In October of 2023, the American Health Information Management Association (AHIMA) conducted a survey of more than 2,500 health organizations on the challenges they face. The data they compiled show a workforce that’s struggling with burnout for a myriad of reasons.
Health Information Management: Staffing shortages are impacting healthcare data quality
While the panic and confusion of the COVID-19 pandemic’s early days have long since dissipated, many of the workforce issues that affect all aspects of the healthcare industry have remained. According to the survey, 66% of the organizations that responded experienced staffing shortages over the previous two years. A cycle begins: understaffing leads to burnout and burnout leads to more understaffing. Notably, the organizations have stated that these issues have exacerbated data quality issues at hospital and healthcare systems.
This survey only tells a part of the story, though. “Health information management professional” is a title held by specialized workers in larger medical settings, like major urban or teaching hospitals. Regional hospitals, urgent care clinics, rehab centers, and other smaller medical facilities often rely on nurses to double as their HIM professionals. That’s what makes the conclusions reached by another survey—this one conducted by the American Nurses Association—so worrying:
- The top three on-the-job emotional states reported by nurses are stressed (66%), frustrated (61%), and exhausted (58%).
- 66% disagree, or strongly disagree, that there is enough staff to get all the work done
- 31% say that dealing with EHR systems adds to frustration of the day
What this means is: in facilities with health information professionals, there are nurses picking up the slack of their staffing shortages. And where there are no health information professionals, there are nurses handling data entry—despite their own staffing shortages. It’s a situation that seems to be hitting a breaking point. In 2022, there were eight work stoppages in the healthcare industry involving more than 36k workers. In the first 9 months of 2023, there were six more stoppages involving another 15k workers.
Healthcare’s HIM staffing temporary fixes
While it’s clear that some systemic changes need to happen, they’re not going to happen speedily enough to solve today’s problems any time soon. Organizations have been staffing up and working toward greater pay, but the link provided proves that point goes to a survey from the summer of 2022. It’s currently the beginning of 2024, and staffing shortages are still a problem.
Besides, adding staff now is an expensive proposition that only gets HIM departments back to sea-level after being underwater for a few years. It doesn’t account for the future, making today’s hires a non-scalable solution to a problem that will continue to balloon. Consequently, we see “documentation overload,” as one doctor referred to it. As a result of this extra burden, the speed and accuracy of processing health records suffers.
Tech is, of course, the next obvious option to mitigate the situation. Something like OCR software can extract data much faster than a human, as long as the document image is of readable quality and predictable format. However, the accuracy of OCR has always been statistically far from perfect. Even with AI pitching in, accuracy tops out at 98%, a few points shy of the perfection we expect in our medical charts. And that 98% is what you only get in perfect conditions.
With 43% of rural hospitals still using fax machines and snail mail to send and receive patient records, those perfect conditions are rare. Even in cases where these small hospitals are using modern EHRs, we’ve seen how they can be frustrating to the healthcare staff. The time they spend at a computer is time they aren’t with patients.
This time inefficiency is only part of the problem. Because of the variety of EHR systems used, there is often a lack of interoperability between them; yet another roadblock to EHR accessibility. With value-based healthcare already on the horizon, a payment model which places an even greater emphasis on timely access to health records, this is far from an ideal solution.
HIM directors face a unique challenge, then. Rely solely on people and they’ll fall behind while waiting for new hires to come on board. Rely solely on tech, and they’ll still need people to chase down the inevitable errors and inaccuracies before they cause problems. It’s a dilemma, for sure, but one that’s not without a solution.
How can collective intelligence help health information management?
While there’s no software that can fully automate data extraction and entry, HIM directors are not without options. Software can do a lot of the heavy lifting when it comes to data extraction, especially when it has AI and machine learning capabilities. But humans are still needed to validate and, if necessary, verify the data. There’s also the matter of getting that extracted data, once it’s off the page, entered into an EMR or EHR (electronic medical records / electronic health records) where it will live as part of a patient record.
All these pieces can’t be automated, per se, but we’ve figured out how to make them work together as part of a managed service. Using crowd workers in a secure and HIPAA-compliant way makes this service scalable, too. As the volume of data increases, so does the size of the crowd. To your overwhelmed staff, the process seems automatic—data goes in, data comes out. Behind the scenes, though, is the collective intelligence of machines and humans, working in concert to rapidly index your medical records and healthcare documents, securely and with full patient privacy.
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Bottom line: health organizations don’t need to wait for new hires to provide meaningful relief to their stressed out HIM teams and healthcare staff. With our managed service, HIM organizations can scan, enter, and index any volume of medical records in as little as an hour—with >99% accuracy. Read our white paper to learn more about your options or contact our experts for further information.
