AI in Healthcare: Can it Make Doctors’ and Patients’ Lives Easier And Safer?

29 May

AI in Healthcare: Can it Make Doctors’ and Patients’ Lives Easier And Safer?

Giulia Besana
Research Analyst, IDC Health Insights
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Artificial intelligence is the buzzword in the healthcare space. According to IDC’s European Vertical Markets Survey, 2018–2019, around 30% of healthcare providers in Europe have already invested in AI solutions or plan to do so in 2019. France and the Nordics are the biggest adopters of AI, while the UK and Germany are balancing current implementation with adoption plans for the next 12 months. 

Besides the buzz, finding the right use cases for AI and testing its ability to support changes in the organisation and the healthcare services business models across the region have been the key drivers of investment and research so far. 

From System of Record to System of Engagement: Enabling Precision and Personalisation of Clinical Pathways 

European healthcare providers are betting on AI to support greater personalisation of healthcare services. The principle of value-based healthcare is increasingly becoming part of national healthcare systems, and the complexity of population health needs — such as the growing prevalence of multimorbidity and the risks associated with antimicrobial resistance — requires that healthcare organisations use their data more effectively.

Healthcare organisations are changing the way they use data, from a pure system of record, mainly compliance driven, to a system of insights that, once acted on, will deliver systems of engagement. In these systems of engagement, patient outcomes and experience are top strategic priorities — and AI is expected to drive a quantum leap forward. IDC’s research shows that European healthcare leaders are investing in AI in use cases such as personalisation of clinical pathways, diagnostics and decision support, and health population management. This includes identifying populations at risk and those expected to be at risk, the ability to create and monitor care plans, and the ability to communicate with patients and communities of patients.

The UK and the Nordics are leading the adoption of AI solutions to personalise clinical pathways. Leveraging their strengths in population registries and electronic healthcare record adoption, Nordic countries are starting to use AI for pathway personalisation and precision medicine. Back in 2007, Denmark introduced the concept of “cancer packages” — standardised pathways focusing on faster diagnosis, faster initiation of treatment, more coherent treatment courses and targeted rehabilitation of cancer survivors. AI solutions enable healthcare organisations to personalise cancer treatment even more, thanks to the goldmine of knowledge that can be used to improve treatment quality and care delivery. The Danish healthcare system is also taking a strategic approach to personalised medicine to enhance the use of health data for treatment and research. To prevent strokes, Sweden has introduced a new clinical decision support (CDS) solution, the Cambio CDS Stroke Prevention App. Using the app, at-risk patients can be identified earlier and sent an automatic alert to seek treatment.

Real-Life Applications: From Patient-Flow Predictions to Diagnostics

Besides pilots and proofs of concept, European countries are also increasingly launching actual AI projects. At the Paris Public Hospital (AP-HP), data from internal and external sources — including 10 years of hospital admissions records — has been analysed to provide day- and hour-level predictions on the expected number of patients. This helps create patterns of data and predict admission rates at different times, enabling a more efficient allocation of resources across hospital workflows.

Imaging and diagnostics are among the most researched areas for AI in the healthcare environment. A trained machine can recognise patters among thousands of scans and lab results, reducing time to diagnosis, improving workforce resource utilisation and increasing accuracy. A research team from Heidelberg University, working with colleagues from the US and France, designed a “convolutional neural network” trained with 100,000 photos of both malignant and non-malignant birthmarks. The technology correctly recognised 95 of 100 malignant cases.

AI Skills, Capabilities and Expertise

Another trend in European healthcare is the rise of research plans, academic programmes and capability building. The definition of application potential and national budget allocation for AI and Big Data analytics–related projects in healthcare has boosted the creation of innovation labs, knowledge hubs and centres of excellence focused on implementing the newest technologies, including AI. For example, the German Research Center for AI (Deutsches Forschungszentrum für Künstliche Intelligenz) and the AI-focused programmes at the Institute of Applied Informatics and Formal Description Methods (AIFB) and the Saarland Informatics University are all German-based initiatives aimed at building the AI capabilities and expertise of tomorrow. Similarly, Nordics countries — with their history of cross-national collaboration — have created the Nordic Artificial Intelligence Institute (NAII), a non-profit alliance of international experts in AI and related areas, including machine learning, machine perception, natural language understanding, robotics and autonomous planning.

Next Steps?

IDC recently consolidated its findings and guidance on AI in European healthcare in the Artificial Intelligence Strategies in European Healthcare: Adoption and Investment Plans survey (IDC #EMEA44354519). The report analyses the results of an IDC survey on AI and BDA adoption and investment plans across European healthcare providers and is aimed at helping technology suppliers to identify trending themes around AI, machine learning and BDA. It also compares their strategies and offerings against industry benchmarks.

If you want to learn more about how AI will affect the healthcare market, please contact Giulia Besana.

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