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Earlier identification of seriously ill patients: an implementation case series
  1. Joshua R Lakin1,
  2. Meghna Desai1,
  3. Kyle Engelman1,
  4. Nina O'Connor2,
  5. Winifred G Teuteberg3,
  6. Alison Coackley4,
  7. Laurel B Kilpatrick5,
  8. Atul Gawande1 and
  9. Erik K Fromme1
  1. 1 Ariadne Labs, Boston, Massachusetts, USA
  2. 2 Palliative and Hospice Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
  3. 3 Section of Palliative Medicine, Stanford University School of Medicine, Palo Alto, California, USA
  4. 4 Clatterbridge Cancer Centre NHS Foundation Trust, Bebington, UK
  5. 5 Division of Supportive and Palliative Care, Baylor Scott & White Health, Temple, Texas, USA
  1. Correspondence to Dr Joshua R Lakin, Ariadne Labs, Boston, MA 02215, USA; jlakin{at}


Objective To describe the strategies used by a collection of healthcare systems to apply different methods of identifying seriously ill patients for a targeted palliative care intervention to improve communication around goals and values.

Methods We present an implementation case series describing the experiences, challenges and best practices in applying patient selection strategies across multiple healthcare systems implementing the Serious Illness Care Program (SICP).

Results Five sites across the USA and England described their individual experiences implementing patient selection as part of the SICP. They employed a combination of clinician screens (such as the ‘Surprise Question’), disease-specific criteria, existing registries or algorithms as a starting point. Notably, each describes adaptation and evolution of their patient selection methodology over time, with several sites moving towards using more advanced machine learning–based analytical approaches.

Conclusions Involving clinical and programme staff to choose a simple initial method for patient identification is the ideal starting place for selecting patients for palliative care interventions. However, improving and refining methods over time is important and we need ongoing research into better patient selection methodologies that move beyond mortality prediction and instead focus on identifying seriously ill patients—those with poor quality of life, worsening functional status and medical care that is negatively impacting their families.

  • palliative care
  • triggers
  • patient identification
  • patient selection
  • advance care planning
  • serious illness communication

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  • Contributors JRL and EKF take responsibility for the integrity of the cases reported in this manuscript.

  • Funding This work was supported by the Gordon and Betty Moore Foundation.

  • Disclaimer See ICMJE COI statement.

  • Competing interests AG reports receiving royalties from publishers and media outlets worldwide for writing and other media on healthcare including the subject of serious illness care and checklists during the conduct of this study. AG is also employed as the CEO of the new non-profit-seeking healthcare venture parented by Amazon, Berkshire Hathaway and JP Morgan Chase. JRL reports grants from The Gordon and Betty Moore Foundation, during the conduct of the study; grants from Cambia Health Foundation, outside the submitted work; and JRL receives salary support funding for work related to the Serious Illness Care Program (studied in this manuscript) from his home institutions. Additionally, he receives teaching honoraria related to his academic work on the Program from government and academic entities. EKF reports grants and other from the Gordon and Betty Moore Foundation during the conduct of this study, and is the Director of the Serious Illness Care Program, the quality improvement program referenced in the paper.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data relevant to the study are included in the article or uploaded as online supplementary information.