3 Key Considerations for Using Data to Drive Health Care Decisions

Now that we have easier access to Electronic Health Records (EHR), it should be easier than ever to use data to find best practices and reduce variations in care that hurt patient outcomes. Right? 

In theory, that’s right. In practice, it’s a whole other ballgame. EHR is a great repository of information but it does not magically perform analytics. Also, how do you grade the usefulness of data and how and when it is collected? 

Here are 3 areas to evaluate whether the data you are accumulating can drive better health care decisions for the patient and improved processes and efficiency for hospitals and providers: 

1) Is the data timely? 

Data sitting idly on a terminal or on paper in a drawer is not effective. For example, if you are collecting records that show there is an increase in surgical infections for heart patients, it would be hard to make timely and meaningful improvements if the data is six months old and delivered in a paper report a few times a year. Some information requires more vigilant monitoring. Data like this needs to be refreshed every night and monitored to show trends. 

2) Is the data relevant? 

There has to be a system in place to weed out outliers that skew data. For example, perhaps the emergency department had a bad outcome and then another only six weeks later. But previous to this, there were no other occurrences of this type for the past five years. These may seem to be big data points but they might be attributable to chance, a new staff member, or another reason. And in the big picture they may not be relevant to changing care protocol. 

There is a big challenge in leveraging data to accommodate the massive amounts of variation in surgical procedures where doctors or other clinicians do not use the same pre or post procedures or use different methods of surgery. All these variations can lead to better or worse patient outcomes. The trick is to find which ones are the  significant triggers. 

3) Is the data actionable?

Health care systems have limited resources, so when collecting data for analysis there should be a goal in mind. One of the biggest hurdles hospitals face is helping patients manage serious and chronic conditions like diabetes and cardiovascular disease. This is an area that shows tremendous opportunity for using data to drive better patient outcomes. 

There is also compelling evidence now that making small changes in pre and post surgical care can greatly reduce infection rates. This is one of the areas we emphasize in our Health Care Delivery Institute curriculum. 

Making the change to a data centric health care system 

Hospital systems will have to take a fresh look at the way their systems are set up in order to truly leverage the data in their own facilities. More than likely most accounting systems are not geared toward patient-focused delivery of care. A majority are designed for a fee-for-service volume model, and looking at big picture indexes like revenue per patient. 

There will need to be an investment in software and technology that can segment and analyze data to improve quality and reduce costs. In fact, improving quality alone will significantly reduce costs. And that is important because there is substantially more waste in clinical care than in administrative costs. 

In any business vertical, the company with the product that best pleases the customer is the one that is more likely to stay in business. In health care, the customer is the patient. Data, used in smart and resourceful ways, can provide that single voice of truth about how the “customer” is really doing. Finding out everything we need to know about taking better care of the patient puts hospitals on the path to staying relevant to their communities, keeping their doors open, and delivering on their promise to be a vital contributor to the well-being and health of the cities and towns in which they operate. 


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Topics: Healthcare Data

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