The landscape of healthcare is evolving gradually, and albeit slowly, the main healthcare actors cannot afford to ignore new technologies any longer. Interestingly enough, the first thought that comes to mind when talking about technology in healthcare is new medical equipment: Better machines for better diagnoses.
However, there’s an important aspect of technology that is too frequently overlooked when in the medical world, and this is everyday tech such as computers and, more importantly, data. Despite regular updates and discussions on data usage and privacy in the healthcare sector, data protection still remains a core issue. In fact, one of the largest data breaches of 2023 happened in Massachusetts, at the Shields Health Care Group where a cyber-criminal managed to steal the personal data of 2.3 million individuals. This information compromised included Social Security numbers, dates of births, home addresses, and even healthcare history and providers.
Needless to say, this places again the question of data in healthcare at the center of all debates. Is it truly safe to use data in the healthcare sector when we know the consequences of misuse or loss?
That is probably why one of the foremost challenges in healthcare data management remains to be able to ensure compliance with national and international data regulations, such as GDPR (General Data Protection Regulation) and HIPAA (Health Insurance Portability and Accountability Act). These regulations are designed to protect patient privacy and confidentiality, providing a legal framework that healthcare organizations must adhere to. But with little to rely on, patients have no other option but to “trust” healthcare specialists with their data. It goes without saying that places such as the Shields Health Care Group were not necessarily careless with their patient data. Breaches are prone to happen in an industry where the operational budget prioritizes case management and acquisition rather than data protection. As such, data breach incidents are a recurring occurrence that highlights the critical risk for patient data.
Yet, reliable, accurate, and accessible data are the lifeblood of effective healthcare. Access to comprehensive patient data enables healthcare professionals to treat and diagnose their patients more effectively and rapidly. Data can, therefore, save lives by providing unique insights that lead to quicker and more accurate decisions.
For instance, having a complete medical history of a patient readily available and access to similar cases that can be identified based on symptoms can significantly improve the diagnostic process. Data is knowledge, and knowledge will always remain essential in preventing misdiagnosis and ensuring the right treatment is administered promptly. Yet, healthcare centers need digital systems that are both scalable and secure to transform their digital patient data into a powerful knowledge management platform.
The integration of AI into healthcare is promising when it comes to making sense of large volumes of data. AI-driven diagnostic tools can help physicians make more accurate and timely assessments. AI has the potential to revolutionize the healthcare landscape, making it more efficient and precise. However, AI brings a new dilemma in its over-reliance on data. It takes large volumes of data to constantly train an AI system. When data usage is a worrying and often uncontrollable unknown in the healthcare sector, solutions that feed on data only are a source of concern.
Striking a balance between data accuracy, safe data collection and storage, and data privacy becomes a challenge the healthcare sector has to overcome to grow.
