Smart hospitals: principles and tech trends of tomorrow’s healthcare

Smart hospitals: principles and tech trends of tomorrow’s healthcare

April 6, 2022

Andrea Di Stefano

Technology Research Analyst

In his first interaction with the protagonist of the hit show Scrubs, the cold-hearted and cynical chief physician Bob Kelso candidly says "Dr. Dorian, do you not realize that you're nothing but a large pair of scrubs to me? The only reason I carry this chart around is so I can pretend to remember your damn names!". He also points out that uninsured patients should be kicked out of the hospital, failing miserably to keep the Hippocratic oath that every  doctor is supposed to make at the beginning of their career.

If you are wondering what a smart hospital should be like, well, it's basically a 180-degree turn from the aforementioned scenario. Paper documentation to coordinate human resources? Poor communication between management and staff? Patient neglect? These are vestiges of a past where decision-makers in the healthcare industry were reluctant to embrace medical device software development and, even when they did, were not necessarily able to blend and harmonize such tools with standard clinical processes.

However, things are changing rapidly under the pressure of several socio-economic dynamics, which was effectively pointed out by McKinsey in its 2019 Finding the future of care provision report:

  • The transition from pure disease treatment to health management, a more comprehensive discipline covering prevention through regular screening, well-being (which includes a healthy diet), and rehabilitation.
  • Greater education, awareness and proactivity of patients, which translate into their willingness to be involved and better informed about treatment or hospitalization options.
  • A consistent effort to improve treatment accuracy with robotics and analytics and therefore minimize the possibility of misdiagnosis or even healthcare-related infections.
  • The process of healthcare retailization, which replaces stand-alone structures with networks of geographically distributed but interconnected facilities (such as community clinics, pharmacies, or rapid test laboratories within retail stores) to delegate parts of the hospital workload.
  • Increasing attention to healthcare's financial aspects to avoid growing deficits and the resulting adoption of technologies to streamline clinical processes (via EHRs, automation, etc.) and cut costs without compromising on the quality of services.
Health service retailization

One of the most promising solutions to better address these trends (not to mention the effects of the global pandemic) implies the gradual shift from conventional to smart hospitals. Let's better define their nature and find out what's under their hood, both from a technological and operational point of view.

What is a smart hospital

Even the most traditional hospitals are extremely intricate organizations based on a sprawling network of people, processes, and assets. Improving and balancing this triad of elements to make such structures “smarter” may sound like a challenging task, given their complexity but also the stakes. After all, failures in most organizations or companies usually only result in the loss of capital or jobs, while inefficiency in a hospital is a matter of life or death.

Fortunately, technology comes to our aid, providing us with a wide range of tools to enhance every single aspect of the clinical workflow and patient care and even to launch a digital hospital. Smart hospitals represent the holistic (perhaps even the ultimate) embodiment of such tools, encompassing AI, process automation, VR, healthcare data governance and analytics, the internet of things (IoT), and all related high-tech solutions driving digital transformation in the healthcare sector.

At this point, you may say that this sector is no stranger to investing in hospital management applications and medical device software development, and you would be right. Indeed, the adoption of digital technologies in healthcare for management and operational purposes has undergone a steady growth, further catalyzed by the COVID-19 pandemic, as reported by Deloitte in its 2020 Digital Transformation: Shaping the Future of European Healthcare study.

Post-COVID adoption of digital technologies in healthcare

The real novelty in smart hospitals, however, is the integration of the aforementioned solutions into a coherent and synergistic technological ecosystem, which requires healthcare institutions to configure these facilities according to specific design cornerstones:

  • Smart healthcare harmonization: Hospitals are not just a bunch of technical assets, but rather complex systems combining technologies, processes, and professionals. Making healthcare digital is not that difficult, but turning it into a smart discipline requires a full harmonization of clinical functions, staff members performing such functions, and technologies deployed to streamline them. To do so, smart hospitals rely on centers of excellence to supervise this transformation, staff training to promote digital literacy, healthcare BPM to optimize medical processes, and knowledge sharing across departments to set up new care programs.
  • Patient-centric healthcare: Smart hospitals embrace an approach to medical care focused on patients' physical and psychological well-being. This can be achieved by configuring physical and digital spaces, along with crafting patient engagement strategies, that can actively contribute to enhancing the patient experience and speeding up recovery (the so-called healing environments). Think of mobile apps for self-service scheduling and 24/7 clinical record accessibility, teledermatology apps for self-check, AI-powered smart triage solutions, or health wearables and other telemedicine tools to constantly monitor patients from the comfort of their homes.
  • Data-driven medical care: Another staple of smart hospitals is physicians' experience and intuition complemented with solid data analytics solutions for more efficient risk identification and diagnostics. This requires collecting patient data from their EHRs or via wearables and processing it with machine learning-powered analytical systems to better understand their conditions. A similar logic applies to medical equipment, which can be monitored with proper sensors to spot any sign of malfunction and set up proper maintenance operations.
  • Healthcare decentralization: Smart hospitals are not monolithic, all-encompassing structures, but rather flexible hubs and data aggregators working in partnership and exchanging an ongoing stream of information with other facilities within the same digital ecosystem. These include tech companies providing their expertise and other healthcare actors, such as laboratories and clinics, sharing clinical data and the respective workloads. Service externalization and cooperation can be unlocked through technologies like EHR, health mobile app development, virtual care and IoT-powered health wearables.
  • Workflow automation: Another way for smart hospitals to mitigate their operational and administrative burden is through automation, be it physical (with actual robots) or digital (via RPA bots and digital assistants). The adoption of robotics and RPA to streamline clinical processes, coupled with the implementation of RFID technologies for hospital inventory management, remarkably enhances accuracy and efficiency while allowing physicians to better focus on patient well-being.
Smart hospital adoption drivers and design principles

Smart hospitals: benefits and challenges

Summing up, configuring a smart hospital implies remarkable efforts both in organizational and technological terms. Is the game worth the candle? Well, assessing the intangible benefits ensured by this hospital model (such as patient wellness) can be challenging, but from a practical perspective, we may mention that full-scale healthcare digitalization could easily contribute to national health budget savings of over 10%, based on McKinsey's assessments.

So, it's definitely worth exploring such opportunities, and according to statistics, many investors seem to agree. Juniper Research, for example, reported that the smart hospital market was valued at $29 billion in 2021 and may grow to $59 billion by 2026, with the US and China leading this trend.

The study also identifies the lack of pre-existing digital infrastructures and tools (including specialized systems like dental EHRs, pediatric, or nursing software), poor interoperability between devices and platforms, and relevant investment requirements as the major obstacles to smart hospital adoption. In other words, ambitious moonshots without a solid foundation may lead to complete failure.

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A guide to making your hospital smart

Since we just talked about investments, let's take a look at the key technologies healthcare institutions will need to invest in when shifting from old-school facilities to smart hospitals, along with some real-life examples of their actual deployment on the ground.

1. AI for intelligent healthcare

We'll start this overview with artificial intelligence, which is arguably the most transformative technology for healthcare, according to Deloitte.

Most transformative technologies for hospitals in the next ten years

But really, there is no surprise, since AI is a boundless realm, vaster than doctor Kelso's misanthropy and encompassing or directly affecting a broad range of sub-branches and related disciplines. Therefore, its applications are as numerous as they are impactful. Here are some of the major ones in a smart hospital scenario.

  • Computer vision: Combined with machine learning-based anomaly detection and pattern recognition, AI-powered computer vision can easily identify signs of potential health complications from radiological images or other clinical sources and complement physicians’ expertise for more accurate diagnoses. In this regard, the Cambridge University Hospitals partnered with Microsoft's InnerEye team to develop a computer vision system that automates the tracing of tumors and streamlines radiotherapy planning.
  • Natural language processing: NLP is another subfield of artificial intelligence worth deploying in smart hospitals in a variety of AI use cases. It's commonly used to turn medical documents into a digital format and store them into clinical databases, but also to recognize specific concepts in written texts via NER (named entity recognition) and therefore categorize such content for easier cataloging. The Australian e-Health Research Center, for example, created an NLP tool to digitize free-text medical data from pathology reports and better monitor cancer incidence trends.
  • Chatbots: These represent a (very talkative) embodiment of AI strictly related to the previous point, as they leverage healthcare-specific NLP and machine learning algorithms to mimic human communication and interact with clinical staff and patients. Chatbots and virtual assistants can support smart hospitals' employees in performing several tasks (Providence St. Joseph Health in Seattle uses them to streamline call center routing) or provide non-stop care to patients in need (such as the virtual nurse Molly, deployed by the British NHS to monitor and assist people with chronic diseases).
  • Robotics: Physical robots are chatbots' counterpart in the real world. While robots are not necessarily powered by artificial intelligence (such as human-driven machines for remote surgery), AI-related cognitive technologies like NLP and computer vision have vastly expanded their interaction capabilities. Nowadays, smart hospitals can count on AI-powered robotic surgeons for unassisted operations and robotic helpers to perform routine tasks such as lab sample delivery or room cleaning. For example, have a look at Moxi, a tireless and quite expressive assistant deployed at Texas Health Presbyterian Hospital in Dallas.

2. Less paperwork with RPA

RPA (robotic process automation) bots might be less chatty than the aforementioned robots. However, they have still proved extremely useful in a smart hospital setting, as they can be programmed to replicate (or even learn by themselves, when powered by AI) human interactions with software applications and therefore replace or assist the clinical staff in a broad range of time-consuming clerical duties. The applications of RPA in healthcare include patient appointment scheduling, medical records updating, self-service triage, claims management, and more.

Max Healthcare, a major clinical network in North India, deployed this technology in its 14 hospitals to speed up claims processing and data reconciliation, leading to 50% reduction in turnaround time. Their RPA solution can gather data from emails and PDF files, turn it into CSV format, and enter it into their databases.

3. Data analytics is physicians’ second sight

We mentioned the role of machine learning in fueling cognitive technologies that allow medical devices to see, hear and speak (almost) like humans. But this powerful branch of AI also has a lot to offer in terms of healthcare analytics.

Smart hospitals rely on machine learning algorithms, specifically on their pattern recognition and anomaly detection capabilities, to constantly oversee both patients' health conditions and medical equipment's operation, identify risk factors, and prescribe fully personalized therapies or targeted interventions. The medical datasets required to fuel such algorithms can come from several sources, including EHRs previously stored in the hospital databases, lab tests, PGHD (patient-generated health data), and health wearables, previously collected and processed with a data lake or a data fabric solution.

DNN-based medical anomaly detection

An example of data analytics in a clinical scenario comes from Saratoga Hospital in New York, which implemented healthcare predictive modeling with a solution monitoring patients’ vital signs and identifying those whose conditions are deteriorating. Since its adoption in 2015, this system has reduced patient transfers to intensive care units by 63%.

4. The internet of (medical) things

Considering that, as described above, two cornerstones of smart hospitals are their data-centric approach to medical care and the "sparse" nature of their clinical workflows, the importance of a technology like the Internet of things shouldn't come as a surprise. While data analytics systems are the brain that processes the data, healthcare IoT devices represent the hands collecting data on the ground (typically paired with cloud computing for data storage and sharing).

Health wearables equipped with sensors, GPS asthma inhalers, video conferencing tools, or even smartphones with mobile health apps can easily collect clinical data and patient feedback, allowing smart hospitals to provide remote patient monitoring and consulting 24/7 - both within their facilities and outside their standard geographic reach. In this regard, the Johns Hopkins Hospital at Home, Baltimore, developed an advanced telehealth program designed for elderly patients at risk for nosocomial infections, ensuring better clinical outcomes and cost savings of up to 30% over standard hospital care.

IoT-based telemedicine, however, can also be applied for psychological support. Built by Itransition's team, a remote patient monitoring suite allows expert nurses to communicate with sexual assault victims living in rural areas and perform forensic examination via high-resolution smartphone cameras.

Itransition’s remote patient monitoring suite

Moving from IoT for patients to IoT for technical equipment, it's worth mentioning that this technology has also been implemented in several smart facilities (for example, at OLVG hospital in Amsterdam) to streamline asset management with Real-Time Location Systems (RTLS). These solutions allow the clinical staff to keep track of medical devices via radio frequency identification after placing location-aware tags on such items, remarkably reducing equipment search time.

5. Virtual tools to tackle real challenges

The last smart hospital tech trend in our brief round-up is arguably the most picturesque as well, namely augmented and virtual reality. From a physician's perspective, AR and VR can be exceptional tools to enhance medical training with highly interactive case-based simulations. Not to mention the opportunities opened up by AR-guided surgery in the operating room, where smart glasses can overlay 2D or 3D projections over the patient body to better focus on their anatomy without having to pay attention to different monitors.

On the patient side, instead, AR and VR represent effective training solutions to exercise in immersive virtual scenarios during rehabilitation. Furthermore, they proved to be a valuable source of distraction to relieve chronic pains, as shown by a 2019 study conducted at Cedars-Sinai Medical Center in Los Angeles.

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Conclusion: they are smart, in so far as we are

We live in a world where pinning the word "smart" on anything sounds easy and trendy. But if there is something out there that deserves this title, it's smart hospitals for sure. By embracing the full spectrum of technologies that modernity has gifted us, this innovative model has been able to provide flexible, data-driven medical care, streamline clinical workflows, relieve medical personnel's workload, and enhance the patient experience or, let us  be slightly hyperbolic, reaffirm the centrality of humans over treatments and assets.

However, smart hospitals are something more than a mere collection of technologies with high-sounding names, and reimagining healthcare from the ground up may require a radical redesign of several clinical functions, along with proper upskilling initiatives and the creation of solid partnerships with other institutions to exchange data and expertise. In short, smart hospitals can be truly smart in so far as we wisely adopt all those best practices to harmonize the aforementioned triad of staff, clinical processes, and tools.

Even so, this will probably never lead to Dr. Kelso being a nice guy (at least for seven seasons). But he may decide to replace that terribly vintage clipboard  with a  fancy tablet.