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Research Registry

Patient Governance in a Patient-Powered Research Network for Adult Rheumatologic Conditions

Patient-Powered Research Networks (PPRNs) are a unique type of patient-powered patient registry for patient-centered outcomes research. Nowell et al. describe the governance structure of a newly formed PPRN and the activities undertaken prelaunch and postlaunch to evaluate and improve the engagement of patient stakeholders in governance. Members of an online community for patients are willing to share their expertise to participate in and shape research governance and are able to provide more specific recommendations for improvement than investigator-led pre-evaluation/post evaluation.

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Information Patients Can Provide Will Strengthen the Real-World Evidence That Matters to Them

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Nowell writes that patient-generated data has the potential to improve health outcomes and drive innovation and these potentials have not been fully realized. Nowell highlights the challenges of collecting and using real-world data, the value and challenges of patient-generated data for real-world evidence and engaged patient research networks. Patients can provide real-world data but must be appropriately and effectively engaged to do so.

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Digital Interventions to Build a Patient Registry for Rheumatology Research

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This article describes key issues, processes, and outcomes related to the development of a patient registry for rheumatology research using a digital platform to track useful data about patients’ conditions for their own use while contributing to research. ArthritisPower provides evidence of the value of digital interventions to build community support for research and to transform patient engagement and patient-generated data capture.

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Stakeholders’ Views on Data Sharing in Multicenter Studies

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The aim of this study was to understand stakeholders’ views on data sharing in multicenter comparative effectiveness research studies and the value of privacy-protecting methods. 11 semi-structured interviews were held with patients, researchers, Institutional Review Board staff, multicenter research governance experts, and healthcare system leaders within 5 US Stakeholder groups. Stakeholders were open to data sharing in multicenter studies that offer value and minimize security risks. Cost and security risks were the primary influences against data sharing.

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Validity of Privacy-Protecting Analytical Methods That Use Only Aggregate-Level Information to Conduct Multivariable-Adjusted Analysis in Distributed Data Networks.

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Protecting privacy while adequately adjusting for a large number of covariates poses methodological challenges for distributed data networks that can enable large-scale epidemiologic studies. Using 2 empirical examples, Li et al. determined that when used in conjunction with confounder summary scores, several combinations of data-sharing approaches and confounding adjustment methods allow researchers to perform multivariable-adjusted analysis using only aggregate-level information from participating sites and produce results identical to or comparable to those from pooled individual-level data analysis which help to protect privacy.

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Privacy-Protecting Analytical Methods Permit Multivariable-Adjusted Analysis Using Only Aggregate-Level Data in Multi-Center Distributed Data Networks: Results from Empirical Analyses.

Protecting privacy while adequately adjusting for a large number of covariates poses methodological challenges for distributed data networks that can enable large-scale epidemiologic studies. Using 2 empirical examples, Li et al. determined that when used in conjunction with confounder summary scores, several combinations of data-sharing approaches and confounding adjustment methods allow researchers to perform multivariable-adjusted analysis using only aggregate-level information from participating sites and produce results identical to or comparable to those from pooled individual-level data analysis which help to protect privacy.

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OPEX: Development of a novel overall patient experience measure to facilitate interpretation of comparison effectiveness studies

The objective of this study was to develop a patient reported measure to capture the overall experience, including benefits and harms, of treatment using Rheumatoid Arthritis (RA) as an example. The authors utilized Trajectory Mapping to organize adverse events and improvements from treatments to create a hierarchy of patient experiences. The results of this study help to contextualize what types of adverse events patients are willing to tolerate for levels of improvement when trying treatments.

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The Increasing Focus on the Patient in Patient Registries.

This chapter of “21st Century Patient Registries: Registries for Evaluating Patient Outcomes: A User’s Guide: 3rd Edition” by Daughtery et al. discusses the growing focus on patient-centeredness in clinical research, medical care, and regulatory sciences which can lead to the increase of availability and dissemination of evidence that can be used to inform health care decision-making. There are some challenges in the use of patient registries as highlighted by patients such as accessibility of participation, translation of non-English materials, and privacy concerns that should be addressed. This chapter provides an overview of important topics relating to patient-centeredness in registries, engaging patients as stakeholders, the use of digital health technologies, and other patient-centric designs.

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Statement of Data Sharing Goals for Nonprofit Funders of Clinical Trials

Coetzee et al. reports that nonprofit funders, including disease advocacy and patient-focused organizations, play an important role in the promotion and implementation of data sharing policies in clinical research trials which can help to drive policies and influence research culture. Eight goals are highlighted for nonprofit funders of clinical trials: encouraging the co-development of data sharing policies with patient and lay communities, incorporate data sharing concepts and policies as early as possible in clinical trials, use transparent and FAIR approval processes for data access, promote the development of a sustainable and feasible data sharing infrastructure, promote and support the adoption of standards, standard language, and common data elements, include incentives and enforce requirements in funding structures, provide funding for data sharing, and incorporate previous data sharing as a measure of impact. These goals promote a data sharing toolkit for nonprofit funders.

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