The Data Dilemma: How It's Costing Health Systems Millions

The healthcare industry's data dilemma is costing health systems millions.

Healthcare has a data problem. And it's getting expensive.

Data is more than just a byproduct of medical care—it's the backbone of decision-making. But oftentimes that data is unclear or undefined.

Studies show that data errors in hospitals can occur at a rate from 2.3% to as high as 26.9%. A variety of factors contribute to data challenges such as data entry errors, outdated information, lack of data standardization, and system integration issues.

How much is inaccurate data costing providers?

Despite having access to vast amounts of information, many health systems struggle to use data effectively, and this inefficiency is costing them. Studies show that medical data errors can cost providers up to $20 million a year.

Without real-time data, a hospital may struggle to adjust staffing levels or optimize resource allocation during times of high patient volume. Inefficiencies like this can lead to prolonged patient stays, increased overtime pay, and the risk of misdiagnosis leading to poor clinical outcomes—all of which drain financial resources. One survey showed that up to 20% of patients may not be correctly matched to their records.

Data consistency also plays into the challenge. If each clinician involved in a patient's care journey is working from a different dataset, that will spell trouble for the clinical outcome.

Bradley Hipp is the newly appointed CFO and Vice President of TMC Health, and has years of healthcare finance experience under his belt. He says it's crucial for health systems to have data consistency, yet that is often a problem in health systems.

He says health systems must ensure that “data is being reported the same way, data is being seen the same way, and wherever you are within the health system, it's done the exact same way.”

Data sharing and integrity

A secondary piece to the data challenge for providers is data sharing practices, especially with payers. Incorrect claims submissions, due to data entry mistakes or system glitches, are not only costly in terms of denied payments, but also in the form of reputational damage with insurers and patients alike. CFOs will need to stay on top of payers and ensure that both sides have consistent, accurate data, particularly when it comes to contract negotiations.

New technology has done much to address the healthcare data problem. It enables efficient data collection, storage, analysis, and integration through tools like electronic health records (EHRs), clinical decision support systems, and artificial intelligence (AI).

Despite this, many health systems don't make the best use of technology for data challenges. To stay ahead, CFOs can collaborate with CTOs to ensure their health system has the right technology in place to refine their data practices and determine where data inefficiencies are rooted within the system.

Data analytics

Valuable data can be rendered obsolete if it is not accompanied by the right analytics. By harnessing tools like predictive analytics, CFOs can optimize resource allocation, from staffing levels to inventory management.

UW Health CFO Bob Flannery spoke with HealthLeaders about the importance of data analytics and how it is used at his organization.

"We've built a data mart that elevates expectations at the senior leadership level not to make decisions in a vacuum," he said.

Flannery emphasized the importance of transparency in resource allocation as CFO and how data analytics allows him to do that and clearly show his team where resources are needed.

"And then even sharing that, when we do actually allocate some additional resources, what went into the thought process, what went into the recognition that that really was a high impact area for people that we serve," Flannery said.

The CFO to-do list

To stay on top of the data dilemma, CFOs must invest in robust data infrastructure, including data management platforms and analytics tools. Building cross-departmental collaborations between finance, IT, and clinical teams is essential for creating a data-driven culture.

To take it a step farther, CFOs should advocate for data governance policies that prioritize data accuracy, integrity, and transparency. Collaborating with payers to streamline data exchange processes can reduce reimbursement delays and prevent costly billing errors.

By ensuring the right data is available at the right time, maintaining data integrity, fostering transparency with payers, and leveraging analytics, CFOs can steer their organizations toward an efficient, financially stable future. The cost of neglecting these data challenges is simply too high to ignore.