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An Educational Implementation Of A Cancer Pain Algorithm For Ambulatory Care.
A. R. Du Pen, S. D. Du Pen, J. Hansberry, B. Miller-Kraybill, J. Millen, R. Everly, N. Hansen, K. Syrjala
Published 2000 · Medicine
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Algorithms are proposed as a means of operationalizing guidelines or standards for cancer pain management. Professional education is used as the means to translate knowledge into practice. Outcomes measurement is the gold standard for validating improvement. This study used an educational intervention to transfer knowledge on implementing a previously tested algorithm for cancer pain management into community outpatient oncology clinics and, subsequently, measuring patient outcomes. Physicians and nurses from 9 Puget Sound clinics were randomized by institution blocks to either "training" or "no training." Role model physician/nurse teams were the core faculty for a day-long seminar. Written reference materials and documentation tools were provided to the trained physician/nurse teams. A total of 105 patients of trained and untrained providers were accrued and assessed over 4 months. Patients of trained providers had a significant reduction in usual pain over the 4 months of data collection compared with patients of untrained providers (t = 2.0; p = .05). Improvements were modest in the prescription of opioid analgesics and dramatic in the prescription of co-analgesics for neuropathic pain. There was a clear deterioration in the impact of the training over time. The most significant effect occurred within the first 140 days after the intervention and was followed by a gradual return to baseline practice. In conclusion, algorithmic interventions can be successfully transferred into community practice, but further work must be performed to develop methods for securing retention of knowledge and maintaining improved outcomes.
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