By - Reducing measurement burden, addressing the lag in reporting data quality, and improving data standardization will be key to boosting clinical quality measurement, according to a recent journal article published in JAMA Network.
“There is a lack of information that would help clinicians improve care delivery in the moment and learn for the future,” J. Matthew Austin, PhD, and Allen Kachalia, MD, wrote in the article. “This situation highlights how the current approach to quality and safety measurement remains too labor intensive, contains significant data lags, and lacks sufficient standardization that allows for rapid sharing of data.”
Once the pandemic began to spread at a rapid rate, it was mightily apparent that measuring healthcare quality was not going to be sustainable. As a result, the Centers for Medicare & Medicaid Services (CMS) announced it was allowing exceptions for data submissions for Medicare quality programs due to the patient surges.
However, Austin and Kachalia said if the healthcare system did not rely on manual abstraction and human intervention, CMS would not have had to suspend quality reporting requirements.
“To date, health care has approached quality measurement too much as an ancillary matter, treating it as a double-check after care is delivered, rather than information evaluated simultaneously with the provision of care,” the authors explained. “The current approach, therefore, is simply not resilient enough when attention and resources need to be focused elsewhere, such as during the current pandemic.”
Austin and Kachalia also noted the lag between reporting measurements and provision of care. A lag in between these two measures disrupts feedback and framework improvement.
Unfortunately, data lag is magnified during a crisis and learning opportunities are missed by the time data is available.
“The current approach to quality measurement is also challenged by the insufficient standardization of data for purposes of data sharing,” explained the authors. “When health systems provide care to patients with new types of clinical problems, or provide care in new ways for which there are no standards, it can be helpful for health systems to be able compare their performance with the performance of other health systems.”
The authors highlighted the clear health IT takeaways from the COVID-19 pandemic and recommendations for improvement.
First, it will be critical to reduce the measurement burden.
In order for this to happen, the authors noted the development of data collection systems in health facilities that do not add to clinician workflows. To ensure data collection doesn’t require a manual clinician process, the authors advised it would involve building new data capture systems designed with a quality measurement focus to maximize health IT. The authors said the government could oversee this to expediate the process.
Next, COVID-19 exposed the lag in reporting patient data that ultimately impacts patient care.
Austin and Kachalia suggest a focus on EHR-generated data, rather than claims data, which notoriously has a greater lag in transferring data. The authors noted this newfound focus will require full EHR capabilities, leading to more efficient methods of data validation and a change in care delivery. High engagement with EHR vendors will be necessary for this to occur, they wrote.
Lastly, throughout COVID-19, healthcare experts and the US Department of Health and Human Services (HHS) aimed to improve data standardization.
The authors said a series of national committees or tasks forces should come together to define data standardization measures. With the help of EHR vendors, these committees can share ideas which would allow vendors to optimize EHR systems. Improving health system performance will occur once these methods and ideas come together.
Because healthcare is still being delivered during a crisis, quality measurement of safety and care quality becomes more important due to the constant changing of the care process.
“This crisis has further demonstrated how problematic these challenges can be,” Austin and Kachalia concluded.
“Implementing the recommendations for improvement will require a higher level of planning and coordination than in the past around quality measurement, but the risk in not following these recommendations is too high. The health care system should prevent being in a situation with a poor understanding of the quality of health care being delivered, regardless of whether there is a public health crisis.”
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How to Improve Data Collection, Exchange Following COVID-19 - EHRIntelligence.com
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