Development of a Management Algorithm for Post-operative Pain (MAPP) after total knee and total hip replacement: study rationale and design.

BACKGROUND: Evidence from clinical practice and the extant literature suggests that post-operative pain assessment and treatment is often suboptimal. Poor pain management is likely to persist until pain management practices become consistent with guidelines developed from the best available scientific evidence. This work will address the priority in healthcare of improving the quality of pain management by standardising evidence-based care processes through the incorporation of an algorithm derived from best evidence into clinical practice. In this paper, the methodology for the creation and implementation of such an algorithm that will focus, in the first instance, on patients who have undergone total hip or knee replacement is described. METHODS: In partnership with clinicians, and based on best available evidence, the aim of the Management Algorithm for Post-operative Pain (MAPP) project is to develop, implement, and evaluate an algorithm designed to support pain management decision-making for patients after orthopaedic surgery. The algorithm will provide guidance for the prescription and administration of multimodal analgesics in the post-operative period, and the treatment of breakthrough pain. The MAPP project is a multisite study with one coordinating hospital and two supporting (rollout) hospitals. The design of this project is a pre-implementation-post-implementation evaluation and will be conducted over three phases. The Promoting Action on Research Implementation in Health Services (PARiHS) framework will be used to guide implementation. Outcome measurements will be taken 10 weeks post-implementation of the MAPP. The primary outcomes are: proportion of patients prescribed multimodal analgesics in accordance with the MAPP; and proportion of patients with moderate to severe pain intensity at rest. These data will be compared to the pre-implementation analgesic prescribing practices and pain outcome measures. A secondary outcome, the efficacy of the MAPP, will be measured by comparing pain intensity scores of patients where the MAPP guidelines were or were not followed. DISCUSSION: The outcomes of this study have relevance for nursing and medical professionals as well as informing health service evaluation. In establishing a framework for the sustainable implementation and evaluation of a standardised approach to post-operative pain management, the findings have implications for clinicians and patients within multiple surgical contexts

A Silent Epidemic: Community Nursing and Effective Pain Management

Effective pain management presents challenges to health care practitioners, particularly in the community setting. This is evident from the complexities associated with the phenomenon of pain and the circumstances for those patients suffering from pain. An overwhelming amount of literature and research surrounding pain exists in an effort to improve our understanding of pain, assessment and management strategies. But patients in pain are not managed well in the community or acute setting. Health care professionals continue to underestimate and under treat pain, failing to meet the patient's individual needs. Pain management it is not about cure, nor is it as simple as reporting zero on a pain score- it is about knowledge, expertise and understanding. Pain is a subjective and very personal experience, wherein health care professionals must listen to the patients' story. Myths and fears surrounding pain remains a barrier to effective management and care. This article aims to dispel the myths and improve clinical practice, particularly in effective pain assessment so patients in the community presenting with pain can be managed individually and effectively. Nurses need to be proactive in their approach, through effective communication and decision making, trusting in our patients' and their pain experience. This is key to a successful approach to managing patients' pain effectively