In part one of this two-part series, Jennifer Goldsmith, Tendo President, discussed the problem of disconnected healthcare data and the complexity of data maintained in EHR systems. In part two, she dives more deeply into personal health and wellness data as well as how complex care and the rise of advanced testing contributes to the data disconnect. Personal Health & Wellness Data The rise of personal wellness tracking applications and devices — as well as medical-grade, consumer diagnostics tools — has forever changed the scope of healthcare information. Unlike the medical information resulting from provider interactions, this information is not captured in an EMR. Further, these data streams are often continuous – rather than episodic – showing trends over time versus a single point-in-time view. Wearable devices, such as Fitbits and Apple Watches, have become almost ubiquitous, capturing a continuous stream of information, such as heart rate, body temperature, sleeping patterns, and more. Additionally, more specialized devices are now available to consumers to capture critical information outside the context of a physician’s office. For example, a patient may experience what could be a heart arrhythmia, but it is intermittent and does not occur during visits to their cardiologist’s office. Simple-to-use and portable consumer EKG devices that are FDA-cleared allow patients to capture this information at home and as symptoms occur, providing another window into the patient’s health that goes beyond the four walls of the traditional healthcare provider. With each year, these personal devices improve in both accuracy and data capture and provide another critical tool to clinicians when diagnosing and treating patients. This persistent, longitudinal data captured in real time adds rich insight into patients’ health histories that can assist healthcare professionals in bolstering both health and wellness. The problem, however, is that patients and doctors need a single source of truth across providers, towns, and devices. If a patient goes to an urgent care, then meets with their primary care provider, then follows up with a specialist who recommends a wearable device, the result is numerous sources of truth, which results in no real source of truth at all. While the body of personal health and wellness information continues to increase at an astounding rate, there is still no standard and operationalized way of capturing and digesting data from these types of digital devices. And, while this information is important, it is another set of data points that individual patients need to manually collate. Combining the insights from outside the bricks-and-mortar provider setting with traditional medical information is crucial to creating a 360-degree view of the individual. Without seamless integration, the sources, volume, and complexity of health information will continue to grow, and the problems will compound. Complex Care and the Rise of Advanced Testing Up until now, each twist of this Gordian knot represented more common patients – those who are relatively healthy with occasional injuries or illnesses. However, there are millions of people who suffer from chronic disease, rare disease, cancer, and multiple diseases simultaneously. These complicated patients add another level of complexity to the data interoperability challenges as they often see multiple specialists or need to go to various hospitals to get treatment. It becomes a tangled web of data points. Further complicating the healthcare data picture is the rise of genetic and other testing to better understand complex conditions. Today, when a patient is diagnosed with a serious disease, there are often diagnostic tests ordered to better understand the nature of the condition and the best pathways to care. In many cases, the results of these advanced diagnostics are delivered as unstructured information (i.e., a paper document, PDF, etc.). As such, critical data elements are often lost in paper results documents or attachments in the EMR where both patients and clinicians must manually cross-reference that information with other healthcare data. The impact of this manual collation of data can be seen in everything from clinical decision-making to the identification of potential clinical trial participation. Additionally, some genetic profiling has moved outside the walls of the HCO and into the hands of the healthcare consumer. Direct-to-consumer testing through third parties, such as 23andMe, Ancestry, or emerging consumer lab testing companies like Everlywell, has spiked in the last five years as home kits have become easier to use, more available, and less expensive. In fact, the global direct-to-consumer genetic testing market is expected to grow at a compound annual growth rate of 22.84% between the years 2017 and 2028. With both clinician-prescribed and healthcare consumer-driven testing on the rise, there is an opportunity to harness this information to drive better decision-making on both the part of the patient and the clinician. However, until this data is unified with the rest of an individual’s health information and readily accessible to those who need it, the utility of this testing data will remain limited. A Brave New World of Interoperable Healthcare “But everyone belongs to everyone else.” – Aldous Huxley, Brave New World In contrast to Aldous Huxley’s futuristic “World State,” where the things that make each individual unique have been removed, the real world is composed of billions of biologically complex human beings, each similar in some ways, but different in many others. We are at an inflection point where modern science and modern technology have intersected to create the perfect storm of data dysphoria – a twisted knot of medical data threads. But imagine what could be achieved if we could bring all this medical information together to create a single, streamlined, and accurate medical view? And in a way where additional data sources in the future could be easily sewn into that same patient’s medical tapestry? Achieving this personalized new world becomes more imperative with each passing day, too. Healthcare data is exploding, as well as the diversity of data sources. And, as that data continues to grow, so do the opportunities to dramatically improve care, increase health equity and access, and reduce the burden on clinicians and patients. In this world, clinicians would have easy access to comprehensive data on individual patients, and patients would receive better care with less stress and frustration. Ultimately, this care model would yield a medical system less burdened by cost and more empowered to provide quality treatment to every person across every demographic. Don’t miss part one of this two-part blog.