Literature DB >> 31253736

mHOMR: a feasibility study of an automated system for identifying inpatients having an elevated risk of 1-year mortality.

Pete Wegier1,2,3, Ellen Koo4, Shahin Ansari5, Daniel Kobewka6,7,8, Erin O'Connor9,10,11, Peter Wu12, Leah Steinberg13,3, Chaim Bell14,15, Tara Walton16, Carl van Walraven7,8,17, Gayathri Embuldeniya4,15, Judy Costello18,19, James Downar20,8,21.   

Abstract

OBJECTIVE: The need for clinical staff to reliably identify patients with a shortened life expectancy is an obstacle to improving palliative and end-of-life care. We developed and evaluated the feasibility of an automated tool to identify patients with a high risk of death in the next year to prompt treating physicians to consider a palliative approach and reduce the identification burden faced by clinical staff.
METHODS: Two-phase feasibility study conducted at two quaternary healthcare facilities in Toronto, Canada. We modified the Hospitalised-patient One-year Mortality Risk (HOMR) score, which identifies patients having an elevated 1-year mortality risk, to use only data available at the time of admission. An application prompted the admitting team when patients had an elevated mortality risk and suggested a palliative approach. The incidences of goals of care discussions and/or palliative care consultation were abstracted from medical records.
RESULTS: Our model (C-statistic=0.89) was found to be similarly accurate to the original HOMR score and identified 15.8% and 12.2% of admitted patients at Sites 1 and 2, respectively. Of 400 patients included, the most common indications for admission included a frailty condition (219, 55%), chronic organ failure (91, 23%) and cancer (78, 20%). At Site 1 (integrated notification), patients with the notification were significantly more likely to have a discussion about goals of care and/or palliative care consultation (35% vs 20%, p = 0.016). At Site 2 (electronic mail), there was no significant difference (45% vs 53%, p = 0.322).
CONCLUSIONS: Our application is an accurate, feasible and timely identification tool for patients at elevated risk of death in the next year and may be effective for improving palliative and end-of-life care. © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  decision support, computerized; healthcare quality improvement; trigger tools

Mesh:

Year:  2019        PMID: 31253736     DOI: 10.1136/bmjqs-2018-009285

Source DB:  PubMed          Journal:  BMJ Qual Saf        ISSN: 2044-5415            Impact factor:   7.035


  5 in total

1.  Automated model versus treating physician for predicting survival time of patients with metastatic cancer.

Authors:  Michael F Gensheimer; Sonya Aggarwal; Kathryn R K Benson; Justin N Carter; A Solomon Henry; Douglas J Wood; Scott G Soltys; Steven Hancock; Erqi Pollom; Nigam H Shah; Daniel T Chang
Journal:  J Am Med Inform Assoc       Date:  2021-06-12       Impact factor: 4.497

2.  The interRAI CHESS scale is comparable to the palliative performance scale in predicting 90-day mortality in a palliative home care population.

Authors:  Nicole Williams; Kirsten Hermans; Joachim Cohen; Anja Declercq; Ahmed Jakda; James Downar; Dawn M Guthrie; John P Hirdes
Journal:  BMC Palliat Care       Date:  2022-10-06       Impact factor: 3.113

3.  Estimating real-world performance of a predictive model: a case-study in predicting mortality.

Authors:  Vincent J Major; Neil Jethani; Yindalon Aphinyanaphongs
Journal:  JAMIA Open       Date:  2020-04-26

4.  Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites.

Authors:  Vincent J Major; Yindalon Aphinyanaphongs
Journal:  BMC Med Inform Decis Mak       Date:  2020-09-07       Impact factor: 2.796

5.  Expected clinical utility of automatable prediction models for improving palliative and end-of-life care outcomes: Toward routine decision analysis before implementation.

Authors:  Ryeyan Taseen; Jean-François Ethier
Journal:  J Am Med Inform Assoc       Date:  2021-10-12       Impact factor: 4.497

  5 in total

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