The role of disruptive and hybrid technologies in acute care

(b) Caring for the acutely/critically ill becomes increasingly complex and encompasses multiple intra-hospital transfers and interactions with numerous medical specialties and healthcare professionals. Hence, it involves 24/7 clinical, administrative and managerial documentation and the use of new biosensors, dynamic imaging methods and ever-increasing organ-specific monitoring systems. It is worth mentioning that there has been an exponential increase of FDA licenses to new medical grade devices and software the last few years [in contrast with the stagnation -in relative terms- in developing new new drugs] (FDA.gov). As a result, a wealth of multiform, structured/unstructured data, clinical biosignals -numeric and waveform- and images is produced (Figure 1), nowadays stored and processed in expense of high storage capacity (ten times more for ICU patients than OR) but decremental cost (Burykin et al. 2011; Blum et al. 2015). However, intuitive visualisation and diagnostic/prognostic use of these data has been increasingly problematic, lacking clinical focus and mostly limited to unguided, experiential, pattern recognition and coding (Evans 2016; Islam et al. 2018; Clifton et al. 2015) (Figure 2).

(d) Failure of the vast majority of randomised studies the last decades -the gold standard of clinical experimentation- to bring positive results in complex critical illness i.e. sepsis (Ridgeon et al. 2016) and traumatic brain injury (Asehnoune et al. 2017), have increased the demand for conceptually personalised approaches to diagnosis and treatment. “Precision Medicine (National Research Council 2011),” reflecting the need to deliver the right treatment at the right time to the right group of persons (encompassing similar characteristics) in the right circumstances! High hopes have been ignited by the fact that the IR4 is bringing to the market -even not yet extensively to the bedside- a whole new spectrum of -omics tools producing more and more “personalised” data with a fraction of the cost used to entail (Martin-Sanchez et al. 2015). This is matched with the booming use of ML and AI in Healthcare and the rapid development of “middleware” toolkits which allow biomedical researchers and clinicians to easily access and use predictive analytics tools.

(e) Since the frightening figures of healthcare errors and associated mortality/morbidity have been unveiled during the last decades [3rd leading cause of death and disability in the US] (Makary et al. 2017), new processes and methods to strengthen patient safety and to prevent healthcare associated errors are becoming issues of utmost priority. Digitisation of patient records and the booming penetration of Hospital or Specialty oriented Clinical Information Systems/Patient Data management systems could help towards this direction (Prgomet et al. 2017). However, only a single-digit fraction of USA Hospitals enrolled into the first phase of digitisation of healthcare records has entered the 2nd (HealthIT.gov). It is becoming clear that, knowledge/experience transfer from similar successful implementations like the aviation industry as well as more sophistication and introduction of Artificial Intelligence (AI) tools is the way forward. This pathway, in turn, faces serious conceptual, ethical and financial challenges (Clifton et al. 2015).

(f) Specialty-oriented clinical information systems customised to the needs of acute medical specialties and areas like A&E, ICUs, HDUs, CCUs, ORs etc. are now increasingly being replaced (or attempted to be replaced) by hospital information systems in the name and context of better integration, interoperability and cost control. Serious controversy has been developed since this trend has been enforced by hospital authorities with -frequently- very little discussion and poor customisation process. On the other hand, the arguments for an all-encompassing HIS are solid and intuitive. It is, however, widely accepted in the scientific community, though inadequately investigated, that the usability of those systems is at least sub-optimal (Dincklage et al. 2017). The community of patients, clinicians, administrators, researchers, academics, healthcare industry management shall thus find its way to meet a number of relevant challenges: i) development of acute care specialties ontology involving clinical as well as physiology/pathophysiology and organ support terminology; ii) adoption of common standards that will allow seamless integration of data from medical diagnostic, monitoring and organ support devices; iii) consensus on minimum requirements of clinical information systems functionality; iv) development of new visualisation techniques which will improve clinical decision making with documented results. It is encouraging that quality certification standards are moving towards this direction adopting the “dialogue principles” defined in the ISO standard 9241-110 as suitability for the task, suitability for learning, suitability for individualisation, conformity with user expectations, self-descriptiveness, controllability and error tolerance (sis.se/api/document/preview/907276/).

(g) Clinical education at all levels and for all students and healthcare personnel involved in acute, emergency and intensive care (physicians, nurses, physiotherapists, clinical dieticians, clinical pharmacists, clinical psychologists etc) has been always a high priority, given the complexity of the working environment and the skills required. Nowadays it enters a new era, as time and physical presence boundaries are dissolving, expertise gaps can be bridged, data access is becoming increasingly easy and modelling of diseases/procedures is revolutionised with the use of internet, telemedicine and virtual/augmented reality technologies. Globalisation and free movement of healthcare personnel as well as high demand for competence standardisation and specialisation has rendered international curricula and the role of scientific societies very important, as self-paced eLearning is booming worldwide (docebo.com).

(h) Inter-disciplinary -as opposed to multidisciplinary- approach to challenges, came through 4IR and shall stay with us! Acute, Emergency and Intensive Care is no exception but rather a wonderful example to apply and build on this concept. It is time to think big and bring help in this particularly challenging endeavour where human lives are at stake. On top of the traditional members of the ICU team, basic lifesciences scientists, psychologists, engineers, architects and bioinformaticians should find their place to our routines. Working environment in clinical areas, especially IT HIS/EHR infrastructure is expected to facilitate and provide structured, yet flexible approaches to this interdisciplinary interaction in order to maximise its impact on patient outcomes, our ultimate target!

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