One of the major goals of the federal government's push for nationwide electronic medical record adoption is to create an information network where "health data can flow freely, privately, and securely to the places where they are needed." So far, this is proving to be a challenge for the nation's hospitals and doctors.
Software Advice thinks that this problem presents an opportunity for Google to take a big step into the healthcare IT market in 2010, following other major companies like Microsoft, I.B.M. and insurance giant Aetna. Through their Books project, Google has shown that they can scan, interpret and index a high volume of books in a relatively short amount of time. Unstructured medical records – those not neatly organized within an interoperable EMR system – could be managed in the same fashion. Google possesses many of the requisite skills and technologies to solve this problem.
However, to be successful, Google will have to figure out these issues:
* How to gather structured and unstructured medical data on a large scale;
* How to share and make that data accessible (searchable) to people; and,
* How to comply with privacy regulations.
With Google Health rumored to be on the back burner, working with hospitals and medical providers to aggregate and organize medical data could be Google's window into the growing market that is healthcare IT. Here's how they can do it.
The Benefits of Digital, Private & Secure Health Data
The driving force behind the government's $19 billion EMR incentive program is that medical record software truly can transform the United States' healthcare system for the better. EMR advocates have long touted the software's ability to reduce medical errors, improve clinical decision making, empower patients, and reduce the costs of a bloated system.
When medical data is in digital form, it can be sorted, searched and analyzed at a higher rate of efficiency than paper charts. When implemented correctly, EMR software beats paper charts in efficiency, accuracy and cost savings. The problem that Google can possibly fix is the fact that a majority of health data in the U.S., both historical and current, is in paper form.
Structured & Unstructured Data
Medical data comes in essentially two forms: structured and unstructured. Structured data is information that comes in numbers, tables and rows, for example. It's data that is disciplined and predictable. In the medical world, examples of structured data include insurance codes, HL7 standards and other diagnosis codes. Structured data, relative to unstructured data, is easier to aggregate and analyze.