STaRT-RWE: structured template for planning and reporting on the implementation of real world evidence studies.
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ABSTRACT:
SUBMITTER: Wang SV
PROVIDER: S-EPMC8489282 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Publications
STaRT-RWE: structured template for planning and reporting on the implementation of real world evidence studies.
Wang Shirley V SV Pinheiro Simone S Hua Wei W Arlett Peter P Uyama Yoshiaki Y Berlin Jesse A JA Bartels Dorothee B DB Kahler Kristijan H KH Bessette Lily G LG Schneeweiss Sebastian S
BMJ (Clinical research ed.) 20210112
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Project description:ObjectivesReal-world evidence (RWE) generation can be enhanced by including patient-reported outcomes (PROs). Methods for collecting and using PRO data in the real-world setting are currently underdeveloped and there is no international guidance specific to its use in this context. This study explored stakeholders' perspectives and needs for using PROs in RWE generation. Barriers, facilitators, and opportunities for wider use of PROs in real-world studies were also investigated.MethodsOnline semi-structured interviews were conducted with international stakeholders: patients, patient advocates, regulators, payers, clinicians, academic researchers, and industry experts. Interviews were recorded, transcribed verbatim and analysed using NVivo 20. Thematic analysis was conducted based on the updated Consolidated Framework for Implementation Research (CFIR).ResultsTwenty-three interviews were conducted. Participants confirmed that the use of PROs in RWE generation is not yet well established. Participants expressed a mixed level of confidence in the value of PROs collected in a real-world setting. Operational challenges associated with collecting routine PRO data to inform care delivery at the individual level (e.g., setting up infrastructure) need to be addressed. Methodological and other challenges (e.g., financing research) associated with collecting prospective de novo data in a real-world setting should be considered to facilitate PRO utilisation in real-world studies.ConclusionsSeveral opportunities and challenges were identified regarding the broader use of PROs in RWE research. Joint efforts from different stakeholders are needed to maximise PRO implementation, with consideration given to each stakeholders' specific needs (e.g., by developing good practices).
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Project description:Transparency is increasingly promoted to instill trust in nonrandomized studies using real-world data. Graphics and data visualizations support transparency by aiding communication and understanding, and can inform study design and analysis decisions. However, other than graphical representation of a study design and flow diagrams (e.g., a Consolidated Standards of Reporting Trials [CONSORT] like diagram), specific standards on how to maximize validity and transparency with visualization are needed. This paper provides guidance on how to use visualizations throughout the life cycle of a pharmacoepidemiology study-from initial study design to final report-to facilitate rationalized and transparent decision-making about study design and implementation, and clear communication of study findings. Our intent is to help researchers align their practices with current consensus statements on transparency.
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Project description:Computed tomography (CT) scans represent the gold standard in the planning of functional endoscopic sinus surgeries (FESS). Yet, radiologists and otolaryngologists have different perspectives on these scans. In general, residents often struggle with aspects involved in both reporting and operation planning. The aim of this study was to compare the completeness of structured reports (SR) of preoperative CT images and structured operation planning (SOP) to conventional reports (CR) and conventional operation planning (COP) to potentially improve future treatment decisions on an individual level. In total, 30 preoperative CT scans obtained for surgical planning of patients scheduled for FESS were evaluated using SR and CR by radiology residents. Subsequently, otolaryngology residents performed a COP using free texts and a SOP using a specific template. All radiology reports and operation plannings were evaluated by two experienced FESS surgeons regarding their completeness for surgical planning. User satisfaction of otolaryngology residents was assessed by using visual analogue scales. Overall radiology report completeness was significantly higher using SRs regarding surgically important structures compared to CRs (84.4 vs. 22.0%, p<0.001). SOPs produced significantly higher completeness ratings (97% vs. 39.4%, p<0.001) regarding pathologies and anatomical variances. Moreover, time efficiency was not significantly impaired by implementation of SR (148 s vs. 160 s, p = 0.61) and user satisfaction was significantly higher for SOP (VAS 8.1 vs. 4.1, p<0.001). Implementation of SR and SOP results in a significantly increased completeness of radiology reports and operation planning for FESS. Consequently, the combination of both facilitates surgical planning and may decrease potential risks during FESS.
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Project description:Real-world evidence used for regulatory, payer, and clinical decision-making requires principled epidemiology in design and analysis, applying methods to minimize confounding given the lack of randomization. One technique to deal with potential confounding is propensity score (PS) analysis, which allows for the adjustment for measured preexposure covariates. Since its first publication in 2009, the high-dimensional propensity score (hdPS) method has emerged as an approach that extends traditional PS covariate selection to include large numbers of covariates that may reduce confounding bias in the analysis of healthcare databases. hdPS is an automated, data-driven analytic approach for covariate selection that empirically identifies preexposure variables and proxies to include in the PS model. This article provides an overview of the hdPS approach and recommendations on the planning, implementation, and reporting of hdPS used for causal treatment-effect estimations in longitudinal healthcare databases. We supply a checklist with key considerations as a supportive decision tool to aid investigators in the implementation and transparent reporting of hdPS techniques, and to aid decision-makers unfamiliar with hdPS in the understanding and interpretation of studies employing this approach. This article is endorsed by the International Society for Pharmacoepidemiology.
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Project description:Canadian provinces routinely collect patient-level data for administrative purposes. These real-world data (RWD) can be used to generate real-world evidence (RWE) to inform clinical care and healthcare policy. The CanREValue Collaboration is developing a framework for the use of RWE in cancer drug funding decisions. A Data Working Group (WG) was established to identify data assets across Canada for generating RWE of oncology drugs. The mapping exercise was conducted using an iterative scan with informant surveys and teleconference. Data experts from ten provinces convened for a total of three teleconferences and two in-person meetings from March 2018 to September 2019. Following each meeting, surveys were developed and shared with the data experts which focused on identifying databases and data elements, as well as a feasibility assessment of conducting RWE studies using existing data elements and resources. Survey responses were compiled into an interim data report, which was used for public stakeholder consultation. The feedback from the public consultation was used to update the interim data report. We found that databases required to conduct real-world studies are often held by multiple different data custodians. Ninety-seven databases were identified across Canada. Provinces held on average 9 distinct databases (range: 8-11). An Essential RWD Table was compiled that contains data elements that are necessary, at a minimal, to conduct an RWE study. An Expanded RWD Table that contains a more comprehensive list of potentially relevant data elements was also compiled and the availabilities of these data elements were mapped. While most provinces have data on patient demographics (e.g., age, sex) and cancer-related variables (e.g., morphology, topography), the availability and linkability of data on cancer treatment, clinical characteristics (e.g., morphology and topography), and drug costs vary among provinces. Based on current resources, data availability, and access processes, data experts in most provinces noted that more than 12 months would be required to complete an RWE study. The CanREValue Collaboration's Data WG identified key data holdings, access considerations, as well as gaps in oncology treatment-specific data. This data catalogue can be used to facilitate future oncology-specific RWE analyses across Canada.
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Project description:ObjectiveReal-world data (RWD) and real-world evidence (RWE) have been paid more and more attention in recent years. We aimed to evaluate the reporting quality of cohort studies using real-world data (RWD) published between 2013 and 2021 and analyze the possible factors.MethodsWe conducted a comprehensive search in Medline and Embase through the OVID interface for cohort studies published from 2013 to 2021 on April 29, 2022. Studies aimed at comparing the effectiveness or safety of exposure factors in the real-world setting were included. The evaluation was based on the REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. Agreement for inclusion and evaluation was calculated using Cohen's kappa. Pearson chi-square test or Fisher's exact test and Mann-Whitney U test were used to analyze the possible factors, including the release of RECORD, journal IFs, and article citations. Bonferroni's correction was conducted for multiple comparisons. Interrupted time series analysis was performed to display the changes in report quality over time.Results187 articles were finally included. The mean ± SD of the percentage of adequately reported items in the 187 articles was 44.7 ± 14.3 with a range of 11.1-87%. Of 23 items, the adequate reporting rate of 10 items reached 50%, and the reporting rate of some vital items was inadequate. After Bonferroni's correction, the reporting of only one item significantly improved after the release of RECORD and there was no significant improvement in the overall report quality. For interrupted time series analysis, there were no significant changes in the slope (p = 0.42) and level (p = 0.12) of adequate reporting rate. The journal IFs and citations were respectively related to 2 areas and the former significantly higher in high-reporting quality articles.ConclusionThe endorsement of the RECORD cheklist was generally inadequate in cohort studies using RWD and has not improved in recent years. We encourage researchers to endorse relevant guidelines when utilizing RWD for research.
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Project description:Implementation studies are often poorly reported and indexed, reducing their potential to inform initiatives to improve healthcare services. The Standards for Reporting Implementation Studies (StaRI) initiative aimed to develop guidelines for transparent and accurate reporting of implementation studies. Informed by the findings of a systematic review and a consensus-building e-Delphi exercise, an international working group of implementation science experts discussed and agreed the StaRI Checklist comprising 27 items. It prompts researchers to describe both the implementation strategy (techniques used to promote implementation of an underused evidence-based intervention) and the effectiveness of the intervention that was being implemented. An accompanying Explanation and Elaboration document (published in BMJ Open, doi:10.1136/bmjopen-2016-013318) details each of the items, explains the rationale, and provides examples of good reporting practice. Adoption of StaRI will improve the reporting of implementation studies, potentially facilitating translation of research into practice and improving the health of individuals and populations.
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Project description:BackgroundNumerous models, frameworks, and theories exist for specific aspects of implementation research, including for determinants, strategies, and outcomes. However, implementation research projects often fail to provide a coherent rationale or justification for how these aspects are selected and tested in relation to one another. Despite this need to better specify the conceptual linkages between the core elements involved in projects, few tools or methods have been developed to aid in this task. The Implementation Research Logic Model (IRLM) was created for this purpose and to enhance the rigor and transparency of describing the often-complex processes of improving the adoption of evidence-based interventions in healthcare delivery systems.MethodsThe IRLM structure and guiding principles were developed through a series of preliminary activities with multiple investigators representing diverse implementation research projects in terms of contexts, research designs, and implementation strategies being evaluated. The utility of the IRLM was evaluated in the course of a 2-day training to over 130 implementation researchers and healthcare delivery system partners.ResultsPreliminary work with the IRLM produced a core structure and multiple variations for common implementation research designs and situations, as well as guiding principles and suggestions for use. Results of the survey indicated a high utility of the IRLM for multiple purposes, such as improving rigor and reproducibility of projects; serving as a "roadmap" for how the project is to be carried out; clearly reporting and specifying how the project is to be conducted; and understanding the connections between determinants, strategies, mechanisms, and outcomes for their project.ConclusionsThe IRLM is a semi-structured, principle-guided tool designed to improve the specification, rigor, reproducibility, and testable causal pathways involved in implementation research projects. The IRLM can also aid implementation researchers and implementation partners in the planning and execution of practice change initiatives. Adaptation and refinement of the IRLM are ongoing, as is the development of resources for use and applications to diverse projects, to address the challenges of this complex scientific field.
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