Journal of the Society for Clinical Data Management最新文献

{"title":"Clinical data management A Review of Current Practice in Australia","authors":"L. Houston, Y. Probst","doi":"10.47912/jscdm.62","DOIUrl":"https://doi.org/10.47912/jscdm.62","url":null,"abstract":"The practice of clinical data management (CDM) in Australia has seen and continues to experience tremendous growth. As such, this article reviews the current practice of CDM in Australia. The article addresses the history of the profession and provides insight into the difference between the sectors, the evolving role, ongoing requirements for training and education, and an overview of the regulations and how these impact the Australian CDM landscape. Current practice of CDM in Australia differs considerably between industry, academic, and non-profit sectors though the uniform regulatory requirements are provided nationwide. This has raised challenges for mostly academic, non-profit, and small-scale trials which are more likely to lack access to resources, facilities, management, and funding. Australian clinical data managers are required to have formal skills related to data, technology, security, and project management, though they are also expected to operate at the highest levels of excellence across all areas of their diverse roles. It is only in recent years that CDM has evolved to a stronger focus on data quality. Regardless of these challenges, clinical data managers have played, and continue to play, a key role in Australian biomedical research. They have provided guidance on data collection, processing, and management procedures to ensure that studies achieve high quality outcomes. However, more research is needed to develop specific CDM training courses to help Australian clinical data managers to meet a standard of knowledge, education, and experience to be officially recognised as a profession.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127719485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Year-End Summary and Reflection of SCDM 2021","authors":"Sanjay Bhardwaj","doi":"10.47912/jscdm.147","DOIUrl":"https://doi.org/10.47912/jscdm.147","url":null,"abstract":"","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126181773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CRF Completion Guidelines","authors":"K. Hills, Tara Bartlett, Isabelle Leconte, M. Zozus","doi":"10.47912/jscdm.117","DOIUrl":"https://doi.org/10.47912/jscdm.117","url":null,"abstract":"Case Report Forms (CRFs) are a common data collection mechanism in clinical studies and are sometimes the original recording of study data. CRF completion is one of the earliest opportunities to assure accurate and complete data and to decrease downstream work associated with identification and resolution of data discrepancies. This chapter covers development, maintenance, and implementation of instructions for CRF completion, also called CRF Completion Guidelines (CCGs). Recommendations in this chapter are based on the International Council for Harmonisation (ICH) E6 addendum,1 the MHRA GXP Data Integrity Guidance and Definitions, review of the literature, and writing group consensus.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124891883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vendor Selection & Management","authors":"S. Amatya, D. Edgerton","doi":"10.47912/jscdm.118","DOIUrl":"https://doi.org/10.47912/jscdm.118","url":null,"abstract":"Vendors provide services that are critical to the successful outcome of a clinical study, yet sponsors retain the ultimate responsibility for activities that are outsourced. Thus, if a sponsor delegates study activities to a vendor or a vendor’s vendor and so on, the sponsor should take measures to ensure the vendor and any subcontractors are consistently delivering products or services of acceptable quality. This chapter provides recommendations for evaluating, selecting, and providing oversight of vendors to determine whether their services adequately meet sponsor expectations including quality requirements and regulatory standards.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123276173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Practice of Clinical Data Management Worldwide: Introduction to the Special Issue","authors":"R. Ittenbach, Yiannis Karageorgos","doi":"10.47912/jscdm.146","DOIUrl":"https://doi.org/10.47912/jscdm.146","url":null,"abstract":"<jats:p>None</jats:p>","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129039380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bring Your Own Device (BYOD): A practical framework to leverage in the electronic patient-reported outcomes(ePRO) data collection in clinical trials","authors":"Aman Thukral, Kelsey Linsmeier, Brooks Fowler, Sanjay Bhardwaj","doi":"10.47912/jscdm.110","DOIUrl":"https://doi.org/10.47912/jscdm.110","url":null,"abstract":"Patient-reported outcomes (PROs) are used in pharmaceuticaltrials to obtain trends in health status. Companies commonly provision tabletand smartphone devices to collect PRO information. Alternatively, the BringYour Own Device (BYOD) model allows patients to leverage personal devices andis actively being explored as a solution.  This article investigates thepotential benefits of BYOD and outlines a framework of considerations. Theframework addresses current challenges and proposes potential solutions toMeasurement Equivalence, Technical, and Operational concerns. BYOD has not yet beenimplemented on any studies for regulatory submission. Nonetheless, there isreason to believe the model will gain traction in the coming years. With theprovided framework, sponsors can assess whether the BYOD model is right for theconsidered study.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126348461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Data Management in Japan: Past, Present, and the Future","authors":"Takuhiro Yamaguchi, T. Miyaji, H. Suganami, H. Ohtsu, Y. Ohashi","doi":"10.47912/jscdm.45","DOIUrl":"https://doi.org/10.47912/jscdm.45","url":null,"abstract":"Inthe past 10 years in Japan, clinical trial design and analysis have improved owingto the increased understanding of the role ofresearchers inclinical trials and acknowledging thecontribution of biostatisticians. However, during this time, studies havemainly focused on clinical data management (CDM) and the technicalaspects of trials (e.g., data collection and entry, check), and many differences existamong sites. For clinical trials within academia, although the introduction ofElectronic Data Capture (EDC) had begun, data collection using paper casereport forms was still the mainstream. The aimof CDM was to ensure maintainingthe quality of data at an appropriate level to allow for fair scientificevaluation, and this was not recognized in many educational activities. Therewas an impression that the role of CDM was underestimated because it was notsufficiently positioned as a “profession” in conducting clinical trials. Tosummarize, 1) there was little awareness on the importance of CDM, 2) theeducation system for CDM was not in place, and 3) systematic CDM research wasconducted. Today, with the widespread use of electronic technologies, such asEDC and electronic Patient Reported Outcome, and the introduction of qualitymanagement and risk-based approach, data managers have more opportunities toaccess real-time data. As such, the work ofdata managers has diversified and the range of roles has expanded. Recently, we aimed to establish the Society of Clinical Data Management (SCDM)Japanese Branch to 1) disseminate the activities of SCDM inJapan, 2) promote the value of certified clinical data manager (CCDM) amongJapanese CDM, 3) strengthen the CDMnetwork through the SCDM Japanese regional office, and 4) provide acomprehensive educational program on CDM through SCDM educational material suchas Good Clinical Data Management Practice (GCDMP) to CDM in Japan. SCDM Japan wasofficially approved in February 2019 and the Japanese page of the SCDM website (https://scdm.org/japan/) wasfunctional in August 2020. Sixteen steering committee members from academia,industry, and regulatory affairs manage SCDM Japan. We have five sub-committees,namely, GCDMP, Certification (CCDM), Membership, Publication, Education, andOnline Course Committee. Activities are introduced on the SCDM Japan website. In this specialarticle, we summarize the brief history of CDMin Japan. Here, we have presented special circumstances in which pharmaceuticalcompanies, and not academia, have laid the foundation for clinical trials. We haveexplained the differences in the role of clinical datamanagers in academic research organizations, pharmaceutical companies, and Contact research organizations. The currentstatus and issues of CDM in Japan are introduced, including training, education,and career paths for CDM professionals. Lastly, we express our expectations forthe future of CDM in Japan.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"365 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131815982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The growing opportunity of clinical data management in Ukraine","authors":"S. Glushakov, V. Boichuk","doi":"10.47912/jscdm.43","DOIUrl":"https://doi.org/10.47912/jscdm.43","url":null,"abstract":"Many specialized positions, even entry-level, in the pharmaceutical industry require training above and beyond standard University degree programs. A shortage of specialized clinical data managers in Ukraine means private sector companies are developing internal resource training programs to deepen their pool of available candidates. Given the strong medical education system and established IT outsourcing industry, we believed developing a pool of talented clinical data managers within Ukraine was a feasible goal.The IT outsourcing industry is the second largest export service industry in Ukraine, and one of the main sectors in the economy. More than 50% of Ukraine's IT services revenue came from the United States, the rest mostly from the EU.[1] Ukraine has built a workforce adapted to IT outsourcing, but the lack of local professionals in the fields of clinical data management and clinical data science hinders similar growth in the clinical research sector. Ukraine has a well-established medical education system that trains its healthcare professionals in accordance with EU regulations. Hospitals are predominantly state-owned; the private medical sector is almost nonexistent. The academic and non-profit clinical research sectors are small in comparison to Western European countries, and opportunities for careers within them limited. This leads to a 'brain drain' of medical professionals from Ukraine to other countries in search of higher wages and professional advancement. With its strong education system and highly educated medical workforce, Ukraine is an attractive but under-utilised location for clinical studies. [2] There are approximately 30 clinical research sites in Ukraine handling preclinical through Phase IV studies. In December 2020 on clinicaltrials.gov there were 557 active or recruiting clinical trials listed taking place in Ukraine. Regulatory hurdles and approval timelines have greatly improved in recent years.Currently, when CROs wish to hire data managers to assist with local clinical trials in Ukraine, they have to hire non-specialists who must teach themselves on the job. At present there are no university courses or formal training programs within the country for clinical data managers.Following the success of the Clinical Statistical Programming training program developed by our team and offered since 2013 in partnership V. N. Karazin Kharkiv National University,[3] we recently launched an in-house clinical data management training program in partnership between leading Biometrics CROs Cytel and Intego Group. Upon program completion, students have the opportunity to transition into full-time employment. Ours is the first centralized training program for clinical data managers in the country. We already started a conversation with some of the country's leading universities to help them develop a formal educational program in clinical data management. Our internal training program will serve as a pilot and a proof of concep","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131521358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical research data management in the United States: Where we've been and where we're going","authors":"M. Banach, K. Fendt, J. Proeve, D. Plummer, Samina Qureshi, Ariana Winder, Nimita Limaye","doi":"10.47912/jscdm.61","DOIUrl":"https://doi.org/10.47912/jscdm.61","url":null,"abstract":"With the focus of the COVID-19 pandemic, we wanted to reach all stakeholders representing communities concerned with good clinical data management practices. We wanted to represent not only data managers but bio-statisticians, clinical monitors, data scientists, informaticians, and all those who collect, organize, analyze, and report on clinical research data. In our paper we will discuss the history of clinical data management in the US and its evolution from the early days of FDA guidance. We will explore the role of biomedical research focusing on the similarities and differences in industry and academia clinical research data management and what we can learn from each other. We will talk about our goals for recruitment and training for the CDM community and what we propose for increasing the knowledge and understanding of good clinical data practice to all – particularly our front-line data collectors i.e., nurses, medical assistants, patients, other data collectors. Finally, we will explore the challenges and opportunities to see CDM as the hub for good clinical data research practices in all of our communities.We will also discuss our survey on how the COVID-19 pandemic has affected the work of CDM in clinical research.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127362946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Writing for Publication in Informatics and Data Science in Clinical Research","authors":"R. Ittenbach, William A Ittenbach","doi":"10.47912/jscdm.32","DOIUrl":"https://doi.org/10.47912/jscdm.32","url":null,"abstract":"Clinical data management and its contemporary analogs, clinical research informatics and clinical data science constitute a small but rapidly growing specialty within the broader field of biomedical science. As such, the literature base is just evolving, drawing heavily from the larger and more established disciplines of biomedical informatics, biostatistics, clinical operations, and regulatory affairs. The purpose of this paper is to offer suggestions to individuals interested in submitting their research to the Journal of the Society for Clinical Data Management: Informatics and Data Science in Clinical Research.  ","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114745411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}