Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients

<p>Abstract</p> <p>Background</p> <p>Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision syst...

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Main Authors: Tsalatsanis Athanasios, Barnes Laura E, Hozo Iztok, Djulbegovic Benjamin
Format: Article
Language:English
Published: BMC 2011-12-01
Series:BMC Medical Informatics and Decision Making
Online Access:http://www.biomedcentral.com/1472-6947/11/77
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spelling doaj-89ab5f3238804221a4f70ab671a6db7e2020-11-24T20:48:01ZengBMCBMC Medical Informatics and Decision Making1472-69472011-12-011117710.1186/1472-6947-11-77Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patientsTsalatsanis AthanasiosBarnes Laura EHozo IztokDjulbegovic Benjamin<p>Abstract</p> <p>Background</p> <p>Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed.</p> <p>Methods</p> <p>We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed <it>regret based decision curve analysis </it>(<it>regret DCA</it>). We extend the <it>regret DCA </it>methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care.</p> <p>Results</p> <p>The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, <it>regret </it><it>DCA </it>is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available.</p> <p>Conclusions</p> <p>We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned.</p> http://www.biomedcentral.com/1472-6947/11/77
collection DOAJ
language English
format Article
sources DOAJ
author Tsalatsanis Athanasios
Barnes Laura E
Hozo Iztok
Djulbegovic Benjamin
spellingShingle Tsalatsanis Athanasios
Barnes Laura E
Hozo Iztok
Djulbegovic Benjamin
Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients
BMC Medical Informatics and Decision Making
author_facet Tsalatsanis Athanasios
Barnes Laura E
Hozo Iztok
Djulbegovic Benjamin
author_sort Tsalatsanis Athanasios
title Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients
title_short Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients
title_full Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients
title_fullStr Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients
title_full_unstemmed Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients
title_sort extensions to regret-based decision curve analysis: an application to hospice referral for terminal patients
publisher BMC
series BMC Medical Informatics and Decision Making
issn 1472-6947
publishDate 2011-12-01
description <p>Abstract</p> <p>Background</p> <p>Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed.</p> <p>Methods</p> <p>We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed <it>regret based decision curve analysis </it>(<it>regret DCA</it>). We extend the <it>regret DCA </it>methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care.</p> <p>Results</p> <p>The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, <it>regret </it><it>DCA </it>is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available.</p> <p>Conclusions</p> <p>We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned.</p>
url http://www.biomedcentral.com/1472-6947/11/77
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