The age of big data is upon us. Experts estimate that in today’s world, every two days, more data are produced than were created in human history up to 2003.
Thanks to rapid advancements in technology and analytical capabilities over the last decade, large amounts of raw data can now be handled and studied with relative ease. We hold high hopes for big data and the potential it can have in healthcare, in terms of diagnosis, prevention and decision-making.1 But while many people believe ‘the more data, the better’, others are more concerned with focusing on more specific, finite data on a lesser scale; or what we sometimes call ‘small data’.
Essentially, this refers to data on the scale of individual patients, which is relatively easy to handle, and can be used by physicians during consultations to tailor care.1 It focuses on a single person, rather than giant data sets: it’s a patient’s medical history, the information discussed during a consultation, the step count measured by a Fitbit.2 With big data, we can enhance evidence-based medicine, and with small data, we have patient-centric medicine.
As the number of digital health solutions has soared over the past few years, so has the amount of personal health data collected and which individuals are able to access at their leisure. With wearables such as the Apple Watch, people can now increasingly monitor their health, and collect a whole host of their own valuable health information—a topic we explore in a recent article. So even though it’s not big data, the volume of small data is still increasing, and physicians don’t always have the time to analyze all of the information available, or to act upon it.3 So how can we efficiently collect and collate this data, and use it to our advantage?
A start-up called Doctella has aimed to at least partially bridge this gap, by creating a central repository for such data. Their solution is an online system in which physicians can quickly and inexpensively create simple apps for individual patients, based on their personal data, using iOS frameworks like Apple HealthKit and ResearchKit. The data derived from remote patient monitoring, (through wearables or other medical devices) links up to the Doctella app, which physicians can then access and analyze. The online solution strives to provide healthcare professionals (HCPs) with an easy way to collect their patients’ data in one place, and subsequently intervene on a case-by-case basis.3,4
With so many varying treatment requirements across a population, and different care plans across each hospital and clinic, Doctella CEO, Amer Haider believes that there’s a huge need for personalization in healthcare.4 But why can’t big data analytics benefit the individual, and equally, small data analytics inform the treatment of future patients? One could argue that electronic medical records (EMRs) are the intersection between the two types of data; helping to blend the fields of research and care. Millions of small data are fed into the EMR system, creating big data sets, which can then be analyzed and used to inform evidence-based medicine, and (ideally) benefit the health of individual people.1
But both big and small data are associated with some concerns in the healthcare space. There’s still the challenge of collecting the ever-increasing volume of small data (which services such as Doctella has begun to address), and ensuring that this information is being interpreted and used correctly to inform care. While the use of wearables and personal medical devices is increasing, there are still cost considerations which are hindering the uptake of these new technologies, and thereby the efficiency of small data collection.5 When it comes to big data in healthcare, the disparity of structures across different systems poses difficulties, in terms of quality assurance and analysis. There are major concerns in terms of privacy and confidentiality due to the sensitive nature of healthcare data, and when information storage is centralized, it becomes highly vulnerable to attacks.6
Overcoming these challenges won’t be easy, but if we can manage it, we can integrate the widespread use of both small and big data into healthcare systems, so we can start to truly see their benefits. Increasing knowledge and understanding of data usage in healthcare will help to encourage its uptake, while the technological advancement of EMRs could aid the creation of a system where every HCP-patient interaction drives both patient-centric and evidence-based medicine.1 With such a process, the borders of research and care would begin to blur, and give rise to a system which benefits both the population as a whole, and the individual.