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Using the landmark method for creating prediction models in large datasets derived from electronic health records

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Abstract

With the integration of electronic health records (EHRs), health data has become easily accessible and abounded. The EHR has the potential to provide important healthcare information to researchers by creating study cohorts. However, accessing this information comes with three major issues: 1) Predictor variables often change over time, 2) Patients have various lengths of follow up within the EHR, and 3) the size of the EHR data can be computationally challenging. Landmark analyses provide a perfect complement to EHR data and help to alleviate these three issues. We present two examples that utilize patient birthdays as landmark times for creating dynamic datasets for predicting clinical outcomes. The use of landmark times help to solve these three issues by incorporating information that changes over time, by creating unbiased reference points that are not related to a patient’s exposure within the EHR, and reducing the size of a dataset compared to true time-varying analysis. These techniques are shown using two example cohort studies from the Cleveland Clinic that utilized 4.5 million and 17,787 unique patients, respectively.

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Acknowledgments

The authors would like to acknowledge the writing assistance of Stephanie S. Kocian, M.A.T., M.S.

Conflicts of interest

The authors report no potential conflicts of interest.

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Authors and Affiliations

  1. Department of Quantitative Health Sciences, Cleveland Clinic, 9500 Euclid Avenue/JJN3-01, Cleveland, OH, 44195, USA

    Brian J. Wells, Kevin M. Chagin, Bo Hu, Changhong Yu & Michael W. Kattan

  2. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX, 77030, USA

    Liang Li

Authors
  1. Brian J. Wells
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  2. Kevin M. Chagin
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  3. Liang Li
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  4. Bo Hu
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  5. Changhong Yu
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  6. Michael W. Kattan
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Corresponding author

Correspondence to Brian J. Wells.

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Wells, B.J., Chagin, K.M., Li, L. et al. Using the landmark method for creating prediction models in large datasets derived from electronic health records. Health Care Manag Sci 18, 86–92 (2015). https://doi.org/10.1007/s10729-014-9281-3

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  • DOI: https://doi.org/10.1007/s10729-014-9281-3

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