Articles: pain-management-methods.
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Anesthesia and analgesia · Sep 2022
Situational Awareness of Opioid Consumption: The Missing Link to Reducing Dependence After Surgery?
A tool for collecting and analyzing morphine milligram equivalents (MMEs) can be used to overcome barriers to situational awareness around opioid utilization in the setting of multimodal pain management. Our software application (App) has facilitated data collection, analysis, and benchmarking in a manner that is not logistically feasible using manual methods. Real-time postoperative tracking of MME over the course of an episode of care can be prohibitively labor-intensive, and teams must have practical strategies to overcome this obstacle. In view of the link between the magnitude of opioid prescriptions at discharge and persistent opioid use after cardiac surgery, we believe that improving situational awareness among the patient care team is a vital first step in reducing opioid dependence after cardiac surgery.
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Hospital-based clinicians frequently care for patients with opioid withdrawal or opioid use disorder (OUD) and are well-positioned to identify and initiate treatment for these patients. With rising numbers of hospitalizations related to opioid use and opioid-related overdose, the Society of Hospital Medicine convened a working group to develop a Consensus Statement on the management of OUD and associated conditions among hospitalized adults. The guidance statement is intended for clinicians practicing medicine in the inpatient setting (e.g., hospitalists, primary care physicians, family physicians, advanced practice nurses, and physician assistants) and is intended to apply to hospitalized adults at risk for, or diagnosed with, OUD. ⋯ The iterative development process resulted in a final Consensus Statement consisting of 18 recommendations covering the following topics: (1) identification and treatment of OUD and opioid withdrawal, (2) perioperative and acute pain management in patients with OUD, and (3) methods to optimize care transitions at hospital discharge for patients with OUD. Most recommendations in the Consensus Statement were derived from guidelines based on observational studies and expert consensus. Due to the lack of rigorous evidence supporting key aspects of OUD-related care, the working group identified important issues necessitating future research and exploration.
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Several clinical practice guidelines (CPGs), consensus statements, and recommendations currently exist for the diagnosis and management of breakthrough cancer pain (BTcP). These documents have considerable variability amongst them, and to date, their quality and methodologic rigor have not been appraised. ⋯ Reflecting upon our quality appraisal, it is evident that the quality and methodologic rigor of BTcP guidelines can be improved upon in the future. Our findings also elucidate the existing variability/discrepancies among guidelines in diagnostic criteria and management of BTcP.
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Assessment of pain in the hospital has often relied on intensity rating alone. To address the gap in meeting patients' pain management expectations, a Midwestern medical center implemented the CAPA (Clinical Aligned Pain Assessment) tool for more comprehensive nursing pain assessments. ⋯ As patient advocates, nurses are integral to thorough assessment and treatment of pain. Findings identified the need for methodological research of CAPA. As with any assessment tool, when using CAPA, ongoing monitoring is needed to address how it is administered, coded, and used for decision-making about pain management.
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Pain intensity evaluation by self-report is difficult and biased in non-communicating people, which may contribute to inappropriate pain management. The use of artificial intelligence (AI) to evaluate pain intensity based on automated facial expression analysis has not been evaluated in clinical conditions. ⋯ These original findings represent a major step in the development of a fully automated, rapid, standardized and objective method based on facial expression analysis to measure pain and detect severe pain.