Other Titles

Technologies to influence palliative care

Abstract

Purpose: Timelier referral to palliative care services (PCS) within the acute care setting is a health care priority. End-of-life consumes a disproportionate share of healthcare dollars with studies indicating PCS can save hospitals approximately $1.3 million annually, for every 500 consults completed. Strategies to increase timelier referral are needed. Integration of electronic clinical decision support and utilization of triggers to identify individuals who may benefit from palliative care, using an algorithm embedded with the electronic health record (EHR) may facilitate this identification, but lacks empirical support.

The purpose of this research was to utilize variables available in the electronic healthcare record (EHR) of palliative care patients receiving PCS in the acute care setting to identify triggers which could be used to identify individuals who should be referred for PCS.

Specific Aims:

Aim 1: Characterize EHR data related to palliative care consultations among severely and chronically ill patients in the acute care.

Aim 2: Examine the relationships between the list of clinical EHR data, select demographics, in a sample of palliative care patients

Methods: A descriptive, correlational study using de-identified retrospective data, collected from January 1, 2013 to December 31, 2015. An institutionally derived list of variables was used to provide a foundation for clinical decision support and patient identification integrated into the Cerner EHR system. Data were derived from three hospitals of a large multi-community healthcare system in San Diego County. Descriptive and inferential statistical analyses conducted using SPSS version 23.

Results: A randomized sample yielded 694 palliative care patients seeking acute care treatment at one of the three hospitals. Of these 51.7% were male, 65.4% White, 36.7% Christian, 80.8% English speaking, 49.7% Medicare recipients, 51.4% declared themselves as a ‘do-not-resuscitate" and 97.6% were seen by a palliative care nurse. Significant associations were found between race/ethnicity/code status (X2 = 11.311, p .02), language/presence of advance directive (X2 = 13.845, p .008), and change of code status/loss of responsiveness (X2 =15.129, p<.001).

Conclusion: Using a large sample, a number of statistically significant demographic, physiologic, and clinical variables were found that to identify individuals suitable for timely referral to palliative care services. The integration of an EHR-based trigger system can aid not only nursing, but the interdisciplinary team to identify and refer potential palliative care patients in a timelier manner. The findings lay an important foundation for increased refinement of electronic clinical decision support within the EHR.

Author Details

Tanja Baum, PhD, RN; Ruth A. Bush; Caroline Etland; Cynthia D. Connelly

Sigma Membership

Unknown

Type

Presentation

Format Type

Text-based Document

Study Design/Type

N/A

Research Approach

N/A

Keywords:

Acute Care, Clinical Decision Support, Palliative Care

Conference Name

28th International Nursing Research Congress

Conference Host

Sigma Theta Tau International

Conference Location

Dublin, Ireland

Conference Year

2017

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.

All permission requests should be directed accordingly and not to the Sigma Repository.

All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.

Acquisition

Proxy-submission

Additional Files

download (798 kB)

download (146 kB)

Share

COinS
 

Utilizing clinical decision support within the electronic health record to screen for palliative care

Dublin, Ireland

Purpose: Timelier referral to palliative care services (PCS) within the acute care setting is a health care priority. End-of-life consumes a disproportionate share of healthcare dollars with studies indicating PCS can save hospitals approximately $1.3 million annually, for every 500 consults completed. Strategies to increase timelier referral are needed. Integration of electronic clinical decision support and utilization of triggers to identify individuals who may benefit from palliative care, using an algorithm embedded with the electronic health record (EHR) may facilitate this identification, but lacks empirical support.

The purpose of this research was to utilize variables available in the electronic healthcare record (EHR) of palliative care patients receiving PCS in the acute care setting to identify triggers which could be used to identify individuals who should be referred for PCS.

Specific Aims:

Aim 1: Characterize EHR data related to palliative care consultations among severely and chronically ill patients in the acute care.

Aim 2: Examine the relationships between the list of clinical EHR data, select demographics, in a sample of palliative care patients

Methods: A descriptive, correlational study using de-identified retrospective data, collected from January 1, 2013 to December 31, 2015. An institutionally derived list of variables was used to provide a foundation for clinical decision support and patient identification integrated into the Cerner EHR system. Data were derived from three hospitals of a large multi-community healthcare system in San Diego County. Descriptive and inferential statistical analyses conducted using SPSS version 23.

Results: A randomized sample yielded 694 palliative care patients seeking acute care treatment at one of the three hospitals. Of these 51.7% were male, 65.4% White, 36.7% Christian, 80.8% English speaking, 49.7% Medicare recipients, 51.4% declared themselves as a ‘do-not-resuscitate" and 97.6% were seen by a palliative care nurse. Significant associations were found between race/ethnicity/code status (X2 = 11.311, p .02), language/presence of advance directive (X2 = 13.845, p .008), and change of code status/loss of responsiveness (X2 =15.129, p<.001).

Conclusion: Using a large sample, a number of statistically significant demographic, physiologic, and clinical variables were found that to identify individuals suitable for timely referral to palliative care services. The integration of an EHR-based trigger system can aid not only nursing, but the interdisciplinary team to identify and refer potential palliative care patients in a timelier manner. The findings lay an important foundation for increased refinement of electronic clinical decision support within the EHR.