Key global developments in health information technology

Introduction

Health information technology is one of the fastest growing global industries. Although historically, much growth in the area has been due to advances in now relatively well-known applications such as electronic health records, computerised decision support and telehealthcare, technological advances and the shift to outcomes-based financing mechanisms are catalysing the development of new more disruptive health information technology innovations. Building on our earlier scoping and critique of the health information technology innovation landscape, ¹ we discuss five of the most promising technological and socio-technological developments that are, we believe, likely to constitute the most significant areas in health and care delivery over the coming decade. We focus on person- and patient-generated data, robotics and the automation of healthcare, innovative information infrastructures, smart facilities and the creation of learning health systems. A key feature of these (and other) advances is the technological convergence that is taking place and, thus although separated for the sake of clarity in this article, these developments are increasingly intimately inter-related, often overlapping and combined in creative ways as discussed below.

Person- and patient-generated data: apps and wearables

The generation of person/patient-generated data through mobile apps and wearables is increasing exponentially. ² Apps and wearables such as activity trackers and those that monitor basic physiological signs in both patients and the healthy population are now common place. Developments to look out for in the future include the more sustained collection of health data and biomarkers that allow insights into individual or population health-related outcomes, ³ and the increasing gathering of data for medical research. ⁴

The current first generation of wearables has, however, tended to comprise relatively clunky and expensive devices, which are sometimes perceived as intrusive. ⁵ Second-generation wearables, including smart textiles, are likely to overcome many of these problems. The promise is that that these wearables will generate longitudinal data over sustained periods of time, which will help to anticipate, predict and prevent health problems with minimal effort on the part of the wearer. ⁵ Notable developments in this respect include smart clothes that monitor vital signs, wearable workout technology integrated in clothing and clothing that is able to sense and regulate body temperature (Figure 1).

Figure 1.

Smart sock technology used to monitor diabetic feet. Reproduced from Perrier A, Vuillerme N, Luboz V, Bucki M, Cannard F, Diot B, Colin D, Rin D, Bourg JP, Payan Y. Smart Diabetic Socks: Embedded device for diabetic foot prevention. IRBM 2014; 35: 72–6. © 2016 Elsevier Masson SAS. All rights reserved.

There is considerable interest in efforts to transmit patient-generated data to health and social care providers, and in finding ways to combine patient-collected and clinical data to inform clinical decisions. A recent example of how sharing of digital data between patients and care providers may be conceptualised is uMotif, an app that can send patient-collected clinical information to doctors who can then draw on it to inform decisions and tailor care. ⁶ In addition, there is likely to be a move away from wearables to implantables that can, for example, continuously monitor blood glucose in diabetics and tailor the release of insulin from an implanted artificial pancreas.

Given the increasing number of applications and projected market growth, an important factor to consider relates to the regulatory environment and security. Rigorous independent testing of effectiveness and certification of apps and wearables is therefore likely to become important.

Robotics and automation of healthcare

Robots replacing humans in providing care activities is no longer a vision of the future – it is already a reality. There are potentially very significant efficiency savings associated with automating some operational processes with some estimates suggesting that up to 50% of jobs may be at risk across industries over the next 20 years. ⁷

The application of robotics is already seen in some institutions in the dispensing of medicines and assisted surgery, and it is becoming more widespread in cleaning, transportation, waste disposal and other mechanical tasks such as lifting. For example, the University of California San Francisco Mission Bay Wing is now routinely employing a fleet of 25 robots that deliver drugs and clean and dispose of waste. ⁸

The most promising developments originate from creatively combining robotics with other technologies, such as augmented reality and holographic images. ⁹ A notable development in this respect is the System for Telementoring with Augmented Reality (STAR) developed by Purdue University and the Indiana University School of Medicine (Figure 2). It consists of a tablet computer that is see-through and is placed between an operating trainee doctor and the patient to be operated on. STAR transmits vocal annotations and allows digital instructions to be issued remotely by clinical mentors. It has been suggested that in due course this technology could be combined with robots to allow entirely remote surgery. ¹⁰

Figure 2.

System for Telementoring with Augmented Reality. Reprinted from Andersen D, Popescu V, Cabrera ME, Shanghavi A, Gomez G, Marley S, Mullis B, Wachs JP. Medical telementoring using an augmented reality transparent display. Surgery 2016; 159: 1646–53, with permission from Elsevier.

Robots are now also increasingly being deployed to carry out social tasks in health and social care environments. These include, for example, home care for the elderly. The Japanese humanoid ‘Pepper’ is a companion robot for domestic use that can also display and read emotions. It draws on a cloud-based artificial intelligence system including a range of sensors that record data that are then used to analyse incoming and express outgoing emotions. ¹¹ Robots are also becoming smaller, more nimble and more affordable, paving the way for large-scale adoption of these technologies across a range of care settings.

Innovative information infrastructures: cloud computing

Another development to look out for is innovative information infrastructures. For instance, cloud-based infrastructures are now routinely used in many industries to accumulate data from disparate sources and their application in healthcare presents significant opportunities for developing large networked interoperable digital applications. Besides promoting interoperability and data exchange between discrete applications in different settings, such infrastructures can be accessed by a range of healthcare organisations, and thereby help to reduce cost and streamline efforts as systems can be refined collectively and information can be shared seamlessly between care settings. ¹² In addition, cloud-based infrastructures can also facilitate concerted data analytics efforts across organisations and for large-scale big data research studies (discussed below).

Existing applications range from cloud-based services that allow exchange of specific information between discrete specialties both within and across organisations (such as referral information and oncology and images) to cloud-based electronic health record and big data clouds integrating a range of data from different sources for research purposes. Athenahealth, for example, provides ambulatory cloud-based services for electronic health records. ¹³ Other examples include Google Genomics, which uses cloud computing to share genomic data, and Watson Health, allowing researchers cloud-based access to IBM’s Watson for data linkage studies drawing on a range of data sources from disparate settings. A more recent development, incorporating a range of functionalities across a range of settings, is the Connected Health Cloud. ¹⁴ This allows the integration of electronic health record data from different settings, with patient-collected data (e.g. through wearables), organisational and population health analytic capabilities and data linkage functionality.

Although, cloud-based environments offer considerable flexibility/portability of data, they also pose some important security risks with large volumes of data held in one place. ¹² An increased focus on cybersecurity considerations in relation to cloud-based environments is therefore essential in order to realise the benefits of this important development surrounding informatics infrastructures.

Smart health and living facilities

Smart healthcare facilities may include all of the functionalities discussed above and are characterised by interconnected and intelligent health information technology solutions that gather data automatically and monitor and interpret these to improve operational processes and care outcomes. As the technology is new and smart facilities require a significant amount of upfront investment, there are currently very few such developments up and running. That said, there are several smart hospitals currently being built internationally.^15–17

There are two related trends to look out for when considering the future of smart healthcare facilities. The first is the evolution of smart cities and the second one is the wellness agenda. An example is the Lake Nona Medical City, which is a purpose-built community in Florida, using the latest networked technologies to provide approximately 25,000 residents with smart services including intelligent buildings (e.g. connected smart homes), medical care and research (e.g. through the latest technologies and involvement of citizens in research studies) and digital lifestyles that integrate all aspects of life, work and care systems. ¹⁸ Similar initiatives surrounding integrated smart living facilities are currently being pursued in other parts of the world, and networked healthcare facilities are always an important part of these, reflecting the emerging trend towards integrating the health and wellness agenda across all aspects of human life.

Creating learning health systems through innovative uses of digital data

Health information technology is also increasingly used to contribute to establishing learning health systems through improving organisational processes and health service delivery. This involves continually collecting digital data, analysing these to identify shortfalls in care, and then using this information to provide tailored feedback to providers and organisations on how care processes/outcome can be improved. There are many examples of such work within individual healthcare organisations as they transition from implementing electronic health records towards optimising systems through collection and analysis of data, and drawing on these to feed into organisational processes. For instance, the Parkland Health and Hospital System in Dallas is using predictive analytics drawing on information held in electronic health records to determine mortality and readmission risk in patients with heart failure. ¹⁹ Similarly, data platforms now exist that combine genomic and clinical data to inform clinical decisions. For example, Intermountain Precision Genomics has integrated its electronic health record with an oncology platform that allows clinicians to view genomic patient data, clinical and treatment results and medical knowledge bases, to deliver precision medicine accordingly. ²⁰

There is now also an increasing trend towards wider data integration across health systems, population-based research and linkage of data with sectors other than healthcare. Examples here include the Western Australia Data Linkage Unit, the UK’s Farr Institute, and the Canadian Healthy Child Manitoba initiative. Future developments are likely to be characterised by efforts to integrate genomics, precision medicine and data analytics across a range of sectors to transform health outcomes; but challenges are likely to include interpreting large data sets and finding a balance between patient- and clinician-specific metrics that focus on improving direct care and population health.

Conclusions

We have in this essay explored a few key developments in health information technology that we believe will in the coming years have a major impact on healthcare provision and population health. These are likely to have important implications for the developing workforce of health systems as data science, linkage, analysis and security expertise is becoming increasingly important. This initial exploratory work should be used as a stepping-stone to investigating how technological developments are likely to transform care provision and their impact on health outcomes. This will be the subject of follow-on work, which we are now planning to pursue.

When examining global developments of technological capabilities, it is clear that health information technology is increasingly taking on tasks that were previously firmly situated in the human domain, and also that digital data permeates most of the developments discussed. We can further observe the emergence of networked applications that draw on progressively large amounts of information to generate new insights into care provision and population health. Accompanying these trends is likely to be a more and more global provision of care and consolidation of different sources of information through new methods of data aggregation and linkage.