Matthew B. WEinger - US grants

Potent, short-acting opiate agonists are widely used in anesthesia because they do not cause significant cardiovascular depression. But the profound analgesic effect of high-dose opiates is accompanied by intense generalized muscle rigidity and respiratory depression. These side effects of the opiates severely limit their clinical value. A thorough understanding of the opioid receptor pharmacology of desirable (anesthesia and analgesia) and undesirable (muscle rigidity, respiratory depression, and abuse potential) opiate effects will have important implications for the development of opiate analgesics and anesthetics without major side effects. The proposed experiments are designed to determine in rats: 1) which opioid receptors mediate opiate-induced muscle rigidity; 2) which opioid receptors mediate opiate-induced respiratory depression; 3) what role depressed respiratory drive versus increased chest wall muscle tone (due to muscle rigidity) plays in the respiratory depression seen with high-dose opiates; and 4) which opioid receptors mediate opiate-induced anesthesia. A key question to be addressed is whether the most important desirable effect of high dose opiate administration (anesthesia) can be pharmacologically separated from the two clinically most important undesirable side-effects (muscle rigidity and respiratory depression) on the basis of opioid receptor specificity. Muscle rigidity will be investigated by measuring the electromyographic activity from hindlimb and abdominal muscles. Respiratory function will be assessed using both dual- chamber plethysmography to measure minute ventilation and using arterial blood gases. Opiate anesthesia will be assessed by the absence of the righting reflex as well as by the heart rate and movement responses to a noxious stimulus (tail pressure). The opioid receptor pharmacology of each effect will be examined using selective agonists and antagonists. Drugs will be administered directly into the lateral ventricles of the brain. The main hypothesis these experiments will test is that the desirable effects of opiates (analgesia and anesthesia) will be separable from the undesirable effects (muscle rigidity and respiratory depression) on the basis of opioid receptor pharmacology. Data will be compared by analyzing log dose-response curves and potency ratios to assess the relative separation between desirable and undesirable effects for each receptor- selective drug studied. A secondary hypothesis to be tested will be that opiate-induced truncal rigidity contributes significantly to the respiratory compromise and acidosis seen after large opiate doses. The knowledge of opioid receptor pharmacology derived from this work will form a rational framework within which to develop and clinically use new opiate drugs.

Project Summary/Abstract A common cause of preventable harm is the failure to detect and appropriately respond to clinical deterioration. Timely intervention is needed, particularly in medically complex (e.g., cancer) patients, to mitigate the effects of adverse events, disease progression, and medical error. This challenging problem requires effective clinical surveillance, early recognition, timely notification of the appropriate clinician, and effective intervention. In the hospital setting, ?failure to rescue? (FTR) is a recognized safety failure. To address FTR, hospitals have introduced new tools and processes (e.g., continuous monitoring, early warning systems, and `Rapid Response' teams). Yet, `death in bed' remains common. The Vanderbilt-Ingram Cancer Center, in collaboration with human factors and systems engineering faculty in the Center for Research and Innovation in Systems Safety (CRISS), as well as faculty in our Schools of Engineering and Management, will create the Cancer Patient Safety Learning Laboratory (CaPSLL). We will partner with surgeons, oncologists, nurses, staff, and adult patients with lung and head or neck cancer recovering from and/or undergoing treatment as outpatients, and their lay caregivers, to more reliably detect and respond more effectively to unexpected clinical deterioration. The details that follow in this proposal are based on our current understandings but will be modified as we employ a systems engineering oriented user-centered design (UCD) process to analyze, design, develop, implement, and evaluate innovative tools and processes to address this complex patient safety problem. We will achieve this through three Specific Aims: 1) To create and refine software tools and a predictive model for a surveillance-and-response system to prevent harm from unexpected all-cause clinical deterioration in outpatients receiving cancer treatment; 2) To create and refine processes and training that engage patients and their caregivers as active and reliable participants in detecting and reporting potential clinical deterioration. We will apply high reliability organizational (HRO) principles and theories to develop processes and training for the relevant ?team? ? the cancer patients, their caregivers, and the clinicians who need to respond to signals from the surveillance system; and 3) To implement in the operational environment and formally evaluate the integrated detection and response tools and processes. We hypothesize (H1) that this system will decrease the likelihood and severity of unplanned treatment events (UTE; e.g. hospital admission). Further, with the incorporation of a patient/family focused HRO framework, we hypothesize that the system will increase non-routine event (NRE; deviations from optimal care) reporting (H2) and decrease clinician response time (H3). The resulting tools, methods and predictive model will be scalable to other cancer types as well as being generalizable to other institutions and to other high-risk outpatient populations (e.g., heart failure).

Understanding and improving clinicians' ability to manage critical events is important for patient safety. A team of clinician-scientists, simulation educators, and cognitive scientists propose a five-site in-depth study of the real-time action-oriented decision- making strategies of anesthesiologists during generalizable high-fidelity critical event simulations. The Specific Aims are to: 1) Develop and test a unified cognitive model and taxonomy of the decision-making strategies clinicians use during critical event management; 2) Create detailed profiles of participants' clinical practice and simulation experience; 3) Evaluate the factors affecting physicians' critical event performance; and 4) Evaluate the relationship between simulation-based performance assessment and existing metrics of physician competence (participants' primary board certification exam scores). We will create four 20-minute realistic simulations of critical events that are relevant to many acute-care specialties. 120 anesthesiologists at varying career points will provide detailed demographic, clinical practice, and simulation experience data. They will wear head-mounted video cameras as they perform in all four scenarios. Success of each participant's event management will be assessed later from overhead videos by independent trained experts based on timely completion of pre-defined `critical performance elements' and global technical and non-technical scores. After each scenario, cognitive interviews will be conducted using video-cued recall to ascertain how and why they made their clinical management decisions. We will iteratively code and analyze all of the interview data to develop a taxonomy of decision strategies; Every scenario will be coded for the strategies used. We will then analyze how event performance ratings vary with: participants' actual practice and simulation experience, the decision strategies used, and written and oral board certification examination scores. This innovative study will delineate in depth the thought processes of a diverse sample of physicians in managing critical events. Along with these empirical data, the project will create a new model and taxonomy for dynamic clinical decision-making, extending models previously developed for healthcare and other arenas of similar cognitive demands (e.g. aviation). The study will yield best-practice guidelines on decision-making in critical event management and information to support policymaking about the content, execution, and timing of simulation-based training and assessment.