Article 1
A Systematic Review of Behavioral Interventions to Decrease Opioid Prescribing After Surgery. Zhang DDQ, Sussman J, Dossa F, et al. Ann Surg. 2020 Feb;271(2):266-278.
There has been increasing attention to the opiate crisis in this country, with the CDC reporting > 70,000 deaths from drug overdoses. As a result, it is a leading cause of injury related death in the USA. Many of these deaths are caused by prescription opioids. As such, significant attention has been turned to the provision of prescription opioids, particularly after surgery.
This study was a meta- analysis of behavioral interventions implemented to decrease opioid prescribing after surgery. Ultimately, they identified 24 studies of varying sub- types (randomized controlled trials, non- randomized controlled trials, pre- post studies, interrupted time series studies, cohort studies, case control studies, historically controlled studies, and cross- sectional studies) that utilized various behavioral interventions to decrease opiate prescriptions at discharge. The primary outcome was the amount of opiates prescribed at discharged expressed as MME (milligram morphine equivalent). Secondary outcomes included post - operative pain control as measured by pain scores or need for prescription refills.
In summary, there were six types of behavioral interventions identified: local consensus - based processes, patient mediated interventions. clinical practice guidelines, interprofessional education, education meetings, and clinician reminders. A total of 21, 204 patients were studied who had undergone a myriad of procedures (plastic, general, obstetric, thoracic, urologic, oral and maxillofacial, vascular, and orthopedic surgeries). Most studies excluded patients with a history of chronic pain or opioid use prior to surgery, patients who had complications, or patients with contraindications to non - narcotic medications.
Out of the 24 studies reviewed in this meta- analysis, 23 of them demonstrated a statistically significant decrease in MMEs after the behavioral intervention was implemented. The most common intervention studied was local consensus-based processes (18 studies) based on patient survey data on post-surgery opiate usage, reviewing institutional prescribing practices, or calculating an ideal number of opiates prescribed based on the average consumption for 80% of the patients. The reduction in opiates prescribed at discharged ranged from 34.4 to 212.3 MMEs. There were mixed results on refill requests and pain scores post - discharge. Some studies reported no changes in refill requests or pain scores in several studies after the intervention. Other studies demonstrated an increase in the aforementioned secondary outcomes, but also noted their patients may have been discharged earlier with higher pain at discharge.
Other interventions evaluated included patient mediated interventions such pre - operative education sessions or a computer based shared decision-making tool, clinical practice guideline, resident education sessions, pharmacist assisted prescribing, and electronic based clinician reminders. All of the interventions consistently demonstrated a decrease in MMEs prescribed at discharge.
Limitations of the study include the variety of the types of studies completed and variation in the types of surgical procedures evaluated.
Overall, the authors did an excellent job of highlighting the multitude of behavioral interventions that can be utilized to decrease opiate prescribing at discharge. As a result, if any institution or individual is interested in decreasing post - surgical opioid prescriptions, they can utilize any of the behavioral strategies highlighted and will most likely see a significant change.
Article 2
Does simulation work? Monthly trauma simulation and procedural training are associated with decreased time to intervention. Park C, Grant J, Dumas RP, et al. J Trauma Acute Care Surg. 2020 Feb;88(2):242-248.
The purpose of this study was to evaluate the effect of a monthly procedural and trauma simulation program on time to intervention for trauma procedures. It is a single center study of time to intervention in trauma activations between July 2018 and February 2019. Time to intervention was record for intubations, tube thoracotomy, interosseous access, arterial line, resuscitative endovascular balloon access (REBOA), CT, and operative intervention. The monthly, routine training and simulation program began in November 2018. ATLS like scenarios were simulated and hands on training in percutaneous sheath and arterial line placement, interosseous line, tube thoracostomy, and resuscitative thoracotomy were reviewed. Of note, these simulations took place in the trauma bay to review not only how to complete the procedure, but also where the equipment was located. July 2018 - October 2018 served as the pre- intervention study period, with November 2018 - February 2019 serving as the post - intervention period. A dedicated trauma nurse clinical recorded the time to intervention in real time.
During the study period, there were 294 trauma activations (level 1) with the most common mechanisms being MVC (24%), gunshot wounds (21%), and falls (17%). The most common intervention was time to CT scan (45%). Other interventions such as intubation, operative intervention, percutaneous sheath, tube thoracotomy, interosseous line, and REBOA respectively represented 13, 12, 7.2, 6, 5, and <1% of procedures completed. Median pre and post times to resuscitative thoracotomy were 14 versus 3 minutes, which was statistically significant. Median pre and post times to tube thoracotomy were 13 versus 6 minutes, which was also statistically significant. Median pre- and post-times to all other procedures were not statistically significant.
The paper acknowledges several limitations that may affect time to intervention, including PGY level, number of procedures previously performed by the resident, patient acuity, patient factors such as obesity and agitation, need for sedation or not, and/or time during the academic year.
As the article accurately identifies, there are increasing demands on residents’ time. As a result, there is a need to identify effective teaching strategies and curriculum with measurable outcomes for the management of trauma, in the same way that laparoscopic and robotic skills are evaluated. Two key points notable for this study are 1) they specifically looked at the impact of the simulation sessions in real time, as opposed to in the simulation suite and 2) the training took place in the trauma bay with a specific emphasis on the “equipment, setup, and physical location,” as sometimes this is half the battle.
The study demonstrates the feasibility of creating a durable monthly trauma simulation/training program for trainees with measurable outcomes for the trainees. The next steps would be to see if these improvements result in improvements in patient outcomes, such as morbidity (infections or other complications) or mortality.
Article 3
Detection of Deteriorating Patients on Surgical Wards Outside the ICU by an Automated MEWS - based Early Warning System with Paging Functionality. Heller AR, Mees ST, Lauterwald B, Reeps C, Koch T, Weitz J. Ann Surg. 2020 Jan;271(1):100-105.
The purpose of this study was to evaluate the efficacy of an automated scoring system (MEWS) to identify post- surgical patients who were deteriorating on the wards outside of the ICU in order to improve the failure to rescue rate (FTR). The FTR is defined as death after a major post - operative complication. Previous work has demonstrated that implementation of MEWS (multiparameter early warning scores) on wards outside the ICU showed significant reductions in the incidence of cardiac arrests. MEWS scores are based on the physiologic parameters of respiration rate, oxygen saturation, use of supplemental oxygen, temperature, systolic blood pressure, heart rate, level of consciousness, and team concern.
The was a single institution study of two 56 bed surgical wards. In July of 2016, the automated MEWS based early warning system with paging functionality was installed in these two wards. The measurements from the monitors and cable less devices were transmitted via automatic notification to the ward physician during the daytime, and the on-call physician at night via text message. There was a sliding scale for notification, ranging from the nurse in charge for lower MEWS scores to the ward physician being called to the bedside for the highest MEWS scores. In addition, a dashboard of the MEWS scores for all the patients was displayed in the nurse station and the attending surgeon rooms. Data from 2015, prior to implementation of the MEWS automated warning system served as the historical control.
The control cohort included data on 1896 patients, while the intervention cohort dataset represented 1931 patients. The two patient populations were very similar. The intervention cohort did have slightly higher ASA classes and increased case resource utilization. Patient deterioration in the intervention group was detected more by monitor alert as opposed to staff observation. There was a statistically significant increase in the number of notifications regarding critical conditions to the ward physician, as to be expected. However, there was no significant difference in the number of MET (medical emergency team) calls between the two groups. The rate of cardiac arrests on the ward decreased from 5.3 —> 2.1 per 1000 admissions after the intervention, which was statistically significant. There was a significant decrease in unplanned ICU admissions (3.6% pre - intervention v. 3% post - intervention). There were no differences in MET response time, MET duration, or dosage of epinephrine used during the MET. There was no difference in mortality between the two group.
The authors ultimately conclude that utilizing the automated MEWS system with paging functionality correctly identified patients at risk of deterioration earlier in their disease process, which brought the physician to the bedside sooner. This allowed for the delivery of interventions on the wards that decreased the need for ICU beds, as well as cardiac arrests.
