A simple question…
As part of a “reporting inventory” project, I was recently asked by a young and enthusiastic member of our information technology (IT) staff to provide a list of all the reports my analytics team has built, and how often they were run, and who received them. The question was certainly innocent enough. I viewed this question, however, as an “opening” for a great introduction (OK, well soapbox speech) on the topic of healthcare analytics. Here is a somewhat less colorful version of what I communicated to that young analyst…
As healthcare organizations continue to amass large quantities of data through the accelerating adoption of health information systems, traditional reporting tools are no longer sufficient. Healthcare leaders are dealing with a multitude of regulatory, quality, and financial pressures, and need accurate, timely, and readily available information to make decisions.
Analytics provides insight to data that reports can’t
Healthcare analytics provides the collection of tools and methodologies to provide healthcare leaders the information they need to make critical decisions. As the name implies, analytics provides the horsepower to thoroughly analyze and understand operational performance of a Healthcare Organization (HCO). This typically requires more than mere tables and bar charts showing monthly averages. When paired with quality improvement frameworks such as Lean or Six Sigma (among others), analytics can provide powerful visualizations to determine if performance and/or quality is stable, improving, or getting worse. Machine learning algorithms can scan large volumes of data to identify patterns that may not be detected otherwise. Analytics can provide more insight into data than is possible with standard reporting.
Analytics provides clinical decision support
Not only can analytics be useful for analyzing previous and/or current performance, the branch of predictive analytics is helping healthcare administrators and clinicians alike to peer into the future. Administrators are using predictive analytics to better gauge future demand for services, which results in more efficient and affective resource planning and financial forecasting. Even clinicians are now benefitting from predictive analytics; risk screening tools and other algorithms used to predict likely patient needs and outcomes are increasingly available (even embedded into certain clinical applications) to assist clinicians plan for the most effective care of individual patients.
Analytics can trigger action
Healthcare analytics is much more interactive than standard reporting. Yes, some dashboards may look like fancy reports, but well-designed dashboards help to highlight when processes or performance fall outside of acceptable limits. What might get missed in standard reports becomes apparent when conditionally highlighted in yellow or red on a dashboard, or when an email alert is sent out by an automated monitoring agent. Analytics provides the opportunity to take action as soon as necessary, not when somebody finds a needle in the haystack combing through a report.
Although this is a very high-level of some of how analytics are used in healthcare, it is my hope that analytics is viewed as more than “just” reporting. Analytics are, in fact, a key component in providing vital, up-to-date information in a variety of formats, spanning from past to future performance, to healthcare leaders and other stakeholders tasked with making tough decisions in the operation (and optimization) of healthcare systems.
I’m interested to hear what you, the reader, see as IT misconceptions about healthcare analytics, or even better, how IT “gets it right”! Feel free to comment below.