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The Use of Algorithms in Assessing and Managing Persistent Pain in Older Adults

Jablonski, Anita M. PhD, RN; DuPen, Anna R. MN, ARNP, ACHPN; Ersek, Mary PhD, RN, FAAN

AJN The American Journal of Nursing: March 2011 - Volume 111 - Issue 3 - p 34-43
doi: 10.1097/10.1097/01.NAJ.0000395239.60981.2f
Feature Articles

Overview As the U.S. population ages, nurses will care for increasing numbers of older adults, most of whom suffer from at least one chronic illness. The persistent pain associated with many chronic illnesses can have detrimental effects on patients' functioning and quality of life. Algorithms developed from evidence-based clinical practice guidelines are tools that can facilitate the application of research to practice. This article introduces readers to the use of algorithms in guiding the assessment and management of persistent pain in older adults, and provides an illustrative case study.

Keywords algorithm, clinical decision making, clinical practice guidelines, evidence-based practice, nursing judgment, older adults, pain

This article introduces readers to the use of algorithms in guiding the assessment and management of persistent pain in older adults.

Anita M. Jablonski is an associate professor at the Seattle University College of Nursing. At the time of this writing, Anna R. DuPen was an advanced NP at the Hospice of Kitsap County, Bremerton, WA; currently she's a palliative care NP at the Palliative Care Consultation Service in the Department of Family Medicine at the University of Washington in Seattle. Mary Ersek is associate director of the Center for Integrative Science in Aging and of the John A. Hartford Center of Geriatric Nursing Excellence, as well as an associate professor in the School of Nursing, at the University of Pennsylvania in Philadelphia. Previously she was director of research at the Center for Nursing Excellence, as well as a research scientist, at Swedish Medical Center in Seattle. Contact author: Anita M. Jablonski, jablonsk@seattleu.edu. The research and development of the algorithms discussed herein were supported by funding from the National Institutes of Health, National Institute of Nursing Research (grant No. R01-NR009100). The authors of this article have disclosed no significant ties, financial or otherwise, to any company that might have an interest in the publication of this educational activity.

© 2011 Lippincott Williams & Wilkins, Inc.