Practice-Based Research Networks and the Mandate for Real-World Evidence

2018 ◽  
Vol 44 (2-3) ◽  
pp. 219-236 ◽  
Author(s):  
Elizabeth Hall-Lipsy ◽  
Leila Barraza ◽  
Christopher Robertson
Keyword(s):  
Real World ◽  
Clinical Care ◽  
Observational Research ◽  
Research Networks ◽  
Real World Evidence ◽  
Academic Hospitals ◽  
Challenges And Opportunities ◽  
Practice Based Research ◽  
Research Findings ◽  
Primary Care Clinicians

The 21st Century Cures Act encourages the Food and Drug Administration to consider “real-world evidence” in its regulation of the safety and efficacy of drugs and devices. Many have interpreted this mandate to focus on non-randomized observational research. However, we suggest that regulatory science must also move from rarefied academic hospitals to community-based settings, where the vast majority of patients in fact receive care in the fragmented U.S. healthcare system. This move is especially important if innovations are to reach, and be validated in, more diverse populations. A solution can be found in the 183 Practiced-Based Research Networks (“PBRN”), i.e., groups of primary care clinicians and practices in all 50 states working to improve clinical care and translate research findings into practice. This symposium contribution seeks to (1) describe some of the common shortcomings of clinical trials, (2) explore the opportunities and challenges posed by use of real-world evidence as a basis for drug and device regulation, (3) briefly describe the history and evolution of PBRNs, and (4) articulate the challenges and opportunities for using PBRNs to fulfill the 21st Century Cures Act mandate for real-world evidence.

The role of real-world evidence in clinical care: A survey of oncology leaders.

2018 ◽  
Vol 36 (15_suppl) ◽  
pp. e18515-e18515
Author(s):  
Melissa Stahl ◽  
Alissa M Winzeler ◽  
Ali Zaman ◽  
Nicole Shelby ◽  
James Lin Chen ◽  
...  
Keyword(s):  
Real World ◽  
Clinical Care ◽  
Real World Evidence

scholarly journals Increasing Trust in Real-World Evidence Through Evaluation of Observational Data Quality

2021 ◽  
Author(s):  
Clair Blacketer ◽  
Frank J Defalco ◽  
Patrick B Ryan ◽  
Peter R Rijnbeek
Keyword(s):  
Data Quality ◽  
Real World ◽  
R Package ◽  
Observational Research ◽  
Real World Data ◽  
Quality Reporting ◽  
Healthcare Data ◽  
Real World Evidence ◽  
Quality Checks

Advances in standardization of observational healthcare data have enabled methodological breakthroughs, rapid global collaboration, and generation of real-world evidence to improve patient outcomes. Standardizations in data structure, such as use of Common Data Models (CDM), need to be coupled with standardized approaches for data quality assessment. To ensure confidence in real-world evidence generated from the analysis of real-world data, one must first have confidence in the data itself. The Data Quality Dashboard is an open-source R package that reports potential quality issues in an OMOP CDM instance through the systematic execution and summarization of over 3,300 configurable data quality checks. We describe the implementation of check types across a data quality framework of conformance, completeness, plausibility, with both verification and validation. We illustrate how data quality checks, paired with decision thresholds, can be configured to customize data quality reporting across a range of observational health data sources. We discuss how data quality reporting can become part of the overall real-world evidence generation and dissemination process to promote transparency and build confidence in the resulting output. Transparently communicating how well CDM standardized databases adhere to a set of quality measures adds a crucial piece that is currently missing from observational research. Assessing and improving the quality of our data will inherently improve the quality of the evidence we generate.

OEN: Multi-center, international, real-world evidence studies performed using health records without data pooling—The use of a common data model and shared analytical methods.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13554-e13554
Author(s):  
Bethany Levick ◽  
Sue Cheeseman ◽  
Eun Ji Nam ◽  
Haewon Doh ◽  
Subin Lim ◽  
...  
Keyword(s):  
Real World ◽  
Data Model ◽  
Clinical Care ◽  
Common Data Model ◽  
Local Data ◽  
Large Hospital ◽  
Patient Level Data ◽  
Patient Level ◽  
Real World Evidence ◽  
Level Data

e13554 Background: The value of real-world evidence derived from the care of patients managed outside the context of clinical trials is well recognised. However, the ability to link data from multiple centres, especially those from different countries, is complicated by complex legal and information governance differences. The Oncology Evidence Network is a collaboration of large hospital centres, with strong clinical informatics capabilities in six countries in Europe and Asia working with the support of an industrial partner to provide high quality, real world data reflecting routine clinical care. We have developed an efficient workflow based on a study-specific common data model (CDM) clinically validated at each site and analysed with a single analysis script, which embeds a set of data quality rules. Local implementation allows each centre to generate analytical outputs aligned across the different sites without the need for any patient level data to leave the participating site. This approach has been designed and tested in Epithelial Ovarian Cancer (EOC) patients. Methods: A CDM was agreed using expert advisors from each centre. Clinical alignment was achieved through iterative assessment of clinical vignettes, to ensure common definitions of clinical assessment, prognosis, and treatment algorithms in EOC patients. A data guide detailing variable level derivations and validation rules, general data coding principles, and conversions/codes from international coding systems was developed. The analysis scripts were implemented as a bespoke package (OpenOvary) in R. The package includes functions to validate the data against the CDM, and generate a standard output including tables, numerical summaries and Kaplan-Meier analysis of progression and overall survival. Results: 2,925 patient records from 6 centres across 6 countries were included in the study with 27 key data items curated by each centre. Treatment data is available detailing relevant surgical procedures and their outcomes, and regimens of SACT throughout patients’ care from diagnosis to death. Data completeness was generally high for key data items, with missing data ranging from 0-16% for FIGO stage at diagnosis and 0-14% for tumour morphology. The CDM and R script will be made publicly available for other centres to adopt and facilitate analysis of their local data. Conclusions: This collaboration has brought together a substantial body of data describing the care and outcomes for EOC patients. A CDM and flexible shared analysis approach enabled unified analysis and reporting whilst avoiding the transfer of patient level data and its pooling into a common database. The process of clinical and data alignment has generated a replicable model for rapid extension to other study centres to join the EOC study, or application to other disease areas.

scholarly journals How to Bridge Research Results to Everyday Clinical Care?

2017 ◽  
Vol 42 (1) ◽  
pp. 1-9
Author(s):  
VV Gordan
Keyword(s):  
Clinical Care ◽  
Evidence Based ◽  
Research Model ◽  
Health Providers ◽  
The Public ◽  
New Knowledge ◽  
Practice Based Research ◽  
Research Findings ◽  
Speed Up ◽  
Research Questions

SUMMARY Laboratory and clinical studies are essential to the advancement of sciences. However, a significant gap exists between the research findings and clinical practice. Therefore, research findings can be of little importance if their outcome cannot be directly or indirectly applied to everyday clinical care or readily translated. This paper focuses on how we can shorten the gap between the generation of new knowledge and their implementation into everyday clinical care. A new model is discussed where clinicians are the ones generating the research idea are paired with researchers. They collaborate on studies whose results are readily applicable to everyday practice. Partnering with health providers on studies that address everyday clinical research questions is a potential solution to speed up the translation of the research findings. Generating clinically applicable results can better improve the health of the public. Quoting Dr. Lawrence W. Green: “If we want more evidence-based practice, we need more practice-based evidence.” This paper presents the practice-based research model as a solution to address this knowledge gap.

scholarly journals Bridging the Gap Between RCTs and RWE Through Endpoint Selection

2020 ◽  
Vol 55 (1) ◽  
pp. 90-96
Author(s):  
Robert J. LoCasale ◽  
Chris L. Pashos ◽  
Ben Gutierrez ◽  
Nancy A. Dreyer ◽  
Toby Collins ◽  
...  
Keyword(s):  
Real World ◽  
Clinical Relevance ◽  
Patient Benefit ◽  
Real World Evidence ◽  
Challenges And Opportunities

AbstractThis commentary is authored by several industry real-world evidence (RWE) experts, with support from IQVIA, as part of the 'RWE Leadership Forum': a group of Industry Leaders who have come together as non-competitive partners to understand and respond to RWD/E challenges and opportunities with a single expert voice. Here, the forum discusses the value in bridging the industry disconnect between RTCs and RWE, with a view to promoting the use of RWE in the RCT environment. RCT endpoints are explored along several axes including their clinical relevance and their measure of direct patient benefit, and then compared with their real-world counterparts to identify suitable paths, or gaps, for assimilating RWE endpoints into the RCT environment.

scholarly journals Role of real-world evidence in informing cancer care: lessons from colorectal cancer

2019 ◽  
Vol 26 (1) ◽  
Author(s):  
A. Batra ◽  
W. Y. Cheung
Keyword(s):  
Colorectal Cancer ◽  
Real World ◽  
Cancer Care ◽  
Clinical Care ◽  
Real World Data ◽  
Cancer Management ◽  
Randomized Controlled ◽  
Real World Evidence ◽  
Research Questions

The term “real-world evidence” (rwe) describes the analysis of data that are collected beyond the context of clinical trials. The use and application of rwe have become increasingly common and relevant, especially in oncology, because there is growing recognition that randomized controlled trials (rcts) might not be sufficiently representative of the entire patient population that is affected by cancer, and that specific clinical research questions might be best addressed by real-world data. In this brief review, our main aim is to highlight the role of rwe in informing cancer care, particularly focusing on specific examples from colorectal cancer. Our hope is to illustrate the ways in which rwe can complement rcts in improving the understanding of cancer management and how rwe can facilitate cancer treatment decisions for real-world patients encountered in routine clinical care.

scholarly journals Strengthening pharma's contract with society: the value of trusted partnerships between pharma and healthcare facilitated by real-world data

2020 ◽  
Vol 9 (3) ◽  
pp. 155-159
Author(s):  
Michael J Seewald ◽  
Jonathan M Plumb ◽  
Ben Gutierrez ◽  
Johan Liwing ◽  
Maurille Feudjo Tepie ◽  
...  
Keyword(s):  
Real World ◽  
White Paper ◽  
Medical Community ◽  
Real World Data ◽  
World Data ◽  
Real World Evidence ◽  
Challenges And Opportunities

This White Paper is authored by 11 industry real-world evidence (RWE) experts, with support from IQVIA, as part of the ‘RWE Leadership Forum’: a group of industry leaders who come together as noncompetitive partners to understand and respond to internal or external RWD/E challenges and opportunities with a single expert voice. Herein we aim to clarify the rules of engagement between pharma and healthcare in order to establish trust-based partnerships, which will unlock unique value for society, including the medical community and the ultimate beneficiary, the patient.

Spotlight commentary: A role for real‐world evidence to inform the clinical care of patients with diabetes mellitus

2021 ◽  
Author(s):  
Charles E. Leonard ◽  
James H. Flory ◽  
Robert Likić ◽  
Olayinka O. Ogunleye ◽  
Li Wei ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Real World ◽  
Clinical Care ◽  
Real World Evidence ◽  
Patients With Diabetes

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

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.

Sign in / Sign up

Export Citation Format

Share Document