Saturday, July 13, 2024

Real-World Data Utilization in Healthcare: Unveiling Social Justice and Equity Through Scoping Review

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The healthcare sector grapples with a significant lack of research directly applicable to clinical practice, often hampering the effective delivery of services. Utilizing real-world data, such as routinely collected patient information, emerges as a viable strategy to generate actionable evidence for clinical and service improvement. This study embarks on a quest to map the extent of published research leveraging real-world clinical data and its role in addressing social justice within healthcare.

Methodological Framework

Building on Arksey and O’Malley’s methodological framework for scoping reviews, this study incorporates enhanced team-based and mixed methods approaches. The research process involves comprehensive searches of electronic databases, followed by stringent screening of papers using predefined inclusion and exclusion criteria. The data extracted from these studies includes clinical areas, data sources, and social justice considerations, reflective of their potential to address health inequities.

Data Analysis and Synthesis

Quantitative data will undergo descriptive analysis, while qualitative data will be explored using conceptual content analysis. This dual approach ensures a holistic understanding of how real-world data is utilized and its implications for healthcare equity. The collaborative and iterative nature of the screening and reviewing process leverages the diverse strengths of the research team, allowing for adaptive responses to emerging challenges.

The review aims to highlight the breadth of research employing routinely collected clinical data and its equity implications. By identifying gaps and making recommendations, the findings will be instrumental for practitioners, researchers, service managers, and commissioners in optimizing their use of real-world data.

Key Inferences

The study provides several valuable insights:

  • Real-world data offers a rich, non-selected sample representing diverse populations, crucial for addressing health disparities.
  • The methodological framework ensures a robust, iterative approach, enhancing the reliability of the findings.
  • Collaboration among a diverse research team promotes comprehensive data analysis and synthesis.
  • Addressing social justice in health requires integrating equity considerations into data analysis frameworks.
  • Recommendations will guide future research and funding priorities, emphasizing equity-focused healthcare improvements.

The study underscores the importance of real-world data in bridging research gaps and fostering social justice within healthcare. By mapping the current landscape, it aims to inform future research endeavors, ensuring that healthcare delivery is both equitable and effective.

Original Article:

PLoS One. 2024 Jul 10;19(7):e0306786. doi: 10.1371/journal.pone.0306786. eCollection 2024.

ABSTRACT

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BACKGROUND: Many areas of healthcare are impacted by a paucity of research that is translatable to clinical practice. Research utilising real-world data, such as routinely collected patient data, may be one option to efficiently create evidence to inform practice and service delivery. Such studies are also valuable for exploring (in)equity of services and outcomes, and benefit from using non-selected samples representing the diversity of the populations served in the ‘real world’. This scoping review aims to identify and map the published research which utilises routinely collected clinical healthcare data. A secondary aim is to explore the extent to which this literature supports the pursuit of social justice in health, including health inequities and intersectional approaches.

METHOD: This review utilises Arksey and O’Malley’s methodological framework for scoping reviews and draws on the recommended enhancements of this framework to promote a team-based and mixed methods approach. This includes searching electronic databases and screening papers based on a pre-specified inclusion and exclusion criteria. Data relevant to the research aims will be extracted from included papers, including the clinical/professional area of the topic, the source of data that was used, and whether it addresses elements of social justice. All screening and reviewing will be collaborative and iterative, drawing on strengths of the research team and responsive changes to challenges will be made. Quantitative data will be analysed descriptively, and conceptual content analysis will be utilised to understand qualitative data. These will be collectively synthesised in alignment to the research aims.

CONCLUSION: Our findings will highlight the extent to which such research is being conducted and published, including gaps and make recommendations for future endeavours for real-world data studies. The findings from this scoping review will be relevant for practitioners and researchers, as well as health service managers, commissioners, and research funders.

PMID:38985705 | DOI:10.1371/journal.pone.0306786

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