European Journal of Cardiovascular Medicine

In hospital emergency management, the effectiveness of a Code Blue system (CBS) to respond to in-hospital cardiac arrests is paramount⁽¹⁾. While traditional centralised systems have been widely researched and implemented, there is a need for innovative approaches tailored to the specific environments of tertiary care facilities, particularly in cardiac surgical centres⁽²⁾. This study explores the implementation of a single mobile phone as the central communication device within a CB system, a novel strategy aimed at improving response times and coordination of care among emergency response teams.

In-hospital cardiac arrests present a significant challenge, with survival rates to hospital discharge often below 30%. Factors such as age, presenting rhythm, and the promptness of CPR are critical in influencing outcomes⁽³⁾. Various innovative technology based techniques have been employed for early initiation of bystander CPR in out-of-hospital cardiac arrest⁽⁴⁾. Similarly, models similar to pit crew activation have been evaluated and reported for in-hospital cardiac arrest⁽⁵⁾. In addition, certain automated code-blue activation systems, based on data analysed from in-hospital data, have been reported to be effective⁽⁶⁾. Using a mobile phone-based voice call as the sole communication tool for initiating CB calls, we employed an activation process and improved notifications to the central response team in a cardiothoracic surgical set-up. This approach contrasts with centralised systems involving multiple communication channels and potential delays. This method is in line with the recent advent of silent code activation systems that have been recently reported¹.

Automated Code Blue systems are technological solutions designed to streamline the response to cardiac arrests within healthcare facilities. These systems typically integrate alarm notifications, real-time data monitoring, and electronic health records to enhance the response of emergency medical teams. Automated Code Blue systems improve emergency response by ensuring rapid notifications, reducing human error, and integrating with electronic health records (EHR) for real-time updates. They facilitate data collection, enhancing training and protocol optimisation while promoting standardisation for efficient coordination. However, technical failures, high costs, and the need for staff training pose challenges. Over-reliance on automation may reduce manual resuscitation skills, and data privacy concerns remain critical. Mobile-based systems offer better speed, coordination, and scalability than conventional ones, often lacking efficiency and data-driven insights, making automation a valuable but complex solution in healthcare settings.

Given the technical and personnel-related challenges, including equipment and response time efficiency issues, this paper aims to evaluate the impact of a mobile-based CB system on the effectiveness of cardiac arrest management. Through a detailed analysis of case data from our tertiary care cardiac surgical centre, we seek to assess how this innovative approach can enhance training, optimise emergency protocols, and ultimately improve patient survival rates. The findings of this study could contribute to the growing body of literature on emergency response strategies, providing valuable insights for healthcare practitioners focused on improving clinical outcomes in critical cardiac scenarios.

The study site, a 200 bedded cardio-thoracic centre, employed mobile-phone based code-blue system where a voice call was made to a designated mobile phone number, carried by code-blue team stationed in operation theatre at all times, to activate a code. An audit of all ‘Code Blue’(CB) feedback forms filled up after completing such a mobile-based ‘Code Blue’ call by the team during the study period (Aug 2021 to Dec 2023) was carried out. Data was collected using code blue forms, tabulated and analysed using standard statistical methods. The metrics were compared with previously reported studies where conventional CBS were employed.

A total of 149 code-blue calls during the study period were analysed. Response time of the code-blue team to reach the site along with defibrillators, equipment and medications (2.22±1.43 minutes). Most of the calls (85%) were from Acute care areas. The most common presenting rhythms were severe bradycardia and asystole (54.3%) (Table 1). Chest compressions (53.6%) and endotracheal intubation (7.3%) were the most common interventions before the arrival of the code blue team. Defibrillation was required in 23 code blue calls.

Table 1: Analysis of aspects related to outcomes of mobile-based code blue system.

Among 149 calls, 24.8% of the code-blue calls did not merit CPR. Of the remaining 112 code-blue calls that required CPR, ROSC was achieved in 30 patients (26.7%). No statistically significant difference in age (64.29±19.17 years vs 66.09±14.36 years p=0.944) or gender (Chi-square 0.026, df 1, p=0.87) between patients achieving ROSC and non-ROSC patients. There was no statistically significant difference in response times between patients who achieved ROSC compared to others (1.97±1.2 min vs 2.3±1.5 min; p=0.376). Adrenaline was the most common drug administered by the CB team (66.4%), while 17.4% required defibrillation. There was a statistically significant difference in achieving ROSC when comparing Code blue calls received during working and non-working hours (difference in proportion -0.236 (95%CI -0.42 to -0.052; p=0.036) (Table 2).

Table 2: Key Clinical and Operational Metrics Observed in Mobile-Based CBS Audit

ROSC was achieved in 13.9% of patients with asystole/severe bradycardia. Age more than 60 years and asystole as presenting rhythm showed poor outcomes. 57.7% of the CB calls were made outside working hours. However, the duration of CPR (19.43±16.67 vs 47.1±12.2; p<0.001) and total number of doses of adrenaline (1.95±0.97 vs 3.4±1.81; p<0.001) administered during CPR attempt were significantly different between ROSC and non-ROSC groups. A simple ROC analysis was used to predict the optimal cut-off for CPR duration beyond which there was a failure to achieve ROSC, which was 30 minutes (AU-ROC 0.877, sensitivity 98.39% and specificity 73.9%) (Figure 1).

Figure 1. ROC Curve: CPR Duration as Predictor of ROSC

We evaluated an already functioning code blue system which relied on cell phone-based voice call activation. The response time of the code-blue team to reach the code-blue site (2.22±1.43 minutes) in our study of cell phone code-blue activation was similar to conventional code-blue response times previously reported⁽⁷⁾ from large centres with more than 1000-bed capacity (2.83±1.30 minutes). Although significantly shorter activation time of reaching the designated site was demonstrable on statistical analysis (mean difference -0.6min (95% CI -0.9527 to -0.2673), it would be safer to conclude as a comparable response time due to possible differences in hospital layout and organisation set-up of the code blue team.

The demographic characteristics and proportion of non-shockable rhythms were similar to previously reported studied from the same geographic region employing conventional code-blue systems⁽⁸⁾. However, this was not similar to the rates of non-shockable rhythms reported from other regions of the world (9). Almost one-in-four code blue calls did not merit any intervention considered as CPR. This was similar to the 22% false code-blue activations reported earlier using a conventional code-blue system⁽⁸⁾. The significant differences in achieving ROSC while comparing code blue activation during working hours and non-working hours is similar to results previously reported in literature^(8,10). The metrics that have been analysed in various previous audits^(8,10,11) of conventional code-blue systems like proportion of cases with asystole at presentation, total doses of adrenaline administered and the duration of CPR are similar to the results of the present study.

The cell phone voice call-based activation of Code blue system is able to serve the purpose of a conventional code-blue system in this studied cardiothoracic centre. However, various caveats that are applicable for these results from the study need to be highlighted. Firstly, the system has been found to be sufficient for a cardiothoracic centre with limited incidence of code-blue calls. On an average, 5.3 calls per month were received by the team (149 code blue calls over 28-month duration). It was unusual to have a second code-blue call with an ongoing code-blue call. Hence, one code-blue team, with a cell phone designated for code-blue calls, stationed in a centrally located operation theatre complex was sufficient to serve the purpose. Secondly, the layout of the hospital was limited to a total three floors with a centrally located operation theatre complex on the first floor where the code blue team was stationed. This translates into a quick access to Code blue team to all patient care areas. Hence, the success of the cell phone-based code blue activation system could be attributed to the unique architecture of the hospital and is well-suited. This may not be necessarily applicable to hospitals with wider patient care areas not quickly accessible for resuscitation teams^(5,7).

A novel code-button notification system linked to cell phone-based code blue activation system reported by Morris⁽²⁾ has been demonstrated to be quicker than the conventional systems for responding to in-hospital cardiac arrest. Similarly, technology based innovations have been reported to improve first response from the community in case of out-of-hospital cardiac arrest⁽⁴⁾. The application of a cell phone voice call-based code-blue system in large hospital settings where multiple code blue teams may require to be activated may need such innovative solutions without the need for conversion to conventional code-blue systems that require additional maintenance and risk of downtime. This also paves the way for a silent code blue activation system as envisaged recently⁽¹²⁾. Salient features of the study are summarized in Figure 2. In the present era of ‘internet of things’ and real-time guidance by mobile ‘maps’, various innovative custom-made solutions could pave way for a cheaper, faster, reliable and silent code-blue activation systems.

LIMITATIONS

This study has a few limitations. Being a single-centre audit conducted in a cardiothoracic facility with a compact infrastructure and a centrally located code blue team, the findings may not be generalisable to larger or more dispersed hospital settings. The retrospective nature of the audit, relying on prefilled code blue feedback forms, introduces the potential for reporting and documentation bias. Additionally, the absence of a parallel control group using a conventional code blue activation system within the same institution may limit the ability to draw definitive causal inferences regarding the effectiveness of the mobile-based system. Furthermore, the analysis did not account for variations in the composition or experience of the code blue response team, which may have influenced patient outcomes. Importantly, the study focused only on immediate return of spontaneous circulation (ROSC) and did not evaluate longer-term outcomes such as survival to discharge or neurologic recovery. Finally, qualitative aspects such as staff perceptions, ease of use, and barriers to activating the mobile-based system were not explored, which may have provided additional insight into the operational feasibility and acceptability of this approach.

The present mobile voice call-based CBS was satisfactory regarding response time and provided adequate insights about the patient factors associated with poor outcomes. A single mobile-phone voice-based code blue system is a viable alternative to conventional code blue system in a suitable set-up with a single response team.

Figure 2. Efficiency and Outcomes of a Mobile Voice Call-Based Code Blue System in a Cardiothoracic Centre.

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