Making Sense of Big Data to Improve Perioperative Care: Learning Health Systems and the Multicenter Perioperative Outcomes Group

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.

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.

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

The learning health system for pediatric nephrology: building better systems to improve health

Learning health systems (LHS) align science, informatics, incentives, and culture for continuous improvement and innovation. In this organizational system, best practices are seamlessly embedded in the delivery process, and new knowledge is captured as an integral byproduct of the care delivery experience aimed to transform clinical practice and improve patient outcomes. The objective of this review is to describe how building better health systems that integrate clinical care, improvement, and research as part of an LHS can improve care within pediatric nephrology. This review will provide real-world examples of how this system can be established in a single center and across multiple centers as learning health networks.

Observation on the Effect of Intelligent Machine-Assisted Surgery and Perioperative Nursing

Orthopedic surgery and care during the perioperative period are the key to the treatment of orthopedic diseases, which can quickly and effectively treat orthopedic diseases and can quickly recover during the perioperative period. Therefore, this paper focuses on the observation of the effect of intelligent machine-assisted surgery and perioperative care, combined with smart wearable devices and C-arm camera calibration; the details of the bone surgery are assisted by the machine, and then the recognition ability is accelerated by writing into the digital bone bank. Based on machine vision, CNN training and learning are designed to design a machine-assisted perioperative nursing method. This paper also designed a bone surgery test experiment and perioperative adverse event data analysis, combined with the data obtained from the experiment, designed a comparison experiment with traditional surgery and perioperative nursing. The experimental results show that the success rate of machine-assisted surgery is increased by nearly 2%-15% compared with traditional surgery; and the rehabilitation degree of machine-assisted perioperative nursing is 15.83% higher than that of traditional perioperative nursing.

Variation in propofol induction doses administered to surgical patients over age 65

BACKGROUND/OBJECTIVES

Advanced age is associated with increased susceptibility to acute adverse effects of propofol. The present study aimed to describe patterns of propofol dosing for induction of general anesthesia before endotracheal intubation in a nationwide sample of older adults presenting for surgery.

DESIGN

Retrospective observational study using the Multicenter Perioperative Outcomes Group data set.

SETTING

Thirty-six institutions across the United States.

PARTICIPANTS

A total of 350,766 patients aged over 65 years who received propofol for general anesthetic induction and endotracheal intubation between 2014 and 2018.

INTERVENTION

None.

MEASUREMENTS

Total induction bolus dose of propofol administered.

RESULTS

The mean (SD) weight-adjusted propofol dose was 1.7 (0.6) mg/kg. The mean prevalent propofol induction dose exceeded the upper bound of what has been described as the typical geriatric dose requirement across every age category examined. The percent of patients receiving propofol induction doses above the described typical geriatric range was 64.8% (95% CI 64.6-65.0), varying from 73.8% among patients aged 65-69 to 45.8% among patients aged 80 and older.

CONCLUSION

The present study of a large multicenter cohort demonstrates that prevalent propofol dosing commonly falls above the published typically required dose range for patients aged ≥65 in nationwide anesthetic practice. Widespread variability in induction dose administration remains incompletely explained by known patient variables. The nature and clinical consequences of these unexplained dosing decisions remain important topics for further study. Observed discordance between expected and actual induction dosing raises the question of whether there should be reconsideration of widespread provider practice or, alternatively, whether what is published as the typical propofol induction dose range should be revisited.

Clarifying the concept of a learning health system for healthcare delivery organizations: Implications from a qualitative analysis of the scientific literature

The “learning health system” (LHS) concept has been defined in broad terms, which makes it challenging for health system leaders to determine exactly what is required to transform their organization into an LHS. This study provides a conceptual map of the LHS landscape by identifying the activities, principles, tools, and conditions that LHS researchers have associated with the concept. Through a multi‐step screening process, two researchers identified 79 publications from PubMed (published before January 2020) that contained information relevant to the question, “What work is required of a healthcare organization that is operating as an LHS?” Those publications were coded as to whether or not they referenced each of 94 LHS elements in the taxonomy developed by the study team. This taxonomy, named the Learning Health Systems Consolidated Framework (LHS‐CF), organizes the elements into five “bodies of work” (organizational learning, translation of evidence into practice, building knowledge, analyzing clinical data, and engaging stakeholders) and four “enabling conditions” (workforce skilled for LHS work, data systems and informatics technology in place, organization invests resources in LHS work, and supportive organizational culture). We report the frequency that each of the 94 elements was referenced across the 79 publications. The four most referenced elements were: “organization builds knowledge or evidence,” “quality improvement practices are standard practice,” “patients and family members are actively engaged,” and “organizational culture emphasizes and supports learning.” By dissecting the LHS construct into its component elements, the LHS‐CF taxonomy can serve as a useful tool for LHS researchers and practitioners in defining the aspects of LHS they are addressing. By assessing how often each element is referenced in the literature, the study provides guidance to health system leaders as to how their organization needs to evolve in order to become an LHS ‐ while also recognizing that each organization should emphasize elements that are most aligned with their mission and goals.

Prevalence of aberrant blood pressure readings across two automated intraoperative blood pressure monitoring systems among patients undergoing caesarean delivery

OBJECTIVES

Aberrant automated blood pressure (BP) readings during caesarean delivery may lead to disruptions in monitoring. The present study compared the frequency of aberrant BP readings across two types of commercially available BP monitoring systems in use during caesarean delivery.

METHODS

This was a retrospective observational study using two comparable patient cohorts that resulted from simultaneous introduction of two types of monitors into a single obstetric surgical center in which similar patients were treated for the same surgical procedure by the same set of clinicians during the same year. Our primary hypothesis was that aberrant readings were significantly associated with the type of monitor being used for BP measurement, controlling for a variety of relevant covariates as specified in the analytic plan.

RESULTS

A total of 1418 cesarean delivery patients met inclusion criteria. Gaps of at least 6 min in machine-captured BP readings occurred in 159 (21.1%) of cases done in the operating room using a Datex-Ohmeda monitor vs. 183 (27.5%) of cases in the operating rooms using Phillips monitors (P = 0.005). In multivariable logistic regression analysis, the relative odds of the occurrence of monitoring gaps was 35% higher in rooms with the Phillips BP monitors as compared to the Datex-Ohmeda monitor while controlling for pre-specified covariates (odds ratio = 1.35, 95% confidence interval = 1.04-1.74, P = 0.02).

CONCLUSION

The present analysis suggests that aberrant BP readings for parturients undergoing caesarean delivery are significantly different between the two types of automated BP monitoring systems used in the operating rooms at our institution.