Variation in Intraoperative Opioid Administration by Patient, Clinician, and Hospital Contribution

Importance

The opioid crisis has led to scrutiny of opioid exposures before and after surgical procedures. However, the extent of intraoperative opioid variation and the sources and contributing factors associated with it are unclear.

Objective

To analyze attributable variance of intraoperative opioid administration for patient-, clinician-, and hospital-level factors across surgical and analgesic categories.

Design, Setting, and Participants

This cohort study was conducted using electronic health record data collected from a national quality collaborative database. The cohort consisted of 1 011 268 surgical procedures at 46 hospitals across the US involving 2911 anesthesiologists, 2291 surgeons, and 8 surgical and 4 analgesic categories. Patients without ambulatory opioid prescriptions or use history undergoing an elective surgical procedure between January 1, 2014, and September 11, 2020, were included. Data were analyzed from January 2022 to July 2023.

Main Outcomes and Measures

The rate of intraoperative opioid administration as a continuous measure of oral morphine equivalents (OMEs) normalized to patient weight and case duration was assessed. Attributable variance was estimated in a hierarchical structure using patient, clinician, and hospital levels and adjusted intraclass correlations (ICCs).

Results

Among 1 011 268 surgical procedures (mean [SD] age of patients, 55.9 [16.2] years; 604 057 surgical procedures among females [59.7%]), the mean (SD) rate of intraoperative opioid administration was 0.3 [0.2] OME/kg/h. Together, clinician and hospital levels contributed to 20% or more of variability in intraoperative opioid administration across all analgesic and surgical categories (adjusting for surgical or analgesic category, ICCs ranged from 0.57-0.79 for the patient, 0.04-0.22 for the anesthesiologist, and 0.09-0.26 for the hospital, with the lowest ICC combination 0.21 for anesthesiologist and hosptial [0.12 for the anesthesiologist and 0.09 for the hospital for opioid only]). Comparing the 95th and fifth percentiles of opioid administration, variation was 3.3-fold among anesthesiologists (surgical category range, 2.7-fold to 7.7-fold), 4.3-fold among surgeons (surgical category range, 3.4-fold to 8.0-fold), and 2.2-fold among hospitals (surgical category range, 2.2-fold to 4.3-fold). When adjusted for patient and surgical characteristics, mean (square error mean) administration was highest for cardiac surgical procedures (0.54 [0.56-0.52 OME/kg/h]) and lowest for orthopedic knee surgical procedures (0.19 [0.17-0.21 OME/kg/h]). Peripheral and neuraxial analgesic techniques were associated with reduced administration in orthopedic hip (51.6% [95% CI, 51.4%-51.8%] and 60.7% [95% CI, 60.5%-60.9%] reductions, respectively) and knee (48.3% [95% CI, 48.0%-48.5%] and 60.9% [95% CI, 60.7%-61.1%] reductions, respectively) surgical procedures, but reduction was less substantial in other surgical categories (mean [SD] reduction, 13.3% [8.8%] for peripheral and 17.6% [9.9%] for neuraxial techniques).

Conclusions and Relevance

In this cohort study, clinician-, hospital-, and patient-level factors had important contributions to substantial variation of opioid administrations during surgical procedures. These findings suggest the need for a broadened focus across multiple factors when developing and implementing opioid-reducing strategies in collaborative quality-improvement programs.

Association of Anesthesiologist Staffing Ratio With Surgical Patient Morbidity and Mortality

Importance

Recent studies have investigated the effect of overlapping surgeon responsibilities or nurse to patient staffing ratios on patient outcomes, but the association of overlapping anesthesiologist responsibilities with patient outcomes remains unexplored to our knowledge.

Objective

To examine the association between different levels of anesthesiologist staffing ratios and surgical patient morbidity and mortality.

Design, Setting, and Participants

A retrospective, matched cohort study consisting of major noncardiac inpatient surgical procedures performed from January 1, 2010, to October 31, 2017, was conducted in 23 US academic and private hospitals. A total of 866 453 adult patients (aged ≥18 years) undergoing major inpatient surgery within the Multicenter Perioperative Outcomes Group electronic health record registry were included. Anesthesiologist sign-in and sign-out times were used to calculate a continuous time-weighted average staffing ratio variable for each operation. Propensity score-matching methods were applied to create balanced sample groups with respect to patient-, operative-, and hospital-level confounders and resulted in 4 groups based on anesthesiologist staffing ratio. Groups consisted of patients receiving care from an anesthesiologist covering 1 operation (group 1), more than 1 to no more than 2 overlapping operations (group 1-2), more than 2 to no more than 3 overlapping operations (group 2-3), and more than 3 to no more than 4 overlapping operations (group 3-4). Data analysis was performed from October 2019 to October 2021.

Exposure

Undergoing a major inpatient surgical operation that involved an anesthesiologist providing care for up to 4 overlapping operations.

Main Outcomes and Measures

The primary composite outcome was 30-day mortality and 6 major surgical morbidities (cardiac, respiratory, gastrointestinal, urinary, bleeding, and infectious complications) derived from International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision discharge diagnosis codes.

Results

In all, 578 815 adult patients (mean [SD] age, 55.7 [16.2] years; 55.1% female) were analyzed. After matching operations according to anesthesiologist staffing ratio, 48 555 patients were in group 1; 247 057, group 1-2; 216 193, group 2-3; and 67 010, group 3-4. Increasing anesthesiologist coverage responsibilities was associated with an increase in risk-adjusted surgical patient morbidity and mortality. Compared with patients in group 1-2, those in group 2-3 had a 4% relative increase in risk-adjusted mortality and morbidity (5.06% vs 5.25%; adjusted odds ratio [AOR], 1.04; 95% CI, 1.01-1.08; P = .02) and those in group 3-4 had a 14% increase in risk-adjusted mortality and morbidity (5.06% vs 5.75%; AOR, 1.15; 95% CI, 1.09-1.21; P < .001).

Conclusions and Relevance

This study's findings suggest that increasing overlapping coverage by anesthesiologists is associated with increased surgical patient morbidity and mortality. Therefore, the potential effects of staffing ratios in perioperative team models should be considered in clinical coverage efforts.

Re-evaluating expanding intravenous catheters in medical practice

BACKGROUND

Intravenous catheters are common and essential devices within medical practice. Their placement can be difficult, leading to application of several technologies to improve success. Functionally expanding catheters were once an exciting technology, derailed clinically by hypersensitivity reactions. The exact cause of reactions, attributed to Aquavene catheter materials, remains unknown.

AIMS

To reinvestigate functionally expanding intravenous catheters.

MATERIALS AND METHODS

The history of the functionally expanding intravenous catheter is presented here along with its utility in current medical practice, potential for further investigation, and possible redesign of these once promising devices.

RESULTS

This review demonstrates clinical utility and a lack of definitive cause for failure of the previous functionally expanding intravenous catheter design. As Aquavene materials themselves are commonly considered the cause of hypersensitivity reactions which removed expanding intravenous catheters from the market, this review found several possible substitutes for this material for use in any redesign.

DISCUSSION AND CONCLUSION

The functionally expanding intravenous catheter failed due to hypersensitivity reactions in patients. Alternative materials exist for a possible redesign on this once promising clinical product.

Swellable catheters based on a dynamic expanding inner diameter

Intravenous (IV) fluid administration is critical for all patients undergoing care in a hospital setting. In-patient hospital practice, surgeries, and emergency care require functional IVs for fluid replacement and medication administration. Proper placement of IVs is vital to providing medical services. The ease of placement of an IV catheter, however, depends not only on the size of the catheter but also on provider experience and patient demographics such as age, body mass index, hydration status, and medical comorbidities present challenges to successful IV placement. Smaller diameter IV placement can improve success and there are instances where multiple small diameter catheters are placed for patient care when larger bore access is unattainable. Smaller inner-diameter catheters for anesthesia have functional constraints. Ideally, there would be a smaller catheter for placement that could function as a larger catheter for patient care. One solution is the idea of functionally responsive catheters. Here, we evaluated tubular-shaped hydrogels as potential functional catheters that can increase in inner diameter through fluid swelling using cross-linked homopolymers of polyacrylamide, PAM (10-40% w/w), and their copolymers with 0-8% w/w Poly-(Ethylene Glycol)-Diacrylate, PEGDA. For the PAM gels, the water transport mechanism was shown to be concentration-dependent Fickian diffusion, with the less concentrated gels exhibiting increasingly anomalous modes. Increasing the PEGDA content in the network yielded an initial high rate of water uptake, characterized by Case II transport. The swelling kinetics depended strongly on the sample geometry and boundary conditions. Initially, in a submerged swelling, the annulus expands symmetrically in both outward and inward directions (it thickens), reducing the internal diameter by up to 70%. After 1 h, however, the inner diameter increases steadily so that at equilibrium, there is a net (>100%) increase in all the dimensions of the tube. The amount of linear swelling at equilibrium depended only on the polymer volume fraction as made, while the rate of inner diameter expansion depended on the hydrophilicity of the matrix and the kinetics of sorption. This study serves as proof of concept to identify key parameters for the successful design of hydrogel-based catheter devices with expanding inner-diameters for applications in medical care.

Early Detection of Heart Failure With Reduced Ejection Fraction Using Perioperative Data Among Noncardiac Surgical Patients: A Machine-Learning Approach

BACKGROUND

Heart failure with reduced ejection fraction (HFrEF) is a condition imposing significant health care burden. Given its syndromic nature and often insidious onset, the diagnosis may not be made until clinical manifestations prompt further evaluation. Detecting HFrEF in precursor stages could allow for early initiation of treatments to modify disease progression. Granular data collected during the perioperative period may represent an underutilized method for improving the diagnosis of HFrEF. We hypothesized that patients ultimately diagnosed with HFrEF following surgery can be identified via machine-learning approaches using pre- and intraoperative data.

METHODS

Perioperative data were reviewed from adult patients undergoing general anesthesia for major surgical procedures at an academic quaternary care center between 2010 and 2016. Patients with known HFrEF, heart failure with preserved ejection fraction, preoperative critical illness, or undergoing cardiac, cardiology, or electrophysiologic procedures were excluded. Patients were classified as healthy controls or undiagnosed HFrEF. Undiagnosed HFrEF was defined as lacking a HFrEF diagnosis preoperatively but establishing a diagnosis within 730 days postoperatively. Undiagnosed HFrEF patients were adjudicated by expert clinician review, excluding cases for which HFrEF was secondary to a perioperative triggering event, or any event not associated with HFrEF natural disease progression. Machine-learning models, including L1 regularized logistic regression, random forest, and extreme gradient boosting were developed to detect undiagnosed HFrEF, using perioperative data including 628 preoperative and 1195 intraoperative features. Training/validation and test datasets were used with parameter tuning. Test set model performance was evaluated using area under the receiver operating characteristic curve (AUROC), positive predictive value, and other standard metrics.

RESULTS

Among 67,697 cases analyzed, 279 (0.41%) patients had undiagnosed HFrEF. The AUROC for the logistic regression model was 0.869 (95% confidence interval, 0.829-0.911), 0.872 (0.836-0.909) for the random forest model, and 0.873 (0.833-0.913) for the extreme gradient boosting model. The corresponding positive predictive values were 1.69% (1.06%-2.32%), 1.42% (0.85%-1.98%), and 1.78% (1.15%-2.40%), respectively.

CONCLUSIONS

Machine-learning models leveraging perioperative data can detect undiagnosed HFrEF with good performance. However, the low prevalence of the disease results in a low positive predictive value, and for clinically meaningful sensitivity thresholds to be actionable, confirmatory testing with high specificity (eg, echocardiography or cardiac biomarkers) would be required following model detection. Future studies are necessary to externally validate algorithm performance at additional centers and explore the feasibility of embedding algorithms into the perioperative electronic health record for clinician use in real time.

Considerations for Integration of Perioperative Electronic Health Records Across Institutions for Research and Quality Improvement: The Approach Taken by the Multicenter Perioperative Outcomes Group

Use of the electronic health record (EHR) has become a routine part of perioperative care in the United States. Secondary use of EHR data includes research, quality, and educational initiatives. Fundamental to secondary use is a framework to ensure fidelity, transparency, and completeness of the source data. In developing this framework, competing priorities must be considered as to which data sources are used and how data are organized and incorporated into a useable format. In assembling perioperative data from diverse institutions across the United States and Europe, the Multicenter Perioperative Outcomes Group (MPOG) has developed methods to support such a framework. This special article outlines how MPOG has approached considerations of data structure, validation, and accessibility to support multicenter integration of perioperative EHRs. In this multicenter practice registry, MPOG has developed processes to extract data from the perioperative EHR; transform data into a standardized format; and validate, deidentify, and transfer data to a secure central Coordinating Center database. Participating institutions may obtain access to this central database, governed by quality and research committees, to inform clinical practice and contribute to the scientific and clinical communities. Through a rigorous and standardized approach to ensure data integrity, MPOG enables data to be usable for quality improvement and advancing scientific knowledge. As of March 2019, our collaboration of 46 hospitals has accrued 10.7 million anesthesia records with associated perioperative EHR data across heterogeneous vendors. Facilitated by MPOG, each site retains access to a local repository containing all site-specific perioperative data, distinct from source EHRs and readily available for local research, quality, and educational initiatives. Through committee approval processes, investigators at participating sites may additionally access multicenter data for similar initiatives. Emerging from this work are 4 considerations that our group has prioritized to improve data quality: (1) data should be available at the local level before Coordinating Center transfer; (2) data should be rigorously validated against standardized metrics before use; (3) data should be curated into computable phenotypes that are easily accessible; and (4) data should be collected for both research and quality improvement purposes because these complementary goals bolster the strength of each endeavor.

Pro-region engineering for improved yeast display and secretion of brain derived neurotrophic factor

Brain derived neurotrophic factor (BDNF) is a promising therapeutic candidate for a variety of neurological diseases. However, it is difficult to produce as a recombinant protein. In its native mammalian context, BDNF is first produced as a pro-protein with subsequent proteolytic removal of the pro-region to yield mature BDNF protein. Therefore, in an attempt to improve yeast as a host for heterologous BDNF production, the BDNF pro-region was first evaluated for its effects on BDNF surface display and secretion. Addition of the wild-type pro-region to yeast BDNF production constructs improved BDNF folding both as a surface-displayed and secreted protein in terms of binding its natural receptors TrkB and p75, but titers remained low. Looking to further enhance the chaperone-like functions provided by the pro-region, two rounds of directed evolution were performed, yielding mutated pro-regions that further improved the display and secretion properties of BDNF. Subsequent optimization of the protease recognition site was used to control whether the produced protein was in pro- or mature BDNF forms. Taken together, we have demonstrated an effective strategy for improving BDNF compatibility with yeast protein engineering and secretion platforms.

Bridging the "med-ed gap" for students with special health care needs: a model school liaison program

A successful school experience is critical to the development of all children, particularly in the areas of academic achievement, regular school attendance, and social competency. Vulnerabilities in achieving each of these three goals have been documented among students with special health care needs (SSHCN), and ascribed to the influence of their health-related disabilities. Despite recognition of these vulnerabilities, barriers still exist to successful integration of SSHCN into educational settings. A key barrier to successful integration involves poor linkages between the health and education systems. This article describes a model linkage system--the School Liaison Program at Texas Children's Hospital, developed as a U.S. Dept. of Health and Human Services Maternal and Child Health Bureau Special Project of Regional and National Significance. The program provides educational liaison services between the largest pediatric hospital in the United States and school districts in the fourth largest city. A description of the linkage system emphasizes interdisciplinary staffing by both special educators and health providers. The model for educational liaison service delivery presented includes the elements of eligibility, assessment of the educational implications of illness, plan development and referral, involvement in educational placement, and monitoring. Resources for integrating SSHCN into educational settings are suggested.

Analysis of compressive creep behavior of the vertebral unit subjected to a uniform axial loading using exact parametric solution equations of Kelvin-solid models--Part I. Human intervertebral joints

The creep response phenomena observed on 47 human intervertebral discs subjected to a constant axial compressive stress was analytically studied by two-, three- and four-parameter-solid models employing the Burns- Kaleps 'exact analysis scheme'. The mechanical properties (Young's moduli and viscosity coefficients) associated with each model were calculated for each of the 47 disks, with superior results obtained for the latter two models. Results for the two-parameter-solid model suggest its possible usefulness in simulating creep response that is characteristic of disk degeneration. Results for the three- and four-parameter-solid models were excellent, with an average error for the model predicted strain, epsilon(ti)cal, values from the experimentally measured, epsilon(ti)exp, values of 2.314% for the former model and 4.446% for the latter model on the 47 human spinal segments analyzed. The three-parameter-solid model was most sensitive in its predictability of strain behavior for ti greater than 1 min; whereas the four-parameter-solid model demonstrated greater simulation sensitivity in the 0 less than ti less than or equal to 1 min range.

Analysis of compressive creep behavior of the vertebral unit subjected to a uniform axial loading using exact parametric solution equations of Kelvin-solid models--Part II. Rhesus monkey intervertebral joints

The simulation of long-term creep response behavior, observed on 54 Rhesus monkey intervertebral joints subjected to a constant axial compressive stress, is attempted by two- and three-parameter-solid models utilizing the Burns- Kaleps 'exact analysis scheme'. Model parameters identified by the analysis of each specimen's experimental strain data were optimized via a computer program and the mechanical properties (Young's moduli and the viscosity coefficient) appropriate to each model were calculated for individual spinal segments. Simulation results for the two-parameter-solid (one- Kelvin -unit) model demonstrate its general ineptness in predicting the observed strain-time behavior of normal spinal sements . The three-parameter-solid model yielded excellent results in the simulation of observed spinal segment compressive creep phenomena. It produced an average error between the model predicted and experimental strain values that ranged from a low of 0.4000% to a high of 3.290% for the 54 Rhesus monkey intervertebral joints, with a collective average error for all specimens of only 1.363%.