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Digital Data in Lupus: Metrics and Future Directions

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Outcome Measures and Metrics in Systemic Lupus Erythematosus

Abstract

With technologic advances and changes come opportunities to learn and leverage digital data to advance science and make important insights. Using digital data to answer questions about the causes and consequences of systemic lupus erythematosus (SLE) is not novel, although the types of data that we have access to continue to evolve. In this chapter we begin by describing the major types of digital data, such as electronic health records (EHR), registries, data from wearable technologies, and social media. We then elaborate on important caveats to this kind of research, walking the reader through possible threats to validity including selection bias, limitations to generalizability, measurement error, and missing data.

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Disclosures

YC is a sub-investigator on ClinicalTrials.gov identifier NCT03098823.

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Authors and Affiliations

  1. Department of Epidemiology & Population Health, and Division of Immunology & Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Julia F. Simard

  2. Division of Immunology & Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Yashaar Chaichian

  3. Department of Epidemiology & Population Health, and Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Titilola Falasinnu

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  1. Julia F. Simard
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  3. Titilola Falasinnu
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Correspondence to Julia F. Simard .

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Editors and Affiliations

  1. Medicine, University of Toronto, Toronto, ON, Canada

    Zahi Touma

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Simard, J.F., Chaichian, Y., Falasinnu, T. (2021). Digital Data in Lupus: Metrics and Future Directions. In: Touma, Z. (eds) Outcome Measures and Metrics in Systemic Lupus Erythematosus. Springer, Cham. https://doi.org/10.1007/978-3-030-73303-2_10

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  • DOI: https://doi.org/10.1007/978-3-030-73303-2_10

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  • Online ISBN: 978-3-030-73303-2

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