Managing Acute Pain in Critically Ill Non-communicative Palliative Care Patients

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DESCRIPTION (provided by applicant): This project responds to PA-10-006 Mechanisms, Models, Measurement, & Management in Pain Research (R01). Acutely ill hospitalized palliative care patients who cannot self-report the presence or intensity of their pain are at high risk for under-recognition and under-treatment of pain, experiencing needless suffering and other adverse effects. Across the settings in which palliative care is rendered, there is a dearth of reliable and valid measures for assessing pain in these non-communicative patients, and few standardized protocols or algorithms have been tested for their effects on patients' outcomes. Our recently completed project (5 R01NR009684) tested the psychometric properties and clinical utility of the Multidimensional Objective Pain Assessment Tool (MOPAT) in assessing acute pain in non-communicative palliative care patients, demonstrating strong evidence of validity, reliability, and clinical utility when used regularly over time by trained nurses in critcally ill non-communicative patients. The primary aim of the proposed research is to test whether a pain algorithm that incorporates the MOPAT and an analgesic order set improves pain severity and use of pharmacologic pain management strategies in critically ill non-communicative palliative care patients who are hospitalized on medical, surgical, and trauma intensive care units when compared to patients without the algorithm. We hypothesize: (H1) a decrease in pain severity, (H2) an increase in the number of pharmacologic agents used for pain, and (H3) an increase in the total equi-analgesic dosage of pharmacologic agents used for pain as a result of implementation of the pain algorithm. The secondary descriptive aims are to (S1) Compare pain-related outcomes in patients with and without concurrent pain-related conditions, (S2) Describe the pattern of patients' pain over time, and (S3) Evaluate nurses' perceptions of clinical utility of the pain algorithm. We will use a cohort control group quasi-experimental design conducted in two phases on the medical, surgical, and trauma intensive care units of a major university acute care hospital. In Phase 1 (usual care control cohort n=150 patients), the MOPAT will be incorporated into routine clinical practice and data on pain severity and use of pharmacologic pain management strategies collected. In Phase 2 (intervention cohort n=150 patients), a pain algorithm incorporating MOPAT scores into an analgesic order set will be implemented in routine clinical practice and the same patient outcome data plus nurses' perceptions of clinical utility of the algorithm (including the MOPAT) will be collected. Analysis f the primary aim and its associated hypotheses will be accomplished using the interaction F-test from 2x4 repeated measures analysis or mixed linear modeling and Cochran's Q for 2x2 repeated measures on rank data. Descriptive approaches will be used for the secondary aims, including repeated measures analysis with post-hoc analyses if there are significant interaction effects, graphic techniques (e.g., spaghetti plots) to identify sub-groups, and frequency distributions for responses to questionnaires. This research is significant and innovative because it tests a pain algorithm using an instrument validated in non-communicative patients to guide pain management and improve pain- related outcomes in this vulnerable and understudied population.