Earlier identification of seriously ill patients: An implementation case series

Joshua R. Lakin, Meghna Desai, Kyle Engelman, Nina O'Connor, Winifred G. Teuteberg, Alison Coackley, Laurel B. Kilpatrick, Atul Gawande, Erik Fromme

    Research output: Contribution to journalArticle

    Abstract

    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.

    Original languageEnglish (US)
    JournalBMJ Supportive and Palliative Care
    DOIs
    StatePublished - Jan 1 2019

    Fingerprint

    Patient Selection
    Palliative Care
    Delivery of Health Care
    Practice Guidelines
    England
    Registries
    Patient Care
    Communication
    Quality of Life
    Mortality
    Research

    Keywords

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

    ASJC Scopus subject areas

    • Medicine (miscellaneous)
    • Oncology(nursing)
    • Medical–Surgical

    Cite this

    Lakin, J. R., Desai, M., Engelman, K., O'Connor, N., Teuteberg, W. G., Coackley, A., ... Fromme, E. (2019). Earlier identification of seriously ill patients: An implementation case series. BMJ Supportive and Palliative Care. https://doi.org/10.1136/bmjspcare-2019-001789

    Earlier identification of seriously ill patients : An implementation case series. / Lakin, Joshua R.; Desai, Meghna; Engelman, Kyle; O'Connor, Nina; Teuteberg, Winifred G.; Coackley, Alison; Kilpatrick, Laurel B.; Gawande, Atul; Fromme, Erik.

    In: BMJ Supportive and Palliative Care, 01.01.2019.

    Research output: Contribution to journalArticle

    Lakin, JR, Desai, M, Engelman, K, O'Connor, N, Teuteberg, WG, Coackley, A, Kilpatrick, LB, Gawande, A & Fromme, E 2019, 'Earlier identification of seriously ill patients: An implementation case series', BMJ Supportive and Palliative Care. https://doi.org/10.1136/bmjspcare-2019-001789
    Lakin, Joshua R. ; Desai, Meghna ; Engelman, Kyle ; O'Connor, Nina ; Teuteberg, Winifred G. ; Coackley, Alison ; Kilpatrick, Laurel B. ; Gawande, Atul ; Fromme, Erik. / Earlier identification of seriously ill patients : An implementation case series. In: BMJ Supportive and Palliative Care. 2019.
    @article{279f9981dfdd4c64b267d2e676ab1b79,
    title = "Earlier identification of seriously ill patients: An implementation case series",
    abstract = "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.",
    keywords = "advance care planning, palliative care, patient identification, patient selection, serious illness communication, triggers",
    author = "Lakin, {Joshua R.} and Meghna Desai and Kyle Engelman and Nina O'Connor and Teuteberg, {Winifred G.} and Alison Coackley and Kilpatrick, {Laurel B.} and Atul Gawande and Erik Fromme",
    year = "2019",
    month = "1",
    day = "1",
    doi = "10.1136/bmjspcare-2019-001789",
    language = "English (US)",
    journal = "BMJ Supportive and Palliative Care",
    issn = "2045-435X",
    publisher = "BMJ Publishing Group",

    }

    TY - JOUR

    T1 - Earlier identification of seriously ill patients

    T2 - An implementation case series

    AU - Lakin, Joshua R.

    AU - Desai, Meghna

    AU - Engelman, Kyle

    AU - O'Connor, Nina

    AU - Teuteberg, Winifred G.

    AU - Coackley, Alison

    AU - Kilpatrick, Laurel B.

    AU - Gawande, Atul

    AU - Fromme, Erik

    PY - 2019/1/1

    Y1 - 2019/1/1

    N2 - 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.

    AB - 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.

    KW - advance care planning

    KW - palliative care

    KW - patient identification

    KW - patient selection

    KW - serious illness communication

    KW - triggers

    UR - http://www.scopus.com/inward/record.url?scp=85068340072&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=85068340072&partnerID=8YFLogxK

    U2 - 10.1136/bmjspcare-2019-001789

    DO - 10.1136/bmjspcare-2019-001789

    M3 - Article

    AN - SCOPUS:85068340072

    JO - BMJ Supportive and Palliative Care

    JF - BMJ Supportive and Palliative Care

    SN - 2045-435X

    ER -