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Journal Article
Research Support, Non-U.S. Gov't
Effect and Efficiency of an Embedded Palliative Care Nurse Practitioner in an Oncology Clinic.
Journal of Oncology Practice 2017 September
PURPOSE: To test a simultaneous care model for palliative care for patients with advanced cancer by embedding a palliative care nurse practitioner (NP) in an oncology clinic.
METHODS: We evaluated the effect of the intervention in two oncologists' clinics beginning March 2014 by using implementation strategies, including use of a structured referral mechanism, routine symptom screening, integration of a psychology-based cancer supportive care center, implementation team meetings, team training, and a metrics dashboard for continuous quality improvement. After 1 year of implementation, we evaluated key process and outcome measures for supportive oncology and efficiency of the model by documenting tasks completed by the NP during a subset of patient visits and time-motion studies.
RESULTS: Of approximately 10,000 patients with active cancer treated in the health system, 2,829 patients had advanced cancer and were treated by 42 oncologists. Documentation of advance care planning increased for patients of the two intervention oncologists compared with patients of the other oncologists. Hospice referral before death was not different at baseline, but was significantly higher for patients of intervention oncologists compared with patients of control oncologists (53% v 23%; P = .02) over the intervention period. Efficiency evaluation revealed that approximately half the time spent by the embedded NP potentially could have been completed by other staff (eg, a nurse, a social worker, or administrative staff).
CONCLUSION: An embedded palliative care NP model using scalable implementation strategies can improve advance care planning and hospice use among patients with advanced cancer.
METHODS: We evaluated the effect of the intervention in two oncologists' clinics beginning March 2014 by using implementation strategies, including use of a structured referral mechanism, routine symptom screening, integration of a psychology-based cancer supportive care center, implementation team meetings, team training, and a metrics dashboard for continuous quality improvement. After 1 year of implementation, we evaluated key process and outcome measures for supportive oncology and efficiency of the model by documenting tasks completed by the NP during a subset of patient visits and time-motion studies.
RESULTS: Of approximately 10,000 patients with active cancer treated in the health system, 2,829 patients had advanced cancer and were treated by 42 oncologists. Documentation of advance care planning increased for patients of the two intervention oncologists compared with patients of the other oncologists. Hospice referral before death was not different at baseline, but was significantly higher for patients of intervention oncologists compared with patients of control oncologists (53% v 23%; P = .02) over the intervention period. Efficiency evaluation revealed that approximately half the time spent by the embedded NP potentially could have been completed by other staff (eg, a nurse, a social worker, or administrative staff).
CONCLUSION: An embedded palliative care NP model using scalable implementation strategies can improve advance care planning and hospice use among patients with advanced cancer.
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