Digital hospitals help doctors provide better patient care. Here’s why.

Digital transformation is set to revolutionize how hospitals deliver care. But is digital technology being harnessed equally effectively across all aspects of the healthcare system? “Not quite,” pointed out Pamina Göttelmann, Business Development Manager of imito AG. “Digital technology is well-adopted in areas such as diagnostics and treatment. But if you look at systems for documentation management and communications, technology can still play a bigger role in improving how these processes work.”

In hospitals today, for every hour a physician spends with a patient, they spend an estimated two hours updating the patient’s electronic health record. Unsurprisingly, a recent survey by Merritt Hawkins found that more than 78% of physicians experience periodic feelings of professional burnout due to factors such as loss of clinical autonomy, diminished time with patients, and the administrative burdens of updating electronic health records. “The workload and documentation load of nurses and doctors have increased. Today, everything needs to be documented, and this can be incredibly time-consuming. This is where new technologies can help,” she elaborated.

We rely on medical professionals to provide excellent medical care especially in their direct interactions with patients. So, when hospitals utilize digital technology to improve their legacy documentation management and communication systems, doctors and nurses will be able to focus on what matters most – the patient.

Smartphone technology makes better doctors 

We recently spoke with Pamina, who shared with us about how her team is harnessing smartphone technology to streamline clinical processes in hospitals in Switzerland. The imito mobile app integrates seamlessly into the various systems used in hospitals (e.g. user identification, electronic medical records, archival of images), equipping medical professionals with a user-friendly tool to document photos or videos and communicate directly at a patient’s bedside, scan and save important documents, and digitally measure wounds, everything directly saved in electronic medical records, only while using a smartphone.

“Smartphone technology is not a new technology, but it is relatively under-utilized in the healthcare sector, especially in hospitals,” she explained. At least officially. According to survey results, more than 50% of doctors who work in hospitals use their smartphones for clinical documentation. These are exchanged via Messenger apps such as Whatsapp to gather feedback from more experienced colleagues. Under these conditions, data security is a concern.

When implemented effectively, however, app technology can help keep electronic health records accurate and facilitate the transfer of patient medical data between different healthcare institutions.

The cost of going digital 

The benefits of digitally transforming processes in hospitals are well-documented. In fact, healthcare professionals Pamina’s team spoke to want these systems improved. But convincing decision-makers in hospital management to invest can be a challenge. “If the IT department in the hospital is strong and innovative, they are more likely to get pilots funded. Otherwise budget can be a real issue,” shared Pamina.

This is because overhauling legacy documentation management and communication systems, while necessary, can be costly. As a significant example, The Lucerne Cantonal Hospital purchased a new clinical informational system from the American software manufacturer, Epic, for 65.4 million francs (excluding MWST) in 2016. This cost includes the investment and operational costs for 8 years. A centralized IT solution for all medical, patient-related, and administrative data, implementing it requires the hospital to significantly rethink how its systems operate, how its medical professionals work, and the care that its patients receive.

Though hospitals that opt for digital health products that integrate with their current systems instead of a complete overhaul will find it lighter on their wallets, budgets for such changes still remain tight. This is where having the support of healthcare professionals can make a huge difference. “You have to be very patient. But if your product’s core functionalities are based on solving real pain points that doctors and nurses feel every day, it will eventually succeed. If you show healthcare professionals the potential benefits, their support could mean convincing hospital management to implement your solution,” explained Pamina.

Transforming patient care by supporting digital hospitals in improving its processes, therefore, is a marathon, not a sprint.

What’s next

The future of the digital hospital looks promising. Many new technologies continue to emerge to bridge the gap between patient care and process. New models of digital hospitals continue to develop, such as the “cognitive hospital”, a next-generation hospital that is a “smart” facility itself and a strategic partner in patient care.

However, much of this future depends on how the healthcare industry solves this major challenge: Ensuring medical data security while enabling interoperability between systems. “The digital hospital is data-driven. Sharing medical data across healthcare institutions, however, is so difficult because it remains in isolated information silos. This is one of the reasons why progress continues to be slow,” concluded Pamina.

About Pamina Göttelmann

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After completing her master thesis “Setting Investment Priorities for Mobile Solutions in Hospitals”, Pamina deepened her acquired knowledge with valuable field experience in mHealth. As a project manager at the University Hospital of Zurich, she initiated the introduction of mobile clinical app solutions in the hospital and was responsible for the development of its corporate mobile strategy. She has co-authored and shared some of her field experience in two publications. Pamina joined imito in November 2018 as the Business Development Manager.


About the author

Aisha Schnellmann is a Singaporean sociologist by training, interested in healthcare, education, and sustainability issues. She is passionate about producing content that promotes meaningful dialogue, focusing on print and digital content that resonates with a strong call-to-action. Based in Zurich, her interest in digital healthcare grew from the conversations she had with committed medical staff in rural hospitals in Asia, who remain hard-pressed with the technology available to them.

Artificial Intelligence in healthcare and how it will affect you

Artificial intelligence (AI) is set to transform the healthcare industry, poised to impact the cost, quality, and access to healthcare worldwide. From streamlining the drug research process, enabling personalized patient care, to fixing inefficient miscommunication within medical institutions, the list of ways in which AI will shape how we deliver patient care continues to grow. In fact, according to a research report by Global Market Insights, the global ‘Healthcare Artificial Intelligence Market’ is expected to surpass USD13 billion by 2025. The healthcare industry however, continues to present challenges that threaten to slow down this progress. What are the key opportunities and obstacles facing companies and institutions developing healthcare artificial intelligence, and how will they affect you? 

We recently spoke to Susanne Suter, software engineer at Supercomputing Systems AG, at the ‘Women in Digital Health’ event where she was a guest speaker. She shared with us about these opportunities and challenges, and the innovative healthcare projects her team is currently working on to harness AI technology for good.

How do AI and machine learning work? 

“When we talk about AI nowadays, we mean data-driven systems and machine learning,” explained Susanne. During a training process, machines are essentially fed a tremendous volume of high-quality data, what each piece of data means. When this learning phase is completed, the machines are able to predict or classify any new data that is inputted based on its stored knowledge – hence developing its intelligence.

This ability of AI to analyze tremendous volumes of medical data and recognize meaningful patterns within these data sets has proven groundbreaking in healthcare innovation.

The benefits of AI 

For example, AI technology has made it possible to detect potentially life-threatening medical issues in patients early enough so that they can be treated quickly. Supercomputing Systems AG is working on a project with Prof.Dr.med. Emanuela Keller from the University Hospital in Zurich, to develop an AI research system that monitors and analyses real-time medical data of patients at the neuro-intensive care unit, predicting for example the occurrence of brain hypoxia in patients before it happens so that effective preventive action can be taken.

Pharmaceutical companies are also exploring ways to adopt AI technology in drug development; speeding up the drug discovery process and reducing costs. For example, Berg Health is using massive volumes of data from patients with diseases such as prostate cancer in order to identify new targets and develop new drugs. In Europe, global biopharmaceutical company Sanofi recently signed a 250 million Euros collaboration-deal with leading British drug design company Exscientia to discover bispecific small-molecule drugs against metabolic diseases.

The success of AI technology in healthcare, therefore, hinges fundamentally on its access to quality medical data – and lots of it. Collecting quality medical data however continues to present a real challenge for many companies working on harnessing AI technology for good.

Powering AI technology is challenging

Collecting quality medical data is time-consuming. “From my experience, 30 to 50% of time needed to develop an AI system is spent collecting quality data,” shared Swiss Supercomputing AG software engineer Susanne Suter. Furthermore, medical data in most countries continue to be siloed in disconnected systems that are difficult to access. In some cases, this data still resides in handwritten records stored in file cabinets in the doctor’s office. As expressed in Forbes, “Data must flow freely through AI systems to achieve real results but extracting data from handwritten patient files or PDFs is cumbersome for us, and difficult for AI.”

Successful collaboration by experts from fields including medicine and data science is also necessary in developing useful AI systems in healthcare. In a project with Dr. med. Peter Maloca from the Institute of Molecular and Clinical Ophthalmology Basel (IOB), Susanne’s team is developing automated analysis systems that can detect retinal tissues and medical conditions such as tumors in eyes. The team used over 2,000 images taken from an estimated sample of 650 different eyes. Each image had to be marked by experts, i.e. the retinal tissues are drawn on each image, before this data was fed to AI systems as part of the machine-learning process.

Additionally, companies developing AI solutions for healthcare have to actively consider issues related to cybersecurity and data protection. For AI systems that need to be connected to the internet to make use of powerful cloud-based backends, sufficient cybersecurity needs to be put in place to protect it against hacking. Because AI systems depend on the integrity of large medical data sets to be effective, sufficient measures also need to be put in place to ensure that medical data (e.g. from databases maintained by hospitals and other medical institutions) remain protected.

What’s next

The potential AI in technology has in transforming how we receive medical care continues to grow. However, much of this progress still depends on the speed at which the healthcare industry successfully undergoes digital transformation. Additionally, as its success hinges on its access to a high quantity of medical data, questions remain about how the development of AI technology in healthcare will benefit from current efforts to return data ownership to the people – efforts that thereby free medical data previously siloed in medical institutions and restricted by data consent laws, back in the control of people who can consent their transaction.

“AI will ultimately help us in decision-making, but we are still quite far from a reality where machines can think and draw their own conclusions. And in thinking about how to collect quality data, it’s important to remember, the person who owns the data has the power,” concluded Susanne.

The future of AI in healthcare looks bright, and it will surely be an exciting area of healthcare innovation to watch over the next few years.

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Susanne Suter, Dr. sc. Computer Science University of Zurich, has been successfully involved for over 15 years in multidisciplinary innovative projects at the interface between computer science, biology and medicine (including scientific prizes, third-party funds and publications). Since four years, she is working for Super Computing Systems as a software project leader and engineer producing custom-tailored medical software systems such as a patient monitoring system at a neuro-intensive care unit, second-opinion case-review systems for medical doctors, and an automated surveillance service to track the health condition in human eyes.


About the author

Aisha Schnellmann is a Singaporean sociologist by training, interested in healthcare, education, and sustainability issues. She is passionate about producing content that promotes meaningful dialogue, focusing on print and digital content that resonates with a strong call-to-action. Based in Zurich, her interest in digital healthcare grew from the conversations she had with committed medical staff in rural hospitals in Asia, who remain hard-pressed with the technology available to them.