What can AI do for your Hospital?

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AI artificial intelligence in hospitals

What can AI do for your hospital? A lot, that’s the answer in brief. Which is maybe the reason Mount Sinai recently started a Department of Artificial Intelligence, or why the Federal Government of Belgium is funding an AI4Health consortium, or why Radboud Medical University Center opened its AI-labs, just to name a few initiatives.

By reviewing our past research and curated solution libraries, we managed to summarise 11 key benefits of AI for hospitals. For each benefit, we also provide a few examples of companies active in this area.

1 Give your staff an extra brain

Similar to a spellchecker going through millions lines of text in any language, AI can empower your staff by going through millions of reference pages or EHR data points in the blink of an eye. In this way AI helps medical staff to prevent mis-diagnoses, to triage/prioritise treatments and to assist in detecting rare or uncommon diseases. AI can suggest actions based on someone’s medical history, together with learnings from RWE (Real World Evidence), prompting proactive early interventions and spotting trends that might otherwise be missed. Next to that AI can help to identify which tests or treatments a patient with a long-term health condition needs or might benefit from.

Examples. LynxCare, ScienceIO, Rhino Health

2 Transform heroes into superheroes

Your medical staff are heroes already. But AI can give them superpowers, like extra speed, improved accuracy and seeing things that otherwise wouldn’t be seen. One of those superpowers is pattern recognition which can be deployed in pathology, radiology, dermatology and live video images during surgery. Next to that AI can analyse big data lakes in real-time and this way automate interpretation, properly label and annotate information and detect abnormalities well before heroes are able to detect it. These superpowers improve diagnostic processes, clinical decision-making and thus clinical results and outcomes.

Examples: Centaurlabs, Etiometry, IcoMetrix

3 Unburden your staff

The hospital workforce has to work in a stressful environment with a lot of paperwork. AI helps streamline this paperwork with automated image and text analysis which enhances the processing speed and accuracy of information. Also administrative tasks can be expedited thanks to automated coding and billing as well as suggesting text and (medical) speech recognition. AI will also help avoid the many false alarms and notifications, speed up detection of falls and lighten pressure on staff via AI-powered chatbots and medical assistants. Quality managers will love automated quality assurance, safety inspections and checking of compliance (legal, medical devices, procedures, GDPR, …)

Examples: DeepScribe, Bingli, Newcompliance

4 Revolutionise planning capabilities

How much better would your facility run if you could have had the opportunity to organise a dry run or a simulation before the facility was built? Several companies offer ‘Digital Twins’ and AI simulation tools, not only from the perspective of the infrastructure, but also around processes, patient flows and financial consequences.

Examples: Hakobio, Simul8, AnyLogic

5 Monitor & perfect your machines

In order to assess the use of an individual machine in a large puzzle, you need to put all pieces of that puzzle together. Unfortunately this puzzle is very complex in healthcare. Due to recent evolutions in RFID, QR-codes, barcodes, IoT, GPS, RPA (robotic process automation) edge computing and interconnection services, the pieces of this intricate puzzle can be put together.  

The collected data points can subsequently be analysed and optimized with AI. This enables operators to make optimal use of equipment (utilisation management), determine ideal routing, enhance scheduling, optimise cleaning, save energy, refine footfall analysis and accurately trace equipment. One example of such an automation helps conduct an MRI in 5 minutes instead of 30 minutes. AI-systems can also predict equipment failure and manage technical interventions well in advance. This enables health systems to achieve and sustain peak operational performance.

Examples: Falkonry, MySphera, Synap IoT

6 Optimise revenue

What is the most favorable occupancy of your beds, which savings can you realise per encounter, what is the optimal mix of services and which processes or departments perform best? Your financial department will love to forego the manual labour to answer these questions and rather use that time to focus on strategic actions based on dashboards produced by smart algorithms. Consider this as “precision finance”, AI as your crystal ball for effective use of your financial resources, leveraging RWD (Real World Data) to visualize performance, compare approaches, and adapt across patients, teams, protocols, workflows & facilities.

Examples: VisiqQuate, ClosedLoop, Veda

7 Secure the hospital

The explosion of digitally connected devices (IoT, medical devices, smartphones, …) and users, together with an increase in focused cyberattacks on hospitals has made cybersecurity one of the biggest worries in healthcare organisations. And securing the hospital is much more than this, it also involves signalling anomalies in visitor patterns, access to facilities, secure identification & authentication, fraud detection and so on. AI is ideally placed for real-time identification, accelerated response and mitigation of those risks.

Examples: GoClinic, Asimily, Protenus

8 Bring the hospital to the patient

In the past, patients needed to come to the hospital due to the limitations of technology. Recent evolutions in sensors and connectivity largely start to overcome those limitations. The only obstacle that remained was 24/7 remote monitoring and at the same time guaranteeing that the right persons were contacted when vital signs go wrong, preferably before they go wrong. Again AI is used to interpret the large data sets that sensors produce and subsequently routing potential alarms to the right person(s). These forms of AI are deployed in various phases, from (preventive) screening to treatment and recovery, resulting in shortening the stay at the hospital.

Examples: Biofourmis, Nobi, HumanITcare

9 Personalise the patient service

Generic one-size fits all treatment has serious limitations. Personalised treatment and rehabilitation is more effective. Not only effective from a pure clinical outcome based perspective, but also from a patients’ perspective. Sticking to a customized, tailor fit regimen is so much easier to adhere to. Try sticking to dietary- or fitness- advice that doesn’t fit you well! But in order to be able to give personalised treatment, we need to go through enormous amounts of medical knowledge, RWE (Real World Evidence), genetic information, omics data, input from wearables & medical devices, …. This is too much info for humans to digest, but not for humans + AI.

Examples: Brightseed, Laguna, Tempo

10 Delight your patient

The former sections all have a very positive impact on patients in one way or the other. But to absolutely delight them, now that hospital staff have less administrative burdens due to AI, they can free up time for more empathy towards the patient. On top of that AI can help reduce waiting times, provide personalised information as well as suggest entertainment options, and remove other frictions. Imagine the impact that such an improved experience could have on people suffering from chronic diseases! Moreover, the capabilities of medical staff are augmented with AI which helps them treat and coach patients individually so they don’t get sick anymore, which is the ultimate delight.

Examples: MayaMD, HealthTalk AI, Syllable

11 Win the war for talent

AI doesn’t directly play a major role in attracting and retaining employees. Sure, there are AI-tools for automated screening for candidates, optimisation for staff scheduling and personalised training. But the effects of AI as mentioned in the previous 10 points also contribute to the realisation of a ‘great place to work’ and should attract more and better candidates. AI indirectly helps you to win the war for talent, mark our words.

Examples: Abtrace, XSolis, Olive

As you’ve noticed, AI can do a lot for your hospital. But that’s not all: the examples mentioned in this overview are vendors that focus on hospital clients. We also use lateral thinking and creative processes to also track non-obvious partners outside of healthcare. We have more detailed, proprietary data available about such partners and also have databases of other product categories in the wider digital health field. 

And while you’re here, don’t forget to subscribe to the most delightful newsletter in life sciences at the bottom of this page or here. Thank you!

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