Paperless anesthesia: uses and abuses of these data

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

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

What we can learn from Big Data about factors influencing perioperative outcome

PURPOSE OF REVIEW

This narrative review will discuss what value Big Data has to offer anesthesiology and aims to highlight recently published articles of large databases exploring factors influencing perioperative outcome. Additionally, the future perspectives of Big Data and its major pitfalls will be discussed.

RECENT FINDINGS

The potential of Big Data has given an incentive to create nationwide and anesthesia-initiated registries like the MPOG and NACOR. These large databases have contributed in elucidating some of the rare perioperative complications, such as declined cognition after exposure to general anesthesia and epidural hematomas in parturients. Additionally, they are useful in finding patterns such as similar outcome in subtypes of beta-blockers and lower incidence of pneumonia in preoperative influenza vaccinations in the elderly.

SUMMARY

Big Data is becoming increasingly popular with the collaborative collection of registries offering anesthesia a way to explore rare perioperative complications and outcome to encourage further hypotheses testing. Although Big Data has its flaws in security, lack of expertise and methodological concerns, the future potential of analytics combined with genomics, machine learning and real-time decision support looks promising.

Compliance with perioperative prophylaxis guidelines and the use of novel outcome measures

Postoperative wound infections represent an important source of morbidity and mortality in children. Perioperative antibiotic prophylaxis has been shown to decrease the risk of developing infections and hospital guidelines surrounding antibiotic use exist to standardize patient care. Despite supporting evidence, rates of compliance with guidelines vary. Quality improvement initiatives have been introduced to improve compliance with intraoperative antibiotic guidelines. Thorough infection surveillance, including antibiotic provision in presurgical checklists, computerized voice antibiotic administration prompts, and national feedback systems are now increasingly common. Few studies have been conducted investigating the effectiveness of prophylactic antibiotics in children. Outcome measures such as morbidity and mortality and return to the operating room can be used to examine the relationship between antibiotic use and patient outcome but these measures are limited in that they occur infrequently or are subjective and difficult to measure. Metrics such as days alive out of hospital and length of hospital stay may be useful alternatives for ongoing monitoring of infections and identifying improvements in patient outcomes. Guidelines on antibiotic prophylaxis have facilitated an increase in the correct provision of perioperative antibiotics and a reduction in the incidence of postoperative infection. Measures of patient outcome such as days alive out of hospital and length of hospital stay are easy to collect and calculate but further work is needed to confirm the utility of these measures for monitoring infection rates.

Incidence of Artifacts and Deviating Values in Research Data Obtained from an Anesthesia Information Management System in Children

BACKGROUND

Vital parameter data collected in anesthesia information management systems are often used for clinical research. The validity of this type of research is dependent on the number of artifacts.

METHODS

In this prospective observational cohort study, the incidence of artifacts in anesthesia information management system data was investigated in children undergoing anesthesia for noncardiac procedures. Secondary outcomes included the incidence of artifacts among deviating and nondeviating values, among the anesthesia phases, and among different anesthetic techniques.

RESULTS

We included 136 anesthetics representing 10,236 min of anesthesia time. The incidence of artifacts was 0.5% for heart rate (95% CI: 0.4 to 0.7%), 1.3% for oxygen saturation (1.1 to 1.5%), 7.5% for end-tidal carbon dioxide (6.9 to 8.0%), 5.0% for noninvasive blood pressure (4.0 to 6.0%), and 7.3% for invasive blood pressure (5.9 to 8.8%). The incidence of artifacts among deviating values was 3.1% for heart rate (2.1 to 4.4%), 10.8% for oxygen saturation (7.6 to 14.8%), 14.1% for end-tidal carbon dioxide (13.0 to 15.2%), 14.4% for noninvasive blood pressure (10.3 to 19.4%), and 38.4% for invasive blood pressure (30.3 to 47.1%).

CONCLUSIONS

Not all values in anesthesia information management systems are valid. The incidence of artifacts stored in the present pediatric anesthesia practice was low for heart rate and oxygen saturation, whereas noninvasive and invasive blood pressure and end-tidal carbon dioxide had higher artifact incidences. Deviating values are more often artifacts than values in a normal range, and artifacts are associated with the phase of anesthesia and anesthetic technique. Development of (automatic) data validation systems or solutions to deal with artifacts in data is warranted.

Blood pressure and heart rates in neonates and preschool children: an analysis from 10 years of electronic recording

BACKGROUND

An acceptable systolic or mean arterial blood pressure for children 0-6 years during anesthesia is unknown. Accepted blood pressures reported in standard charts for healthy awake children may not apply to those undergoing anesthesia.

AIM

Our goal was to define observed blood pressures (BP) and heart rate (HR) in children 0-5 years during anesthesia.

METHODS

Data from the electronic health record database were available for a 10-year period from June 29, 2005 to July 22, 2015. A simple band-pass filter was applied to remove artifact in the physiologic time-series data for heart rate and blood pressure, with heart rate values 40 or above 250, mean or diastolic blood pressures below 20 or above 200, and systolic blood pressures below 30 or above 200 all excluded. For each anesthetic, the centiles of physiological variables (BP, HR) were calculated.

RESULTS

Data were available for 54 896 anesthetics in children 6 years and younger. There were 898 anesthesia reports available that included blood pressure measures immediately before induction. A larger number of anesthesia records (n = 30 008) were available for intraoperative blood pressure recording. The BP decrease after anesthesia induction was most pronounced in infants 0-10 weeks of age where there was a mean arterial blood pressure (MAP) decrease of 16.6-34.5% (mean 28.6%). Systolic blood pressure decreased by 16.3-32.6% (mean 25.5%). Values above a systolic blood pressure of 60 mm Hg were only noted in half the neonates during anesthesia. Heart rates, both before and after anesthesia induction, were similar.

CONCLUSION

Heart rate while under anesthesia appears a poor indicator for blood pressure changes. Recorded blood pressures in this current study, measured immediately before induction, were consistent with those in the literature. A mean MAP decrease of 28.6% was typical in those infants 0-10 weeks of age.