Background

Guidelines recommend continuous electroencephalography (EEG) monitoring of select critically ill patients [1,2,3,4]. Continuous EEG can assist with detection and management of nonconvulsive seizures (NCSZs), ischemia, and elevated intracranial pressure as well as prognostication. Most centers, however, utilize EEG to identify NCSZs [5] that occur in approximately 10% of comatose patients [2] and have been associated with neurophysiologic disturbances, morbidity, and mortality [6,7,8,9,10,11,12].

Guidelines recommend frequent review of continuous EEG by neurodiagnostic technologists (NDTs) for technical quality and neurophysiologists for interpretation and clinical correlation [3]. At most centers, tracings are only reviewed remotely by neurophysiologists a few times per day [5]. In addition, bedside personnel generally do not have specific proficiencies in EEG application, troubleshooting, or interpretation. To ensure treatments are delivered in a timely manner, strategies are needed to better integrate EEG information into patient care and “bridge the gap” between bedside care providers and neurophysiologists [13]. Several simplified technologies such as electrode caps [14], abbreviated montages [15,16,17,18], and user-friendly EEG machines [19,20,21] have been designed to facilitate timely application of EEG by bedside healthcare professionals. Transformation of raw EEG data into more intelligible modalities such as sonified [20,21,22,23] and quantitative EEG [24] may also assist bedside care providers in detecting clinically relevant events such as NCSZs.

The accuracy of bedside care provider screening of continuous EEG for NCSZs is likely influenced by various inherent EEG and electrographic seizure characteristics. Despite these inherent factors, we hypothesize that bedside care providers can be trained to accurately perform and screen EEG in a manner that positively impacts patient care. Understanding the influence of modifiable factors such as the modality of EEG, type of bedside care provider, and the educational curriculum and teaching methods utilized to train them may aid healthcare teams in developing EEG training strategies and improving upon how EEG is integrated into the care of critically ill patients. The aim of this systematic review was twofold: first, to qualitatively summarize the curricula and teaching methods of educational programs for training non-neurophysiologists (hereafter referred to as non-experts) in the performance and screening of adult EEG and second, to quantitatively summarize the effectiveness of these educational interventions including diagnostic accuracy of non-expert screening of EEG for electrographic seizures as an indicator of NCSZs.

Methods

This systematic review was conducted according to established methodological standards and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [25,26,27]. The study protocol was registered in PROSPERO (https://www.crd.york.ac.uk/PROSPERO/registration number CRD42019126639).

Search Strategy

In consultation with a librarian, a search strategy was developed (Appendix 1). Search terms included EEG, education, seizures, epilepsy, interpretation, and all related synonyms. No restrictions were placed on the date of publication or the language. The search was executed on February 26, 2020, and included seven biographical databases (MEDLINE, EMBASE, Cochrane, CINAHL, WOS, Scopus, and MedEdPORTAL). Reference lists of all included articles were manually searched to identify additional studies. References were exported and managed using EndNote X7 [28].

Study Selection

All titles and abstracts were independently screened in duplicate by three blinded reviewers (JK, KMF, and AA) to identify potentially relevant studies. When corresponding author information was available, attempts were made to obtain more detailed information for selected studies only published in abstract form. Potentially relevant full-text articles and studies available only in abstract form were subsequently independently reviewed in duplicate by the same three blinded reviewers, who applied the inclusion and exclusion criteria. Disagreements were resolved by discussion or consensus with a fourth reviewer (CJ). Studies were included if they were original research; involved non-experts performing, troubleshooting, or screening any format of adult (>16 years old) EEG as part of the study; and provided qualitative descriptions of curricula and teaching methods and/or quantitative assessment of non-experts (vs gold standard EEG performance by NDTs or interpretation by neurophysiologists). Drawing from meta-synthesis methods, we purposely broadened our scope to ensure data adequacy and included studies conducted both within and outside the intensive care unit (ICU) with the assumption that some educational components in one setting could potentially be extrapolated to others [26, 27]. However, studies assessing non-expert interpretation of EEG during electroconvulsive therapy were deemed beyond the scope of this review and therefore excluded. We also limited our selection to studies involving only adult (>16 years old) EEGs, given the differences between neonatal, infant, pediatric, and adult EEGs that could affect the required knowledge, skills, and therefore curricula required for non-experts [29].

Study Quality and Risk of Bias Assessment

Three blinded reviewers (JK, KMF, and AA) independently assessed the quality of included studies using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS2) tool [30]. This tool was chosen on the basis that the quantitative component of the review focusing on the effectiveness of educational programs was often reported as a measure of non-experts’ ability to diagnose EEG patterns. Each study was assessed for risk of bias and applicability within four domains: patient/EEG selection, index test (non-experts’ performance or screening of EEG), reference standard (NDT performance or neurophysiologist interpretation of EEG), and flow/timing of the index test in relation to the reference standard. Applicability was assessed within the broad scope of EEG education, as well as from an ICU perspective. Concerns regarding risk of bias and applicability were graded as high or low. If the study contained insufficient information about a specific domain or if it was not designed as a diagnostic accuracy study, it was graded as unclear or not applicable, respectively.

Data Synthesis

All data from included articles were independently extracted and agreed upon in duplicate by three authors (JK, KMF, and AA) using a standard Microsoft Excel [31] data form created by the study team. Appendix 1 provides a list of all extracted data. A content analysis and a meta-narrative review detailing the entire body of literature as well as a subset specific to ICU EEGs and personnel were conducted [26, 27]. Due to contextual and methodological heterogeneity, as well as limited availability of raw data, a meta-analysis was not possible. However, we did summarize the diagnostic accuracy of non-experts in identifying electrographic seizures, as the most clinically relevant quantitative outcome.

Results

Results of the Search

A total of 2430 unique studies were identified (Fig. 1). After applying inclusion and exclusion criteria, 35 studies remained.

Fig. 1
figure 1

PRISMA diagram of study selection

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Description of Studies

Appendix 2 presents the characteristics of the 35 included studies. We were able to obtain data for three of the six included studies published only in abstract form [32,33,34]. The overall number of publications on the topic of EEG education has increased since the first publication by Pauri in 1992 [35]. Since 2000, the number of publications has exponentially increased, which has largely been driven by those within the ICU and acute care settings (Fig. 2).

Fig. 2
figure 2

Publication trend of EEG education studies

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Fifteen studies were performed in an ICU setting, utilizing EEGs of ICU patients [18, 20, 21, 36,37,38,39,40,41,42,43,44,45,46,47]. Another nine studies were completed in acute care settings including with emergency medical services, the emergency room, and/or inpatient wards (sometimes including ICU) [14,15,16,17, 19, 22, 32, 48, 49]. Two studies were completed within seizure monitoring units [23, 35], and seven involved both inpatient and outpatient settings [33, 50,51,52,53,54,55].

Two ICU and acute care studies limited patients to those with hypoxemic ischemic brain injury [36, 37]. Otherwise, the diagnosis of patients within the ICU and acute care settings when specified varied widely within studies.

Study Quality Assessment

Three studies did not assess diagnostic (and/or pre-/posttest) accuracy and therefore could not be assessed by the QUADAS-2 tool [47, 52, 55]. For the remaining studies, the results of the QUADAS-2 assessment are shown in Fig. 3.

Fig. 3
figure 3

QUADAS-2 results. Graphs demonstrating percentage of studies with low, high, and unclear risk of bias (a), general EEG education applicability concerns (b), and ICU applicability concerns (c). Risk of bias was deemed low in the majority of domains with the exception of patient selection. Patient/EEG selection was biased in several studies because non-consecutive patients/EEGs that provided good examples of various EEG patterns were purposely chosen. Concern regarding EEG education applicability was low in the majority of studies; however, when assessed in regard application within the ICU, the proportion of studies with high concerns increased across all domains. Concerns regarding ICU applicability of the index test (non-expert performance/screening of EEG) and reference standard (expert performance/interpretation of EEG) increased as several studies involved non-experts’ and experts’ interpretation of short EEG epochs that did not emulate the amount of EEG required to screen for ICU patients undergoing continuous EEG

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Educational Objectives

ICU and acute care non-experts included ICU physicians and fellows, emergency physicians, neurology residents, nurses, NDTs, and medical students. Non-experts in other studies also included neurosurgery residents. Thirty-three papers reported on training non-experts to screen EEG [14,15,16,17,18, 20,21,22,23, 32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47, 49,50,51,52,53,54,55,56], and nine studies reported data on non-experts performing and/or troubleshooting EEGs [14, 16, 17, 19,20,21, 45, 48, 49] (Table 1).

Table 1 Qualitative and quantitative summary of EEG education
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EEG Screening

Studies training non-experts to screen EEG focused on various modalities. The most common modality was raw EEG (24 studies total, 14 ICU and acute care) [14,15,16,17,18, 22, 23, 32,33,34,35,36,37, 39, 41, 45,46,47, 50,51,52,53,54,55], followed by amplitude integrated EEG (aEEG) (six studies, all ICU and acute care) [37, 38, 41, 43, 44, 49], color and/or density spectral array (CSA, CDSA, DSA) (four studies, all ICU and acute care) [40, 41, 43, 44] and sonified EEG (four studies, three ICU and acute care) [20,21,22,23]. Six studies taught non-experts to analyze combinations of modalities, most often containing aEEG (5/6 studies), followed by CSA, CDSA, and/or DSA (3/6 studies), raw EEG (2/6 studies), and rhythmicity spectrograms (2/6 studies) [37, 38, 41,42,43,44] (Table 1).

A primary focus of most EEG screening curriculums was electrographic seizure detection that in the majority of studies consisted of NCSZs (32 studies, 22 ICU and acute care) [14,15,16,17,18, 20,21,22,23, 32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47, 49,50,51,52,53,54,55]. Several studies did broaden their objectives to identification of various EEG patterns including periodic discharges, rhythmic delta activity, slowing, burst suppression, sleep architecture, normal variants and artifacts (13 studies, five ICU and acute care) [22, 32,33,34, 39, 46, 47, 50,51,52,53,54,55]. In ICU and acute care settings, this was often done with the intent of minimizing false positives when screening for seizures (Table 1).

EEG Performance

One study involved medical students performing EEGs with a full 21-electrode complement with the assistance of an electrode cap (Hydrodot EzeNet, Hydrodot Inc.) after 20 h of didactic and hands-on training [48]. Seiler and colleagues utilized a portion of their 4-h EEG curriculum toward both didactic and hands-on sessions detailing lead identification and repair, stopping/starting recordings, focusing the EEG camera and annotating [45]. Other studies focused on training non-experts to perform EEGs with abbreviated electrode complements and the assistance of simplified technology such as peel and stick electrodes and electrode caps [14, 16, 17, 19,20,21, 49] (Table 1).

Educational Methods

Methods of teaching varied (Table 1). The most utilized method was use of an instructional lecture whether delivered live or via video (16 studies, 14 ICU and acute care) [14, 21,22,23, 37,38,39,40, 42, 43, 45,46,47,48,49, 56]. This was followed closely by practice/hands-on learning (17 studies total, 12 ICU and acute care) [14, 17, 19, 23, 32, 37,38,39,40, 45, 46, 48,49,50,51,52, 55]. Half of all studies utilized two or more teaching methods and most often combined instructional lectures and practice (17 studies, 13 ICU and acute care) [14, 17, 23, 32, 34, 37,38,39,40, 44,45,46,47,48,49, 52, 55].

The duration of training was mentioned by 18 studies and varied from a 4-min video to a 4-month EEG/epilepsy residency rotation [21, 51]. The longest duration of training within ICU and acute care studies focused on performing and interpreting EEGs was 20 h and 30 h, respectively [48, 54]. Only two studies mentioned ongoing, regular training of non-experts [14, 46] (Table 1).

Educational Outcomes

Figure 4 demonstrates the sensitivity and specificity of non-experts in identifying electrographic seizures using various EEG modalities. These seizures were NCSZs in all but two studies [23, 35]. The sensitivity and specificity of seizure identification varied from 38 to 100% and 65 to 100% for raw EEG; 95 to 100% and 65 to 85% for sonified EEG, and 40 to 93% and 38 to 95% for quantitative EEG, respectively (Table 1). Appendix 3 demonstrates these same values with the addition of other markers of diagnostic accuracy/agreement. Studies did not provide enough qualitative information to determine reasons for interstudy variability of non-expert sensitivity and specificity for electrographic seizures.

Fig. 4
figure 4

Sensitivity and specificity of non-experts identifying electrographic seizures. aMD attending physician; CI confidence interval; EEG electroencephalography; fMD fellow physician; MS medical student; qEEG quantitative electroencephalography; rMD resident physician; and RN nurse. *Number of seizures indicated unless otherwise specified. † fMD were epilepsy fellows. ‡ Sensitivity and specificity for detection of patients with seizures not total seizure count

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Most studies using pre-/posttest designs showed statistically significant improvement in scores following education with effect size varying based on the unit of measurement: 52% and 12% improvement in sensitivity and specificity for seizures, respectively (p < 0.0001) [32], and up to 33% improvement in test scores (p < 0.001) [33, 45, 53, 54].

Studies that tracked outcomes of training non-experts to perform EEGs demonstrated a statistically significant reduction in delay (86 min, p < 0.0001 [14]; 196 min, p < 0.0001 [19]; 667 min, p < 0.005 [20]) and setup time (8 min, p < 0.0001 [19]) of non-expert vs conventional EEGs. One study found no difference in the quality of non-expert compared to conventional EEG as judged by interpreting experts [19], while another found that 30% of non-expert (vs 5% conventional) EEGs were uninterpretable (p < 0.0375) [14]. Three studies demonstrated non-expert performed EEGs appropriately changed management approximately 40% of the time as illustrated in Fig. 5 [20, 21, 48] (Fig. 5; Table 1).

Fig. 5
figure 5

Change in seizure suspicion and treatment pre- vs post-non-expert EEG. x represents individual patients from Yazbeck et al. [20]; o represents individual patients from Hobbs et al. [21]. Arrows indicate direction of change in treatment decisions (e.g., dosing of sedatives, addition/removal of antiseizure medications) for individual patients. Zetabchi et al. [48] did not report on individual patients but reported that non-expert performed EEG on patients with altered mental status helped establish the diagnosis in 59%, changed the overall work-up or disposition in 49% and changed the treatment plan in 42%

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Discussion

This systematic review included 35 studies detailing quantitative and/or qualitative results of education of non-experts in the performance and screening of various EEG modalities. Contextual and methodological heterogeneity as well as limited raw data prohibited a meta-analysis; however, results were examined via a content analysis and meta-narrative process [26, 27]. The results suggest that several different members of the clinical team including physicians, fellows, residents, medical students, nurses, and NDTs can be educated to perform and screen EEG, particularly for the purpose of diagnosing NCSZs.

Within the acute care setting, the sensitivity of non-expert screening of sonified EEG for NCSZs was an impressive 95–100% [21, 22]. While promising, these values derive from one study with only seven non-experts that produced a wide confidence interval and another study that involved screening of a relatively small duration of EEG. Both studies had only seven seizures for non-experts to identify and were conducted within the same center. While these values are not externally validated within the acute care setting, the final study assessing non-expert screening of sonified EEG within the seizure monitoring unit of a different center produced a similar sensitivity (90%) [23]. Within the acute care setting, the sensitivities for non-expert screening of quantitative EEG for seizures varied widely from 40 to 93% [37, 38, 40,41,42,43,44, 49]. Specificities of non-expert screening of sonified and quantitative EEG for seizures were 65–85% and 38–95%, respectively [21, 22, 37, 38, 40,41,42,43,44, 49] (Table 1).

False negatives may occur with seizures that are low in amplitude, low in frequency, focal, brief, or have characteristics that prevent them from standing out compared to the EEG background [38]. False positives can arise from artifacts and other EEG patterns. Both may cause significant clinical consequences including ongoing NCSZs, neurophysiologic disturbances, morbidity, mortality, complications, increased length of stay, and additional health care costs [6,7,8,9,10,11,12, 20, 57]. While it is ideal and recommended to obtain confirmation of potential NCSZs identified by ICU professionals by a neurophysiologist [3], high false positive rates would cause this approach to be arduous and nonsustainable. Therefore, while techniques of screening for NCSZs require a high sensitivity, an adequate specificity and false positive rate are also advisable. Reported false positive rates for NCSZs within the acute care setting which hypothetically could translate into neurophysiologist notifications ranged from 3.2/hr to 1/10 hr in the studies [38, 40, 44].

Various modalities of quantitative EEG were taught to non-experts, including aEEG, CSA, CDSA, DSA, and rhythmicity spectrogram. These modalities were often used in combinations, making it difficult to determine whether one was superior. However, the studies that only used a single quantitative trend [37, 40, 49] produced the lowest sensitivities and specificities of all quantitative EEG studies, suggesting that combinations of trends may outperform single trends (Fig. 4; Appendix 3).

It is also possible that combining quantitative EEG screening with raw EEG confirmation may improve specificity and allow non-experts to rule out artifacts and other patterns that may mimic seizures on quantitative EEG. This would warrant non-expert education of raw EEG interpretation which was shown possible in 14 acute care settings involving nurses, physicians, residents, and medical students reviewing full (18-channel) and abbreviated (2–15-channel) montage EEGs for NCSZs [14,15,16,17,18, 22, 32, 36, 37, 39, 41, 45,46,47]. Sensitivities and specificities ranged between 75 and 100% and 76 and 100%, respectively, for nurses, residents, and physicians [15, 16, 18, 22, 32, 36].

Research regarding artificial intelligence and machine learning is evolving, as are seizure detection algorithms [58, 59]. These have the potential to facilitate precision medicine within neurocritical care as well as other areas. However, there are multiple challenges related to implementing these techniques including safe implementation of data-driven conclusions [60]. A future area for research should include integration of these tools at the bedside along with non-expert screening of EEG and data-driven conclusions.

To further facilitate timely access to EEG, several technologies have been developed including abbreviated montages [15,16,17,18], peel and stick electrodes, electrode caps/bands [14], and simplified EEG machines [19,20,21]. Many of the included studies demonstrated that nurses, physicians, fellows, and residents can be trained to perform good quality EEGs utilizing such technology resulting in significantly reduced delays in EEG setup time and completion, as well as appropriate modifications (most often de-escalation) to treatment in approximately 40% of patients [14, 16, 17, 19,20,21, 49] (Fig. 5). Ruling out NCSZs may help avoid medications with unnecessary risks [57]. Yazbeck and colleagues hypothesize that this de-escalation of unnecessary treatment may lead to reduced ICU and hospital length of stay as well as healthcare costs [20]. While access to these additional technologies may not be possible for all, Zehtabchi’s research protocol suggests that with a modest investment of time even medical students can be trained to perform high-quality conventional 18-channel EEG [48]. Furthermore, to assist with maintaining good-quality continuous EEG, Seiler et al. demonstrated that nurses could be trained to identify and repair faulty electrodes, set and focus the camera, start/stop recordings for investigations and procedures as well as annotate EEG [45]. Such skills could lessen the times NDTs are required to attend patients undergoing continuous EEG, leaving them with more time to focus on other responsibilities.

Education of non-expert clinical team members may help better integrate continuous EEG data into patient management, particularly in regard to timely detection and management of NCSZs that could potentially reduce neurophysiologic disturbances, mortality, and morbidity of affected patients [1, 2, 4, 6,7,8,9,10,11,12]. With such an approach, critical care and neurology teams could expand and intensify their continuous EEG programs through relatively inexpensive means. It is likely that much of the existing literature stems from these overarching goals given the increase in publications on this subject (Fig. 2) since formative papers were published regarding the incidence and impact of NCSZs in critically ill patients [6, 61].

The use of EEG is also expanding beyond that of NCSZ detection and management and includes ischemia monitoring [62], detection of cortical spreading depressions [63], noninvasive intracranial pressure monitoring [64], and neuro-prognostication [65,66,67,68]. No studies within this review focused on teaching bedside healthcare workers elements important for these domains and may prove to be an area for future research. It is also possible that similar teaching methods may prove useful in training bedside non-experts to utilize and interpret other multimodal neuromonitoring modalities.

This systematic review has many strengths. It used established systematic review methodology and a preregistered protocol. We searched seven large online databases, without restrictions on language or date of publication. We also screened all reference lists of selected studies. Furthermore, the processes of title/abstract screening, full-text selection, and quality rating were performed in duplicate by three independent and blinded reviewers. Our review also has limitations. While we did search MedEdPORTAL, we may have missed grey literature and therefore studies may have been missed. We included six studies only published in abstract form in our analysis but were only able to obtain full data for three. Given the heterogeneity of studies (even within the ICU and acute care setting) as well as limited raw data, a meta-analysis was not possible. We therefore relied heavily on content analysis and meta-narrative approaches; however, some included studies provided minimal qualitative descriptions, thereby limiting this approach as well. Lastly, very few studies evaluated non-experts pre- and post-educational interventions which further limits our ability to quantitatively summarize the effectiveness of educational interventions on improving diagnostic accuracy for screening of seizures. Regardless, to our knowledge, this is the first systematic review of this important and evolving topic.

Continuing medical education for healthcare professionals is a necessity and has several potential advantages including improved patient care and outcomes, improved job satisfaction and staff retention, reduced healthcare costs, improved organizational reputations, and potentially less medical malpractice lawsuits [69, 70]. This review demonstrates that a variety of teaching methods can be utilized to train an assortment of healthcare workers in the performance and screening of EEG. To enhance the success, applicability and reproducibility of future curricula and research in this area several factors need to be addressed. Formalized curriculum development [71] and research [72] following proposed methods should be completed. Considerations should be made of learning theories [73], and curriculums, such as many studies herein, should utilize interactive formats and combined teaching methods, as these have shown previously to have greater effects than those using a didactic format and single interventions, respectively [69]. Teams need to reflect upon barriers to continuing medical education [74,75,76] and strategically address these through accessible (e.g., online) and versatile curricula. Lastly, the effectiveness of training needs to be measured both pre- and post-implementation, on multiple levels, including learner satisfaction, learning curves, competence and performance as well as organizational results such as patient outcomes, length of stay, and healthcare costs [69, 70, 76, 77].

Conclusion

Several different bedside providers can be educated to perform and screen adult EEG particularly for the purpose of diagnosing NCSZs. Numerous teaching methods have been utilized and often combined, with hands-on/practice and instructional techniques the most common. EEG performed by non-experts results in reduced delays in EEG setup times and completion, as well as changes in management for many patients. Sensitivity and specificity of non-experts’ detection of NCSZs vary widely, and the current literature is limited in providing explanations for this. While further rigorous research is warranted, this review demonstrates several potential bridges by which EEG may be integrated into the care of patients.