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

Neuromuscular Blockade and Antagonism in Patients with Renal Impairment: A Multicenter Retrospective Cross-sectional Study

BACKGROUND

Current practice guidelines do not address the use of neuromuscular blocking and antagonism agents in patients with renal impairment. The U.S. Food and Drug Administration (Silver Spring, Maryland) label for sugammadex advises against use in patients with severe renal impairment (estimated glomerular filtration rate [eGFR] less than 30 ml/min). Using a multicenter electronic health record registry, the authors sought to understand the modern use of neuromuscular blockade and antagonism agents in patients with significant renal impairment (eGFR less than 60 ml/min).

METHODS

Data were obtained from the Multicenter Perioperative Outcomes Group (MPOG) registry for adult patients (older than 18 yr) with an eGFR less than 60 ml/min, based on most recent serum creatinine, receiving general anesthesia for a nonrenal transplant procedure with an endotracheal tube between January 1, 2016, and July 31, 2022. Patients were classified into three mutually exclusive blockade and reversal strategies: rocuronium-sugammadex, cisatracurium-neostigmine, and rocuronium-neostigmine. Adjusted incidence of each blockade reversal strategy was established by a multinomial mixed effects model. The contribution of institution, anesthesiologist, and patient or case factors to variation in strategy choice was assessed by multilevel mixed effects models.

RESULTS

In 243,944 cases across 5,133 anesthesiologists and 48 institutions, adjusted use of rocuronium-sugammadex increased from 4.4 to 95.2%, rocuronium-neostigmine decreased from 84.7 to 4.3%, and cisatracurium-neostigmine decreased from 10.9 to 0.5%. In patients with an eGFR less than 15 ml/min, rocuronium-sugammadex use increased from 0.5 to 86.9%. Of the variation in choice of rocuronium-sugammadex versus cisatracurium-neostigmine, 30.1% was attributed to the institution, 22.7% to the attending anesthesiologist, and 47.2% to patient/case factors or was unexplained. The adjusted median odds ratio for this choice was 2.5 for clinicians and 3.1 for institutions.

CONCLUSION

Rocuronium-sugammadex is the primary neuromuscular blockade-antagonism strategy for patients with moderate and severe renal impairment. Variation in choice is significantly impacted by the institution and attending anesthesiologist providing care.

Opioid Dose Variation in Cardiac Surgery: A Multicenter Study of Practice

BACKGROUND

Although high-opioid anesthesia was long the standard for cardiac surgery, some anesthesiologists now favor multimodal analgesia and low-opioid anesthetic techniques. The typical cardiac surgery opioid dose is unclear, and the degree to which patients, anesthesiologists, and institutions influence this opioid dose is unknown.

METHODS

We reviewed data from nonemergency adult cardiac surgeries requiring cardiopulmonary bypass performed at 30 academic and community hospitals within the Multicenter Perioperative Outcomes Group registry from 2014 through 2021. Intraoperative opioid administration was measured in fentanyl equivalents. We used hierarchical linear modeling to attribute opioid dose variation to the institution where each surgery took place, the primary attending anesthesiologist, and the specifics of the surgical patient and case.

RESULTS

Across 30 hospitals, 794 anesthesiologists, and 59,463 cardiac cases, patients received a mean of 1139 (95% confidence interval [CI], 1132-1146) fentanyl mcg equivalents of opioid, and doses varied widely (standard deviation [SD], 872 µg). The most frequently used opioids were fentanyl (86% of cases), sufentanil (16% of cases), hydromorphone (12% of cases), and morphine (3% of cases). 0.6% of cases were opioid-free. 60% of dose variation was explainable by institution and anesthesiologist. The median difference in opioid dose between 2 randomly selected anesthesiologists across all institutions was 600 µg of fentanyl (interquartile range [IQR], 283-1023 µg). An anesthesiologist's intraoperative opioid dose was strongly correlated with their frequency of using a sufentanil infusion (r = 0.81), but largely uncorrelated with their use of nonopioid analgesic techniques (|r| < 0.3).

CONCLUSIONS

High-dose opioids predominate in cardiac surgery, with substantial dose variation from case to case. Much of this variation is attributable to practice variability rather than patient or surgical differences. This suggests an opportunity to optimize opioid use in cardiac surgery.

Accounting for Healthcare Structures When Measuring Variation in Care

Health services research frequently focuses on variation in the structure, process, and outcomes of clinical care. Robust approaches for detection and attribution of variation are foundational to both quality improvement and outcomes research. Describing care in structured healthcare systems across hospitals in which clinicians work to provide care for patients as a multileveled structure allows the impact of organization on practice and outcome to be ascertained. Mixed-effect statistical models can describe both the partitioning of variation among levels of these structures and by inclusion of explanatory variables the valid estimation of the features of health systems, clinicians, or patients, with observed differences in processes or patient outcomes. In this Readers' Toolbox, the authors describe the rationale for considering healthcare structures when assessing clinical practice, outcomes, and sources of variation. They describe statistical considerations and methods for the estimation of analysis of structured data and assessment of variance.

Hospital and Clinician Practice Variation in Cardiac Surgery and Postoperative Acute Kidney Injury

Importance

Approximately 30% of US patients develop acute kidney injury (AKI) after cardiac surgery, which is associated with increased morbidity, mortality, and health care costs. The variation in potentially modifiable hospital- and clinician-level operating room practices and their implications for AKI have not been rigorously evaluated.

Objective

To quantify variation in clinician- and hospital-level hemodynamic and resuscitative practices during cardiac surgery and identify their associations with AKI.

Design, Setting, and Participants

This cohort study analyzed integrated hospital, clinician, and patient data extracted from the Multicenter Perioperative Outcomes Group dataset and the Society of Thoracic Surgeons Adult Cardiac Surgical Database. Participants were adult patients (aged ≥18 years) who underwent cardiac surgical procedures between January 1, 2014, and February 1, 2022, at 8 geographically diverse US hospitals. Patients were followed up through March 2, 2022. Statistical analyses were performed from October 2024 to February 2025.

Exposures

Hospital- and clinician-level variations in operating room hemodynamic practices (inotrope infusion >60 minutes and vasopressor infusion >60 minutes) and resuscitative practices (homologous red blood cell [RBC] transfusion and total fluid volume administration).

Main Outcomes and Measures

The primary outcome was consensus guideline-defined AKI (any stage) within 7 days after cardiac surgery. Hospital- and clinician-level variations were quantified using intraclass correlation coefficients (ICCs). Associations of hospital- and clinician-level practices with AKI were analyzed using multilevel mixed-effects models, adjusting for patient-level characteristics.

Results

Among 23 389 patients (mean [SD] age, 63 [13] years; 16 122 males [68.9%]), 4779 (20.4%) developed AKI after cardiac surgery. AKI rates varied across hospitals (median [IQR], 21.7% [15.5%-27.2%]) and clinicians (18.1% [10.1%-23.7%]). Significant clinician- and hospital-level variation existed for inotrope infusion (ICC, 6.2% [95% CI, 4.2%-8.0%] vs 17.9% [95% CI, 3.3%-31.9%]), vasopressor infusion (ICC, 11.7% [95% CI, 8.3%-14.9%] vs 44.5% [95% CI, 11.7%-63.5%]), RBC transfusion (ICC, 1.7% [95% CI, 0.9%-2.6%] vs 4.5% [95% CI, 1.2%-9.4%]), and fluid volume administration (ICC, 2.1% [95% CI, 1.3%-2.7%] vs 23.8% [95% CI, 2.7%-39.9%]). In multilevel risk-adjusted models, the AKI rate was higher for patients at hospitals with higher inotrope infusion rates (adjusted odds ratio [AOR], 1.98; 95% CI, 1.18-3.33; P = .01) and lower among clinicians with higher RBC transfusion rates (AOR, 0.89; 95% CI, 0.79-0.99; P = .03). Other practice variations were not associated with AKI.

Conclusions and Relevance

This cohort study of adult patients found that hospital- and clinician-level variation in operating room practices was associated with AKI after cardiac surgery, suggesting possible targets for intervention.

Clinician attitudes, opinions and practice patterns regarding inotrope use for cardiac surgery in the USA: a multicentre mixed methods study protocol

INTRODUCTION

Cardiac inotrope medications administered to cardiac surgical patients carry steep risk-benefit trade-offs, yet wide inter-institutional variation exists in inotrope practices. Despite known wide variation in use of any inotrope for cardiac surgery, limited multicentre data exist regarding determinants of inotrope selection and time course for use. Additionally, the reasons that underpin how clinicians decide on inotrope usage and the factors that influence inotrope practice change are not well understood.

METHODS AND ANALYSIS

This is an investigator-initiated, multicentre mixed methods study. Quantitative data will include electronic health records from an observational cohort of adult cardiac procedures within the Multicenter Perioperative Outcomes Group (MPOG) database, comprising cardiac surgical procedures from over 30 US academic and community hospitals. Additional quantitative data will be collected via surveys of clinicians involved in inotrope decision-making, contacted through an existing multicentre research and quality improvement infrastructure with engaged clinician representatives participating across MPOG hospitals. Qualitative data will be collected from open-ended questions within surveys, as well as semi-structured interviews with surveyed clinicians, sampled across approximately six institutions selected for diversity of settings and inotrope practices. An explanatory sequential mixed methods design will merge quantitative and qualitative data to develop meta-inferences explaining inotrope practices, as guided by an existing framework for characterising clinical practice variation and levers for practice change.

ETHICS AND DISSEMINATION

The study is approved by the institutional review board at the University of Michigan Medical School (HUM00245353). Findings will be disseminated through peer-reviewed journals, conference proceedings and quality improvement forums. The study began in February 2025 and will continue until 2028.

Environmental and patient safety outcomes of a health-system Green Anesthesia Initiative (GAIA): a retrospective observational cohort study

BACKGROUND

Inhaled anaesthetics are greenhouse gases. However, changes in the delivery of inhaled anaesthetics can mitigate environmental impact. We hypothesised that system-wide changes to the delivery of anaesthesia care would reduce environmental harm without compromising patient outcomes.

METHODS

We launched the Green Anesthesia Initiative (GAIA) in March, 2022, with the aims of reducing the use of nitrous oxide, using less environmentally harmful inhaled fluorinated ethers, and increasing intravenous anaesthetic use. In this retrospective cohort study, we used electronic health record data from general anaesthetics performed on all patients older than 1 year between March 1, 2021, and Feb 28, 2023, at a single US academic medical centre across multiple sites, collecting data from before and after the introduction of GAIA. Patients with missing or invalid data recorded by the anaesthesia machine, patients given general anaesthetics for electroconvulsive therapy, and patients who met American Society of Anesthesiologists Physical Status Classification 6 were excluded. Using multivariable modelling, we compared estimated CO2, equivalents and, secondarily, anaesthetic dose, postoperative nausea and vomiting, pain scores on a 0-10 scale, and reports of intraoperative awareness with explicit recall.

FINDINGS

We recorded 45 692 patients pre-intervention (23 193 [50·8%] female, 22 494 [49·2%] male, five [<0·1%] unknown) and 47 199 post-intervention (23 981 [50·8%] female, 23 209 [49·2%] male, nine [<0·1%] unknown). After the implementation of GAIA, CO2, equivalents were reduced by 14·38 kg per patient (95% CI -14·68 to -14·07; p<0·0001). There was no clinically meaningful difference in median anaesthetic delivered (minimum alveolar concentration -0·02 [95% CI -0·02 to -0·01]; p<0·0001) nor pain scores (-0·34 [-0·39 to -0·29]; p<0·0001). Postoperative nausea and vomiting was unchanged (odds ratio 0·98 [95% CI 0·94-1·02]; p=0·26). A small number of definite intraoperative awareness events were reported in both periods (one pre-intervention and two post-intervention).

INTERPRETATION

A health-system wide intervention reduces greenhouse gas emissions attributable to anaesthesia care without detriment to patient outcomes.

FUNDING

University of Michigan Medical School and National Institutes of Health.

Intraoperative hypoglycemia among adults with intraoperative glucose measurements: a cross-sectional multicentre retrospective cohort study

PURPOSE

Intraoperative hypoglycemia is presumed to be rare, but generalizable multicentre incidence and risk factor data for adult patients are lacking. We used a multicentre registry to characterize adults with intraoperative hypoglycemia and hypothesized that intraoperative insulin administration would be associated with hypoglycemia.

METHODS

We conducted a cross-sectional retrospective multicentre cohort study. We searched the Multicenter Perioperative Outcomes Group registry to identify adult patients with intraoperative hypoglycemia (glucose < 3.3 mmol·L-1 [< 60 mg·dL-1]) from 1 January 2015 to 31 December 2019. We evaluated characteristics of patients with intraoperative glucose measurements and with intraoperative hypoglycemia.

RESULTS

Of 516,045 patients with intraoperative glucose measurements, 3,900 (0.76%) had intraoperative hypoglycemia. Diabetes mellitus and chronic kidney disease were more common in the cohort with intraoperative hypoglycemia. The odds of intraoperative hypoglycemia were higher for the youngest age category (18-30 yr) compared with the odds for every age category above 40 yr (odds ratio [OR], 1.57-3.18; P < 0.001), and were higher for underweight or normal weight patients compared with patients with obesity (OR, 1.48-2.53; P < 0.001). Parenteral nutrition was associated with lower odds of hypoglycemia (OR, 0.23; 95% confidence interval [CI], 0.11 to 0.47; P < 0.001). Intraoperative insulin use was not associated with hypoglycemia (OR, 0.996; 95% CI, 0.91 to 1.09; P = 0.93).

CONCLUSION

In this large cross-sectional retrospective multicentre cohort study, intraoperative hypoglycemia was a rare event. Intraoperative insulin use was not associated with hypoglycemia.

Variability in Intraoperative Opioid and Nonopioid Utilization During Intracranial Surgery: A Multicenter, Retrospective Cohort Study

BACKGROUND

Key goals during intracranial surgery are to facilitate rapid emergence and extubation for early neurologic evaluation. Longer-acting opioids are often avoided or administered at subtherapeutic doses due to their perceived risk of sedation and delayed emergence. However, inadequate analgesia and increased postoperative pain are common after intracranial surgery. In this multicenter study, we describe variability in opioid and nonopioid administration patterns in patients undergoing intracranial surgery.

METHODS

This was a multicenter, retrospective observational cohort study using the Multicenter Perioperative Outcomes Group database. Opioid and nonopioid practice patterns in 31,217 cases undergoing intracranial surgery across 11 institutions in the United States are described.

RESULTS

Across all 11 institutions, total median [interquartile range] oral morphine equivalents, normalized to weight and anesthesia duration was 0.17 (0.08 to 0.3) mg.kg.min -1 . There was a 7-fold difference in oral morphine equivalents between the lowest (0.05 [0.02 to 0.13] mg.kg.min -1 ) and highest (0.36 [0.18 to 0.54] mg.kg.min -1 ) prescribing institutions. Patients undergoing supratentorial surgery had higher normalized oral morphine equivalents compared with those having infratentorial surgery [0.17 [0.08-0.31] vs. 0.15 [0.07-0.27] mg/kg/min -1 ; P <0.001); however, this difference is clinically small. Nonopioid analgesics were not administered in 20% to 96.8% of cases across institutions.

CONCLUSION

This study found wide variability for both opioid and nonopioid utilization at an institutional level. Future work on practitioner-level opioid and nonopioid use and its impact on outcomes after intracranial surgery should be conducted.

Identifying Variation in Intraoperative Management of Brain-Dead Organ Donors and Opportunities for Improvement: A Multicenter Perioperative Outcomes Group Analysis

BACKGROUND

Intraoperative events and clinical management of deceased organ donors after brain death are poorly characterized and may consequently vary between hospitals and organ procurement organization (OPO) regions. In a multicenter cohort, we sought to estimate the incidence of hypotension and anesthetic and nonanesthetic medication use during organ recovery procedures.

METHODS

We used data from electronic anesthetic records generated during organ recovery procedures from brain-dead adults across a Multicenter Perioperative Outcomes Group (MPOG) cohort of 14 US hospitals and 4 OPO regions (2014-2020). Hypotension, defined as mean arterial pressure or MAP <60 mm Hg for at least 10 cumulative minutes was the primary outcome of interest. The associations between hypotension and age, sex, race, anesthesia time, OPOs, and OPO case volume were examined using multivariable mixed-effects Poisson regression analyses with robust standard error estimates. We calculated intraclass correlation coefficients (ICCs) to describe the variation between-MPOG centers and the OPO regions in the use of medications, time of the operation, and duration of the operation.

RESULTS

We examined 1338 brain-dead adult donors, with a mean age of 42± (standard deviation [SD] 15) years; 60% (n = 801) were males and 67% (n = 891) non-Hispanic White. During the entire intraoperative monitoring period, 321 donors (24%, 95% confidence interval [CI], 22%-26%) had hypotension for a median of 13.8% [quartile1-quartile 3: 9.4%-21%] of the monitoring period and a minimum of 10 minutes to a maximum of 96 minutes [(median: 17, quartile1-quartile 3: 12-24]). The probability having hypotension in donors 35 to 64 years and 65 years and older were approximately 30% less than in donors 18 to 34 years of age (adjusted relative risk ratios, aRR, 0.68, 95% CI, 0.55-0.82, aRR, 0.63, 95% CI, 0.42-0.94, respectively). Donors received intravenous heparin (96.4%, n = 1291), neuromuscular blockers (89.5%, n = 1198), vasoactive medications (82.7%, n = 1108), crystalloids (76.2%, n = 1020), halogenated anesthetic gases (63.5%, n = 850), diuretics (43.8%, n = 587), steroids (16.7%, n = 224), and opioids (23.2%, n = 310). The largest practice heterogeneity observed between the MPOG center and OPO regions was steroids (between-center ICCs = 0.65, 95% CI, 0.62-0.75, between-region ICCs = 0.39, 95% CI, 0.27-0.63) and diuretics (between-center ICCs = 0.44, 95% CI, 0.36-0.6, between-region ICCs = 0.30, 95% CI, 0.22-0.49).

CONCLUSIONS

Despite guidelines recommending maintenance of MAP >60 mm Hg in adult brain-dead organ donors, hypotension during recovery procedures was common. Future research is needed to clarify the relationship between intraoperative events with donation and transplantation outcomes and to identify best practices for the anesthetic management of brain-dead donors in the operating room.

Polygenic Score for the Prediction of Postoperative Nausea and Vomiting: A Retrospective Derivation and Validation Cohort Study

BACKGROUND

Postoperative nausea and vomiting (PONV) is a key driver of unplanned admission and patient satisfaction after surgery. Because traditional risk factors do not completely explain variability in risk, this study hypothesized that genetics may contribute to the overall risk for this complication. The objective of this research is to perform a genome-wide association study of PONV, derive a polygenic risk score for PONV, assess associations between the risk score and PONV in a validation cohort, and compare any genetic contributions to known clinical risks for PONV.

METHODS

Surgeries with integrated genetic and perioperative data performed under general anesthesia at Michigan Medicine (Ann Arbor, Michigan) and Vanderbilt University Medical Center (Nashville, Tennessee) were studied. PONV was defined as nausea or emesis occurring and documented in the postanesthesia care unit. In the discovery phase, genome-wide association studies were performed on each genetic cohort, and the results were meta-analyzed. Next, the polygenic phase assessed whether a polygenic score, derived from genome-wide association study in a derivation cohort from Vanderbilt University Medical Center, improved prediction within a validation cohort from Michigan Medicine, as quantified by discrimination (c-statistic) and net reclassification index.

RESULTS

Of 64,523 total patients, 5,703 developed PONV (8.8%). The study identified 46 genetic variants exceeding the threshold of P < 1 × 10-5, occurring with minor allele frequency greater than 1%, and demonstrating concordant effects in both cohorts. Standardized polygenic score was associated with PONV in a basic model, controlling for age and sex (adjusted odds ratio, 1.027 per SD increase in overall genetic risk; 95% CI, 1.001 to 1.053; P = 0.044), a model based on known clinical risks (adjusted odds ratio, 1.029; 95% CI, 1.003 to 1.055; P = 0.030), and a full clinical regression, controlling for 21 demographic, surgical, and anesthetic factors, (adjusted odds ratio, 1.029; 95% CI, 1.002 to 1.056; P = 0.033). The addition of polygenic score improved overall discrimination in models based on known clinical risk factors (c-statistic, 0.616 compared to 0.613; P = 0.028) and improved net reclassification of 4.6% of cases.

CONCLUSIONS

Standardized polygenic risk was associated with PONV in all three of the study's models, but the genetic influence was smaller than exerted by clinical risk factors. Specifically, a patient with a polygenic risk score greater than 1 SD above the mean has 2 to 3% greater odds of developing PONV when compared to the baseline population, which is at least an order of magnitude smaller than the increase associated with having prior PONV or motion sickness (55%), having a history of migraines (17%), or being female (83%) and is not clinically significant. Furthermore, the use of a polygenic risk score does not meaningfully improve discrimination compared to clinical risk factors and is not clinically useful.

EDITOR’S PERSPECTIVE

Heart failure diagnostic accuracy, intraoperative fluid management, and postoperative acute kidney injury: a single-centre prospective observational study

BACKGROUND

The accurate diagnosis of heart failure (HF) before major noncardiac surgery is frequently challenging. The impact of diagnostic accuracy for HF on intraoperative practice patterns and clinical outcomes remains unknown.

METHODS

We performed an observational study of adult patients undergoing major noncardiac surgery at an academic hospital from 2015 to 2019. A preoperative clinical diagnosis of HF was defined by keywords in the preoperative assessment or a diagnosis code. Medical records of patients with and without HF clinical diagnoses were reviewed by a multispecialty panel of physician experts to develop an adjudicated HF reference standard. The exposure of interest was an adjudicated diagnosis of heart failure. The primary outcome was volume of intraoperative fluid administered. The secondary outcome was postoperative acute kidney injury (AKI).

RESULTS

From 40 659 surgeries, a stratified subsample of 1018 patients were reviewed by a physician panel. Among patients with adjudicated diagnoses of HF, those without a clinical diagnosis (false negatives) more commonly had preserved left ventricular ejection fractions and fewer comorbidities. Compared with false negatives, an accurate diagnosis of HF (true positives) was associated with 470 ml (95% confidence interval: 120-830; P=0.009) lower intraoperative fluid administration and lower risk of AKI (adjusted odds ratio:0.39, 95% confidence interval 0.18-0.89). For patients without adjudicated diagnoses of HF, non-HF was not associated with differences in either fluids administered or AKI.

CONCLUSIONS

An accurate preoperative diagnosis of heart failure before noncardiac surgery is associated with reduced intraoperative fluid administration and less acute kidney injury. Targeted efforts to improve preoperative diagnostic accuracy for heart failure may improve perioperative outcomes.

Factors Associated With Decision to Use and Dosing of Sugammadex in Children: A Retrospective Cross-Sectional Observational Study

BACKGROUND

Sugammadex was initially approved for reversal of neuromuscular blockade in adults in the United States in 2015. Limited data suggest sugammadex is widely used in pediatric anesthesia practice however the factors influencing use are not known. We explore patient, surgical, and institutional factors associated with the decision to use sugammadex versus neostigmine or no reversal, and the decision to use 2 mg/kg vs 4 mg/kg dosing.

METHODS

Using data from the Multicenter Perioperative Outcomes Group (MPOG) database, an EHR-derived registry, we conducted a retrospective cross-sectional study. Eligible cases were performed between January 1, 2016 and December 31, 2020, for children 0 to 17 years at US hospitals. Cases involved general anesthesia with endotracheal intubation and administration of rocuronium or vecuronium. Using generalized linear mixed models with institution and anesthesiologist-specific random intercepts, we measured the importance of a variety of patient, clinician, institution, anesthetic, and surgical risk factors in the decision to use sugammadex versus neostigmine, and the decision to use a 2 mg/kg vs 4 mg/kg dose. We then used intraclass correlation statistics to evaluate the proportion of variance contributed by institution and anesthesiologist specifically.

RESULTS

There were 97,654 eligible anesthetics across 30 institutions. Of these 47.1% received sugammadex, 43.1% received neostigmine, and 9.8% received no reversal agent. Variability in the choice to use sugammadex was attributable primarily to institution (40.4%) and attending anesthesiologist (27.1%). Factors associated with sugammadex use (compared to neostigmine) include time from first institutional use of sugammadex (odds ratio [OR], 1.08, 95% confidence interval [CI], 1.08-1.09, per month, P < .001), younger patient age groups (0-27 days OR, 2.59 [2.00-3.34], P < .001; 28 days-1 year OR, 2.72 [2.16-3.43], P < .001 vs 12-17 years), increased American Society of Anesthesiologists [ASA] physical status (ASA III: OR, 1.32 [1.23-1.42], P < .001 ASA IV OR, 1.71 [1.46-2.00], P < .001 vs ASA I), neuromuscular disease (OR, 1.14 (1.04-1.26], P = .006), cardiac surgery (OR, 1.76 [1.40-2.22], P < .001), dose of neuromuscular blockade within the hour before reversal (>2 ED95s/kg OR, 4.58 (4.14-5.07], P < .001 vs none), and shorter case duration (case duration <60 minutes OR, 2.06 [1.75-2.43], P < .001 vs >300 minutes).

CONCLUSIONS

Variation in sugammadex use was primarily explained by institution and attending anesthesiologist. Patient factors associated with the decision to use sugammadex included younger age, higher doses of neuromuscular blocking agents, and increased medical complexity.

International multi-institutional external validation of preoperative risk scores for 30-day in-hospital mortality in paediatric patients

BACKGROUND

Risk prediction scores are used to guide clinical decision-making. Our primary objective was to externally validate two patient-specific risk scores for 30-day in-hospital mortality using the Multicenter Perioperative Outcomes Group (MPOG) registry: the Pediatric Risk Assessment (PRAm) score and the intrinsic surgical risk score. The secondary objective was to recalibrate these scores.

METHODS

Data from 56 US and Dutch hospitals with paediatric caseloads were included. The primary outcome was 30-day mortality. To assess model discrimination, the area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUC-PR) were calculated. Model calibration was assessed by plotting the observed and predicted probabilities. Decision analytic curves were fit.

RESULTS

The 30-day mortality was 0.14% (822/606 488). The AUROC for the PRAm upon external validation was 0.856 (95% confidence interval 0.844-0.869), and the AUC-PR was 0.008. Upon recalibration, the AUROC was 0.873 (0.861-0.886), and the AUC-PR was 0.031. The AUROC for the external validation of the intrinsic surgical risk score was 0.925 (0.914-0.936) and AUC-PR was 0.085. Upon recalibration, the AUROC was 0.925 (0.915-0.936), and the AUC-PR was 0.094. Calibration metrics for both scores were favourable because of the large cluster of cases with low probabilities of mortality. Decision curve analyses showed limited benefit to using either score.

CONCLUSIONS

The intrinsic surgical risk score performed better than the PRAm, but both resulted in large numbers of false positives. Both scores exhibited decreased performance compared with the original studies. ASA physical status scores in sicker patients drove the superior performance of the intrinsic surgical risk score, suggesting the use of a risk score does not improve prediction.

Disparities in Anti-emetic Prophylaxis Care Processes are Predicted by Patient Neighborhood: A Retrospective Cohort and Geospatial Analysis

Background

Social Determinants of Health (SDoH) continue to drive persistent disparities in perioperative care. Our team has previously demonstrated racial and socioeconomic disparities in perioperative processes, notably in the administration of antiemetic prophylaxis, in several large perioperative registries. Given how neighborhoods are socially segregated in the US, we examined geospatial clustering of perioperative antiemetic disparities.

Methods

We conducted a retrospective cohort study of anesthetic records from the University of Utah Hospital with 19,477 patients meeting inclusion criteria. We geocoded patient home addresses and combined them with the Census Block Group(CBG) level neighborhood disadvantage (ND), a composite index of from the National Neighborhood Data Archive (NaNDA). We stratified our patients by antiemetic risk score and calculated the number of anti-emetic interventions. We utilized Poisson Spatial Scan Statistics, implemented in SaTScan, to detect geographic clusters of under-treatment.

Results

We identified one significant cluster (p < .001) of undertreated perioperative antiemetic prophylaxis cases. The relative risk (RR) of the whole cluster is 1.44, implying that patients within the cluster are 1.44 times more likely to receive fewer antiemetics after controlling for antiemetic risk. Patients from more disadvantaged neighborhoods were more likely to receive below median antiemetic prophylaxis after controlling for risk.

Conclusions

To our knowledge, this is the first geospatial cluster analysis of perioperative process disparities; we leveraged innovative geostatistical methods and identified a spatially defined, geographic cluster of patients whose home address census-tract level neighborhood deprivation index predicted disparities in risk adjusted antiemetic prophylaxis.

Association between inspired oxygen fraction and development of postoperative pulmonary complications in thoracic surgery: a multicentre retrospective cohort study

BACKGROUND

Limited data exist to guide oxygen administration during one-lung ventilation for thoracic surgery. We hypothesised that high intraoperative inspired oxygen fraction during lung resection surgery requiring one-lung ventilation is independently associated with postoperative pulmonary complications (PPCs).

METHODS

We performed this retrospective multicentre study using two integrated perioperative databases (Multicenter Perioperative Outcomes Group and Society of Thoracic Surgeons General Thoracic Surgery Database) to study adult thoracic surgical procedures using one-lung ventilation. The primary outcome was a composite of PPCs (atelectasis, acute respiratory distress syndrome, pneumonia, respiratory failure, reintubation, and prolonged ventilation >48 h). The exposure of interest was high inspired oxygen fraction (FiO2), defined by area under the curve of a FiO2 threshold > 80%. Univariate analysis and logistic regression modelling assessed the association between intraoperative FiO2 and PPCs.

RESULTS

Across four US medical centres, 141/2733 (5.2%) procedures conducted in 2716 patients (55% female; mean age 66 yr) resulted in PPCs. FiO2 was univariately associated with PPCs (adjusted OR [aOR]: 1.17, 95% confidence interval [CI]: 1.04-1.33, P=0.012). Logistic regression modelling showed that duration of one-lung ventilation (aOR: 1.20, 95% CI: 1.03-1.41, P=0.022), but not the time-weighted average FiO2 (aOR: 1.01, 95% CI: 1.00-1.02, P=0.165), was associated with PPCs.

CONCLUSIONS

Our results do not support limiting the inspired oxygen fraction for the purpose of reducing postoperative pulmonary complications in thoracic surgery involving one-lung ventilation.

Anesthesia Techniques for Vitreoretinal Surgery in the United States: A Report from the Multicenter Perioperative Outcomes Group Research Consortium

PURPOSE

To explore the patterns of anesthesia use and their determinants during vitreoretinal (VR) surgeries in academic and community hospitals across the US, using data from the Multicenter Perioperative Outcomes Group (MPOG).

DESIGN

A retrospective, multicenter, cohort study.

METHODS

We queried the MPOG database of 107,066 patients undergoing VR surgeries. Patients (≥18 years) undergoing VR surgery with monitored anesthesia care (MAC) or general anesthesia (GA) from January 1, 2015 to December 31, 2021 were included. Patient-level, case-based, and institutional-level covariates were collected. We performed multivariable mixed-effects models to determine predictors of anesthesia type use. The primary outcome was the type of anesthesia (MAC or GA) used during VR surgeries. As a secondary outcome, MAC cases were further classified based on the additional use of sedation into MAC with or without sedation.

RESULTS

We found that 67.45% of VR surgery cases received MAC, and 73.63% of institutions administered MAC to more than half of cases. Random effect modeling revealed that 47.76% of the variation in MAC use was attributed to institutions. A trend toward increased use of MAC with increasing age was observed. Patients diagnosed with chronic pulmonary disease, liver disease, or a history of drug abuse were less likely to receive MAC. Conversely, we found that patients with reported alcohol abuse disorder, diabetes with complications, and those with American Society of Anesthesiologists (ASA) physical status of 4 (vs. 1, 2, or 3) were more likely to use MAC. Compared to non-complex VR surgeries, there was a notably decreased likelihood of MAC use in complex PPV (P = .004), PPV + scleral buckle (SB) for retinal detachment (P < .0001), and primary SB surgery (P < .0001).

CONCLUSIONS

Approximately 2/3 of VR anesthesia is under MAC, but GA is still preferred for SBs, complex vitrectomy, and younger patients. We show that large interinstitutional variation for using MAC in practice exists.

Optimizing pediatric tonsillectomy outcomes with an opioid sparing anesthesia protocol: Learning and continuously improving with real-world data

INTRODUCTION

This quality improvement initiative is a continued pursuit to optimize outcomes by iteratively improving our opioid sparing anesthesia protocol for tonsillectomy with or without adenoidectomy at our pediatric ambulatory surgical center through data driven Plan-Do-Study-Act cycles.

METHODS

From 1/2015 through 12/2023, our standardized tonsillectomy protocol underwent nine procedure-specific perioperative Plan-Do-Study-Act cycles, three procedure-specific postoperative prescription Plan-Do-Study-Act cycles, and four general ambulatory surgical center enhanced recovery Plan-Do-Study-Act cycles. We analyzed data from the medical record using statistical process control charts. The primary outcome measure was the percent of patients requiring intravenous opioid in the post anesthesia care unit. Secondary outcomes included maximum post anesthesia care unit pain score, the percent of patients requiring treatment for nausea and/or vomiting in the post anesthesia care unit, and the number of postoperative opioid prescription dosages. Balancing measures were average post anesthesia care unit length of stay, percent of patients with prolonged Post Anesthesia Care Unit length of stay (>120 min), and 30-day reoperation rate.

RESULTS

A total of 5654 tonsillectomy with or without adenoidectomy cases were performed at our ambulatory surgical center from 2015 to 2023. The incidence of intravenous opioid administered in the post anesthesia care unit initially rose with opioid free anesthesia launch, but subsequently decreased below the target of 10%. Maximum post anesthesia care unit pain scores rose from mean 3.6 to 4.5, but subsequently returned to the baseline of 3.5, while the incidence of postoperative nausea and/or vomiting improved. The average post anesthesia care unit length of stay increased by 10 min with opioid free anesthesia; however, prolonged post anesthesia care unit stay and 30-day reoperation rates were unchanged.

CONCLUSIONS

The continued refinement of our opioid sparing anesthesia protocol has led to reduced perioperative and home opioid use, stable maximum post anesthesia care unit pain scores, and improved postoperative nausea and vomiting rates, with only a slight increase in mean post anesthesia care unit length of stay.

Determinants and Practice Variability of Oxygen Administration during Surgery in the United States: A Retrospective Cohort Study

BACKGROUND

The best approaches to supplemental oxygen administration during surgery remain unclear, which may contribute to variation in practice. This study aimed to assess determinants of oxygen administration and its variability during surgery.

METHODS

Using multivariable linear mixed-effects regression, the study measured the associations between intraoperative fraction of inspired oxygen and patient, procedure, medical center, anesthesiologist, and in-room anesthesia provider factors in surgical cases of 120 min or longer in adult patients who received general anesthesia with tracheal intubation and were admitted to the hospital after surgery between January 2016 and January 2019 at 42 medical centers across the United States participating in the Multicenter Perioperative Outcomes Group data registry.

RESULTS

The sample included 367,841 cases (median [25th, 75th] age, 59 [47, 69] yr; 51.1% women; 26.1% treated with nitrous oxide) managed by 3,836 anesthesiologists and 15,381 in-room anesthesia providers. Median (25th, 75th) fraction of inspired oxygen was 0.55 (0.48, 0.61), with 6.9% of cases less than 0.40 and 8.7% greater than 0.90. Numerous patient and procedure factors were statistically associated with increased inspired oxygen, notably advanced American Society of Anesthesiologists classification, heart disease, emergency surgery, and cardiac surgery, but most factors had little clinical significance (less than 1% inspired oxygen change). Overall, patient factors only explained 3.5% (95% CI, 3.5 to 3.5%) of the variability in oxygen administration, and procedure factors 4.4% (95% CI, 4.2 to 4.6%). Anesthesiologist explained 7.7% (95% CI, 7.2 to 8.2%) of the variability in oxygen administration, in-room anesthesia provider 8.1% (95% CI, 7.8 to 8.4%), medical center 23.3% (95% CI, 22.4 to 24.2%), and 53.0% (95% CI, 52.4 to 53.6%) was unexplained.

CONCLUSIONS

Among adults undergoing surgery with anesthesia and tracheal intubation, supplemental oxygen administration was variable and appeared arbitrary. Most patient and procedure factors had statistical but minor clinical associations with oxygen administration. Medical center and anesthesia provider explained significantly more variability in oxygen administration than patient or procedure factors.

EDITOR’S PERSPECTIVE

Enhancing nursing home quality through electronic health record implementation

Background: The quality of care in nursing homes (NHs) in the United States has long been a matter of policy concern. Although electronic health records (EHRs) are argued to improve quality, implementation has lagged due to various factors such as financial constraints and limited research on their impact on NH quality. Objective: This study examined the relationship between EHR implementation and NH quality using Donabedian's structure-process-outcome model. Method: Data on EHR implementation were collected via a 2018 survey of all Federally certified Arkansas NHs (n = 223). Of the 63 responding NHs, 48 reported EHR implementation. Survey data were merged with secondary sources such as Certification and Survey Provider Enhanced Reporting. A total of 744 NH-years for the period 2008-2020 were included in the final sample. A pre-post negative binomial panel data regression was used to examine the relationship between EHR implementation (dichotomous variable) and NH deficiencies (dependent count variable) with facility/community-level control variables. Results were reported as incidence rate ratios (IRR). Results: NHs that had implemented EHR experienced an 18% reduction in the rate of deficiencies compared to those without EHR systems (IRR = 0.82, 95% CI [0.70, 0.99], p = 0.035). Conclusion: EHR implementation had a favourable impact on NH quality. Implications: Past research suggests that higher NH quality may be associated with improved financial performance. Therefore, EHR implementation has the potential to address two critical challenges: enhancing care quality and improving financial outcomes. However, government financial incentives may be necessary to address the high-cost of implementing EHR systems.

Precision feedback: A conceptual model

Introduction

When performance data are provided as feedback to healthcare professionals, they may use it to significantly improve care quality. However, the question of how to provide effective feedback remains unanswered, as decades of evidence have produced a consistent pattern of effects-with wide variation. From a coaching perspective, feedback is often based on a learner's objectives and goals. Furthermore, when coaches provide feedback, it is ideally informed by their understanding of the learner's needs and motivation. We anticipate that a "coaching"-informed approach to feedback may improve its effectiveness in two ways. First, by aligning feedback with healthcare professionals' chosen goals and objectives, and second, by enabling large-scale feedback systems to use new types of data to learn what kind of performance information is motivating in general. Our objective is to propose a conceptual model of precision feedback to support these anticipated enhancements to feedback interventions.

Methods

We iteratively represented models of feedback's influence from theories of motivation and behavior change, visualization, and human-computer interaction. Through cycles of discussion and reflection, application to clinical examples, and software development, we implemented and refined the models in a software application to generate precision feedback messages from performance data for anesthesia providers.

Results

We propose that precision feedback is feedback that is prioritized according to its motivational potential for a specific recipient. We identified three factors that influence motivational potential: (1) the motivating information in a recipient's performance data, (2) the surprisingness of the motivating information, and (3) a recipient's preferences for motivating information and its visual display.

Conclusions

We propose a model of precision feedback that is aligned with leading theories of feedback interventions to support learning about the success of feedback interventions. We plan to evaluate this model in a randomized controlled trial of a precision feedback system that enhances feedback emails to anesthesia providers.

Exploring Anesthesia Provider Preferences for Precision Feedback: Preference Elicitation Study

Background

Health care professionals must learn continuously as a core part of their work. As the rate of knowledge production in biomedicine increases, better support for health care professionals' continuous learning is needed. In health systems, feedback is pervasive and is widely considered to be essential for learning that drives improvement. Clinical quality dashboards are one widely deployed approach to delivering feedback, but engagement with these systems is commonly low, reflecting a limited understanding of how to improve the effectiveness of feedback about health care. When coaches and facilitators deliver feedback for improving performance, they aim to be responsive to the recipient's motivations, information needs, and preferences. However, such functionality is largely missing from dashboards and feedback reports. Precision feedback is the delivery of high-value, motivating performance information that is prioritized based on its motivational potential for a specific recipient, including their needs and preferences. Anesthesia care offers a clinical domain with high-quality performance data and an abundance of evidence-based quality metrics.

Objective

The objective of this study is to explore anesthesia provider preferences for precision feedback.

Methods

We developed a test set of precision feedback messages with balanced characteristics across 4 performance scenarios. We created an experimental design to expose participants to contrasting message versions. We recruited anesthesia providers and elicited their preferences through analysis of the content of preferred messages. Participants additionally rated their perceived benefit of preferred messages to clinical practice on a 5-point Likert scale.

Results

We elicited preferences and feedback message benefit ratings from 35 participants. Preferences were diverse across participants but largely consistent within participants. Participants' preferences were consistent for message temporality (α=.85) and display format (α=.80). Ratings of participants' perceived benefit to clinical practice of preferred messages were high (mean rating 4.27, SD 0.77).

Conclusions

Health care professionals exhibited diverse yet internally consistent preferences for precision feedback across a set of performance scenarios, while also giving messages high ratings of perceived benefit. A "one-size-fits-most approach" to performance feedback delivery would not appear to satisfy these preferences. Precision feedback systems may hold potential to improve support for health care professionals' continuous learning by accommodating feedback preferences.

Overview and Clinical Applications of Artificial Intelligence and Machine Learning in Cardiac Anesthesiology

Artificial intelligence- (AI) and machine learning (ML)-based applications are becoming increasingly pervasive in the healthcare setting. This has in turn challenged clinicians, hospital administrators, and health policymakers to understand such technologies and develop frameworks for safe and sustained clinical implementation. Within cardiac anesthesiology, challenges and opportunities for AI/ML to support patient care are presented by the vast amounts of electronic health data, which are collected rapidly, interpreted, and acted upon within the periprocedural area. To address such challenges and opportunities, in this article, the authors review 3 recent applications relevant to cardiac anesthesiology, including depth of anesthesia monitoring, operating room resource optimization, and transthoracic/transesophageal echocardiography, as conceptual examples to explore strengths and limitations of AI/ML within healthcare, and characterize this evolving landscape. Through reviewing such applications, the authors introduce basic AI/ML concepts and methodologies, as well as practical considerations and ethical concerns for initiating and maintaining safe clinical implementation of AI/ML-based algorithms for cardiac anesthesia patient care.

Reduce intraoperative albumin utilisation in cardiac surgical patients: a quality improvement initiative

BACKGROUND

Albumin continues to be used routinely by cardiac anaesthesiologists perioperatively despite lack of evidence for improved outcomes. The Multicenter Perioperative Outcomes Group (MPOG) data ranked our institution as one of the highest intraoperative albumin users during cardiac surgery. Therefore, we designed a quality improvement project (QIP) to introduce a bundle of interventions to reduce intraoperative albumin use in cardiac surgical patients.

METHODS

Our institutional MPOG data were used to analyse the FLUID-01-C measure that provides the number of adult cardiac surgery cases where albumin was administered intraoperatively by anaesthesiologists from 1 July 2019 to 30 June 2022. The QIP involved introduction of the following interventions: (1) education about appropriate albumin use and indications (January 2021), (2) email communications reinforced with OR teaching (March 2021), (3) removal of albumin from the standard pharmacy intraoperative medication trays (April 2021), (4) grand rounds presentation discussing the QIP and highlighting the interventions (May 2021) and (5) quarterly provider feedback (starting July 2021). Multivariable segmented regression models were used to assess the changes from preintervention to postintervention time period in albumin utilisation, and its total monthly cost.

RESULTS

Among the 5767 cardiac surgery cases that met inclusion criteria over the 3-year study period, 16% of patients received albumin intraoperatively. The total number of cases that passed the metric (albumin administration was avoided), gradually increased as our interventions went into effect. Intraoperative albumin utilisation (beta=-101.1, 95% CI -145 to -56.7) and total monthly cost of albumin (beta=-7678, 95% CI -10712 to -4640) demonstrated significant decrease after starting the interventions.

CONCLUSIONS

At a single academic cardiac surgery programme, implementation of a bundle of simple and low-cost interventions as part of a coordinated QIP were effective in significantly decreasing intraoperative use of albumin, which translated into considerable costs savings.

The impact of an anesthesia residency teaching service on anesthesia-controlled time and postsurgical patient outcomes: a retrospective observational study on 15,084 surgical cases

BACKGROUND

Limited data exists regarding the impact of anesthesia residents on operating room efficiency and patient safety outcomes. This investigation hypothesized that supervised anesthesiology residents do not increase anesthesia-controlled or prolonged extubation times compared to supervised certified registered nurse anesthetists (CRNA)/certified anesthesiologist assistants (CAA) or anesthesiologists working independently. Secondary objectives included differences in critical outcomes such as intraoperative hypotension, cardiac and pulmonary complications, acute kidney injury, and mortality.

METHODS

This retrospective single-center 24-month (January 1, 2020- December 31, 2021) cohort focused on primary outcomes of anesthesia-controlled times and prolonged extubation (>15 min) with additional assessment of secondary patient outcomes in adult patients having general anesthesia with an endotracheal tube or laryngeal mask airway for elective non-cardiac surgery. The study excluded sedation, obstetric, endoscopic, ophthalmology, and non-operating room procedures. Procedures were divided into three groups: anesthesiologists working solo, anesthesiologists supervising residents, or anesthesiologists supervising CRNA/CAAs. After univariate analysis, multivariable models were constructed to control for the univariate cofactor differences in the primary and secondary outcomes.

RESULTS

A total of 15,084 surgical cases met the inclusion criteria for this study for the three different care models: solo anesthesiologists (1,204 cases), anesthesiologist/resident pairing (3,146 cases), and anesthesiologist/CRNA/CAA (14,040 cases). Before multivariate analysis, the resident group exhibited longer anesthesia-controlled times (median, [interquartile range], 26.1 [21.7-32.0], p < 0.001), compared to CRNA/CAA (23.9 [19.7-29.5]), and attending-only surgical cases (21.0 [17.9-25.4]). After adjusting for covariates in a general linear regression model (age, BMI, ASA classification, comorbidities, arterial line insertion, surgical service, and surgical location), there were no significant differences in the anesthesia-controlled times between the provider groups. Prolonged extubation times (>15 min) were significantly less common in the anesthesiologist-only group compared to the other groups (p < 0.001). Despite these time differences, there were no clinically significant differences among the groups in postoperative pulmonary or cardiac complications, renal impairment, or the 30-day mortality rate of patients.

CONCLUSION

Anesthesia residents do not increase anesthesia-controlled operating room times or adversely affect clinically relevant patient outcomes compared to anesthesiologists working independently or supervising certified registered nurse anesthetists or certified anesthesiologist assistants.

Predicting outcomes following lower extremity open revascularization using machine learning

Lower extremity open revascularization is a treatment option for peripheral artery disease that carries significant peri-operative risks; however, outcome prediction tools remain limited. Using machine learning (ML), we developed automated algorithms that predict 30-day outcomes following lower extremity open revascularization. The National Surgical Quality Improvement Program targeted vascular database was used to identify patients who underwent lower extremity open revascularization for chronic atherosclerotic disease between 2011 and 2021. Input features included 37 pre-operative demographic/clinical variables. The primary outcome was 30-day major adverse limb event (MALE; composite of untreated loss of patency, major reintervention, or major amputation) or death. Our data were split into training (70%) and test (30%) sets. Using tenfold cross-validation, we trained 6 ML models. Overall, 24,309 patients were included. The primary outcome of 30-day MALE or death occurred in 2349 (9.3%) patients. Our best performing prediction model was XGBoost, achieving an area under the receiver operating characteristic curve (95% CI) of 0.93 (0.92-0.94). The calibration plot showed good agreement between predicted and observed event probabilities with a Brier score of 0.08. Our ML algorithm has potential for important utility in guiding risk mitigation strategies for patients being considered for lower extremity open revascularization to improve outcomes.

The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry

BACKGROUND

To enhance perioperative outcomes, a perioperative registry that integrates high-quality real-world data throughout the perioperative period is essential. Singapore General Hospital established the Perioperative and Anesthesia Subject Area Registry (PASAR) to unify data from the preoperative, intraoperative, and postoperative stages. This study presents the methodology employed to create this database.

METHODS

Since 2016, data from surgical patients have been collected from the hospital electronic medical record systems, de-identified, and stored securely in compliance with privacy and data protection laws. As a representative sample, data from initiation in 2016 to December 2022 were collected.

RESULTS

As of December 2022, PASAR data comprise 26 tables, encompassing 153,312 patient admissions and 168,977 operation sessions. For this period, the median age of the patients was 60.0 years, sex distribution was balanced, and the majority were Chinese. Hypertension and cardiovascular comorbidities were also prevalent. Information including operation type and time, intensive care unit (ICU) length of stay, and 30-day and 1-year mortality rates were collected. Emergency surgeries resulted in longer ICU stays, but shorter operation times than elective surgeries.

CONCLUSIONS

The PASAR provides a comprehensive and automated approach to gathering high-quality perioperative patient data.

Improving Anesthesia Start Time Documentation Through a Departmental Education Initiative at Yale New Haven Hospital, New Haven, United States

Background Reimbursement for anesthetic services in the United States utilizes a formula that incorporates procedural and patient factors with total anesthesia time. According to the Centers for Medicare & Medicaid Services and the American Society of Anesthesiologists, the period of billable time starts when the anesthesia practitioner assumes care of the patient and may include transport to the operating room from the preoperative holding area. In this report on a quality improvement effort, we implemented a departmental education initiative aimed at improving the accuracy of anesthesia start-time documentation. Methods Utilizing de-identified, internal data on surgical procedures at Yale New Haven Hospital (YNHH), New Haven, United States, the difference between documented anesthesia start and patient in-room time was determined for all cases. Those with a difference between 0-1 minute were assumed "likely underbilled," and the total revenue lost for these cases was estimated using a weighted average of institutional reimbursement per unit of time. A monthly, department-wide educational email was then introduced to inform practitioners about the guidelines around start-time documentation, and the percentage of "likely underbilled" cases and lost revenue estimates trended over a one-year period. Results Baseline data in December 2020 showed that of the 6,877 total surgical cases requiring anesthesia at YNHH, 55.1% (N=3,790) had an anesthesia start to in-room time of 0-1 minute, which were considered "likely underbilled." The average start-to-in-room time for properly recorded cases (44.9%, N=3,087) was 4.42 minutes. The baseline revenue lost in December 2020 for underbilled cases was estimated at $52,302. Over the one-year quality improvement initiative, the proportion of underbilled cases showed a downward trend, decreasing to 29.2% of total cases by November 2021. The estimate of revenue lost due to underbilling also showed a downward trend, decreasing to $29,300 in November 2021. Conclusion This quality improvement study demonstrated that a relatively simple, department-wide educational email sent monthly correlated with an improvement in anesthesia start-time documentation accuracy and a reduction in estimated revenue lost to underbilling over a one-year period.

Public Health Informatics and the Perioperative Physician: Looking to the Future

The role of informatics in public health has increased over the past few decades, and the coronavirus disease 2019 (COVID-19) pandemic has underscored the critical importance of aggregated, multicenter, high-quality, near-real-time data to inform decision-making by physicians, hospital systems, and governments. Given the impact of the pandemic on perioperative and critical care services (eg, elective procedure delays; information sharing related to interventions in critically ill patients; regional bed-management under crisis conditions), anesthesiologists must recognize and advocate for improved informatic frameworks in their local environments. Most anesthesiologists receive little formal training in public health informatics (PHI) during clinical residency or through continuing medical education. The COVID-19 pandemic demonstrated that this knowledge gap represents a missed opportunity for our specialty to participate in informatics-related, public health-oriented clinical care and policy decision-making. This article briefly outlines the background of PHI, its relevance to perioperative care, and conceives intersections with PHI that could evolve over the next quarter century.

Perioperative Mortality of the COVID-19 Recovered Patient Compared to a Matched Control: A Multicenter Retrospective Cohort Study

BACKGROUND

Surgical procedures performed on patients with recent exposure to COVID-19 infection have been associated with increased mortality risk in previous studies. Accordingly, elective surgery is often delayed after infection. The study aimed to compare 30-day hospital mortality and postoperative complications (acute kidney injury, pulmonary complications) of surgical patients with a previous COVID-19 infection to a matched cohort of patients without known previous COVID-19. The authors hypothesized that COVID-19 exposure would be associated with an increased mortality risk.

METHODS

In this retrospective observational cohort study, patients presenting for elective inpatient surgery across a multicenter cohort of academic and community hospitals from April 2020 to April 2021 who had previously tested positive for COVID-19 were compared to controls who had received at least one previous COVID-19 test but without a known previous COVID-19-positive test. The cases were matched based on anthropometric data, institution, and comorbidities. Further, the outcomes were analyzed stratified by timing of a positive test result in relation to surgery.

RESULTS

Thirty-day mortality occurred in 229 of 4,951 (4.6%) COVID-19-exposed patients and 122 of 4,951 (2.5%) controls. Acute kidney injury was observed in 172 of 1,814 (9.5%) exposed patients and 156 of 1,814 (8.6%) controls. Pulmonary complications were observed in 237 of 1,637 (14%) exposed patients and 164 of 1,637 (10%) controls. COVID-19 exposure was associated with an increased 30-day mortality risk (adjusted odds ratio, 1.63; 95% CI, 1.38 to 1.91) and an increased risk of pulmonary complications (1.60; 1.36 to 1.88), but was not associated with an increased risk of acute kidney injury (1.03; 0.87 to 1.22). Surgery within 2 weeks of infection was associated with a significantly increased risk of mortality and pulmonary complications, but that effect was nonsignificant after 2 weeks.

CONCLUSIONS

Patients with a positive test for COVID-19 before elective surgery early in the pandemic have an elevated risk of perioperative mortality and pulmonary complications but not acute kidney injury as compared to matched controls. The span of time from positive test to time of surgery affected the mortality and pulmonary risk, which subsided after 2 weeks.

EDITOR’S PERSPECTIVE

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.

Differences between patients in whom physicians agree versus disagree about the preoperative diagnosis of heart failure

STUDY OBJECTIVE

To quantify preoperative heart failure (HF) diagnostic agreement and identify characteristics of patients in whom physicians agreed versus disagreed about the diagnosis.

DESIGN

Observational cohort study.

SETTING

Patients undergoing major non-cardiac surgery at an academic center between 2015 and 2019.

PATIENTS

40,659 patients undergoing major non-cardiac surgery, among which a stratified subsample of 1018 patients with and without documented HF was reviewed.

INTERVENTIONS

Via a panel of physicians frequently managing patients with HF (cardiologists, cardiac anesthesiologists, intensivists), detailed chart reviews were performed (two per patient; median review time 32 min per reviewer per patient) to render adjudicated HF diagnoses.

MEASUREMENTS

Adjudicated diagnostic agreement measures (percent agreement, Krippendorf's alpha) and univariate comparisons (standardized differences) between patients in whom physicians agreed versus disagreed about the preoperative HF diagnosis.

MAIN RESULTS

Among patients with documented HF, physicians agreed about the diagnosis in 80.0% of cases (consensus positive), disagreed in 13.8% (disagreement), and refuted the diagnosis in 6.3% (consensus negative). Conversely, among patients without documented HF, physicians agreed about the diagnosis in 88.0% (consensus negative), disagreed in 8.4% (disagreement), and refuted the diagnosis in 3.6% (consensus positive). The estimated agreement for the 40,659 cases was 91.1% (95% CI 88.3%-93.9%); Krippendorff's alpha was 0.77 (0.75-0.80). Compared to patients in whom physicians agreed about a HF diagnosis, patients in whom physicians disagreed exhibited fewer guideline-defined HF diagnostic criteria.

CONCLUSIONS

Physicians usually agree about HF diagnoses adjudicated via chart review, although disagreement is not uncommon and may be partly explained by heterogeneous clinical presentations. Our findings inform preoperative screening processes by identifying patients whose characteristics contribute to physician disagreement via chart review. Clinical Trial Number / Registry URL: Not applicable.

Intraoperative Use of Albumin in Major Noncardiac Surgery: Incidence, Variability, and Association With Outcomes

BACKGROUND

The impact of albumin use during major surgery is unknown, and a dearth of evidence governing its use in major noncardiac surgery has long precluded its standardization in clinical guidelines.

OBJECTIVE

In this study, we investigate institutional variation in albumin use among medical centers in the United States during major noncardiac surgery and explore the association of intraoperative albumin administration with important postoperative outcomes.

METHODS

The study is an observational retrospective cohort analysis performed among 54 U.S. hospitals in the Multicenter Perioperative Outcomes Group and includes adult patients who underwent major noncardiac surgery under general anesthesia between January 2014 and June 2020. The primary endpoint was the incidence of albumin administration. Secondary endpoints are acute kidney injury (AKI), net-positive fluid balance, pulmonary complications, and 30-day mortality. Albumin-exposed and albumin-unexposed cases were compared within a propensity score-matched cohort to evaluate associations of albumin use with outcomes.

RESULTS

Among 614,215 major surgeries, predominantly iso-oncotic albumin was administered in 15.3% of cases and featured significant inter-institutional variability in use patterns. Cases receiving intraoperative albumin involved patients of higher American Society of Anesthesiologists physical status and featured larger infused crystalloid volumes, greater blood loss, and vasopressor use. Overall, albumin was most often administered at high-volume surgery centers with academic affiliation, and within a propensity score-matched cohort (n=153,218), the use of albumin was associated with AKI (aOR 1.24, 95% CI 1.20-1.28, P <0.001), severe AKI (aOR 1.45, 95% CI 1.34-1.56, P <0.001), net-positive fluid balance (aOR 1.18, 95% CI 1.16-1.20, P <0.001), pulmonary complications (aOR 1.56, 95% CI 1.30-1.86, P <0.001), and 30-day all-cause mortality (aOR 1.37, 95% CI 1.26-1.49, P <0.001).

CONCLUSIONS

Intravenous albumin is commonly administered among noncardiac surgeries with significant inter-institutional variability in use in the United States. Albumin administration was associated with an increased risk of postoperative complications.

Electronic health record data quality assessment and tools: a systematic review

OBJECTIVE

We extended a 2013 literature review on electronic health record (EHR) data quality assessment approaches and tools to determine recent improvements or changes in EHR data quality assessment methodologies.

MATERIALS AND METHODS

We completed a systematic review of PubMed articles from 2013 to April 2023 that discussed the quality assessment of EHR data. We screened and reviewed papers for the dimensions and methods defined in the original 2013 manuscript. We categorized papers as data quality outcomes of interest, tools, or opinion pieces. We abstracted and defined additional themes and methods though an iterative review process.

RESULTS

We included 103 papers in the review, of which 73 were data quality outcomes of interest papers, 22 were tools, and 8 were opinion pieces. The most common dimension of data quality assessed was completeness, followed by correctness, concordance, plausibility, and currency. We abstracted conformance and bias as 2 additional dimensions of data quality and structural agreement as an additional methodology.

DISCUSSION

There has been an increase in EHR data quality assessment publications since the original 2013 review. Consistent dimensions of EHR data quality continue to be assessed across applications. Despite consistent patterns of assessment, there still does not exist a standard approach for assessing EHR data quality.

CONCLUSION

Guidelines are needed for EHR data quality assessment to improve the efficiency, transparency, comparability, and interoperability of data quality assessment. These guidelines must be both scalable and flexible. Automation could be helpful in generalizing this process.

Machine Learning for the Prediction of Procedural Case Durations Developed Using a Large Multicenter Database: Algorithm Development and Validation Study

BACKGROUND

Accurate projections of procedural case durations are complex but critical to the planning of perioperative staffing, operating room resources, and patient communication. Nonlinear prediction models using machine learning methods may provide opportunities for hospitals to improve upon current estimates of procedure duration.

OBJECTIVE

The aim of this study was to determine whether a machine learning algorithm scalable across multiple centers could make estimations of case duration within a tolerance limit because there are substantial resources required for operating room functioning that relate to case duration.

METHODS

Deep learning, gradient boosting, and ensemble machine learning models were generated using perioperative data available at 3 distinct time points: the time of scheduling, the time of patient arrival to the operating or procedure room (primary model), and the time of surgical incision or procedure start. The primary outcome was procedure duration, defined by the time between the arrival and the departure of the patient from the procedure room. Model performance was assessed by mean absolute error (MAE), the proportion of predictions falling within 20% of the actual duration, and other standard metrics. Performance was compared with a baseline method of historical means within a linear regression model. Model features driving predictions were assessed using Shapley additive explanations values and permutation feature importance.

RESULTS

A total of 1,177,893 procedures from 13 academic and private hospitals between 2016 and 2019 were used. Across all procedures, the median procedure duration was 94 (IQR 50-167) minutes. In estimating the procedure duration, the gradient boosting machine was the best-performing model, demonstrating an MAE of 34 (SD 47) minutes, with 46% of the predictions falling within 20% of the actual duration in the test data set. This represented a statistically and clinically significant improvement in predictions compared with a baseline linear regression model (MAE 43 min; P<.001; 39% of the predictions falling within 20% of the actual duration). The most important features in model training were historical procedure duration by surgeon, the word "free" within the procedure text, and the time of day.

CONCLUSIONS

Nonlinear models using machine learning techniques may be used to generate high-performing, automatable, explainable, and scalable prediction models for procedure duration.

Patient-, Clinician-, and Institution-level Variation in Inotrope Use for Cardiac Surgery: A Multicenter Observational Analysis

BACKGROUND

Conflicting evidence exists regarding the risks and benefits of inotropic therapies during cardiac surgery, and the extent of variation in clinical practice remains understudied. Therefore, the authors sought to quantify patient-, anesthesiologist-, and hospital-related contributions to variation in inotrope use.

METHODS

In this observational study, nonemergent adult cardiac surgeries using cardiopulmonary bypass were reviewed across a multicenter cohort of academic and community hospitals from 2014 to 2019. Patients who were moribund, receiving mechanical circulatory support, or receiving preoperative or home inotropes were excluded. The primary outcome was an inotrope infusion (epinephrine, dobutamine, milrinone, dopamine) administered for greater than 60 consecutive min intraoperatively or ongoing upon transport from the operating room. Institution-, clinician-, and patient-level variance components were studied.

RESULTS

Among 51,085 cases across 611 attending anesthesiologists and 29 hospitals, 27,033 (52.9%) cases received at least one intraoperative inotrope, including 21,796 (42.7%) epinephrine, 6,360 (12.4%) milrinone, 2,000 (3.9%) dobutamine, and 602 (1.2%) dopamine (non-mutually exclusive). Variation in inotrope use was 22.6% attributable to the institution, 6.8% attributable to the primary attending anesthesiologist, and 70.6% attributable to the patient. The adjusted median odds ratio for the same patient receiving inotropes was 1.73 between 2 randomly selected clinicians and 3.55 between 2 randomly selected institutions. Factors most strongly associated with increased likelihood of inotrope use were institutional medical school affiliation (adjusted odds ratio, 6.2; 95% CI, 1.39 to 27.8), heart failure (adjusted odds ratio, 2.60; 95% CI, 2.46 to 2.76), pulmonary circulation disorder (adjusted odds ratio, 1.72; 95% CI, 1.58 to 1.87), loop diuretic home medication (adjusted odds ratio, 1.55; 95% CI, 1.42 to 1.69), Black race (adjusted odds ratio, 1.49; 95% CI, 1.32 to 1.68), and digoxin home medication (adjusted odds ratio, 1.48; 95% CI, 1.18 to 1.86).

CONCLUSIONS

Variation in inotrope use during cardiac surgery is attributable to the institution and to the clinician, in addition to the patient. Variation across institutions and clinicians suggests a need for future quantitative and qualitative research to understand variation in inotrope use affecting outcomes and develop evidence-based, patient-centered inotrope therapies.

EDITOR’S PERSPECTIVE

Antiemetic Administration and Its Association with Race: A Retrospective Cohort Study

BACKGROUND

Anesthesiologists' contribution to perioperative healthcare disparities remains unclear because patient and surgeon preferences can influence care choices. Postoperative nausea and vomiting is a patient- centered outcome measure and a main driver of unplanned admissions. Antiemetic administration is under the sole domain of anesthesiologists. In a U.S. sample, Medicaid insured versus commercially insured patients and those with lower versus higher median income had reduced antiemetic administration, but not all risk factors were controlled for. This study examined whether a patient's race is associated with perioperative antiemetic administration and hypothesized that Black versus White race is associated with reduced receipt of antiemetics.

METHODS

An analysis was performed of 2004 to 2018 Multicenter Perioperative Outcomes Group data. The primary outcome of interest was administration of either ondansetron or dexamethasone; secondary outcomes were administration of each drug individually or both drugs together. The confounder-adjusted analysis included relevant patient demographics (Apfel postoperative nausea and vomiting risk factors: sex, smoking history, postoperative nausea and vomiting or motion sickness history, and postoperative opioid use; as well as age) and included institutions as random effects.

RESULTS

The Multicenter Perioperative Outcomes Group data contained 5.1 million anesthetic cases from 39 institutions located in the United States and The Netherlands. Multivariable regression demonstrates that Black patients were less likely to receive antiemetic administration with either ondansetron or dexamethasone than White patients (290,208 of 496,456 [58.5%] vs. 2.24 million of 3.49 million [64.1%]; adjusted odds ratio, 0.82; 95% CI, 0.81 to 0.82; P < 0.001). Black as compared to White patients were less likely to receive any dexamethasone (140,642 of 496,456 [28.3%] vs. 1.29 million of 3.49 million [37.0%]; adjusted odds ratio, 0.78; 95% CI, 0.77 to 0.78; P < 0.001), any ondansetron (262,086 of 496,456 [52.8%] vs. 1.96 million of 3.49 million [56.1%]; adjusted odds ratio, 0.84; 95% CI, 0.84 to 0.85; P < 0.001), and dexamethasone and ondansetron together (112,520 of 496,456 [22.7%] vs. 1.0 million of 3.49 million [28.9%]; adjusted odds ratio, 0.78; 95% CI, 0.77 to 0.79; P < 0.001).

CONCLUSIONS

In a perioperative registry data set, Black versus White patient race was associated with less antiemetic administration, after controlling for all accepted postoperative nausea and vomiting risk factors.

EDITOR’S PERSPECTIVE

Platform trials for anaesthesia and perioperative medicine: a narrative review

Large randomised trials provide the most reliable evidence of effectiveness of new treatments in clinical practice. However, the time and resources required to complete such trials can be daunting. An overarching clinical trial platform focused on a single condition or type of surgery, aiming to compare several treatments, with an option to stop any or add in new treatment options, can provide greater efficiency. This has the potential to accelerate knowledge acquisition and identify effective, ineffective, or harmful treatments faster. The master protocol of the platform defines the study population(s) and standardised procedures. Ineffective or harmful treatments can be discarded or study drug dose modified during the life cycle of the trial. Other adaptive elements that can be modified include eligibility criteria, required sample size for any comparison(s), randomisation assignment ratio, and the addition of other promising treatment options. There are excellent opportunities for anaesthetists to establish platform trials in perioperative medicine. Platform trials are highly efficient, with the potential to provide quicker answers to important clinical questions that lead to improved patient care.

Rescuing the right ventricle: A conceptual framework to target new interventions for patients receiving a durable left ventricular assist device

Despite significant advances in durable LVAD technology, right heart failure remains a morbid and fatal condition that is difficult to predict, prevent, and successfully treat.

Leveraging observational data to identify targeted patient populations for future randomized trials

Randomized controlled trials reported in the literature are often affected by poor generalizability, and pragmatic trials have become an increasingly utilized workaround approach to overcome logistical limitations and explore routine interventions demonstrating equipoise in clinical practice. Intravenous albumin, for example, is commonly administered in the perioperative setting despite lacking supportive evidence. Given concerns for cost, safety, and efficacy, randomized trials are needed to explore the clinical equipoise of albumin therapy in this setting, and we therefore present an approach to identifying populations exposed to perioperative albumin to encourage clinical equipoise in patient selection and optimize study design for clinical trials.

Feasibility pilot trial for the Trajectories of Recovery after Intravenous propofol versus inhaled VolatilE anesthesia (THRIVE) pragmatic randomised controlled trial

INTRODUCTION

Millions of patients receive general anaesthesia for surgery annually. Crucial gaps in evidence exist regarding which technique, propofol total intravenous anaesthesia (TIVA) or inhaled volatile anaesthesia (INVA), yields superior patient experience, safety and outcomes. The aim of this pilot study is to assess the feasibility of conducting a large comparative effectiveness trial assessing patient experiences and outcomes after receiving propofol TIVA or INVA.

METHODS AND ANALYSIS

This protocol was cocreated by a diverse team, including patient partners with personal experience of TIVA or INVA. The design is a 300-patient, two-centre, randomised, feasibility pilot trial. Patients 18 years of age or older, undergoing elective non-cardiac surgery requiring general anaesthesia with a tracheal tube or laryngeal mask airway will be eligible. Patients will be randomised 1:1 to propofol TIVA or INVA, stratified by centre and procedural complexity. The feasibility endpoints include: (1) proportion of patients approached who agree to participate; (2) proportion of patients who receive their assigned randomised treatment; (3) completeness of outcomes data collection and (4) feasibility of data management procedures. Proportions and 95% CIs will be calculated to assess whether prespecified thresholds are met for the feasibility parameters. If the lower bounds of the 95% CI are above the thresholds of 10% for the proportion of patients agreeing to participate among those approached and 80% for compliance with treatment allocation for each randomised treatment group, this will suggest that our planned pragmatic 12 500-patient comparative effectiveness trial can likely be conducted successfully. Other feasibility outcomes and adverse events will be described.

ETHICS AND DISSEMINATION

This study is approved by the ethics board at Washington University (IRB# 202205053), serving as the single Institutional Review Board for both participating sites. Recruitment began in September 2022. Dissemination plans include presentations at scientific conferences, scientific publications, internet-based educational materials and mass media.

TRIAL REGISTRATION NUMBER

NCT05346588.

Digitization of Symbol-Denoted Blood Pressure Data From Intraoperative Paper Health Records in a Low-Middle-Income Country Using Deep Image Segmentation and Associated Postoperative Outcomes: A Feasibility Study

BACKGROUND

In low-middle-income countries (LMICs), perioperative clinical information is almost universally collected on paper health records (PHRs). The lack of accessible digital databases limits LMICs in leveraging data to predict and improve patient outcomes after surgery. In this feasibility study, our aims were to: (1) determine the detection performance and prediction error of the U-Net deep image segmentation approach for digitization of hand-drawn blood pressure symbols from an image of the intraoperative PHRs and (2) evaluate the association between deep image segmentation-derived blood pressure parameters and postoperative mortality and length of stay.

METHODS

A smartphone mHealth platform developed by our team was used to capture images of completed intraoperative PHRs. A 2-stage deep image segmentation modeling approach was used to create 2 separate segmentation masks for systolic blood pressure (SBP) and diastolic blood pressure (DBP). Iterative postprocessing was utilized to convert the segmentation mask results into numerical SBP and DBP values. Detection performance and prediction errors were evaluated for the U-Net models by comparison with ground-truth values. Using multivariate regression analysis, we investigated the association of deep image segmentation-derived blood pressure values, total time spent in predefined blood pressure ranges, and postoperative outcomes including in-hospital mortality and length of stay.

RESULTS

A total of 350 intraoperative PHRs were imaged following surgery. Overall accuracy was 0.839 and 0.911 for SBP and DBP symbol detections, respectively. The mean error rate and standard deviation for the difference between the actual and predicted blood pressure values were 2.1 ± 4.9 and -0.8 ± 3.9 mm Hg for SBP and DBP, respectively. Using the U-Net model-derived blood pressures, minutes of time where DBP <50 mm Hg (odds ratio [OR], 1.03; CI, 1.01-1.05; P = .003) was associated with an increased in-hospital mortality. In addition, increased cumulative minutes of time with SBP between 80 and 90 mm Hg was significantly associated with a longer length of stay (incidence rate ratio, 1.02 [1.0-1.03]; P < .05), while increased cumulative minutes of time where SBP between 140 and 160 mm Hg was associated with a shorter length of stay (incidence rate ratio, 0.9 [0.96-0.99]; P < .05).

CONCLUSIONS

In this study, we report our experience with a deep image segmentation model for digitization of symbol-denoted blood pressure from intraoperative anesthesia PHRs. Our data support further development of this novel approach to digitize PHRs from LMICs, to provide accessible, curated, and reproducible data for both quality improvement- and outcome-based research.

Digital Health Data Quality Issues: Systematic Review

BACKGROUND

The promise of digital health is principally dependent on the ability to electronically capture data that can be analyzed to improve decision-making. However, the ability to effectively harness data has proven elusive, largely because of the quality of the data captured. Despite the importance of data quality (DQ), an agreed-upon DQ taxonomy evades literature. When consolidated frameworks are developed, the dimensions are often fragmented, without consideration of the interrelationships among the dimensions or their resultant impact.

OBJECTIVE

The aim of this study was to develop a consolidated digital health DQ dimension and outcome (DQ-DO) framework to provide insights into 3 research questions: What are the dimensions of digital health DQ? How are the dimensions of digital health DQ related? and What are the impacts of digital health DQ?

METHODS

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a developmental systematic literature review was conducted of peer-reviewed literature focusing on digital health DQ in predominately hospital settings. A total of 227 relevant articles were retrieved and inductively analyzed to identify digital health DQ dimensions and outcomes. The inductive analysis was performed through open coding, constant comparison, and card sorting with subject matter experts to identify digital health DQ dimensions and digital health DQ outcomes. Subsequently, a computer-assisted analysis was performed and verified by DQ experts to identify the interrelationships among the DQ dimensions and relationships between DQ dimensions and outcomes. The analysis resulted in the development of the DQ-DO framework.

RESULTS

The digital health DQ-DO framework consists of 6 dimensions of DQ, namely accessibility, accuracy, completeness, consistency, contextual validity, and currency; interrelationships among the dimensions of digital health DQ, with consistency being the most influential dimension impacting all other digital health DQ dimensions; 5 digital health DQ outcomes, namely clinical, clinician, research-related, business process, and organizational outcomes; and relationships between the digital health DQ dimensions and DQ outcomes, with the consistency and accessibility dimensions impacting all DQ outcomes.

CONCLUSIONS

The DQ-DO framework developed in this study demonstrates the complexity of digital health DQ and the necessity for reducing digital health DQ issues. The framework further provides health care executives with holistic insights into DQ issues and resultant outcomes, which can help them prioritize which DQ-related problems to tackle first.

Hyperoxemia During Cardiac Surgery Is Associated With Postoperative Pulmonary Complications

The use of hyperoxemia during cardiac surgery remains controversial. We hypothesized that intraoperative hyperoxemia during cardiac surgery is associated with an increased risk of postoperative pulmonary complications.

DESIGN

Retrospective cohort study.

SETTING

We analyzed intraoperative data from five hospitals within the Multicenter Perioperative Outcomes Group between January 1, 2014, and December 31, 2019. We assessed intraoperative oxygenation of adult patients undergoing cardiac surgery with cardiopulmonary bypass (CPB). Hyperoxemia pre and post CPB was quantified as the area under the curve (AUC) of Fio₂ above 0.21 in minutes when the corresponding peripheral oxygen saturation was greater than 92% measured by pulse oximetry. We quantified hyperoxemia during CPB as the AUC of Pao₂ greater than 200 mm Hg measured by arterial blood gas. We analyzed the association of hyperoxemia during all phases of cardiac surgery with the frequency of postoperative pulmonary complications within 30 days, including acute respiratory insufficiency or failure, acute respiratory distress syndrome, need for reintubation, and pneumonia.

PATIENTS

Twenty-one thousand six hundred thirty-two cardiac surgical patients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

During 21,632 distinct cardiac surgery cases, 96.4% of patients spent at least 1 minute in hyperoxemia (99.1% pre-CPB, 98.5% intra-CPB, and 96.4% post-CPB). Increasing exposure to hyperoxemia was associated with an increased risk of postoperative pulmonary complications throughout three distinct surgical periods. During CPB, increasing exposure to hyperoxemia was associated with an increased odds of developing postoperative pulmonary complications (p < 0.001) in a linear manner. Hyperoxemia before CPB (p < 0.001) and after CPB (p = 0.02) were associated with increased odds of developing postoperative pulmonary complications in a U-shaped relationship.

CONCLUSIONS

Hyperoxemia occurs almost universally during cardiac surgery. Exposure to hyperoxemia assessed continuously as an AUC during the intraoperative period, but particularly during CPB, was associated with an increased incidence of postoperative pulmonary complications.

Postoperative Acute Kidney Injury by Age and Sex: A Retrospective Cohort Association Study

BACKGROUND

Acute kidney injury (AKI) after noncardiac surgery is common and has substantial health impact. Preclinical and clinical studies examining the influence of sex on AKI have yielded conflicting results, although they typically do not account for age-related changes. The objective of the study was to determine the association of age and sex groups on postoperative AKI. The authors hypothesized that younger females would display lower risk of postoperative AKI than males of similar age, and the protection would be lost in older females.

METHODS

This was a multicenter retrospective cohort study across 46 institutions between 2013 and 2019. Participants included adult inpatients without pre-existing end-stage kidney disease undergoing index major noncardiac, nonkidney/urologic surgeries. The authors' primary exposure was age and sex groups defined as females 50 yr or younger, females older than 50 yr, males 50 yr or younger, and males older than 50 yr. The authors' primary outcome was development of AKI by Kidney Disease-Improving Global Outcomes serum creatinine criteria. Exploratory analyses included associations of ascending age groups and hormone replacement therapy home medications with postoperative AKI.

RESULTS

Among 390,382 patients, 25,809 (6.6%) developed postoperative AKI (females 50 yr or younger: 2,190 of 58,585 [3.7%]; females older than 50 yr: 9,320 of 14,4047 [6.5%]; males 50 yr or younger: 3,289 of 55,503 [5.9%]; males older than 50 yr: 11,010 of 132,447 [8.3%]). When adjusted for AKI risk factors, compared to females younger than 50 yr (odds ratio, 1), the odds of AKI were higher in females older than 50 yr (odds ratio, 1.51; 95% CI, 1.43 to 1.59), males younger than 50 yr (odds ratio, 1.90; 95% CI, 1.79 to 2.01), and males older than 50 yr (odds ratio, 2.06; 95% CI, 1.96 to 2.17).

CONCLUSIONS

Younger females display a lower odds of postoperative AKI that gradually increases with age. These results suggest that age-related changes in women should be further studied as modifiers of postoperative AKI risk after noncardiac surgery.

EDITOR’S PERSPECTIVE

Geospatial analysis of patients' social determinants of health for health systems science and disparity research

Social context matters for health, healthcare processes/quality and patient outcomes. The social status and circumstances we are born into, grow up in and live under, are called social determinants of health; they drive our health, and how we access and experience care; they are the fundamental causes of disease outcomes. Such circumstances are influenced heavily by our location through neighborhood context, which relates to support networks. Geography can influence proximity to resources and is an important dimension of social determinants of health, which also encompass race/ethnicity, language, health literacy, gender identity, social capital, wealth and income. Beginning with an explanation of social determinants, we explore the use of Geospatial Analysis methods and geocoding, including the importance of collaborating with geography experts, the pitfalls of geocoding, and how geographic analysis can help us to understand patient populations within the context of Social Determinants of Health. We then explain mechanisms and methods of geospatial analysis with two examples: (1) Bayesian hierarchical regression with crossed random effects and (2) discontinuity regression i.e., change point analysis. We leveraged the local University of Utah and Yale cohorts of the Multicenter Perioperative Outcomes Group (MPOG.org ), a perioperative electronic health registry; we enriched the Utah cohort with US-census tract level social determinants of health after geocoding patient addresses and extracting social determinants of health from the National Neighborhood Database (NaNDA). We explain how to investigate the impact of US-census tract level community deprivation indices and racial/ethnic composition on (1) individual clinicians’ administration of risk-adjusted perioperative antiemetic prophylaxis, (2) patients’ decisions to defer cataract surgery at the cusp of Medicare eligibility and finally (3) methods to further characterize patient populations at risk through publicly available datasets in the context of public transit access. Our examples are not rigorous analyses, and our preliminary inferences should not be taken at face value, but rather seen as illustration of geospatial analysis processes and methods. Our worked examples show the potential utility of geospatial analysis, and in particular the power of geocoding patient addresses to extract US-census level social determinants of health from publicly available databases to enrich electronic health registries for healthcare disparity research and targeted health system level countermeasures.

Improving Compliance With Institutional Performance on Train of Four Monitoring

BACKGROUND

We performed a multistep quality improvement project related to neuromuscular blockade and monitoring to evaluate the effectiveness of a comprehensive quality improvement program based upon the Multi-institutional Perioperative Outcomes Group (MPOG) Anesthesiology Performance Improvement and Reporting Exchange (ASPIRE) metrics targeted specifically at improving train of four (TOF) monitoring rates.

METHODS

We adapted the plan-do-study-act (PDSA) framework and implemented 2 PDSA cycles between January 2021 and December 2021. PDSA Cycle 1 (Phase I) and PDSA Cycle 2 (Phase II) included a multipart program consisting of (1) a departmental survey assessing attitudes toward intended results, outcomes, and barriers for TOF monitoring, (2) personalized MPOG ASPIRE quality performance reports displaying provider performance, (3) a dashboard access to help providers complete a case-by-case review, and (4) a web-based app spaced education module concerning TOF monitoring and residual neuromuscular blockade. Our primary outcome was to identify the facilitators and barriers to implementation of our intervention aimed at increasing TOF monitoring.

RESULTS

In Phase I, 25 anesthesia providers participated in the preintervention and postintervention needs assessment survey and received personalized quality metric reports. In Phase II, 222 providers participated in the preintervention needs assessment survey and 201 participated in the postintervention survey. Thematic analysis of Phase I survey data aimed at identifying the facilitators and barriers to implementation of a program aimed at increasing TOF monitoring revealed the following: intended results were centered on quality of patient care, barriers to implementation largely encompassed issues with technology/equipment and the increased burden placed on providers, and important outcomes were focused on patient outcomes and improving provider knowledge. Results of Phase II survey data was similar to that of Phase I. Notably in Phase II a few additional barriers to implementation were mentioned including a fear of loss of individualization due to standardization of patient care plan, differences between the attending overseeing the case and the in-room provider who is making decisions/completing documentation, and the frequency of intraoperative handovers. Compared to preintervention, postintervention compliance with TOF monitoring increased from 42% to 70% (28% absolute difference across N = 10 169 cases; P < .001).

CONCLUSIONS

Implementation of a structured quality improvement program using a novel educational intervention showed improvements in process metrics regarding neuromuscular monitoring, while giving us a better understanding of how best to implement improvements in this metric at this magnitude.

Association between choice of reversal agent for neuromuscular block and postoperative pulmonary complications in patients at increased risk undergoing non-emergency surgery: STIL-STRONGER, a multicentre matched cohort study

BACKGROUND

Postoperative pulmonary complications are a source of morbidity after major surgery. In patients at increased risk of postoperative pulmonary complications we sought to assess the association between neuromuscular blocking agent reversal agent and development of postoperative pulmonary complications.

METHODS

We conducted a retrospective matched cohort study, a secondary analysis of data collected in the prior STRONGER study. Data were obtained from the Multicenter Perioperative Outcomes Group. Included patients were aged 18 yr and older undergoing non-emergency surgery under general anaesthesia with tracheal intubation with neuromuscular block and reversal, who were predicted to be at elevated risk of postoperative pulmonary complications. This risk was defined as American Society of Anesthesiologists Physical Status 3 or 4 in patients undergoing either intrathoracic or intra-abdominal surgery who were either aged >80 yr or underwent a procedure lasting >2 h. Cohorts were defined by reversal with neostigmine or sugammadex. The primary composite outcome was the occurrence of pneumonia or respiratory failure.

RESULTS

After matching by institution, sex, age (within 5 yr), body mass index, anatomic region of surgery, comorbidities, and neuromuscular blocking agent, 3817 matched pairs remained. The primary postoperative pulmonary complications outcome occurred in 224 neostigmine cases vs 100 sugammadex cases (5.9% vs 2.6%, odds ratio 0.41, P<0.01). After adjustment for unbalanced covariates, the adjusted odds ratio for the association between sugammadex use and the primary outcome was 0.39 (P<0.0001).

CONCLUSIONS

In a cohort of patients at increased risk for pulmonary complications compared with neostigmine, use of sugammadex was independently associated with reduced risk of subsequent development of pneumonia or respiratory failure.