Throughout the health care industry, clinical quality has traditionally been measured on an ad-hoc basis. Instead of attempting to collect and collate typically slippery subjective outcome reports into larger wholes, most organizations have settled for looking in the aggregate only at those measures that were most easily quantified. While this approach could sometimes produce some useful insights, the reality is that it never really put into reach the true potential of clinical quality improvement.

That is now changing quickly, however. As the federal Medicare and Medicaid programs have sought to incentivize health organizations to move toward electronic records and analysis, many state and county-level bodies have joined the fray. Today, there is a great deal of pressure being exerted in this direction, whether of a positive sort that takes the form of financial incentives or other kinds that involve penalties.

That means that many health organizations, even the most traditional and conservative of them, are finding themselves forced into a period of transition. While the promise of quality improvement in healthcare is a powerful and attractive one, this period of change can also be difficult. How to begin clinical quality improvement is a question that does not always seem easy to answer, but the reality is that there are some good, well-understood principles that can help.

One of these is that clinical process improvement cannot occur without good means of making measurements and collecting and analyzing them. In organizations where an older way of doing business has prevailed for many years, everyone from doctors and nurses to administrators can be resistant to making this leap. For this reason, overcoming this inertia has to be a key goal of those entrusted with seeing an organization through this period of change.

The reason that this is so important is that inaccuracies and quality measures in healthcare other deficits, if left to fester, can do worse than prevent fruitful analysis. They can actually contribute to mistaken ideas about where inefficiencies and ineffectiveness lie, turning the goal of improved health outcomes squarely on its head. Making use of powerful analytic techniques to improve health care quality requires more in the way of measurement rigor than in the past, and this has to be recognized at a fundamental level.

With this relatively straightforward principle in mind, though, the way forward tends to become clearer in and of itself. As many organizations are discovering, pushing ahead with the process can be among the most rewarding challenges of all to accept.