Is Your Hospital's Data Reliable? The Most Common Error in Hospital Data

In an industry that focuses on evidence-based practices, measurable progress and performance-based payment, hospitals' management of data is becoming more important than ever. "Data is experiencing explosive growth in hospitals right now," says Russ Richmond, MD, CEO of Objective Health, the McKinsey & Company unit that serves hospitals. "But, data are fragmented, and they are not all that useful unless they are accurate and analyzed properly."

The accuracy of hospitals' reported data can affect the number of patients they attract and their reimbursement, as hospitals are becoming financially accountable for quality care. In addition, hospital leaders make decisions based on data; if the data are faulty, hospital leaders' decisions may negatively influence the safety and quality of care. To ensure high quality and reach their strategic goals, hospitals need to ensure they are collecting and using data appropriately.


Consider the source
Dr. Richmond says there are generally two categories of error in data — errors in the collection of data by the source and errors after data are collected — with the first category causing the most problems. "The biggest risk [to the accuracy and reliability of hospitals' data] is that at the source level, the data are entered or collected inaccurately," he says.

For example, a human resource software system may include time sheets and collect data on staff members' work hours and locations. A hospital that uses this system to analyze productivity may not get accurate data if the system focuses only on staff hours and location, not the product of those hours. "It might be very accurate in terms of looking at payroll and how to pay nurses, but it might be inaccurate if used for a different purpose, like productivity," Dr. Richmond says.

Consider the purpose
To avoid collecting inaccurate data due to the source, Dr. Richmond suggests hospitals determine the reason for collecting each piece of data as early as possible. "Understand how the data ultimately will be used." While hospitals may use collective data points for several reasons, the specific purpose of each data point can guide hospitals to the most accurate source.

Dr. Richmond provides an example: "Electronic medical records are structured to collect data for certain purposes. It might be extraordinarily accurate from a billing perspective, but it actually might be wholly inadequate from a patient care perspective.  The data are collected with a different lens." In this example, hospitals seeking to collect data on the procedures physicians perform would therefore use a different source — one that is programmed specifically for patient care data.

One of the challenges of verifying data by tracking it to its source is the number of separate IT systems hospitals have — EMRs, billing systems, HR payroll systems, a discharge system, etc. Dr. Richmond says hospitals can lessen the burden of seeking different kinds of data from different sources by creating a data warehouse that collates data from all of the hospitals' systems, presenting a unified source of data.

Keeping data top of mind
To ensure data are collected from the right source, hospital leaders need to make data reliability a top-of-mind initiative and should incorporate this goal into their strategic plan, according to Dr. Richmond. "Hospitals need to think strategically about the power and value of their data sets. They need to have a senior executive take responsibility to make sure [the hospital] is getting the right value in terms of decision making," he says.

Making data accuracy a priority will require process and cultural changes in the hospital. By requiring accountability for the accuracy of data, hospital leaders demonstrate their support of evidence-based medicine and their commitment to "getting it right" the first time instead of making decisions based on faulty data.

More Articles on Hospital Data:

4 Recommendations to Fight Rising Prevalence, Cost of Hospital Data Breaches
University of Pittsburgh Medical Center Invests $100M in Data Analytics

7 Ways Analytics Can Help Hospitals Gain Competitive Edge

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