Pre-thinking Data

There’s so much data available to today’s organizations. Sometimes the data are easy to collect because they come from web-based platforms. Other times, organizations go through the trouble of writing surveys and delivering them to clients. However, regardless of the effort it takes to get it, data too often don’t fulfill their promise. One major reason for this is that too little thought is applied before the data are collected.

An example of this comes at the expense of a hospital system where my wife recently had back surgery. She has never really had back pain but over the last few years, she’s had increasing leg and foot pain and numbness. Before the surgery, the surgeon told us that the surgery would correct her symptoms. The surgery was successful in a technical sense and my wife had relief from the leg and foot pain she’d been suffering. However, as soon as she stopped taking the post-surgery narcotics, the leg and foot pain started up again at pre-surgery levels. The surgeon’s PA assured us at the first post-op follow-up that this was normal and it could take up to 2 years for the nerves to recover from the damage her condition caused. In other words, all was proceeding as normal.

Then came the post-op survey from the hospital system where she had the surgery…

One of the questions asked whether the surgery solved the symptoms it was supposed to solve. She was conflicted about the question. The surgeon had told her that the surgery was a success, and she had no reason to believe otherwise, but the PA said that she shouldn’t expect that the symptoms would immediately abate. So, imagining that an honest response to the question would end up sending the wrong message about how she was feeling about her surgery, she didn’t respond. Had she, though, it would have resulted in data whose only conclusion could have been that the outcome of the surgery was bad and that the patient was not happy with it.

The problem with this survey is that not enough thought was put into who would be answering it and what information would be needed for the data to offer actionable insight on the patient experience. We can avoid these kinds of problems if we think about the contexts of the data and questions we will ask of it before it is collected.