Approaches to Facilitate Institutional Review Board Approval of Multicenter Research Studies

Variability in Ethics Review for Multicenter Protocols in Buenos Aires, Argentina. An Observational Study

It has been reported that significant variability in the ethics review process affects multisite studies. We analyzed 1,305 applications for multicenter studies (409 unique protocols), from 1^st January 2020 to 20^th September 2021. We examined the variability in the times to approval and the first observation and the variation in the level of risk assigned. The median [IQR] variabilities were 42.19 [15.23-82.36] days and 8.00 [3.12-16.68] days, for the times to approval and to the first observation, respectively. There was disagreement in the level of risk assigned by the Research Ethics Committee (REC) in 24.0% of cases. Independent predictors of variability included the number of REC members. In our study, we found substantial variability in the ethics review process among health research protocols. Also, we describe methods to readily measure the delays and the variations in the ethics review process.

Management strategies for implementing a multicenter cross-sectional study: lessons from the ADHERE Brazil study

BACKGROUND

Epidemiological studies involving large samples usually face financial and operational challenges.

OBJECTIVES

To describe the planning and execution of ADHERE Brazil, an epidemiological study on 1,105 kidney transplant patients, and report on how the study was structured, difficulties faced and solutions found.

DESIGN AND SETTING

Cross-sectional multicenter study in 20 Brazilian kidney transplantation centers.

METHODS

Actions developed in each phase of implementation were described, with emphasis on innovations used within the logistics of this study, aimed at estimating the prevalence of nonadherence to treatment.

RESULTS

Coordination of activities was divided into four areas: general, regulatory, data collection and statistics. Weekly meetings were held for action planning. The general coordination team was in charge of project elaboration, choice of participating centers, definition of publication policy and monitoring other coordination teams. The regulatory team provided support to centers for submitting the project to ethics committees. The data collection team prepared a manual on the electronic collection system, scheduled web meetings and was available to respond to queries. It also monitored the data quality and reported any inadequacies found. Communication with the centers was through monthly reports via e-mail and distribution of exclusive material. The statistical team acted in all phases of the study, especially in creating the data analysis plan and data bank, generation of randomization lists and data extraction.

CONCLUSIONS

Through these logistics, we collected high-quality data and built a local research infrastructure for further studies. We present supporting alternatives for conducting similar studies.

CLINICAL TRIAL ANNOTATION

http://clinicaltrials.gov/ on October 10, 2013; NCT02066935.

Conducting multicenter research in healthcare simulation: Lessons learned from the INSPIRE network

Simulation-based research has grown substantially over the past two decades; however, relatively few published simulation studies are multicenter in nature. Multicenter research confers many distinct advantages over single-center studies, including larger sample sizes for more generalizable findings, sharing resources amongst collaborative sites, and promoting networking. Well-executed multicenter studies are more likely to improve provider performance and/or have a positive impact on patient outcomes. In this manuscript, we offer a step-by-step guide to conducting multicenter, simulation-based research based upon our collective experience with the International Network for Simulation-based Pediatric Innovation, Research and Education (INSPIRE). Like multicenter clinical research, simulation-based multicenter research can be divided into four distinct phases. Each phase has specific differences when applied to simulation research: (1) Planning phase, to define the research question, systematically review the literature, identify outcome measures, and conduct pilot studies to ensure feasibility and estimate power; (2) Project Development phase, when the primary investigator identifies collaborators, develops the protocol and research operations manual, prepares grant applications, obtains ethical approval and executes subsite contracts, registers the study in a clinical trial registry, forms a manuscript oversight committee, and conducts feasibility testing and data validation at each site; (3) Study Execution phase, involving recruitment and enrollment of subjects, clear communication and decision-making, quality assurance measures and data abstraction, validation, and analysis; and (4) Dissemination phase, where the research team shares results via conference presentations, publications, traditional media, social media, and implements strategies for translating results to practice. With this manuscript, we provide a guide to conducting quantitative multicenter research with a focus on simulation-specific issues.

Are Research Ethics Committees Prepared for Community-Based Participatory Research?

Community-based participatory research (CBPR) is challenging to research ethics committees (RECs). We reviewed the REC preparedness when reviewing CBPR projects. We searched the MEDLINE database and included qualitative studies of CBPR researchers or REC members about their experiences with RECs. The search yielded 107 studies, of which 10 met our criteria. Barriers were that the community is not prepared to conduct research, the reluctance of RECs to work outside the university, the difficulty RECs have understanding CBPR, and that REC forms evaluate individual rather than community risk. Facilitators were having a CBPR expert as an REC member and educating RECs. Therefore, RECs are not prepared to evaluate CBPR projects leading to unnecessary delays in the approval process.

Utilizing data consortia to monitor safety and effectiveness of biosimilars and their innovator products

BACKGROUND

The Biologics Price Competition and Innovation Act, introduced as part of the Affordable Care Act, directed the FDA to create an approval pathway for biologic products shown to be biosimilar or interchangeable with an FDA-approved innovator drug. These biosimilars will not be chemically identical to the reference agent. Investigational studies conducted with biosimilar agents will likely provide limited real-world evidence of their effectiveness and safety. How do we best monitor effectiveness and safety of biosimilar products once approved by the FDA and used more extensively by patients?

OBJECTIVE

To determine the feasibility of developing a distributed research network that will use health insurance plan and health delivery system data to detect biosimilar safety and effectiveness signals early and be able to answer important managed care pharmacy questions from both the government and managed care organizations.

METHODS

Twenty-one members of the AMCP Task Force on Biosimilar Collective Intelligence Systems met November 12, 2013, to discuss issues involved in designing this consortium and to explore next steps.

RESULTS

The task force concluded that a managed care biosimilars research consortium would be of significant value. Task force members agreed that it is best to use a distributed research network structurally similar to existing DARTNet, HMO Research Network, and Mini-Sentinel consortia. However, for some surveillance projects that it undertakes, the task force recognizes it may need supplemental data from managed care and other sources (i.e., a "hybrid" structure model).

CONCLUSIONS

The task force believes that AMCP is well positioned to lead the biosimilar-monitoring effort and that the next step to developing a biosimilar-innovator collective intelligence system is to convene an advisory council to address organizational governance.

VATE: VAlidation of high TEchnology based on large database analysis by learning machine

SUMMARY 

The interaction between implementation of new technologies and different outcomes can allow a broad range of researches to be expanded. The purpose of this paper is to introduce the VAlidation of high TEchnology based on large database analysis by learning machine (VATE) project that aims to combine new technologies with outcomes related to rectal cancer in terms of tumor control and normal tissue sparing. Using automated computer bots and the knowledge for screening data it is possible to identify the factors that can mostly influence those outcomes. Population-based observational studies resulting from the linkage of different datasets will be conducted in order to develop predictive models that allow physicians to share decision with patients into a wider concept of tailored treatment.

Accelerating regulatory progress in multi-institutional research

Purpose:

Multi-institutional collaborations are necessary in order to create large and robust data sets that are needed to answer important comparative effectiveness research (CER) questions. Before scientific work can begin, a complex maze of administrative and regulatory requirements must be efficiently navigated to avoid project delays.

Innovation:

Staff from research, regulatory, and administrative teams involved in three HMO Research Network (HMORN) multi-institutional collaborations developed and employed novel approaches: to secure and maintain Institutional Review Board (IRB) approvals; to enable data sharing, and to expedite subawards for two data-only minimal risk studies. These novel approaches accelerated required processes and approvals while maintaining regulatory, human subjects, and institutional protections.

Credibility:

Outcomes from the processes described here are compared with processes outlined in the research and regulatory literature and with processes that have been used in previous multisite research collaborations.

Conclusion and Discussion:

Research, regulatory, and administrative staff are essential contributors to the success of multi-institutional collaborations. Their flexibility, creativity, and effective communication skills can lead to the development of efficient approaches to achieving the necessary oversight for these complex projects. Elements of these specific strategies can be adapted and used by other research networks. Other efforts in these areas should be evaluated and shared. The processes that help develop a “learning research system” play an important and complementary role in sustaining multi-institutional research collaborations.

Navigating the institutional review board approval process in a multicenter observational critical care study

OBJECTIVE

To characterize variation in the institutional review board application process of a multicenter, observational critical care study.

DESIGN, SETTING, AND SUBJECTS

Survey analysis of 36 investigators who applied for participation in the United States Critical Illness and Injury Trials Group: Critical Illness and Outcomes Study, an observational study of 69 adult ICUs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Analysis of investigator-specific characteristics, institutional review board process, application and approval dates, and level of difficulty in obtaining approval. Surveys were analyzed from 36 sites (95%) that applied for institutional review board approval. Level of review ranged from full board, expedited, to exempt. Seventy-five percent of applications were submitted by an experienced investigator while 25% were submitted by a less experienced investigator. Median time to institutional review board approval was 30 days (interquartile range, 14-54) and ranged from 5 days to 5.5 months. Time to approval was 29 days (interquartile range, 17-48) for applications submitted by an experienced investigator compared with 97 days (interquartile range, 25-159) for those submitted by a less experienced investigator (p = 0.08). Subjective level of difficulty was significantly higher for less experienced investigators (4 of 10; interquartile range, 2-8) vs experienced investigators (2 of 10; interquartile range, 1-3) (p = 0.04). Four sites cited institutional review board concern regarding waiver of consent as a major barrier to approval and were required to perform revisions or participate in board meetings regarding this concern.

CONCLUSIONS

In a multicenter, observational critical care study, significant variation was observed between sites in all aspects of the institutional review board evaluation and approval process. The level of difficulty was significantly higher for less experienced investigators with a trend toward longer time to institutional review board approval. Variation in institutional review board interpretation of waiver of informed consent regulations was cited as a major barrier to approval.

Variability of the institutional review board process within a national research network

OBJECTIVE

To determine the variability of the institutional review board (IRB) process for a minimal risk multicenter study.

METHODS

Participants included 24 Continuity Research Network (CORNET) sites of the Academic Pediatric Association that participated in a cross-sectional study. Each site obtained individual institutional IRB approval. An anonymous questionnaire went to site investigators about the IRB process at their institution.

RESULTS

Twenty-two of 24 sites (92%) responded. Preparation time ranged from 1 to 20 hours, mean of 7.1 hours. Individuals submitting ≤3 IRB applications/year required more time for completion than those submitting >3/year (P < .05). Thirteen of 22 (59%) study sites received approval with "exempt" status, and 6 (27%) approved as "expedited" studies.

CONCLUSIONS

IRB experiences were highly variable across study sites. These findings indicate that multicenter research projects should anticipate barriers to timely study implementation. Improved IRB standardization or centralization for multicenter clinical studies would facilitate this type of practice-based clinical research.

An umbrella protocol for standardized data collection (SDC) in rectal cancer: a prospective uniform naming and procedure convention to support personalized medicine

Predictive models allow treating physicians to deliver tailored treatment moving from prescription by consensus to prescription by numbers. The main features of an umbrella protocol for standardizing data and procedures to create a consistent dataset useful to obtain a trustful analysis for a Decision Support System for rectal cancer are reported.

eGEMs: Pathways to Success for Multisite Clinical Data Research

There are numerous and significant challenges associated with leveraging electronic clinical data (ECD) for purposes beyond treating an individual patient and getting paid for that care. Optimizing this secondary use of clinical data is a key underpinning of many health reform goals and triggers numerous issues related to data stewardship and, more broadly, data governance. These challenges often involve legal, policy, and procedural issues related to the access, use, and disclosure of electronic health record (EHR) data for quality improvement and research. This paper contributes to the ongoing discussion of health data governance by detailing the experiences of nine multisite research initiatives across the country. The rich set of experiences from these initiatives, as well as a number of resources used by project participants to work through various challenges, are documented and collected here for others wishing to learn from their collective efforts. The paper does not attempt to catalog the full spectrum of governance issues that could potentially surface in the course of multisite research projects using ECD. Rather, the goal was to provide a snapshot in time of data-sharing challenges and navigation strategies, as well as validation that privacy-protective, legally compliant clinical data sharing across sites is currently possible. Finally, the paper also provides a foundation and framing for a broader community resource on governance-a "governance toolkit"-that will create a virtual space for the further discussion and sharing of promising practices.

Preparing Electronic Clinical Data for Quality Improvement and Comparative Effectiveness Research: The SCOAP CERTAIN Automation and Validation Project

Background:

The field of clinical research informatics includes creation of clinical data repositories (CDRs) used to conduct quality improvement (QI) activities and comparative effectiveness research (CER). Ideally, CDR data are accurately and directly abstracted from disparate electronic health records (EHRs), across diverse health-systems.

Objective:

Investigators from Washington State’s Surgical Care Outcomes and Assessment Program (SCOAP) Comparative Effectiveness Research Translation Network (CERTAIN) are creating such a CDR. This manuscript describes the automation and validation methods used to create this digital infrastructure.

Methods:

SCOAP is a QI benchmarking initiative. Data are manually abstracted from EHRs and entered into a data management system. CERTAIN investigators are now deploying Caradigm’s Amalga™ tool to facilitate automated abstraction of data from multiple, disparate EHRs. Concordance is calculated to compare data automatically to manually abstracted. Performance measures are calculated between Amalga and each parent EHR. Validation takes place in repeated loops, with improvements made over time. When automated abstraction reaches the current benchmark for abstraction accuracy - 95% - itwill ‘go-live’ at each site.

Progress to Date:

A technical analysis was completed at 14 sites. Five sites are contributing; the remaining sites prioritized meeting Meaningful Use criteria. Participating sites are contributing 15–18 unique data feeds, totaling 13 surgical registry use cases. Common feeds are registration, laboratory, transcription/dictation, radiology, and medications. Approximately 50% of 1,320 designated data elements are being automatically abstracted—25% from structured data; 25% from text mining.

Conclusion:

In semi-automating data abstraction and conducting a rigorous validation, CERTAIN investigators will semi-automate data collection to conduct QI and CER, while advancing the Learning Healthcare System.

Expanding research to provide an evidence base for nutritional interventions for the management of inborn errors of metabolism

A trans-National Institutes of Health initiative, Nutrition and Dietary Supplement Interventions for Inborn Errors of Metabolism (NDSI-IEM), was launched in 2010 to identify gaps in knowledge regarding the safety and utility of nutritional interventions for the management of inborn errors of metabolism (IEM) that need to be filled with evidence-based research. IEM include inherited biochemical disorders in which specific enzyme defects interfere with the normal metabolism of exogenous (dietary) or endogenous protein, carbohydrate, or fat. For some of these IEM, effective management depends primarily on nutritional interventions. Further research is needed to demonstrate the impact of nutritional interventions on individual health outcomes and on the psychosocial issues identified by patients and their families. A series of meetings and discussions were convened to explore the current United States' funding and regulatory infrastructure and the challenges to the conduct of research for nutritional interventions for the management of IEM. Although the research and regulatory infrastructure are well-established, a collaborative pathway that includes the professional and advocacy rare disease community and federal regulatory and research agencies will be needed to overcome current barriers.

Ensuring Support for Research and Quality Improvement (QI) Networks: Four Pillars of Sustainability-An Emerging Framework

Multi-institutional research and quality improvement (QI) projects using electronic clinical data (ECD) hold great promise for improving quality of care and patient outcomes but typically require significant infrastructure investments both to initiate and maintain the project over its duration. Consequently, it is important for these projects to think holistically about sustainability to ensure their long-term success. Four "pillars" of sustainability are discussed based on the experiences of EDM Forum grantees and other research and QI networks. These include trust and value, governance, management, and financial and administrative support. Two "foundational considerations," adaptive capacity and policy levers, are also discussed.

Learning How to Learn: How AcademyHealth is Supporting Evidence Generation in a Transforming World

The field of health services research faces significant challenges as it aims to address pressing issues of quality and cost in the US healthcare system. Major advances in the availability of electronic clinical data (ECD) provide the opportunity to address questions that are important to the recipients, providers, and purchasers of health care. This is where eGEMs has a role to play, meeting an expressed need in the scientific community by disseminating approaches and methods for using ECD. eGEMs can help researchers address these important questions and consider strategies to further improve the US healthcare system.

A tall order on a tight timeframe: stakeholder perspectives on comparative effectiveness research using electronic clinical data

Background & significance: The AcademyHealth Electronic Data Methods Forum aims to advance the national dialogue on the use of electronic clinical data (ECD) for comparative effectiveness research (CER), patient-centered outcomes research, and quality improvement by facilitating exchange and collaboration among eleven research projects and external stakeholders. AcademyHealth conducted a mixed-method needs assessment with the Electronic Data Methods Forum’s key stakeholders to assess: stakeholder views on developing new infrastructure for CER using ECD; current gaps in knowledge with respect to CER; and expectations for a learning health system. Methods: AcademyHealth conducted 50 stakeholder interviews between August 2011 and November 2011 with participants from the following seven stakeholder groups: government, business/payer, industry, healthcare delivery, patient/consumer, nonprofit/policy and research. With input from key collaborators, AcademyHealth designed a semi-structured interview guide and a short survey. Reviewers used the qualitative data analysis software NVivo to code the transcripts and to identify and manage complex concepts. Quantitative data from the questionnaire has been integrated with the final analysis as relevant. Results: The analysis of recurring concepts in the interviews focus on five central themes: stakeholders have substantial expectations for CER using ECD, both with respect to addressing the limitations of traditional research studies, and generating meaningful evidence for decision-making and improving patient outcomes; stakeholders are aware of many challenges related to implementing CER with ECD, including the need to develop appropriate governance, assess and manage data quality, and develop methods to address confounding in observational data; stakeholders continue to struggle to define ‘patient-centeredness’ in CER using ECD, adding complexity to attaining this goal; stakeholders express that improving translation and dissemination of CER, and how research can be ‘useful’ at the point of care, can help mitigate negative perceptions of the CER ‘brand’; and stakeholders perceive a need for a substantial ‘culture shift’ to facilitate collaborative science and new ways of conducting biomedical and outcomes research. Many stakeholders proposed approaches or solutions they felt might address the challenges identified.