It's time for hospitals to get smart with data

Whether it’s a 25-hospital health system or a 50-bed rural hospital, the amount of data collected to ensure quality and efficiency is endless. With computer networks inundated with data, gleaning valuable insights from this surplus of information can be a significant challenge. 

Hospitals are looking to data to answer performance-related questions and help direct quality and operational performance improvement initiatives. Does the hospital need to cut its average length of stay? Are outcomes similar to other hospitals in the market or region? How does the organization's readmission rate compare to the national average?

C-suite executives are constantly evaluating these questions, compiling new data at every meeting to improve decisions moving forward. However, it can be difficult to truly understand what the surplus of data is saying.

For example, let's say a hospital's annual opportunity for orthopedic surgery is $4.5 million — a striking number by itself. However, if the hospital compared this data point to the $10.3 million of annual opportunity in cardiac surgery, a key performance improvement target emerges — it's time to focus on cardiac surgery.

During a May 1 webinar presented by Becker's Hospital Review and sponsored by Leidos Health, Scott Woodard, Director of Analytics at the information technology and data analysis company, stressed the importance of creating cross-functional improvement using clinically- and risk-adjusted data to get a 360-degree view of an organization’s past performance and future opportunity.

How to gather and assess data

As the healthcare landscape shifts, hospitals and health systems must reexamine the data they have and how they use it. For example, if a 500-bed hospital performs well in cardiac care, transplant, joint, trauma and outpatient surgery, leaders can't measure this success against a 100-bed hospital that is only performing well in outpatient surgery.

Instead, data has to be adjusted for risk and clinical considerations to create apples-to-apples comparative information.

"Let's say I took a 300-bed facility in Iowa and compared it to a 300-bed facility in New York. Those two hospitals are very different. The patients are different. The cost models are different. The cost of living is different. So, there are a lot of things that go into comparing 300-bed hospitals," Mr. Woodard said.

To evaluate performance accurately, leaders need access to clinically- and risk-adjusted data. One possible means of adjustment is applying a binary logistic regression model to determine  precise quality, cost, and length of stay information. In this model, hospitals adjust performance relative to patient age, gender, chronic conditions and significant comorbidities to give a complete composite quality score.

What this is saying is that patients have an expected outcome based on age, gender, chronic conditions, and comorbidities for a particular procedure and the observed instance of those adverse events cannot be “blamed” on the sickness of the patient.

Hospitals should also adjust for severity, intensity and complexity to determine an accurate assessment of resources. This allows hospitals to compare to one another on a national level in order to better determine future opportunities and potential savings.

Don't overlook performance improvement opportunities

A 2019 healthcare CFO outlook survey from Kaufman Hall found 94 percent of CFOs have experienced increased pressure to have more insight into how financial results impact business strategy. However, these same executives lack confidence in their ability to utilize data to support actionable, informed decision-making in a quickly evolving environment.

Mr. Woodard stressed that organizations need to give more context and add information to different data points in order to develop meaningful and sustainable solutions. Without discovering clinically and risk-adjusted opportunity, an organization may deploy resources in areas that will never see improvement.  If an organization’s length of stay (LOS) in pulmonary care is 5.0 days, they may undertake initiatives to lower that rate 4.5 days, a Geometric Mean Length of Stay (GMLOS) identified by leadership.  However, the clinically-adjusted LOS might be 5.3.  This is to say they are already above average based on their particular cases (5.0 < 5.3) and could focus resources on more impactful areas of change.


To achieve impactful, sustainable change within a hospital or health system, leaders must look at the clinically- and risk-adjusted data to identify opportunity for improvement, Mr. Woodard said. Hospitals cannot just evaluate themselves alone to measure success. Rather, it is imperative for hospital and health system leaders to look outside their four walls to collect appropriate data to improve overall costs and quality standards. With comprehensive data at their fingertips, hospitals can begin aligning their values to strategic initiatives.


To learn more about Leidos Health, click here.

To watch the webinar, click here.

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