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• W2913634518 abstract "•Discuss how development of a software tool can drive development of inpatient and outpatient palliative care programs.•Discuss Algorithms 101.•Discuss ‘lessons learned’ and results of going live with a Palliative Care Algorithm in the acute care setting. One of the largest barriers for seriously ill patients, is timely identification of Palliative Care needs. In the acute care setting, many admitting and consulting physicians struggle with identification of appropriate patients. Intermountain Healthcare and Ascension Health, in collaboration with an electronic medical record company, developed an electronic Palliative Care identification algorithm, or trigger, which leverages historical and near real-time data to identify patients that would benefit from Palliative Care services. This project allowed several iterations of the algorithm, which ran in ‘silent mode’ in the electronic medical record. Over time, accuracy has improved with a current positive predictive value of 80%. It has identified nearly 26% of this 310 bed hospital’s adult population as appropriate for Palliative Care services. This algorithm led to accurate data for program development and resource allocation at Intermountain Healthcare. Ascension’s St. John Providence Hospital has utilized this same Palliative Care identification algorithm in a live clinical setting since April 2017. Many lessons were learned at both the algorithm development and the deployment state which can benefit others hoping to utilize similar methods. Due to the high volume of patients and staffing capacity of most palliative care programs, risk stratification for identified patients will be necessary. Therefore, development is underway for a machine learning algorithm to help assign a risk score to each patient identified as appropriate for palliative care services. This stratification will allow for appropriate resource allocation, identification and education about primary Palliative Care, and further adjustments to the electronic solution to help embed Palliative Care throughout the healthcare continuum. This presentation reviews the current state of an ongoing collaborative project between a major electronic medical record company and multiple large healthcare systems, as well as the lessons learned in the technology and healthcare delivery industries." @default.
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• W2913634518 date "2019-02-01" @default.
• W2913634518 modified "2023-10-14" @default.
• W2913634518 title "Build It and They Will Come: Outcomes of Developing a Palliative Care Identification and Machine Learning Algorithm (FR403)" @default.
• W2913634518 doi "https://doi.org/10.1016/j.jpainsymman.2018.12.103" @default.
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