Heart Failure Data Challenge: Democratizing Data, Modernizing Methods, and Interpreting Inequity

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This thematic issue of Circulation: Heart Failure is dedicated to the findings of the Heart Failure Data Challenge. In 2021, the American Heart Association and the Association of Black Cardiologists came together to encourage cross collaboration among researchers to deepen understanding of the influence of social determinants of health on heart failure. The resulting initiative challenged applicants to leverage the de-identified Get With The Guidelines (GWTG)-Heart Failure (https://www.heart.org/en/professional/quality-improvement/get-with-the-guidelines/get-with-the-guidelines-heart-failure) registry data combined with other publicly available datasets (eg, those at BioLINCC [https://biolincc.nhlbi.nih.gov/home/] and dbGAP [https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/about.cgi]). Specifically, applicants were asked to include 1 of 3 questions in their proposal: evaluate the association of certain social factors on incident heart failure risk; evaluate the association of certain social factors on outpatient care related to hospital admission; and evaluate the impact of social factors on hospital length of stay according to race and ethnicity. The results of this collaborative effort have led to an entire issue of Circulation: Heart Failure dedicated to the best of that science and the multiple lessons learned.

The Heart Failure Data Challenge was enabled by a democratization of the GWTG data for broader use. GWTG (https://www.heart.org/en/professional/quality-improvement) is the American Heart Association’s premier hospital-based quality improvement program designed to close the treatment gap in cardiovascular disease, stroke, and resuscitation. The GWTG-Heart Failure registry collects patient-level data elements and evidence-based measures. Each challenge participant was provided a free Precision Medicine Platform (PMP) workspace (https://precision.heart.org/workspace) to conduct all analyses. The PMP warehouses de-identified GWTG-Heart Failure data from 2017 to 2020 in HIPPA compliant and FedRAMP certified workspaces. The PMP provides an easy-to-use, web-based user interface that allows participants to access a secure, cloud-based environment. It contains a variety of standard software and packages such as Python and R. The platform workspace leverages Jupyter (https://precision.heart.org/jupyter_notebooks/about) Notebooks and RStudio (https://bookdown.org/yihui/rmarkdown/notebook.html) to allow users to create notebooks to document and display results. Thus, the PMP effectively allows the valuable GWTG to be used by anyone with the clinical questions, technical skill, and motivation to dig in, consistent with broader national efforts to create open access to publicly funded and charitable foundation-based datasets. The PMP is further optimized by encouraging users to review the Quality Research Library (https://www.heart.org/en/professional/quality-improvement/quality-research-and-publications) to ensure their proposed research does not overlap existing publications and ongoing analyses. And given the complexity of the registry data and a long history of analyses, the AHA Heart Failure Systems of Care Advisory Group oversees the PMP to limit redundancy, check feasibility, focus questions, answer questions (at ), and moderate the overall activity within the GWTG registry.

The Heart Failure Data Challenge resulted in a flurry of analyses from around the world. In this thematic issue, Circulation: Heart Failure publishes 5 of the best PMP analyses lead by 5 world-class teams of researchers: Li et al1 “Improving Fairness in the Prediction of Heart Failure Length-of-Stay by Integrating Social Determinants of Health”; Pandey et al2 “Race, Social Determinants of Health, and Length of Stay Among Hospitalized Patients With Heart Failure: An Analysis From the Get With The Guidelines-Heart Failure Registry”; Rao et al3 “Neighborhood Socioeconomic Disadvantage and Hospitalized Heart Failure Outcomes in the American Heart Association Get With The Guidelines-Heart Failure Registry”; Tran et al4 “Clinical and Socioeconomic Determinants of Angiotensin Receptor Blocker/Neprilysin Inhibitor Prescription at Hospital Discharge in Patients With Heart Failure With Reduced Ejection Fraction”; and Zheng et al5 “Disparities in Hospital Length of Stay Across Race and Ethnicity Among Patients With Heart Failure.”

These manuscripts provide valuable insights into 3 broader areas of science. First, clinical takeaways: what does this body of science tell us about caring for diverse populations with heart failure? Second, understanding social constructs: what have we learned about disparities, disadvantage, and outcomes in patients hospitalized with heart failure? Third, comparing methods: as some of these analyses came to different conclusions about similar questions, what lessons can we draw about optimal approaches and techniques? Each of these 3 areas is further explored in 3 accompanying editorials.

The totality of knowledge generated by the Heart Failure Data Challenges and brought together in this thematic issue is remarkable. With unfettered and supported access to GWTG data, we now know far more about the relationship of heart failure with environmental threats, poverty, and inadequate access to health care, food, housing and education. Researchers, clinicians, administrators, and policymakers can use this knowledge to better tackle the health disparities that plague heart failure care.

Article Information

Disclosures Dr Allen reports grant funding from the National Institutes of Health and the Patient-Centered Outcomes Research Institute and consulting fees from ACI Clinical, Boston Scientific, Cytokinetics, and Novartis. Dr Fonarow reports consulting for Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Edwards, Janssen, Medtronic, Merck, and Novartis. Dr Yancy reports no relevant conflicts.

Footnotes

For Disclosures, see page 1006.

The opinions expressed in this article are not necessarily those of the American Heart Association.

Correspondence to: Larry Allen, MD, MHS, 12631 E 17th Ave, Academic Office One, No. 7019, Mailstop B130, Aurora, CO 80045. Email

References

  • 1. Li Y, Wang H, Luo Y. Improving fairness in the prediction of heart failure length-of-stay by integrating social determinants of health.Circ Heart Fail. 2022; 15:1048–1056. doi: 10.1161/CIRCHEARTFAILURE.122.009473LinkGoogle Scholar
  • 2. Segar MW, Keshvani N, Rao S, Fonarow GC, Das SR, Pandey A. Race, social determinants of health, and length of stay among hospitalized patients with heart failure: an analysis from the Get With The Guidelines-Heart Failure registry.Circ Heart Fail. 2022; 15:1026–1035. doi: 10.1161/CIRCHEARTFAILURE.121.009401.LinkGoogle Scholar
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  • 5. Zheng J, Tisdale RL, Heidenreich PA, Sandhu AT. Disparities in hospital length of stay across race and ethnicity among patients with heart failure.Circ Heart Fail. 2022; 15:1057–1068. doi: 10.1161/CIRCHEARTFAILURE.121.009362.LinkGoogle Scholar

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