As healthcare technology advances, there will continue to be even more platforms for collecting and storing patient data digitally. While these systems are convenient and efficient for healthcare providers, not all communicate and share information, creating data silos.
Data silos occur when you have patient data stored on different systems and applications that do not communicate with each other. A patient that sees multiple healthcare providers will have data repeated or hidden on the systems used by those providers. Data silos in healthcare can also occur within an organisation if multiple departments use different applications. Silos create various challenges for healthcare providers, making it difficult to comprehensively understand a patient’s health status, medical history, and treatment options.
Breaking down these data silos is a critical step in improving patient care. From obvious reasons, like giving patients access to their data, to newer use cases, like leveraging machine learning, here are four reasons we must break down these silos.
Enabling data-driven decision-making
Data silos in healthcare prevent providers from accessing all the necessary data required to make informed decisions and provide the best possible care. In one survey, only 20% of participants said they fully trust the data available to make decisions.
Breaking down data silos is crucial for enabling data-driven decision-making. Integrating data from different sources gives healthcare providers a more comprehensive understanding of a patient’s health status, medical history, and treatment options. So they can make more informed decisions and better tailor care to the patient’s needs.
One example of how data-driven decision-making has improved patient care and outcomes is analytics. Analytics can help healthcare providers identify patients at risk of developing chronic conditions such as diabetes or heart disease. They can then establish proactive treatment plans that prevent the onset of these conditions.
Improving privacy and security in healthcare
Data silos in healthcare can also affect privacy and security. When you have data stored across different systems, each with its own authentication process, the risk of a data breach increases. Each system needs to be secured separately, and a strong security model in one system does not mean the other systems are secure. Identifying the people accessing the data in those silos also becomes more complex, leading to unauthorised access and compromised patient privacy and security.
Breaking down data silos is crucial for improving privacy and security in healthcare. By integrating data from different sources, healthcare providers can develop a more comprehensive view of patient data, making it easier to identify who can access patient data and monitor breaches. Integrated systems with modern authentication processes, such as single sign-on and MFA, mean there is only one platform to manage access controls and permissions, enabling providers to prevent unauthorised access to patient information.
Putting patients in control with access to their data
Breaking down data silos in healthcare is crucial for giving patients access to their own data. By integrating data from different sources, patients can access a comprehensive view of their health information, enabling them to take a more active role in managing their health. In this way, breaking down data silos can improve patient outcomes by facilitating more informed decision-making and empowering patients to take a proactive approach to their health.
Patient portals and patient digital front door systems are examples of how breaking down data silos in healthcare has given patients access to their data and improved patient care and outcomes. Patient portals are secure online platforms that allow patients to access their health records, schedule appointments, and communicate with healthcare providers. By integrating data from different sources, patient portals provide patients with a comprehensive view of their health data and connect them with providers, enabling them to take a more active role in their own healthcare journey.
Harnessing the power of machine learning
Machine learning (ML) uses algorithms to learn from data and make predictions or decisions. In healthcare, it can help providers identify patterns and trends in patient data, make more accurate diagnoses, and develop personalised treatment plans.
However, data silos in healthcare pose a significant challenge for machine learning applications in healthcare. Data silos can result in incomplete or inaccurate data, leading to incorrect predictions or decisions by machine learning algorithms.
Breaking down data silos is essential for machine learning in healthcare, enabling providers to integrate data from different sources and creating a more comprehensive and accurate dataset. In turn, ML algorithms have the data to make more informed predictions and decisions that deliver better patient outcomes.
Conclusion
Breaking down data silos in healthcare is critical for improving patient care and outcomes. Healthcare providers can give patients personalised, coordinated, and effective care by enabling data-driven decision-making, harnessing the power of machine learning, improving privacy and security, and putting patients in control of their healthcare information so that they take a more active part in their healthcare journey.
Data silos can create significant challenges for providers, patients, and the system. However, by breaking down these silos, integrating data from different sources and enabling interoperability, healthcare providers can gain a comprehensive view of a patient’s health and provide more effective care.
How Fluffy Spider can help you break down data silos in healthcare
We help organisations move toward a future of connected digital healthcare, making existing systems interoperable and modernising infrastructure to unlock the potential of new technologies.
We can help you identify the relevant opportunities to incorporate modern web services and standards for health information exchange, such as HL7 and FHIR (Fast Healthcare Interoperability Resources). We enable systems to interoperate with other modern health information exchange technologies from the medical software industry and those already implemented by large healthcare providers such as Government health departments.
Visit our Healthcare Integration Services page to learn more about our capabilities and solutions.
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