Why Hospitals Can't Settle for "Later:" Tracking Data in Real Time to Reduce Readmissions
Demand for instant gratification — receiving responses to questions, gaining access to products and resolving discomfort immediately — is often viewed as a fault of today's society. When it comes to healthcare data, however, instant gratification can become a competitive advantage. Pressure to improve quality and reduce costs is driving hospitals and health systems to adopt new technology, like electronic health records, that can collect useful data about a patient population.
Often, however, actionable data is available only after the fact — after an error has occurred or after a patient has been readmitted. Hospitals today have to work to access concurrent data they can use to proactively prevent readmissions and promote population health. Chris Cashwell, senior director of analytics-based solution marketing for health IT company Nuance Healthcare, explains how healthcare providers can use technology to extract and apply patients' data before they leave the hospital.
Value of "now"
For many hospitals, looking at data retrospectively has been the status quo. Now, however, there are technologies that allow organizations to view patient data in real time and act to prevent readmissions and adverse events instead of making changes after the fact. For example, a technology called clinical language understanding allows healthcare providers to extract important data points from physicians' narrative documentation. "Capture those patients before they fall through the cracks and [efforts become] reactionary. Now you can do something for patients before they become statistics as opposed to only changing [something] for future patients," Mr. Cashwell says.
For example, Mr. Cashwell says hospitals can determine whether patients have received discharge instructions before they leave the hospital. If the technology does not find evidence that discharge instructions were delivered, an alert can be sent to providers so they can be aware of the situation and talk with the patient before he or she leaves to help reduce the risk of readmission.
In addition to process information, the technology can scan clinical information to tell providers about possible underlying causes of conditions or comorbidities that might otherwise go overlooked. "Clinical indicators may indicate this patient is leaving the hospital with something they may come back with. [He or she] may be developing pneumonia while in the hospital, and the doctor may or may have not documented the pneumonia. Either rule it out before [he or she] leaves or keep the patient another day to address it," Mr. Cashwell says.
Another value of collecting data in real time is the ability to identify what additional data is needed and alert physicians, nurses and other providers to collect that data. For example, Mr. Cashwell says the CLU engine may scan information on a cardiac patient and determine there is not sufficient data to calculate the patient's risk for readmission. The system can then request the physician provide more detailed documentation on the patient's diagnosis in real time.
Proactive patient management
In addition to looking at individual patients' data, hospitals can use real-time data tracking systems to analyze data for specific patient populations. Hospitals can filter patients with specific diagnoses to guide strategies for different initiatives, such as reducing falls. Mr. Cashwell says the CLU technology can identify patients that meet certain criteria, such as risk factors for falls. For example, hospitals can look at patients that have specific neurologic risks for falling, have functional issues, take medications that increase the risk of falling and meet demographic criteria that increase the risk of falling.
"Every patient that fits the criteria will pop up while they're still in the hospital, and you'll be able to see the trends," Mr. Cashwell says. "You can create whatever hypothesis you think meets the readmission focus you're trying to combat, then run that over the entire population and compare it to your last quarter discharges." By teasing out this information, hospitals can more easily predict which patients are most at risk for different outcomes and implement strategies to prevent adverse events.
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