Introduction

Digitalisation has significantly transformed society and working life during recent decades, and its effects are strongly visible in healthcare and laboratory work. The development of Information and Communication Technology (ICT) has enabled electronic health record systems, laboratory automation, remote services, and more efficient utilisation of data in decision-making. As a registered nurse and biomedical laboratory scientist, I have followed this development in my practical work and have seen how digitalisation has improved work efficiency, patient safety, and multidisciplinary collaboration.

In this report, I examine the effects of digitalisation in my own field of expertise and evaluate the opportunities it provides as well as its future perspectives. I also discuss the risks of an open digital society, the significance of the General Data Protection Regulation (GDPR), and the benefits and challenges of artificial intelligence in healthcare. Finally, I evaluate the suitability of ChatGPT as a support tool for information retrieval in my field and reflect on my own learning based on this assignment.

ICT and the Impact of Digitalisation on Healthcare and Laboratory Work

Information and communication technology (ICT) has significantly changed healthcare during recent decades. Digitalisation has influenced how healthcare professionals communicate, search for information, perform diagnostics, and provide patient care. I have experienced this development in my daily work. Digital tools have improved work efficiency, increased patient safety, and supported evidence-based decision-making.

Finnish citizens’ attitudes towards digitalisation in healthcare are mainly positive. According to research, Finns have greater confidence than other Nordic citizens in the possibilities of digitalisation to improve healthcare and address challenges related to limited resources (Pihlava 2023). Research also shows that healthcare information systems can improve the quality of care, reduce clinical errors, and make service processes more efficient (Patrikainen 2020, 13). At the same time, digitalisation introduces new challenges related to data security, privacy protection, and the competence of healthcare professionals. The usability of information systems, system interruptions, and insufficient training may reduce their usefulness and user satisfaction (Patrikainen 2020, 15–16).

Digitalisation has also increased the amount of data generated in healthcare. The analysis of large datasets makes it possible to identify new phenomena and connections that would not be detected from smaller datasets (Cukier 2014). Maurice Conti describes a future where humans, artificial intelligence, and robots work together by complementing each other’s abilities (Conti 2016). These developments can already be seen in healthcare and laboratory environments.

However, successful utilisation of digitalisation requires sufficient digital competence. According to the Ministry of Social Affairs and Health, there are still regional and organisational differences in the digital skills of social and healthcare professionals, and there is a recognised need to develop competence related especially to artificial intelligence (Sosiaali- ja terveysministeriö 2024). As technology continues to develop, continuous learning is therefore an essential part of maintaining professional competence in healthcare.

Digitalisation in My Own Field of Expertise

Healthcare has become an increasingly digital operating environment. Paper-based patient records have largely been replaced by electronic health record systems, which allow patient information to be accessed quickly and securely by healthcare professionals. Laboratory information systems have also improved the processing of test requests, sample tracking, result reporting, and collaboration between laboratories and clinical departments (Patrikainen 2020, 13–16).

In my work as a biomedical laboratory scientist, digital systems are an essential part of daily activities. Laboratory analysers are connected to laboratory information systems that receive test requests, process analytical results, and transfer verified results directly to healthcare professionals. Automation has reduced manual work, decreased the possibility of errors, and improved the reliability of laboratory testing (Patrikainen 2020, 13–16).

Sample collection has also developed through digital solutions. Barcodes and electronic patient identification reduce identification errors and improve patient safety. Automated analysers can process large numbers of samples quickly and accurately, which speeds up the availability of test results and supports better patient care.

Digitalisation has also facilitated multidisciplinary collaboration. Physicians, nurses, biomedical laboratory scientists, and other healthcare professionals can access the same patient information in real time. This improves information flow and supports evidence-based decision-making.

Based on my own experiences, digitalisation has improved the smoothness of work processes, reduced the possibility of errors, and freed more time for professional tasks requiring expertise. At the same time, it requires continuous development of professional skills because information systems and technologies are constantly changing. In addition to clinical competence, healthcare professionals increasingly need stronger digital skills to ensure that new solutions can be used safely and effectively for the benefit of patients.

Healthcare professionals therefore need not only clinical expertise but also stronger digital competence in order to utilise new solutions safely and effectively for the benefit of patients (Sosiaali- ja terveysministeriö 2024).

The Future of Digitalisation in Healthcare

The future of healthcare will increasingly rely on data, artificial intelligence, and intelligent technologies. Smart systems are able to collect and analyse large amounts of data and identify connections that humans may not be able to detect without technological support (Cukier 2014). This enables the development of predictive healthcare, where diseases and patient risks can be identified earlier than before.

Artificial intelligence, machine learning, robotics, and automation will also play an increasingly important role in laboratory environments. In the future, artificial intelligence can help identify abnormal laboratory results, support diagnostics, predict disease risks, and assist in processing large amounts of data. Automation can also reduce routine tasks, allowing healthcare professionals to focus more on tasks requiring specialist expertise (Ministry of Social Affairs and Health 2024). According to research, the full potential of digital health solutions has not yet been reached, and in the future they are expected to support predictive medicine and personalised healthcare more effectively (Patrikainen 2020, 14).

Remote services and digital healthcare solutions are also likely to increase in the future. They enable healthcare and diagnostic services to be provided even when patients are unable to visit healthcare facilities physically. In my own work, this development has been utilised in the research and development project of my Master’s degree in Health Care. In this project, we designed a remote service channel for patients undergoing limited-channel overnight sleep studies (limited-channel polysomnography). Patients are able to complete the examination with the support of digital instructions instead of attending a traditional 30-minute guidance appointment. This reduces the need for staff resources and improves accessibility of healthcare services.

Wearable health technologies, such as smart watches and various sensors, may also transform health monitoring. Continuously collected health data enables the identification of new connections and earlier detection of diseases (Cukier 2014). In the future, digital information may become increasingly integrated into everyday life through intelligent interfaces and technologies (Mistry 2009).

Automation in laboratories will continue to increase. In the future, robots may participate in sample processing, sorting, and transportation, allowing biomedical laboratory scientists to focus more on quality assurance, problem-solving, and clinical interpretation of results. Autonomous robots are capable of cooperating and performing complex tasks efficiently, which may enable increasingly automated laboratory environments (Kumar 2012).

Despite technological development, healthcare will continue to require human expertise. The purpose of artificial intelligence and robotics is not to replace healthcare professionals but to support their work and free time for tasks requiring clinical knowledge, ethical judgement, and interpersonal skills. Collaboration between humans and intelligent systems will be a central part of future healthcare (Annunziata 2013; Kumar 2012).

The success of future digital solutions requires user-centred design, sufficient training, and technologies that adapt to the needs of healthcare professionals rather than requiring professionals to adapt to technology (Mistry 2009). The goal of digitalisation should be safer, more efficient, and more patient-centred healthcare, where technology functions as a tool supporting professionals.

Risks of an Open Digital Society

Digitalisation provides significant opportunities for developing healthcare, but an open digital society also introduces new risks. Healthcare organisations process highly sensitive personal data, which makes them attractive targets for cyberattacks. Data breaches, ransomware attacks, identity theft, and unauthorised access to patient information can have serious consequences for both individuals and organisations.

Cybercrime has become a professional and highly organised activity, where criminals often exploit people’s insufficient knowledge of cybersecurity and careless behaviour (Lyne 2013). Healthcare operations are also increasingly dependent on digital systems. If information systems fail or network connections are interrupted, the effects can quickly become visible in patient safety and laboratory operations.

One of the most significant challenges is privacy protection. Digital services, social media platforms, and various applications continuously collect information about their users, but not all users understand how extensively their data can be collected and used (Yen 2014). In healthcare, protecting information is especially important because patient data belongs to the most sensitive categories of personal information. Privacy protection is not only a technical issue but also a fundamental digital right. Ensuring privacy requires secure systems as well as users’ awareness of how their personal information is processed (Yen 2014).

In addition to cybersecurity, challenges include system failures, problems with data transfer, and the usability of information systems. These issues can directly affect patient safety and the quality of care (Patrikainen 2020, 15). Furthermore, a large amount of inaccurate health information is available online. Patients increasingly search for health-related information on the internet, but not all available information is reliable. An important role of healthcare professionals is to guide patients towards evidence-based and trustworthy sources of information.

An open digital society requires a balance between utilising technological opportunities and protecting individual privacy. The benefits of digitalisation can only be achieved when cybersecurity, ethical considerations, and users’ trust are integrated into the development of digital services.

The Effects of GDPR

The purpose of the General Data Protection Regulation (GDPR) is to strengthen the protection of personal data, increase transparency in data processing, and provide individuals with better opportunities to control their own personal information (EUR-Lex 2026). In healthcare, the importance of GDPR is particularly significant because patient information belongs to sensitive personal data. The development of digital healthcare services requires citizens’ trust, secure practices, and an understanding of how health data is collected, processed, and protected (Eriksen et al. 2024).

In my own work, GDPR is visible every day when handling patient information. Data is only processed when it is necessary for professional duties. Strong authentication, access control management, audit logs, and healthcare professionals’ confidentiality obligations are used to ensure that patients’ privacy and data security are maintained in all situations.

In my personal life, GDPR has increased my awareness of data protection. I pay more attention to the information I share online, use strong passwords, and utilise multi-factor authentication in services where it is available. I am also careful about what kind of information about myself or my children is shared on the internet. The amount of information collected online has increased significantly, which is why every user should understand the importance of their own digital footprint (Yen 2014).

One of the major benefits of GDPR is improved protection of personal data, increased transparency, and stronger individual rights regarding personal information. The regulation requires organisations to explain more clearly what data is collected, why it is used, and how long it is stored. In addition, organisations must consider data protection already during the design phase of services and implement appropriate technical and organisational safeguards (EUR-Lex 2026).

However, GDPR has also increased administrative work and costs for organisations. Meeting data protection requirements requires documentation, staff training, and development of information systems. In some situations, strict data protection regulations may also slow down information sharing because the legality of processing and transferring information must be carefully assessed before data can be disclosed (European Parliament 2024).

Although GDPR has increased responsibilities for healthcare organisations and other institutions, I consider it an important reform. It has strengthened the protection of personal data, increased individuals’ rights, and improved trust in digital services (European Parliament 2024). Especially in healthcare, confidence in the secure handling of personal information is essential for developing and utilising digital services in the future.

My Experiences with ChatGPT

As part of this assignment, I explored how ChatGPT works and tested its suitability as a support tool for information retrieval and learning in my own field. I asked it several questions related to laboratory science:

• How does haemolysis affect laboratory results?
• What are the most common preanalytical errors in laboratory testing and how can they affect results?
• How could artificial intelligence be utilised in clinical laboratories in the future?

The answers provided by ChatGPT were mainly clear, well-structured, and easy to understand. It was able to explain complex laboratory concepts in a simpler way and provide useful background information and practical examples.

For example, the answer concerning the effects of haemolysis on laboratory results was mainly correct and demonstrated an understanding of the basic principles of laboratory processes. However, the response also had limitations. It did not include references and did not consider all method-specific and laboratory-specific differences. Therefore, information produced by artificial intelligence cannot be used directly as a basis for professional decision-making. The information must always be critically evaluated and verified using reliable sources.

Artificial intelligence is also not able to assess an individual patient’s overall situation in the same way as a healthcare professional. Laboratory results must always be interpreted together with the patient’s symptoms, medical history, medication, and other examination findings.

However, I consider artificial intelligence a very useful tool. It can support learning, information retrieval, report writing, summarising research, and organising work. In the future, artificial intelligence may also support laboratory work, for example in quality management, result analysis, and processing large amounts of data.

Based on my experience, artificial intelligence works best as a support tool for professionals. It can accelerate information processing and help understand complex topics, but it cannot replace professional critical thinking, clinical competence, or responsibility in decision-making.

Self-Evaluation

Completing this assignment increased my understanding of how significant the impact of digitalisation is on healthcare and laboratory work. I gained a deeper understanding that ICT and digital solutions are no longer only supporting functions but are an essential part of patient care, laboratory processes, and the entire healthcare system.

During this assignment, I learned that digitalisation provides significant opportunities to improve patient safety, work efficiency, and accessibility of healthcare services. At the same time, I realised that the use of technology also involves responsibility regarding data protection, cybersecurity, and ethical decision-making. Successful implementation of digital solutions requires not only technology but also user training, involvement of professionals, and effective change management.

Testing ChatGPT helped me better understand the strengths and limitations of artificial intelligence. AI can be a valuable tool for information retrieval, learning, and supporting professional work, but its outputs must always be evaluated critically. It cannot replace evidence-based knowledge, professional expertise, or the responsibility of healthcare professionals in decision-making.

In the future, I would like to develop my competence especially in the following areas:

• artificial intelligence and machine learning in laboratory medicine
• healthcare data analytics
• cybersecurity and data protection
• digital quality management
• laboratory automation and future technologies

Overall, this assignment strengthened my understanding that in future healthcare, technology, artificial intelligence, and professional expertise will work increasingly closely together. The goal of digitalisation is not to replace humans but to support healthcare professionals and enable safer, more efficient, and more patient-centred healthcare.

As part of this assignment, I also commented on two other students’ articles, which provided new perspectives on digitalisation, artificial intelligence, and data protection in healthcare:

DIGI SOCIETY | Sami’s site*

DIGI SOCIETY | Bluestream Blog

References:

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Conti M. 2016. The incredible inventions of intuitive AI. Ted talks. https://www.ted.com/talks/maurice_conti_the_incredible_inventions_of_intuitive_ai. Retrieved 10.7.2026.

Cukier, K. 2014. Big data is better data. Ted Talks. https://www.ted.com/talks/kenneth_cukier_big_data_is_better_data. Retrieved 6.7.2026.

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