As patients and providers, we trust that the systems we rely upon for diagnoses and treatment within healthcare facilities are accurate and reliable. But healthcare quality is not a guarantee, which is why in the United States there are so many systems and quality control measures in place to ensure healthcare compliance throughout the hospital.
Administrators, clinicians, and technologists spend a significant amount of time and resources in pursuit of quality compliance, readying for inspections and accreditation. But there are some critical things the current system can’t control when it comes to quality in healthcare, and those inconsistencies can negatively affect patient outcomes.
Find out how data drives quality in healthcare, and why everyone from providers to patients should question the status quo.
As an example, consider quality control standards in radiology.
Radiology departments in hospitals manage a steady load of patients daily, running scans on the machines that populate the department - from X-rays to MRI and CT scanners. To ensure that the images produced by these machines (and subsequently used for diagnosis) are accurate, radiology technologists are tasked with a long list of quality compliance checks that must be run on each machine every day.
In an average hospital, a radiology department might have four to six scanners, and a technologist will spend 15-20 minutes running a quality compliance (QC) test on each machine before it can be used to scan patients for the day. The QC test involves placing a static item, called a “phantom” in a specific location on the machine and running a scan. When the image is available, the tech annotates it, taking measurements and validating that the image is correct and within the baselines for that machine.
Once the QC tests are complete, technologists are responsible for documenting the results, and taking any follow-up actions necessary for a machine that fails a scan or needs service. All of this is recorded, often in a paper log.
Back to the radiology example: at the best of times, techs correctly run all the scans, and carefully mark and record the data produced. The hospital environment, however, is rarely optimized for careful, quiet work. Instead:
All of this leads to a lack of consistent reliability in the data determining the quality and safety of the radiologic equipment on which providers and patients rely. And in some cases, QC is inadvertently skipped altogether, creating an issue when time for inspection rolls around.
Most hospitals go through an accreditation process every three years, and the goal is to ensure a standard of quality in healthcare.
In addition to accreditation, there are government organizations that require compliance with specific standards across departments, and they use the data collected to determine reimbursements and funding in some cases. There are more than 600 separate regulatory requirements, which can be a challenge for some hospitals to keep up with. The administrative burden placed on institutions - originally created to provide quality care to patients - is becoming more complex, and in some cases, makes it difficult to focus on high-quality patient care.
The standards and measures that have been put in place over the years are intended to keep the quality of healthcare in the United States high, but in many places, the burden is creating unintended consequences like those mentioned above.
Administrators and departments driven to maintain a high quality of care must seek more reliable methods for ensuring quality, and many of those methods will come from the technology sector. A variety of data management tools are evolving for use in healthcare, and the challenge will be for those technologies to find ways to seamlessly integrate with existing practices and procedures.
The goal of any data management platform in healthcare must be to ensure the quality of the data and translate that to optimum patient outcomes. In the radiology example, an automated platform could automate testing, make error reporting more efficient, and allow clinicians to make decisions more quickly. Ensuring timely attention to service and compliance issues adds efficiencies throughout the department.
For technicians, a data application would need to accept and organize daily QC entries and alert them to numbers that are out of established tolerance ranges or let them know when a test has been skipped. For administrators, this application could offer a simple dashboard to allow them to visualize inspection readiness across departments, without having to track down paper records and fill in missing numbers from months past. For providers, knowing that compliance is being tracked electronically and that machines are kept to high standards and free from potential human error gives them confidence that the diagnostic information they have is correct. And for patients, this type of data management system would ensure that their care is of the highest quality possible.
The way we manage quality in healthcare is due for disruption, and everyone involved will benefit - especially patients.
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In the near future, Enzee’s platform will provide the same features from radiology and radiation oncology to the entire hospital equipment QA program and also connect to existing compliance and test tracking apps, providing a holistic picture of a facility’s compliance and quality across personnel and departments.