Future perspectives

The ability and competence of an EMS system to manage and care for patients experiencing OHCA have been conceived as measurements of the overall performance of the system. The recognition of OHCA emergencies is the catalyst of the survival process, for without the recognition of OHCA, action in response will not be taken. In this context, such an action consists of prompt dispatching and bystander-performed CPR. The education of the CPR-administering ability and willingness of bystanders to perform CPR will remain the foundation whilst striving to improve survival rates for patients with OHCA, despite the fact that the importance of bystander-performed CPR has also been argued by the medical community (Bardy, 2011).

Increasingly often, bystanders can be activated to engage in the CPR process in lieu of EMS personnel; for most people, before thinking selfishly, the basic instinct is to help other people. This preference or feature is worth to be set and used as part of the chain of survival as was done in Sweden and Denmark, where CPR-trained lay volunteers were dispatched to a nearby patient with out-of-hospital cardiac arrest (Ringh et al., 2015b, Schakow, Larsen & Henriksen, 2015).

The more active recruitment and education of youth in schools can be used to strengthen the team of CPR-motivated and -capable bystanders. The EMD’s recognition of OHCA, as well as the recognition process of many other conditions of people, will be supported with smart mobile devices or wearables that can measure far more physiological parameters than simply heart rhythm.

Although there is not yet sufficient experience to know the exactly future spread and use of personal mobile devices, it is reasonable to expect that society´s surroundings, homes, houses, cars, clothing, jewellery and accessories will all be monitoring and following mankind in the future (Baird, 2017). Technology in the future will likely consist of personal devices as well as handheld and movable applications that will authorise individuals to monitor their physiology from anywhere and transmit the information directly to health care providers, if necessary (Horn, 2017). Such variable measurements will be able to provide feedback to the users of the novel technology, warn them of alarming results of the measurements and even call for help in certain circumstances. As a result, increasing remote communication with healthcare providers will reduce the need for personal visits. Since the community cannot afford to continue investing billions to keep the persistently growing and ageing population healthy, healthcare technologies that solve the challenge of economical demands, cost-effectivity and affordability will be able to achieve a position in healthcare in the future. In the years ahead, everyone in the area of healthcare will have to prove that their new and innovative products or services are able to deliver better outcomes than the alternatives (Rhea, 2017).

The heart rhythm-based recognition of OHCA will be further studied and could be integrated as part of the chain of survival process to support EMDs in their work. The possibility of splitting and recoding the touchscreens of mobile phones or devices to ECG electrodes would allow to use the rhythm-recognising applications without accessories. A scheme or design that requires only the smartphone app would allow a far easier route to distribute the new approach.

Cardiac arrest as a form of dysrhythmia, though the most hazardous, is only the tip of the iceberg of arrhythmias. Whether the experienced dysrhythmia is benign is impossible to judge without documenting the rhythm. Supraventricular arrhythmias or paroxysmal atrial fibrillation is often challenging to detect if the ECG recording is impossible to read when the patient experiences or senses dysrhythmia. Furthermore, asymptomatic atrial fibrillation is increasingly common in the ageing population and implicated in many forms of ischemic stroke. The earlier identification of asymptomatic atrial fibrillation with appropriate anticoagulation may decrease stroke morbidity and mortality (Halcox et al., 2017). The arrhythmia-recognising platform of mobile devices will thus prove their value in the diagnostic process or screening of those dysrhythmias.

Handheld devices, single-channel ECGs and photoplethysmographical pulse waves have been researched and are partly available to detect and recognise certain dysrhythmias and ischemia of the heart (Muhlestein et

recognition are also available. They are just waiting for the opportunity and occasion to breakthrough to be a part of the OHCA recognition process.

8 CONCLUSIONS

As the catalyst of the chain of survival for patients with OHCA, recognition of OHCA by dispatchers at EMCCs has been associated with reduced response times by EMS, increased rates of bystander-performed CPR as well as achieved ROSC and improved rates of survival for patients. When cardiac arrest was recognised by EMCCs, rates of achieved ROSC and survival to hospital discharge were 49% and 23%, respectively; however, when it was not, those rates dropped to 40% and 16%. Open-minded efforts to promote and improve the recognition of OHCA as the initial step in the survival process for patients with OHCA are, therefore, strongly recommended.

Bipolar ECGs of good quality can be recorded by using devices with an area the size of a mobile phone.

Although the average amplitude of the recordings was low, the software of the AED could analyse the recorded rhythms promptly, even amidst the interference of muscle tension. The most reliable recording position was vertical at the mid-sternum level. Such recordings accomplished in a small area of the body, could apply to automatic, remote or next-to-patient rhythm analysis.

Recordings of normal ECG rhythm and VF within an area the size of a mobile phone appear to have sufficient quality for use in rhythm-based OHCA recognition. Such an approach could improve the success rate of the first essential steps in the chain of survival of patients with OHCA and improve cardiac arrest outcomes. In that sense, the proposed operating model for OHCA recognition deserves further study.

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In document Recognition of out-of-hospital cardiac arrest (sivua 80-102)