4. Embrace complexity, deliver transparency! With many healthcare providers supporting more than 30 systems which collect and store data, there is no doubt the average healthcare data landscape is full of complexity. Don’t try to boil the ocean in a week – pick a subset of data systems and think about the obvious connections and how to simplify those relationships. For example, linking clinical and workforce data together can deliver fascinating (and valuable) insights. Are patients more likely to fall during a shift change? What impact does shift pattern and resource availability have on the discharge process? The data is complex, but the insights need to be beautifully simple and transparent.
5. Enable discovery, don’t force it! This point might appear obvious and comes from the "teach a man to fish" school of thought. Healthcare employees are highly intelligent, naturally analytic thinkers – what can be a better example of analysis than diagnosing a condition? The most successful programs I have seen embrace this by enabling discovery for all, taking advantage of the combined IQ of the entire workforce. Insights discovered at the top and pushed down are never, I repeat, never as effective as those uncovered by the teams at the coal face. Identifying and reducing unwarranted clinical variation is by far the best example of this in the healthcare setting. When clinicians are engaged, trust the data and able to quickly and easily see their behaviors compared to their peers, amazing things start to happen. Variation reduces impacting costs, quality, length of stay and patient satisfaction. Naturally competitive teams strive to be the best and all you had to do was make the data accessible, transparent and easy to engage with – clearly selecting the right technology has a key role to play at this point!
Qlik healthcare solutions are used by more than 2,000 organizations around the world, to see more great examples of success, or learn more about the platform visit http://healthcare.qlik.com.