I have a vested interest in better health informatics at the primary care level, both because I am a patient and because of my consulting relationship with Cielo Medsolutions LLC. In the current political environment, with its emphasis on throwing money at the problem, I fear for the public health. Bad health IT is worse than no health IT.
How would I define good health IT at the primary care level? I define it in terms of accuracy and completeness. For your electronic health record (EHR) to be accurate and complete, the information in it must be up-to-date and cover all key facts about the state of your health and the care provided to you. Because many patients have multiple providers, this means that your EHR must be available to all participating care providers, both to read and to update.
Providers often use different EHR systems from disparate vendors, most of whom store data in proprietary formats, and each of whom has a fiduciary responsibility to its shareholders to resist dilution of control over the health information managed by the vendor's software. Moreover, providers belong to different HIPAA covered entities (i.e. custodians of records containing HIPAA-protected health information).
Thus the challenges in achieving a seamlessly integrated health record are daunting, spanning the technical, political, and regulatory realms. Nonetheless, their is a significant push at the Federal level with bipartisan support to achieve health information integration.
Third-party payers have already compelled a degree of standardization with respect to some of the information in the EHR, though the information they need for efficient claims processing is only a subset of what is needed from the care provider perspective. Adequate or no, at least it's a start.
In addition to the provider and vendor challenges, both because providers can make data entry errors and because the patient does not always take the provider's advice, the record must also be available to the patient to read and update. This latter problem is a matter of providing a patient portal to the integrated EHR shared by the providers, and while it presents its challenges, this is an easier problem to solve than getting to the integrated EHR in the first place.
Solving the political challenges, both inter-vendor and at the governmental level, is outside my scope. I do, however, have some insights into the technical challenges to health information integration, in particular the syntactic and semantic obstacles that must be overcome.
Getting information out of proprietary systems is essential to making it available for integration, and there do exist commercial entities who specialize in "cracking" proprietary schemas. Recently, though, I learned of the existence of an Open Source initiative in this arena, which brings me to the interview linked below from opensource.com. In it, Jason Hibbets of Red Hat interviews Matt Mattox of Axial Exchange, a company that provides an Open Source data interchange appliance and sells services related thereto.
I'll provide a taste from the interview, and leave you to read it (or not) without further commentary on my part. I'm still investigating them so I can't provide an opinion of any sort with respect to Axial, but I do have to say I find their business concept highly intriguing.
When you take a system where suppliers create their own demand--which is what happens when physicians both diagnose and treat illness--and combine it with model where a third party picks up most of the fees, costs can rise quickly.
In terms of the care model, the physician practice and acute care hospital were designed in the early 1900s. Medical knowledge has evolved dramatically since then. Today, there are relatively inexpensive ways to treat conditions that a century ago were understood only by their symptoms. We have an opportunity to re-organize our institutions around the state of the science.
These changes won't happen overnight. The first step is to extract data from locked-down proprietary systems so that health information can be made available to the appropriate people at the appropriate times. Once the data has been freed, we can begin to innovate around new care and payment models. Freeing clinical data is the problem we're working on at Axial.