Out-of-hospital cardiac arrest (OHCA) is a major public health concern, affecting 300,000 victims per year in Europe,1 and resulting in 420,000 annual 9-1-1 calls in the United States.2 Despite significant advances in the range of interventions and skills provided by EMS, little change has been seen in overall OHCA survival rates, with average survival to hospital discharge rates ranging from 8.6–20%.3-6 This variance may be influenced by a variety of factors such as mechanisms of reporting, health systems, geography and response time.
Care recommendations increasingly emphasize improvements in BLS training, public education and access to automated external defibrillators (AEDs), as the majority of OHCAs are witnessed in a public place or discovered by family members at home.7,8 These are elements of the chain of survival, which represents a series of sequential actions to be taken to improve chances of survival from OHCA: early access, CPR, defibrillation and ALS.
Increased access to mobile phones has undoubtedly supported earlier contact with EMS and increased the potential for dispatchers to support bystanders with instructions. And with the advanced capabilities of today’s smartphones, with a host of built-in sensors and the capability to run standalone software applications (apps), new opportunities have emerged. In fact, a modified version of the chain of survival, with each of its links enriched by the use of mobile phones and mobile technology, has been proposed.9 The aim of this study was to conduct an up-to-date systematic review of the literature on mobile phone use in OHCA.
After a rigorous search and screening process (see sidebar, “Methods, results & limitations,” below) three themes were identified: training, performance aids, and access and identification.
Community responders who receive nearby OHCA alerts on their smartphones reach the patient almost four minutes before EMS.
Watching training videos on a smartphone: Repeated viewing of a reminder video clip on a mobile phone has been shown to increase retention of CPR and AED skills in lay responders.10 Of 75 students who received training in CPR and AED use, the videoreminded group showed more accurate airway opening, breathing check, first rescue breathing, hand positioning, electrode positioning, pre-shock safety check, defibrillation and resuming CPR after defibrillation. There was also more confidence and increased willingness to perform bystander CPR after three months.
Using training apps: Many mobile apps were found through grey literature—research output produced by organizations outside of commercial or academic publishing—but few were formally evaluated. An app for self-directed CPR training included a feedback module; the iCPR feedback tool was able to improve performance of chest compression rate in cardiac arrest scenarios.11
Two independent medical experts evaluated content of CPR apps from the Google Play store and the Apple App Store, based on minimum medical content of BLS guidelines.12 Of 61 apps, only five were recommendable. The authors concluded that although CPR training and real incident support apps are available, very few are designed according to current BLS guidelines and therefore don’t offer an acceptable level of usability.
Animation-assisted CPR instruction: A team of researchers developed a CPR instruction program using motion capture animation integrated into mobile phones.13 They conducted a single-blind cluster randomized trial comparing effectiveness of animationassisted CPR(AA-CPR) instruction vs. dispatcher- assisted CPR (DA-CPR) instruction. They found the AA-CPR had significantly better checklist scores, time to completion of one CPR cycle, and more accurate hand positioning and compression rate than DA-CPR.
Video call guidance: Evaluated quality of simulated dispatcher-assisted CPR with guidance relayed by video calls or audio from mobile phones showed median CPR time without chest compression was shorter in the video-call group, but median time to first compression wasn’t shorter, nor median time to first ventilation.14
It was concluded video communication is unlikely to significantly improve telephone CPR without proper training of dispatchers and when using dispatch protocols written for audio-only calls. Video instruction in this study relied on the phones being held by the caller, with resuscitation carried out by two others; therefore OHCA with less than three respondents may not yield the same effect. Despite this, such video instruction may have a use prior to starting CPR with single responders.
Instructions given by mobile phone video teleconferencing: A prospective observational study of 52 public officers with no defibrillator experience found correct pad placement and shock delivery can be performed using an AED when instructions are provided via video telephone.15 As with all of the studies, technical problems included lost connection, visualizing the display and operating the phone—this may improve as technology develops.
Prerecorded audio CPR instructions: In 2010, researchers evaluated prerecorded audio CPR instructions delivered by mobile phone in untrained and trained lay rescuers.16 They randomly assigned both groups previously CPR-trained and -untrained volunteers to perform CPR on a manikin with or without audio instructions from a mobile phone. They found better performance among participants randomized to receive mobile phone intervention, regardless of whether they had received previous CPR training. They concluded a simple audio program for cell phones increases the quality of bystander CPR in a manikin simulation.
Researchers found that responders using a map on their smartphones significantly reduced their time to find and retrieve an AED.
CPR apps: Using the iCPR app significantly optimizes CPR performance for international standards and resulted in improvements in the number of cycles in two minutes, ratio 30:2 compression/ventilation, chest compressions frequency between 100–120 minutes, administration of drugs every 3–5 minutes, minimally interrupted chest compressions, assessment of reversible causes, rescuer change every two minutes, thoracic decompressions, rhythm assessment every two minutes, no interruption of chest compressions to assess the rhythm within two minutes, and leadership.17
The iResus app significantly improved performance of ALS.18 However, these studies are limited in being based on simulation rather than actual practice.17,18
BLS rescuers using the aid of a BLS app were found, in comparison to those not using an app, to protect themselves more often from environmental risks, call for help, open the airway, and have more correct chest compression rates. However, they were slower in calling the dispatch center and initiating chest compressions. This time delay was replicated in another study.19
AED ACCESS & IDENTIFICATION
OHCA Alerts: Mobile phones are progressively being recognized as a means for increasing access and identification of AED locations. A system was conceived to alert citizens through mobile phone text messaging that urged them to respond to patients by retrieving an AED or, if no AED was available, start CPR.20 A total of 6,000 volunteers and 475 AEDs were registered. The alerts were activated for 52 OHCAs, sending 3,227 alerts to 2,287 laypersons. In 85% (2,742) of alerts, laypersons were within 1,000 meters of the patient—of these, 144 retrieved a nearby AED and five were used.
Action was only taken in 579 alerts, 87% (504) of which no aid was provided, often because professionals were already present. The remaining 75 alerts involving 47 patients and included aid such as laypersons starting early CPR and defibrillation, assisting EMS personnel, or taking care of family. Laypersons arrived before EMS personnel in 45% (21) of patients, started CPR and defibrillation in 38% (18), and assisted EMS personnel in 19% (nine) of patients.
Dispatching: A team of researchers constructed a prototype community first responder (CFR) dispatch system that relays incident information, including a map, to a CFR’s mobile phone.21 They evaluated 30 OHCA simulated incidents from the previous year, sending 30 CFRs to the same locations. Mean time of receiving dispatch information to scene arrival was three minutes 37 seconds faster than historical control, and median distance was 3.4 km (2.1 miles). CFRs could reach an OHCA before EMS in 83% of cases.
Mobile maps: Researchers who, via an OHCA scenario, compared time and travel distance to access an AED with or without a mobile AED map found the overall travel distance to find and retrieve an AED was significantly shorter for those with a map (606±315 meters) vs. those without a map (891±445 meters).22 Despite this, the mean overall time required to find and retrieve a nearby AED was not significantly different (400±238 seconds for those with a map and 407Â±256 seconds in the control group).
In the post-trial inquiry, 86% (18/21) in the control group said they had difficulties finding the AED, compared to 50% (11/22) of those with a map. Authors concluded that although the mobile AED map reduced the travel distance to access and retrieve the AED, it failed to shorten the time. Further technological improvements of the system are needed to increase its usefulness in emergency settings.
Mobile positioning system: A mobile phone positioning system (MPS) named Mobile Life Saver was developed to locate selected mobile phone users.23 A simulation study was conducted with 25 volunteer mobile responders (MRs). Ambulance time intervals from 22 consecutive OHCAs in 2005 were used as controls. The MRs randomly moved around in Stockholm and were dispatched to simulated OHCAs identical to controls if they were within 350 meters. They reached the OHCA before EMS in 72% of cases by an average of about two minutes and the median response time for MRs was reduced by 56% compared to historical EMS time intervals.
In a follow-up study that took place over 25 weeks, 1,271–1,801 CPR-trained MRs were connected to the MPS.23 They were dispatched if they were within 500 meters (about one-third mile) from an OHCA. During this time, 92 cases of suspected OHCA occurred.
In 99% of cases, one or more MRs was dispatched and reached the location. In 45% of cases, one or more MRs reached the location prior to EMS. The authors concluded MPS can, in an urban setting, be used to identify and recruit nearby CPR-trained citizens to respond to suspected OHCA and provide bystander CPR prior to EMS arrival.
Another group of researchers conducted a blinded, randomized, controlled trial on OHCA, investigating whether bystanderinitiated CPR could be increased by use of an MPS that could locate mobile phone users and dispatch lay volunteers to a patient nearby with OHCA.24 It was the highest quality study of the review, involving actual OHCAs. The MPS was activated when ambulance, fire and police services were dispatched, and used to locate 9,828 trained volunteers who were within 500 meters of patients with OHCA. These volunteers were then either dispatched to the patients (the intervention group) or not given an alert (the control group). The MPS activated 667 OHCAs. The rate of bystander CPR was 62% in the intervention group and 48% in the control group. Authors concluded that using MPS to dispatch lay volunteers trained in CPR was associated with significantly increased rates of bystander-initiated CPR in OHCA.
OHCA is a major public health concern, but despite advances in ALS, survival hasn’t improved significantly in 30 years.25 CPR training to the public is seen as key to improving OHCA survival, and both the American Heart Association and the European Resuscitation Council Guidelines emphasize the importance of high-quality, uninterrupted CPR26,27 Despite this, only about 20–30% of CPR-trained bystanders will perform CPR.27-30 Indeed, when tested on manikins, the quality of CPR performed by lay people and healthcare professionals does tend to deteriorate significantly within a few months after training.7 A range of smartphone technology and apps point to their utility in improving performance and skills retention of CPR, but these studies are simulated and none have yet to demonstrate any clinical or performance improvements in actual OHCA
Approximately 85% of medical professionals use smartphones, and nearly 50% use apps in assisting clinical judgements.31,32 There are currently around 40,000 healthcare-related apps available through app stores,33 and their use in clinical practice is increasing.34 However, many available CPR apps don’t meet the basic requirements of current guidelines and, in the worst case, an app might inhibit optimal chest compressions.12
The studies in this paper don’t represent the true scale of smartphone apps available. Apps are continuously emerging to train and direct responders in resuscitation, and identify and retrieve AEDs, but few reports of their effectiveness exist. Furthermore, poorly developed apps may end up being counterproductive and misleading. The term “app overload” was coined to describe such a situation,35 and the absence of medical professionals’ involvement in app development has resulted in concern regarding misleading content, with calls for regulation and robust clinical trials to prove efficacy.36-42
The use of MPS were found to have statistically significant results in improving bystander BLS,24 but some studies found problems retrieving AEDs through issues of mapping.21,22
Mobile phones are effective in self-directed training and real-time performance of CPR. Mobile phone positioning systems can also be used to identify AED locations and direct nearby CPR-trained citizens to suspected OHCA. However, only one study appears to have been conducted that considered their use in actual OHCA,24 and improved survival from OHCA is yet to be demonstrated.
There are significant concerns over mobile phone use in OHCA and healthcare in general. Technological challenges such as mapping, which directs responders and identifies AED locations, require robust monitoring for accuracy to avoid misdirecting responders when time is of utmost importance. Apps that train and direct CPR that are developed with little medical involvement and aren’t responsive to changes in guidelines can likewise mislead responders or learners in CPR, thus limiting their effect. For these reasons we call for developers of mobile phone technology used for OHCA to consider their role as medical devices. This is in line with the growing consensus surrounding the role of mobile phones in other areas of healthcare where the course of treatment for a patient is altered. When considered as medical devices, it would naturally follow that improved oversight and regulation is justified to ensure safe and effective care. The growing evidence base for the use of mobile phones in OHCA calls for large scale trials to evaluate their impact on survival.
SIDEBAR: Methods, Results & Limitations
Methods: A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered prospectively with PROSPERO.
A search was done using headings of “mobile telephone,” including sub headings of “CPR,” “resuscitation,” “out-of-hospital cardiac arrest” and “cardiac massage.” Papers were screened independently against a priori criteria by title, abstract and full paper by review authors.
Data abstraction included trial characteristics and outcomes, demographics, device or application, method of use, methodology, quality, and outcomes. Quality of studies was assessed using GRADE. A population, intervention, comparison, outcomes study (PICOS) question screened for the following inclusion and exclusion criteria:
The number of reports was so limited, and differences between study design and measures so great, that combining results with statistical testing for bias and heterogeneity was inappropriate and meta-analysis wasn’t undertaken.
Data synthesis comprised of data extraction and descriptive analysis. There exists a potential for publication bias, where there’s selective reporting of complete studies with positive results. To limit these potential biases, we hand-searched reference lists and also contacted first authors of all included studies to ask about unpublished material, but this had a very low yield.
Results: A total of 803 papers were reviewed independently—both abstracts and full reports. Disagreements were resolved by discussion until the final sample agreed. Data was abstracted from 17 studies, evaluating a range of aspects within and across studies: 11 of those evaluated mobile phones to learn BLS, five evaluated mobile phone apps, eight evaluated real-time support, and four used mobile phones to identify and recruit responders or retrieve AEDs.
One study was graded as moderate quality; all others were low. Eleven used randomized methods, one was observational, one used questionnaire, one used a case-controlled study, two were simulation studies and one was an expert evaluation. None evaluated mobile phone use in actual OHCA. Demographic, descriptors and outcome measures varied considerably.
Limitations: Although our overview used rigorous methods to systematically review the literature on mobile phone use in OHCA, the authors recognize with widespread use of smartphone technology, it’s likely that uses exist which are not reported in the literature.
Acknowledgments: The authors wish to thank Ffion Rees, an independent researcher, for her contribution in this paper.
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