action on Research Implementation in Health Services framework.ResultsAll nine CRCs from five partner health regions of a large rehabilitation research centre agreed to participate in the study. The data suggest that CRCs are like knowledge brokers and boundary spanners. As information managers, linkage agents and facilitators, CRCs play a pivot role in diffusion, dissemination, synthesis and tailoring of knowledge to improve evidence informed practices and quality of care in rehabilitation. The factors influencing CRCs’ KT activities are mostly linked to the context such as the receptivity of the organization as well as the lack of time and resources, and limited understanding of their roles by stakeholders. Two main suggestions made to enhance CRCs’ contribution to KT activities include the harmonisation of expectations between the large research centre and their partner health regions, and better promotion of their role to clinical and research teams.ConclusionsThis study provides valuable insights into the scope of CRCs’ role. The results shed light on the challenges that they face and potential solutions to overcome them. The knowledge generated in this study can be used to implement this role with similar duties in rehabilitation settings or other health care domains.

Abstract TMP40: Cost Analysis Of A Pooled Coordinator Model Versus Traditional Staffing For Acute Stroke Trials

Introduction: Enrollment in acute stroke clinical trials (ASCTs) is complex and unpredictable. Traditional staffing models (TSMs) of research coordinator coverage assign a single research coordinator to cover specific clinical trials, whereas pooled staffing models (PSMs) utilize staff research coordinators to cross-cover multiple clinical trials, typically beyond traditional daytime hours. Methods: We calculated actual PSM costs accrued during one year (1/1/21-12/31/21) for two Phase III ASCTs (NCT03735979, NCT03785678). PSM costs were obtained from existing billing records for specific research coordinator tasks billed hourly ($78/hour) and a “retainer fee” ($690/month) for 24-7 on-call research coordinator coverage. Aspects of research coordinator work included: enrollment, data entry, query resolution, monitor visits, regulatory management, meetings, training/retraining, and patient visits. We compared PSM costs to the cost (salary + fringe) of a TSM full-time research nurse (1.0 full-time equivalent [FTE]) in the identical job class and salary as those employed in the PSM. Results: The estimated one-year cost (salary + fringe) of a 1.0 FTE RN research coordinator was $109,755.36. During the study period, there were 19 enrollments in NCT03735979; 9 occurred outside daytime working hours. The PSM cost was $60,813, equivalent to 0.55 FTE of coordinator coverage in a TSM with 90.0% more enrolled subjects. Additionally, there were 6 enrollments for NCT03785678; 4 outside daytime working hours. The PSM cost was $69,857.00, equivalent to the cost of 0.64 FTE of standardized research coordinator in a TSM with 200% more enrolled subjects. Conclusions: We demonstrated that a PSM for ASCT can be cost-effective for individual studies while increasing enrollment opportunities through 24-7 coordinator coverage. PSMs may offer a solution to the staffing and coverage challenges faced by many institutions seeking to participate in emergent clinical trials. Cost increases or savings with the PSM model would be dependent upon staff compensation, rates of enrollment, and reimbursement at individual sites.

Democratizing access to research for patients with pancreatic cancer across a diverse health system through natural language processing of radiology reports.

664 Background: Access to clinical trials and translational research studies is integral to improving cancer care for pancreatic cancer. The in-patient setting is a valuable opportunity to obtain research specimens and establish transition to out-patient oncology. However, samples coordinators rarely have sufficient lead time prior to biopsy to consent patients and be present for tissue collection. Meanwhile, histopathology of biopsied specimens may not be complete prior to discharge, hindering follow-up planning. Polyethnic-1000 is a research study enrolling African American patients with pancreatic cancer, is a priority study for our institution, and was the target study that motivated the below innovative strategy to better obtain research samples and ensure adequate follow-up. Methods: We observed recurrent suspicious abnormalities on abdominal radiology reports that foreshadow subsequent biopsy of the pancreas. To explore this further, we trained a natural language classifier to identify radiology reports as suspicious for pancreatic cancer. The pretrained model used is RadBERT, a custom-built language model based on Google’s BERT and further pretrained on several million radiology text reports. A gastrointestinal oncologist, clinical research coordinator, and radiologist informatician curated a dataset consisting of 1136 CT abdominal radiology reports, among which 696 were considered suspicious for pancreatic cancer. Among this curated database of reports, a training set consisting of 908 reports was used to fine-tune the RadBERT base model and produce our pancreatic cancer suspicion classifier. A validation and test dataset each consisting of 114 cases were reserved for model evaluation. We computed the final classifier performance metrics over the test dataset. Results: The model obtained an accuracy of 92%, and produced an F1 score of 0.936, a recall of 0.943, and a precision of 0.930. Conclusions: An early iteration model to classify CT abdominal radiology reports was highly accurate and has the potential to substantially increase identification of patients who may be suitable for clinical research studies and trials. We are now working to improve and expand our dataset in order to train classifiers with greater and more robust performance, while simultaneously developing an automated near real-time process that will leverage our models to identify reports suspicious for pancreatic cancer and then notify a coordinator and navigator.

42. Creation of a Novel Plastic Surgery Research Program Framework: A Single Division’s Experience

Background: The influence of research team structure on institutional scholarly activity, culture, and productivity is sparsely reported in the literature. Here, we present a single institution’s experience with the development of a novel divisional plastic surgery research team structure, predominantly focused on clinical research and its impact on research productivity. Methods: From August 2021- July 2022, our research team structure changed from the traditional “single-PI single-fellow” structure to a three-tiered hierarchy system managed by the Chief Research Fellow, Director of Research, and System Chief. The Chief Research Fellow acted as a research coordinator and lead investigator, and enforced expectations for inclusivity, reliability, professional mobility and adaptability, and trust. Research projects were de-siloed and characterized into 1 of 10 subdivisions. To maximize opportunity, any research personnel could participate in any subdivision. A standardized workflow was established to encourage involvement and aid efficiency. At the conclusion of the Chief Research Fellow’s tenure, research productivity from her tenure was compared to September 2018- July 2019. Results: The Chief Research Fellow established new institutional processes and culture, which aided productivity and attracted team members. This culture change also led to research personnel both generating more research ideas and willingly giving first authorship to more junior members to help develop their skill sets. Compared to 2018-2019, there was a significant increase in publications by 131% (16 vs 37), abstract acceptances by 269% (16 vs 59), podium presentations by 820% (5 vs 36), and poster presentations by 18% (11 vs 13) (p<0.037). At the end of June 2022, there were 2 Chief Research Fellows, 6 Full-time Research Fellows, 6 Summer Research Fellows, and 198 part-time research personnel. Conclusion: Research and continuous innovation are major pillars of plastic surgery academia. However, the ability to pursue and publish scholarly activity can be limited by professional and personal barriers. When scholarly activity is pursued at an academic institution, it is imperative that a collaborative structured process is in place for optimal efficiency. Here, we propose a beneficial research structure based on inclusivity, professional mobility, altruism, and scholarly productivity.

Abstract TMP38: Remote Research Practices Enhance Acute Stroke Clinical Trial Enrollment

Background: Many acute stroke clinical trials (ASCTs) are underpowered, inconclusive, or terminated early. A pervasive challenge to ASCT recruitment is the physical separation of patients, their legally authorized representatives, research coordinators, and clinician investigators when trial-eligible patients present emergently. Remote research practices (RRPs) may aid time-critical ASCT enrollment and follow-up, however, their feasibility and effectiveness are understudied. Methods: We retrospectively reviewed ASCT enrollment (NCT03785678, NCT03735979, NCT02072681) at two institutions. Essential clinical trial elements (ECTEs) consisted of eligibility screening, informed consent, randomization, study intervention, and inpatient/outpatient follow-up assessments. When conventional in-person clinical research was not possible, ECTEs were attempted via RRPs utilizing either telemedicine evaluation or telephone communication. The primary outcome was the successful execution of accurate, complete ECTEs by research communication modality (in-person, telemedicine, or telephone). The secondary outcome was the protocol violation rate by modality. We utilized Fisher’s Exact Test for primary and secondary outcomes and descriptive statistics to report RRP utilization. Results: A total of 1600 individual ECTEs were attempted on 169 subjects. RRPs were utilized for 53.7% of ECTEs (19.1% telemedicine, 34.6% telephone). ECTEs were more likely to be completed successfully with telemedicine (100%) than in-person (98.5%) or telephone (92.2%), (p&lt;0.01). Additionally, protocol deviations were less common with telemedicine (0.0%) than in-person (2.6%), or telephone (2.8) (p=0.04). Randomization (94.7%) and outpatient assessments (90.3%) were frequently completed via RRPs compared to eligibility screening (39.1%), informed consent (40.2%), supervision of study intervention (36.8%), and inpatient assessments (21.9%). Conclusion: RRPs were widely utilized. Telemedicine execution of ECTEs was associated with the highest rate of successful completion and lowest rate of protocol deviations. These findings, while retrospective and confounded by indication, suggest RRPs are effective and require confirmatory study.

Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular Clinics (VOICE-COVID-19-II): Protocol for a Randomized Controlled Trial.

The COVID-19 pandemic has disrupted the health care system, limiting health care resources such as the availability of health care professionals, patient monitoring, contact tracing, and continuous surveillance. As a result of this significant burden, digital tools have become an important asset in increasing the efficiency of patient care delivery. Digital tools can help support health care institutions by tracking transmission of the virus, aiding in the screening process, and providing telemedicine support. However, digital health tools face challenges associated with barriers to accessibility, efficiency, and privacy-related ethical issues. This paper describes the study design of an open-label, noninterventional, crossover, randomized controlled trial aimed at assessing whether interactive voice response systems can screen for SARS-CoV-2 in patients as accurately as standard screening done by people. The study aims to assess the concordance and interrater reliability of symptom screening done by Amazon Alexa compared to manual screening done by research coordinators. The perceived level of comfort of patients when interacting with voice response systems and their personal experience will also be evaluated. A total of 52 patients visiting the heart failure clinic at the Royal Victoria Hospital of the McGill University Health Center, in Montreal, Quebec, will be recruited. Patients will be randomly assigned to first be screened for symptoms of SARS-CoV-2 either digitally, by Amazon Alexa, or manually, by the research coordinator. Participants will subsequently be crossed over and screened either digitally or manually. The clinical setup includes an Amazon Echo Show, a tablet, and an uninterrupted power supply mounted on a mobile cart. The primary end point will be the interrater reliability on the accuracy of randomized screening data performed by Amazon Alexa versus research coordinators. The secondary end point will be the perceived level of comfort and app engagement of patients as assessed using 5-point Likert scales and binary mode responses. Data collection started in May 2021 and is expected to be completed in fall 2022. Data analysis is expected to be completed in early 2023. The use of voice-based assistants could improve the provision of health services and reduce the burden on health care personnel. Demonstrating a high interrater reliability between Amazon Alexa and health care coordinators may serve future digital tools to streamline the screening and delivery of care in the context of other conditions and clinical settings. The COVID-19 pandemic occurs during the first digital era using digital tools such as Amazon Alexa for disease screening, and it represents an opportunity to implement such technology in health care institutions in the long term. ClinicalTrials.gov NCT04508972; https://clinicaltrials.gov/ct2/show/NCT04508972. DERR1-10.2196/41209.

電子的手法によるインフォームド・コンセントを受ける手続きに関する実態調査： 臨床研究コーディネーター等を対象としたWebアンケート調査

電子的手法によるインフォームド・コンセントを受ける手続きに関する実態調査： 臨床研究コーディネーター等を対象としたWebアンケート調査

The MPRINT Hub Data, Model, Knowledge and Research Coordination Center: Bridging the gap in maternal-pediatric therapeutics research through data integration and pharmacometrics.

Maternal and pediatric populations have historically been considered "therapeutic orphans" due to their limited inclusion in clinical trials. Physiologic changes during pregnancy and lactation and growth and maturation of children alter pharmacokinetics (PK) and pharmacodynamics (PD) of drugs. Precision therapy in these populations requires knowledge of these effects. Efforts to enhance maternal and pediatric participation in clinical studies have increased over the past few decades. However, studies supporting precision therapeutics in these populations are often small and, in isolation, may have limited impact. Integration of data from various studies, for example through physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling or bioinformatics approaches, can augment the value of data from these studies, and help identify gaps in understanding. To catalyze research in maternal and pediatric precision therapeutics, the Obstetric and Pediatric Pharmacology and Therapeutics Branch of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) established the Maternal and Pediatric Precision in Therapeutics (MPRINT) Hub. Herein, we provide an overview of the status of maternal-pediatric therapeutics research and introduce the Indiana University-Ohio State University MPRINT Hub Data, Model, Knowledge and Research Coordination Center (DMKRCC), which aims to facilitate research in maternal and pediatric precision therapeutics through the integration and assessment of existing knowledge, supporting pharmacometrics and clinical trials design, development of new real-world evidence resources, educational initiatives, and building collaborations among public and private partners, including other NICHD-funded networks. By fostering use of existing data and resources, the DMKRCC will identify critical gaps in knowledge and support efforts to overcome these gaps to enhance maternal-pediatric precision therapeutics.

Clinical research coordinators: Key components of an efficient clinical trial unit

Clinical research coordinators: Key components of an efficient clinical trial unit

Integration of patient experience factors improves readmission prediction.

Many readmission prediction models have marginal accuracy and are based on clinical and demographic data that exclude patient response data. The objective of this study was to evaluate the accuracy of a 30-day hospital readmission prediction model that incorporates patient response data capturing the patient experience. This was a prospective cohort study of 30-day hospital readmissions. A logistic regression model to predict readmission risk was created using patient responses obtained during interviewer-administered questionnaires as well as demographic and clinical data. Participants (N = 846) were admitted to 2 inpatient adult medicine units at Massachusetts General Hospital from 2012 to 2016. The primary outcome was the accuracy (measured by receiver operating characteristic) of a 30-day readmission risk prediction model. Secondary analyses included a readmission-focused factor analysis of individual versus collective patient experience questions. Of 1754 eligible participants, 846 (48%) were enrolled and 201 (23.8%) had a 30-day readmission. Demographic factors had an accuracy of 0.56 (confidence interval [CI], 0.50-0.62), clinical disease factors had an accuracy of 0.59 (CI, 0.54-0.65), and the patient experience factors had an accuracy of 0.60 (CI, 0.56-0.64). Taken together, their combined accuracy of receiver operating characteristic = 0.78 (CI, 0.74-0.82) was significantly more accurate than these factors were individually. The individual accuracy of patient experience, demographic, and clinical data was relatively poor and consistent with other risk prediction models. The combination of the 3 types of data significantly improved the ability to predict 30-day readmissions. This study suggests that more accurate 30-day readmission risk prediction models can be generated by including information about the patient experience.

Clinical trial units and clinical research coordinators: a system facing crisis?

We are currently witnessing an increase in procedural and managerial complexities within the field of clinical research, which require greater human and infrastructural resources as well as imply the need for a greater skill set and expertise on the part of professionals. Within this frame of reference clinical trial units and clinical research coordinators play a vital role in the design and conduct of clinical trials in Italy. There is a current recruitment and retention crisis for this specialist role due to a complex set of factors, most likely to have come to a head due to the lack of recognition at the Italian institutional level, that lead to precarious work contracts, lack of identity, and excessive turnover at experimental sites. This article, led by the Italian Group of Clinical Research Coordinator (GIDMcrc), presents some of the issues and ways in which national stakeholders may be able to address this.