Walk into twenty different doctors in twenty different states and you’ll find twenty different software systems running their practices. Die under their care and your death will be recorded in twenty different ways. The problem is as old as the states themselves and the practice of medicine within their distinct borders. Where data is concerned, uniformity matters. In medical terms, our inability to manage data can and does lead to deaths.
Covid has highlighted these systemic craters in the US medical landscape, showing them up for what we have always known them to be. A major impediment to the delivery of effective healthcare across America. We can now contemplate a manned mission to Mars in the next decade but can’t match data between two hospitals separated by less than a mile.
As Covid developed and spread across the US, it became glaringly obvious there were massive constraints in terms of the free sharing of data based on any industry standards. There are none. No standardization exists. An excellent example provided by a colleague highlights this.
A pre-term birth in Texas, at 20 weeks, results in the death of the infant. Our lungs only develop at 23 weeks. The death certificate issued in Texas will list asphyxiation as the cause of death. Arguably, the baby was doing perfectly well until the mother unexpectedly went into labor. So shouldn’t the real cause of death be exactly that, premature labor? Other states think so and may use that as the cause of death.
Researchers delving into preterm deliveries and mortalities associated with it have to manually sift through data from 50 states, account for variances in the way the data is collected and interpreted, and then reformat the data into a system that accounts for all these variables. It is an impossible task. The end result is that the benefits of the actual data collected are lost, permanently.
Identifying disease trends and prevalence, treatment outcomes, drug efficacy, spikes in notifiable diseases and any other use you care to attach to the data become all but impossible. This results in two very distinct outcomes. Poor response times and poor delivery of care based on evidence, the cornerstone of effective medicine. We are drowning our patients and caregivers in a worthless sea of uninterpretable data. It is unsustainable and patently stupid.
Again, in Texas, a doctor friend’s office has one electronic health record. He works with various hospitals in the area. One hospital uses its own proprietary system. The other two hospitals both use Epic. None of them can communicate Covid results to each other without someone manually inputting the result from one system to the other. The duplication, the loss of man-hours, and the lack of transparency simply beggar belief.
When you are forced to resort to Facebook and Twitter to share information about potentially beneficial results in treating your pandemic patients, we know the system is broken. When you cannot medically assess your population at glance, you lose the ability to respond in a timely fashion to threats. You lose the ability to assess the efficacy of treatments across a population. All of which boils down to one simple thing. Poorly managed and mismatched data aggregation resulting from fragmented systems. No standardization.
Medicine understands and obeys protocols. The practical implementation of treatments functions more effectively within a predetermined set of parameters, created by the industry, for the industry and that evolve along with the industry. The same needs to hold true of the software that endeavors to understand, collect and sort the data the industry produces. Its primary purpose must be to serve the industry.
America’s IT health issues stem directly from its political system and the autonomy enjoyed by states over their own healthcare and health software. It simply promotes fragmented solutions. Add insurance companies, federal systems, and pharma to the mix and the complexity of a “one system for all” solution becomes apparent.
Hospitals who wish to protect their financial models, income streams and other data are loathe to share. Financial motives outweigh the overriding need for open transparency. These are issues that occur within the confines of the same city, and when distances move these treasure troves of data into different states, any hope of meaningful data sharing is all but lost.
To formalize or standardize this turbulent sea of data, the industry must develop a clear and medically relevant set of healthcare data standards. Guidelines that allow national and state-wide access to data for caregivers, patients, stakeholders, and regulatory authorities. It is an insanely simple task, complicated to impossibility by the interference of influences from outside the sphere of healthcare.
Politics, law, legislation, profits, and privacy issues notwithstanding, the ever-increasing fragmentation needs to be addressed now. Not by outside parties, but by those who intimately understand the inner workings of the industry. We may be divided geographically and politically, but our physiology and susceptibility to illness remain a global shared constant.
This is the foundation we need to build from, never losing sight of the end goal. The effective and timely delivery of meaningful care for patients. They are, after all, the reason the industry exists.
Past Failures and Present Day Winners
Remember Google Health and Microsoft’s brave version. They were going to conquer health and change the world. It’s been a decade. Neither has achieved much, not even a perceptible dent or scratch on the surface of healthcare in the US, and this failure is telling.
Change cannot be driven by agents outside of the industry. Patients can also not impact this eco-system in a meaningful way. It is the caregivers that matter most, the individuals who use the systems, day in and day out, in the pursuit of their noble cause. These are the individuals who can and must demand standardization, who must enforce conformity for the data they produce to enable the amazing benefits we currently blithely ignore.
Oklahoma has done things right. Their medical system functions incredibly efficiently. Built by doctors for doctors, it has served the state well and this system, along with others can provide hugely valuable insights into a real-world working model for efficient medical data sharing.
In much the same way Android and Apple can both access the internet and the data it contains, despite their glaringly different operating systems, healthcare needs to set about creating its own intranet. Call it Mednet or Healthnet, it really doesn’t matter. Just build it. It is medicines “Field of Dreams” moment. Build it and they will come.
Ask me what I see for medicine, ten years from now and you better have a chair handy. Essentially it is this.
Medicine is a trailblazer when it comes to embracing new technologies, often an early adopter and equally often, an innovator. In ten years and possibly far sooner, your smartwatch will save your life. Data it collects will be fed back via a secure network to your healthcare provider. Automated triggers will be enacted allowing your doctor to schedule medical interventions, adjust medication dosages and monitor your overall health.
This streamlining of services will only become possible once the healthcare industry develops those standards we were discussing. That way Apple and Android will know exactly how to connect to healthcare’s internet. Standardized protocols matter. They enable the rapid development of supporting software, products, and services.
Imagine in 2020, if we’d been able to pick up by location, spikes in body temperature for covid infected Americans. Arguably, millions of infectious people could have been isolated or quarantined within hours. Time matters, responses matter. Both require standardized data. We need to use the impetus covid has provided to make work of this.
That elusive commodity we have come to take for granted. Any system is only as good as the data it can collect and without widescale adoption, the system fails. Trust plays an integral part in the delivery of effective healthcare. Compromise the ability of the public to trust and you are lost, Again, covid has provided a rude wake-up call, vaccines being the casualty in this instance.
Wide-scale abuse of patient data is prevalent in the industry, accompanied by unethical practices, including the illegal harvesting of patient DNA. These practices need to be vigorously outlawed and policed to restore public faith. To restore trust.
Take Facebook and Apple as an excellent analogy. Facebook enjoys almost no trust in the public mind relating to its data collection and use. It’s one of the reasons I don’t use the Facebook platform, but I happily let Apple intrude on my life. The difference. Trust.