I’ve had the opportunity to work in health data for a while now. There are most definitely gradations and ranks in the data verse career list. In my first role as a health technologist, I learned a massive wealth of experience and practical knowledge about what works and how to achieve small (and large) goals.

Working at smaller health care centers, often somebody will need to do double-duty in the clinic. For my work at Ke Ola Mamo in Honolulu, I not only built out the Cognos engine for our analytics, but digitized paper records, helped developed workflows for case managers, and customized the electronic medical record system to fit the clinic needs (probably saving the organization $20,000 or so in consultant fees).

In addition, I mapped the clinic population to KML for Google Earth and build a reporting engine to extract system data and deliver staff productivity reports to management. Importantly, keep in mind this was my first job in healthcare analytics.

Had this been a larger health system, my role would have been much more constricted and specific. The breadth of the work role was mandated by the lack oF IT staff and the available budget, not necessarily the original job description. When I saw an opportunity to develop or experiment with data in one of its permutations, I grasped it (hence the reporting engine and KML analysis). For this, I’ve got three points of advice: 1. I acted first, 2. My typical method was that I informed management of my end goals rather than processes, and 3. I understood that not all my development efforts would be rewarded equally.

Indeed, the prime element about #3 is crucial: not everything will succeed. Often multiple incarnations of a project are required to have a polished result – Rome wasn’t built in a day. Undertaking projects involves being able to spend the concentrated time and focus until you’ve got working results. The world is big on people who dream big, but fruitful action is in short supply.