Degree Name

Doctor of Nursing Practice

Document Type

Scholarly Project

Date Created



Older adults are prescribed more medications for chronic issues due to increased age, a phenomenon called polypharmacy. Unfortunately, older adults also experience persistent pain more often than younger adults. This age group is prone to utilizing opioids for longer than expected due to lack of screening for pain by providers accompanied by a lack of open and ongoing discussion about pain management options with patients. Evidence suggested that older adults are at an increased risk for improper use of opioids for pain management and often suffer side effects from long-term opioid use. Some possible side effects of opioid use in this patient population include increased risk of respiratory depression, falls, hospitalizations, and mortality rates. The rate of opioid use in older adults continues to increase each year despite current regulations in place for limiting opioid prescribing. Therefore, there is a need for providers to properly screen older adults for chronic pain and to effectively manage their pain utilizing a myriad of treatment interventions. Implementing a proper screening tool and following an evidence-based pain treatment algorithm could improve patient satisfaction and reduce the risks associated with opioid use in older adults. The purpose of this Doctor of Nursing Practice scholarly project was to create a clinical pain treatment algorithm designed for use with older adults through critical appraisal of the current literature and by collecting feedback from a panel of healthcare providers with expertise in geriatric pain management. Using the Delphi technique for data collection and analysis, six advanced practice providers participated and after two rounds of revisions, the panelists reached consensus on the algorithm draft. In addition, a pilot testing plan in the clinical setting for the developed algorithm is proposed at the end of this project.


opioid use; chronic pain; older adults; pain treatment; pain screening; clinical algorithm

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Copyright is held by the author.