Imagine a world where you go to the doctor and they are able to see your activity levels, food choices, heart rate and sleep data as you choose to allow and they are able to see this all in one place through your electronic medical record (EMR). While many other areas of our lives enjoy this type of connectivity for example our location data informing restaurant recommendations and organizing our day or our historical data informing personalized search results. Unfortunately, the healthcare many of us receive today is fragmented, which can lead to costly and less effective care. However, it is not the lack of high quality technology that is holding patients and society back from receiving better care and outcomes- it is outdated data policy.
Data policy holds significant potential to enable the unmet need of better connectivity of data in healthcare; we need to modernize data policy from analogue to digital. Connected data can enable healthcare to become smart, by benefitting from learning and applying the latest innovation in real time. Apps guide you to the nearest doctor, offer counseling for mental health and you can be in the driver seat of what health data you would like to share with your doctor.
Data privacy and protection need to be at the foundation of policy change. If data privacy is developed and implemented effectively it should liberate data and empower patients and citizens to exercise control over what data they share, with whom. However, despite some data privacy regulations’ intention to achieve this, they are being implemented in a way that locks down that data, making it difficult to access, share and use. Data protection will ensure that when data is exchanged it is done so in a safe way. And that data needs to be able to flow beyond borders, enabling global data flows as research and innovation in healthcare are a global activity. Therefore, data policy requires quality and interoperability standards that are set on a national, if not international level. This helps to ensure that we are comparing apples to apples when deploying artificial intelligence and machine learning in delivery of clinical decision support and other healthcare tools dependent on data at scale.
Besides privacy, protection and standards, data policy requires collaboration across stakeholder groups in the healthcare system and other sectors. Data policy may be designed across sectors independently but comes together under data governance of health data ecosystems. The role of data governance is expanding and evolving, which makes it key in building trust among data partners. It requires health system leaders, policy makers and data partners that traditionally would have viewed data governance as a technical topic to address data governance early on in data projects and the establishment of data ecosystems. They need to consider who gets access to data, for what purposes and how that data is shared. What are the standards needed to ensure that data can support data partners in achieving their respective goals and they are interoperable with other relevant data sources. All while ensuring data privacy is respected and data is protected.
All challenges aside: if we break down data policy and address it’s individual parts while maintaining the overarching objective to enable connectivity of data to deliver optimized care for patients, we can realize a higher potential of electronic medical records.
