I recently published an article on SearchHealthIT.com that discusses how productive healthcare analytics requires high-quality data. A few excerpts from the article are:
In the age of big data and enterprise data warehouses, issues of data volume, system scalability and infrastructure management simply cannot be ignored. It is possible, though, that in our rush to incorporate ever larger data sets from new sources, we sometimes lose sight of the more mundane but critical need to ensure that the data we have access to is high quality through health data governance programs and policies.
Large data sets are beneficial for healthcare analytics, but quantity isn’t the goal. High-quality data is an essential ingredient to accurate, valid and trusted analytics that are used by healthcare leaders. Having good data cannot alone ensure that analytics built and utilized by a healthcare organization will result in the desired transformations in quality, performance and patient safety. Bad data, however, will almost guarantee that efforts to use information will be scuttled due a lack of trust or belief in the analytics results.
Analytics teams need to work together with data warehouse managers and front-line staff to ensure that all possible sources of poor data quality are reduced or eliminated. As clinical systems and the data warehouses on which information is stored become more complex, data quality must become a shared responsibility among all data owners within a healthcare organization. Healthcare organizations need to work more diligently than ever before to ensure the availability and trustworthiness of the data and information that decision makers require.
In the article, I discuss six common causes of poor data quality. Click here to read the entire article on SearchHealthIT.com.