Background Monitoring complications associated with medical procedures requires reliable and accurate record keeping. Nudge reminders executed by way of electronic medical record (EMR) alerts influence clinician behaviour. We hypothesised that the introduction of an EMR nudge would improve documentation of replaced neuraxial blocks by obstetric anaesthesiologists at our institution.
Methods We developed an EMR nudge that would alert the physician to a replaced neuraxial block if two or more neuraxial procedure notes in a single patient encounter were detected. The nudge encouraged physicians to document neuraxial block replacements in our institution’s quality improvement database. We assessed the rate of physician adherence to replaced neuraxial block charting prior to the introduction of the nudge (January 2019–September 2019) and after the implementation (October 2019–December 2020).
Results 494 encounters during the chart review period, January 2019–December 2020, required a neuraxial block replacement, representing an actual neuraxial replacement rate of 6.3% prior to the introduction of the nudge in October 2019. This rate was largely unchanged (6.2%) after the introduction of the nudge (0.1% difference, 95% CI: −0.0119 to 0.0099). Prior to the introduction of the nudge, the proportion of correctly charted failed/replaced blocks in our quality improvement database was 80.0%, and after nudge introduction, the rate was 96.2% (p value <0.00001, OR=6.32, 95% CI: 3.15 to 12.66). A p-chart of the monthly adherence rate demonstrated sustained improvement over time.
Conclusions EMR nudge technology significantly improved adherence with quality metric monitoring of neuraxial catheter replacement in obstetric patients. The results imply that data collection for quality metric databases of neuraxial block failures and replacements that rely on clinician memory without a nudge are likely under-reporting neuraxial block failures and replacements. This study supports widespread implementation of nudges in EMRs to improve quality metric reporting.
- quality improvement
- obstetrics and gynecology
Data availability statement
Data are available upon reasonable request.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
Using nudge technology helps guide clinicians to adhere to guidelines.
WHAT THIS STUDY ADDS
Using nudge technology improves adherence to obstetric anaesthesiology quality metric monitoring of replaced neuraxial blocks.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
Relying on clinician memory to collect data on quality metrics such as failed or replaced neuraxial blocks most likely leads to under-reporting. Practices should incorporate nudge strategies into EMR to improve the accuracy of data collection.
In order to track key obstetric anaesthesiology-related complications and/or events at Lucile Packard Children’s Hospital, Stanford, we developed quality improvement (QI) metrics and integrated their collection into our electronic medical record (EMR) (figure 1A). Before an anaesthesiologist can close a patient encounter, they must complete the QI database charting for the case by documenting any relevant complications and/or events or select ‘None’ if no events occurred (figure 1A). The accuracy of the QI data in this system relies on the anaesthesiologist to correctly enter the data at the time of event or recall any complications that occurred during the case prior to closing the record. Because of the demands of a busy obstetric service and the potential for several handovers to occur, the anaesthesiologist closing the chart may not be aware or may not remember to chart pertinent data. Literature regarding the effectiveness of protocols that rely on human recall and motivation to document complications in this manner conclude that these means are often inadequate, variable and not sustainable.1
Behavioural economic concepts such as ‘choice architecture’ and ‘nudge theory’ are used across industries to better facilitate decision-making and reduce human error and misjudgment.2 3 The incorporation of nudge theory and choice architecture into EMRs to influence decision-making by clinicians has a growing body of support and success in delivering quality, evidence-based care.4 5 To improve the documentation of the replaced neuraxial block metric in our QI database, we implemented an electronic nudge that would display a reminder when two or more neuraxial block procedure notes were detected within a single patient’s encounter (figure 1B). This nudge would alert the anaesthesiologist that a block replacement may have occurred and suggest that, if true, this be logged in the QI database.
The primary aim of this study was to determine if this system improved documentation of neuraxial block replacements in the obstetric setting. We hypothesised that the introduction of an EMR nudge would improve the documentation of replaced neuraxial blocks by anaesthesiologists in the QI database at our institution.
This report conforms to the SQUIRE V.2.0 guidelines for reporting new work to improve healthcare safety.6 The project did not meet the definition of human subjects research as defined in 45 CFR 46, nor the FDA definition of a clinical investigation as defined in 21 CFR 56, and was approved for IRB review exemption.
Since 2015, we have employed the use of an EMR collection tool to track quality metrics relevant to obstetric anaesthesiology (figure 1A). These data are collated for review and discussion on a weekly basis and is tracked by our division on a quarterly basis for quality assurance purposes. This custom-developed QI database within our EMR (Epic Systems Corp, Verona, Wisconsin, USA) allows frequent reporting of collected data and is superior to other means of attaining metrics from our EMR that are labour intensive and require restricted access. Each labour and delivery record associated with a procedure note must have a completed QI database entry prior to closure of the chart. The inclusion of events in the QI database requires clinician entry at the time of the event or recall of the event prior to closure of the record. Inclusion in the QI database is not driven by any electronic automation. The clinician can select ‘None’ if desired in the QI database. All significant QI database events such ‘Failed catheter/block that required replacement, repeating, or changing anaesthetic technique’ require active selection. Without the clinician reporting a failed or replaced block, the patient’s QI database will read ‘None’. A ‘Failed catheter/block’ may therefore not be appropriately logged, and the QI database not updated to reflect a patient whose neuraxial block had been replaced.
Our labour and delivery unit is in a tertiary referral, American College of Obstetricians and Gynecologists (ACOG) Level 4, academic hospital that saw an average of 4364 deliveries/year for 2019 and 2020. Our institution has been designated a Society of Obstetric Anesthesia and Perinatology (SOAP) Center of Excellence in Obstetric Care since 2018. Our neuraxial placement rate for 2019 was 88.9% and for 2020 was 89.0% . Our labour neuraxial technique breakdown is approximately 55% combined spinal epidurals, 35% standard epidurals and 10% dural puncture epidurals. The obstetric anaesthesiology service is staffed by a dedicated labour and delivery 24/7 service, with mostly obstetric anaesthesiology-fellowship trained personnel. We offer an Accreditation Council for Graduate Medical Education (ACGME)-accredited obstetric anaesthesiology fellowship and provide training to Stanford University School of Medicine anaesthesiology residents. Our institution implemented the Epic EMR (Verona, Wisconsin, USA) in 2014 and have ongoing analyst support for modifications to the EMR build.
Analysis inclusion/exclusion criteria
From January 2019 until December 2020, patient data required to determine overall rates of neuraxial block replacement and the adherence rate of physician QI database logging were attained from our EMR database. All obstetric patients included in our analysis had received neuraxial anaesthesia from our service.
Working with our EMR developers and our clinical team, we developed an EMR nudge that would alert the physician to a potential replaced neuraxial block based on the detection of two or more neuraxial placement procedure notes in a single patient encounter. On detection of multiple neuraxial anaesthesia procedure notes, a reminder alert (ie, nudge) stating ‘Possible failed block. Update QI’ would populate within the patient’s labour record, flash briefly and remain visible until acknowledged by the clinician (figure 1B). Notably, the reminder is not a pop-up and does not obstruct routine workflow or charting. It is a not a ‘hard stop’, and the physician can continue charting or close the chart without ever pursuing the nudge, if desired. Acknowledgement of the nudge by selecting the textbox electronically opens the data entry form for the QI database. The clinician can update the QI database and select ‘Failed catheter/block…’, if appropriate, for collection in our records.
To compare adherence rates with charting replaced blocks in the QI database before and after implementation of the EMR nudge, we collected charts that had more than one neuraxial procedure note listed, and assessed whether these had been charted as replaced blocks in our QI database. Charts that were detected via the two-note detection rule but not entered in the QI database were audited to confirm whether a neuraxial block replacement had occurred. We only included those confirmed to have had a block replacement as part of our analysis (figure 2). We then calculated the incidence of adherence to replaced block charting in the QI database before and after implementation of the EMR nudge. The replaced block rate was plotted in a p-chart using QI Macros for Excel (Denver, Colorado, USA) to show adherence rate over time, which can be seen in figure 3.
Patient and members of the public were not involved in the study design or analysis.
Between January 2019 and December 2020, there were a total of 494 patient encounters in which a replaced epidural block occurred, based on detection of two or more neuraxial procedure notes per encounter. Figure 2 outlines the validation performed to confirm that patients truly had a replaced block. Five patients in chart review were determined not to have had a replaced block. Prior to introduction of the nudge, the replaced block rate was 6.2% and after the introduction of the nudge, the replaced block rate was unchanged at 6.3% (0.1% difference, 95% CI: −0.0119 to 0.0099). Thus, the true block replacement rate in the study period was 6.3% (489 out of 7768 neuraxial catheters placed) over the course of the 2 years. Two hundred of these replaced neuraxial blocks occurred prior to our intervention (October 2019), and 289 were detected after our intervention. Prior to the introduction of the nudge in October 2019, the appropriately charted replaced block rate in our QI database was 80.0% (160 out of 200), and after the intervention, the rate was 96.2% (278 out of 289) (p value <0.00001, OR=6.32, 95% CI: 3.15 to 12.66). The adherence rates reported monthly are shown in the p-chart (figure 3). After intervention, there is a shift in the median with sustained improvement in the adherence rate to charting replaced blocks.
We demonstrated that an EMR nudge improved and sustained adherence to quality metric monitoring of neuraxial block replacement in obstetric patients. This is significant, as accurately monitoring quality metrics such as the rate of failed and replaced neuraxial blocks for labour analgesia provides insight into the quality of obstetric anaesthesiology care delivered. The ability to produce such data reliably and quickly is also important, as frequent peer review by quality assurance teams may allow detection of concerning trends and allow surveillance of any changes in practice that may have been employed. This single-site, pre–post QI project demonstrates that the use of ‘nudge technology’ and ‘choice architecture’ in obstetric anaesthesiology may positively influence the behaviour of clinicians and, in turn, positively influence the effectiveness of other QI efforts.
National and international agencies continue to pursue the development of quality metrics to measure individuals and institutional care. The Obstetric Anaesthetists’ Association and the National Perinatal Epidemiology Unit used Delphi methodology to determine ‘key indicators to drive quality improvement in obstetric anaesthesia’.7 One of the five key metrics was ‘percentage of epidurals for labour analgesia that provided adequate pain relief within 45 min of placement’. The Society for Obstetric Anesthesia and Perinatology (SOAP) offers a designation titled ‘Centers of Excellence’ to hospitals offering obstetric anaesthesia care.8 The SOAP Centers of Excellence expects centres to monitor their neuraxial block failures/replacements, and suggest aiming for a failure/replacement rate of 3%–6%.9 Monitoring one’s block replacement rate is important. A labour epidural block replacement rate that is too low may indicate that an insufficient number of inadequate blocks are being appropriately replaced, while a block replacement rate that is too high may imply poor epidural insertion technique, inadequate supervision of trainees or suboptimal local anaesthetic/opioid maintenance solution or epidural pump settings. Additionally, one of the SOAP Centers of Excellence essential criteria is the presence of ‘quality assurance and patient follow-up systems’, in addition to a description of ‘systems used to track labour epidural replacement’. These international agencies recognise the importance of accurately tracking the rate of failed and replaced neuraxial blocks, further supporting the importance of QI initiatives such as ours. Our results show that institutions relying on clinicians to remember to document neuraxial block failures and replacements may be under-reporting without an EMR-specific nudge. Implementation of this or similar nudges in EMRs may be necessary to improve quality metric reporting of failed and replaced blocks and other key quality metrics.
Due to the high acuity and/or fluctuating workload on labour and delivery, even those who are motivated to change or improve compliance with best practice guidelines and protocols may fall short in their efforts. This ‘intention–action gap’ is a phenomenon well described by behavioural scientists.10 Across medical specialties, methodology used to influence physician behaviour to close this gap has garnered a wide array of interest. Most of the research surrounding clinical decision-making and implementation science concludes that the promotion of change with simple audit and feedback, didactic educational tools and individually targeted interventions yield poor results with waning sustainability.11 12 Examination of behaviour patterns when analysing clinician decision-making highlights the influence of rationality, habits and implicit processes/biases that impact clinicians’ choices.1 The assumption that these cognitive processes are always sound and effective is flawed, and clinicians may require influence in their decision-making on a more granular cognitive level.13
The act of ‘nudging’ is defined as a ‘function of any attempt at influencing people’s judgement, choice or behaviour in a predictable way, that is made possible because of cognitive boundaries, biases, routines and habits in individual and social decision-making’.13 Similarly, the concept of ‘choice architecture’ involves ‘the design of different ways in which choices can be presented to individuals’.13 The origins of these theories stem from the schools of economics and behaviour science. Their applications have become very popular in present-day medicine, especially when used in combination with EMRs and information systems. Despite the accelerated advancements in our knowledge of disease and innovation in healthcare technology over the past century, the ‘evidence-to-practice’ gap (ie, the time between description of an effective and evidence-based intervention and large-scale uptake into clinical practice), is on average, 17 years.14
A recent systematic review of trials using nudge technology within the Cochrane network found that, of the outcomes impacted by a clinician nudge, 86% influenced clinician behaviour in the hypothesised direction, with 53% of these achieving statistical significance.5 Among the studies included in the Last et al systematic review analysing the efficacy of different nudge strategies employed in healthcare, the most used nudge strategy was ‘framing’, and the most effective nudge strategies were those that employed ‘default’ selections.15 The authors describe a clever graphic depicting a ‘nudge ladder’, with the least desirable/effective nudge strategies at the bottom (those that simply provide information), and the most desirable/effective at the top (those that guide choice through defaults; figure 4). The nudge strategy described in our study strongly aligns with the second highest nudge strategy on the nudge ladder, those that ‘enable choice’. Although several aspects of EMR nudges commonly use forcing functions and default selection to achieve clinician compliance,16 the unique benefit of the use of a nudge such as ours is the maintenance of physician autonomy, space for nuance and freedom from a forcing function to make alternative choices. For example, despite using an electronic tool to highlight all patient records that contained two or more neuraxial procedure notes, our audit revealed that some of these charts did not meet our clinical criteria for block failure (figure 2). Using the nudge allowed us to maintain clinician oversight in keeping these records sound and accurate. Additionally, the reminder to consider charting a replaced block was designed to be unobtrusive and not directly interfere with routine workflow.
Although the data we collect on failed and replaced neuraxial blocks are for the purpose of review and analysis for our own division, a simple intervention like this has potential to be implemented on a much larger scale and to make significant impact on patient care and cost-savings strategies for hospitals and healthcare systems. Nudge theory and choice architecture have been successfully used in the promotion of smoking cessation in pregnancy17 and pre-eclampsia prevention in obstetric patients.18 Particular to anaesthesiology, similar principles have been used to encourage adherence with guidelines for lung protective ventilation strategies during surgery,19 safer opioid prescribing practices,20 sedation minimisation and liberation from mechanical ventilation in the ICU21 and antibiotic stewardship.22 Obstetric anaesthesiology is a unique subspecialty in that a provider may be caring for several patients at once in different stages of their pregnancies and deliveries. Accurate record keeping may be increasingly challenging given the potential acuity of a labour and delivery unit. Reducing the cognitive load of the clinician and absolving them of the need to ‘remember’ what to chart is one of the greatest theorised benefits in using a real-time, EMR nudge such as ours.23 However, EMR nudges and similar reminder messages may contribute to another rising phenomenon in EMR charting—‘click fatigue’ or ‘alert burden’. In addition to their association with physician burnout, fatigue from these alerts can also lead to active ignoring of nudges such as ours, especially if not clinically relevant.24 Assessing the effects of any added EMR tools and their contribution to burnout should be a balancing measure assessed alongside QI initiatives, and clinical informaticists implementing additional alerts should ensure they are only active when clinically relevant and quiescent when not.
There are several limitations to our study. We relied on retrospective data collection as this study aimed to assess routine clinical practice that would be impacted if a prospective study design were applied. We only collected data on replaced blocks and acknowledge that inadequate blocks that were not replaced would not have been detected in this analysis. We appreciate that failed or replaced neuraxial block trends over time could be impacted by staffing and institutional changes. However, we have made no significant changes in our clinical care during this study period, and our p-chart analysis shows a real and sustained impact of the nudge on replaced block detection. The success of this project highlights the potential to apply equivalent EMR nudges to the collection of other QI data, for example, a nudge to document haemorrhage on detection of blood product charting, or a nudge to document a patient’s ICU admission with detection of an ICU intake note or transfer of care in the EMR.
In conclusion, the addition of an EMR nudge improved the accuracy of replaced neuraxial block QI metric documentation in our obstetric patients. The results show that institutions attempting to gather quality metric data and relying on clinician memory to do so are likely under-reporting neuraxial block failures and replacements. If national or institutional QI metric comparisons are made, the accuracy of data collection should be a priority. The study findings support widespread implementation of this or similar nudges in EMRs to improve obstetric anaesthesiology quality metric reporting. However, this technology should be appropriate and applied sparingly to minimise click fatigue and alert burden. Further research exploring techniques to optimise QI metric monitoring should address the ideal number and key QI metrics to document, without increasing the potential for physician cognitive overload or burnout.
Data availability statement
Data are available upon reasonable request.
Patient consent for publication
The project did not meet the definition of human subjects research as defined in 45 CFR 46, nor the FDA definition of a clinical investigation as defined in 21 CFR 56, and was approved for IRB review exemption.
Contributors Dr KF, MD FRCPC, helped with the conception of the work, acquisition of the data, analysis and interpretation of data, drafted the work and revised it critically and approved the final manuscript. Dr JX, MD, helped with the conception of the work, acquisition of the data, analysis and interpretation of data, helped draft the work and revised it critically and approved the final manuscript. Dr EW, MD, helped with the conception of the work, revised the draft critically and approved the final manuscript. Dr CF, MD MPH PhD, helped with the conception of the work, revised the draft critically and approved the final manuscript. Dr ER, MD, helped with the conception of the work, data analysis and interpretation of data, revised the draft critically and approved the final manuscript. Dr BC, MBBCh, FRCA, MDCH, the guarantor of the manuscript, helped with the conception of the work, analysis and interpretation of data, helped revise the draft critically and approved the final manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.