  Objective: Implement and assess personal health identifying information (PHI)
substitution strategies and quantify their privacy preserving benefits.
  Materials and Methods: We implement and assess 3 different `Hiding in Plain
Sight` (HIPS) strategies for PHI replacement including a standard Consistent
replacement strategy, a Random replacement strategy and a novel Markov
model-based strategy. We evaluate the privacy preserving benefits of these
strategies on a synthetic PHI distribution and real clinical corpora from 2
different institutions using a range of false negative error rates (FNER).
  Results: Using FNER ranging from 0.1% to 5% PHI leakage at the document level
could be reduced from 27.1% to 0.1% (0.1% FNER) and from 94.2% to 57.7% (5%
FNER) utilizing the Markov chain strategy versus the Consistent strategy on a
corpus containing a diverse set of notes from the University of Alabama at
Birmingham (UAB). The Markov chain substitution strategy also consistently
outperformed the Consistent and Random substitution strategies in a MIMIC
corpus of discharge summaries and on a range of synthetic clinical PHI
distributions. Discussion: We demonstrate that a Markov chain surrogate
generation strategy substantially reduces the chance of inadvertent PHI release
across a range of assumed PHI FNER and release our implementation
`BRATsynthetic` on Github.
  Conclusion: The Markov chain replacement strategy allows for the release of
larger de-identified corpora at the same risk level relative to corpora
released using a consistent HIPS strategy.
