乌鸦传媒

In general, I think that good data is a good thing. But is bad data of any use, and is it better than no data at all?

In our lives as healthcare providers, we encounter enormous amounts of data. All day long we are brushed by and inundated with data points, be they individual things like the number of patients on our schedules, or the number of times our patients' hearts beat as we lay our fingers gently on the wrist to measure their pulses, or listen with our stethoscope to the number of breaths per minute.

Our inboxes and the electronic health record are filled with data, labs that indicate health or illness, or variations about the mean. Is this one dangerous? Is that one bad? Do I need to do something about this? Is this just a fluke?

Due to some internal restructuring, there are an enormous number of new efforts being built or overhauled that look at quality -- since this reflects on patient safety -- and also for the purpose of regulatory requirements and reporting.

At one meeting this week, we saw data on patient feedback on how our practices are doing, including such items as "Provider listens carefully to you," "Clerk treats you with courtesy and respect," and "Phone during office hours answers same day." (Really, same day? Shouldn't the goal be one ring or two?)

Each of these measures had a goal, plus our 2017 year-to-date data, the variance to the goal, the numbers from which these data were received, and the national percentiles with which to compare us, benchmarking us against institutions across the nation.

Yesterday I got a report on the percentage for each provider within our practice who had done a Medicare Annual Wellness Visit on patients who were eligible to have received one in the past quarter.

The problem with that list was, there were multiple providers on the list who are not in our practice. Similarly, there were multiple patients on that list who were "attributed to us," but who we've never seen. And some who were dead.

At our own internal quality review meeting, we went over the quality reports that we receive quarterly from our electronic health record, seeing how we're doing on multiple measures, including counseling on smoking, cholesterol screening, colon cancer screening, mammography, vaccinations and immunizations.

The data were all over the place. Some measures showed we were at 100% (doubtful), others were at 0% (also doubtful), some were pretty much exactly where we expected them to be, some of them were a little bit better, and some were ridiculously worse. What happened next was a lively debate in the room, more accurately described as a lot of shouting.

"That data is no good." "How can I be responsible for that?" "We never see that little box we are supposed to click." "How come the tech can't do that?" "They never scan the report against my order so it doesn't satisfy the health-maintenance field and give me credit for it." And on and on and on.

We all recognize that this is the world we live in -- that people are looking at all our data, putting it under magnifying glasses, scrutinizing it and criticizing it, judging us on how we're doing on all these measures that they've decided are the important things to take care of for patients.

But we who do the work recognize that our patients are made up of an infinite array of data points, like stars in the sky, and it's our job to cradle these data points and use them to help take better care of our patients.

These institutional goals, these mandates from insurers, these federal rules, often seem to lose sight of why the data exists, where the data come from, and what it means for patients and providers.

Quality and patient safety are critically important, and having the infrastructure in place to take care of this stuff, to make sure that the right things are happening for patients at the right times, is really one of the major goals as we build a 21st-century healthcare system for our patients. In population health, looking at our practice as a whole, looking at groups of patients and helping use this data to remove inequities, is also the lifeblood of the new way to take care of people.

But it all has to come down to taking better care of patients. We can massage the reports all we want, we can set up structures that allow us to game the system so that our reports look clean, our data is perfect, and our scores blow the national percentiles out of the water.

However, eventually it all comes back to the patient, how they may not think of themselves as data points, and they may resent the fact that we see them as such.

We need to build a practice centered around our patients that helps them participate in their health and recognize the value of all this data, for themselves and others around them. But we cannot make this data the priority, or we lose sight of the human being that stands behind it. If we turn the system around and make it about the patient instead of the data, the rest should surely follow.

Build us the best possible data collection system in the world, link it all together, and make sure that the reports are accurate, timely, and actionable, and you'll help us move our patients toward the best health we can help them achieve.

So now we have started a journey to clean up our data reports, making sure we put the right data in to get the right answer out, measuring what we think we are measuring and what we want to measure, so that we can produce a report that gives us useful information and data points that can lead our patients to the places we think they need to be.

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