For most of us it may have slipped under the radar, but in December a groundbreaking Patient Demographic Data Quality framework was jointly released by a US government agency and the CMMI Institute.
In response to findings that many “safety-related events were caused by or related to incorrect patient identification”, the Office of the National Coordinator for Health Information Technology (ONC) worked with CMMI to develop the PDDQ Framework in order help organizations implement effective, sustainable data management practices around patient data management.
Groundbreaking? Yes. As a lean framework appropriate for small business the PDDQ shows how you can rightsize the Data Management Maturity Model to match your situation. That it is freely available demonstrates CMMI’s commitment to improving data quality in healthcare. Continue reading
The well-publicized problems with healthcare.gov are disturbing, especially when we remember they might result in many continuing without health insurance. But it seemed a step in the right direction when recent a news report differentiated between “front end” and “back end” problems. The back end problems were data issues, like a married applicant with two kids being sent to an insurer’s systems as a man with three wives.
Coincidently, I recently responded to a questionnaire about health care data. I’ve paraphrased the questions and my responses below. Perhaps the views of someone who’s spent a lot of time in the health care engine room might provide some useful perspective. Continue reading
It is really bad, according to a recent survey by the Ponemon Institute (available here with registration). The white paper, entitled Health Data at Risk in Development: A Call for Data Masking, presents the results of a survey of 492 health care IT professionals on their companies’ practices regarding use of live personal health care data in application testing.
It makes a scary read. Here are the lowlights: Continue reading
Who would want to be a national health care administrator? Who would want the responsibility for managing health care and formulating health policy for tens or hundreds of millions of people? It seems obvious that such decisions would rely on quality data. A recent interview impressed upon me how much data managers can learn from a field where data recording millions of separate life and death decisions aggregates to support decisions on the future allocation of health care resources.
The Atlantic, not typically a technical rag, recently presented an article by business and economics editor Megan McArdle on health care data integration entitled “Paging Dr. Luddite”. The article brings to a mass audience an understanding of both the importance and difficulty of data integration, but the title and general anti-healthcare-professional tone seem counterproductive.
I’ve worked with health care data for the past few years, and in a recent conversation I realized it might be valuable to detail some of the complexities of health care data for those who might enter this growing field. Of course these considerations aren’t unique to health care, but they are typical of the challenges that the new health care application developer or analyst might face. Continue reading