The National Academies of Science (formerly IOM) published the Report, Improving Diagnosis in Health Care, in which it highlighted the value of data from medical malpractice insurers and what can be learned from such datasets.
“Improved collaboration between health professional liability insurance carriers and health care professionals and organizations could help to identify resources, prioritize areas of concern, and devise interventions. ”—National Academies of Science Report, Improving Diagnosis in Health Care
The collaboration between health medical professional liability (MPL) insurance carriers and health care organizations may be applied differently from organization to organization. Not every health care organization has the risk management and clinical coding resources of an academic medical center. A small hospital may have only a handful of claims each year. But even a single claim, turned into a compelling story, can become a potent teaching tool to think about malpractice vulnerabilities elsewhere in the institution.
MPL DATA IN PRACTICE AT UMASS MEMORIAL HEALTHCARE
UMass Memorial Health Care’s ability to embed claims data use into its culture and to share learning across clinical services offers lessons for health care organizations of any size. UMass Memorial harnesses its deeply coded medical malpractice data as a patient safety tool. It has leveraged these data to reveal clinical patterns that contribute to medical errors which enables leadership to more accurately plan investments in patient safety and risk management.
A case study published in the Journal of Healthcare Risk Management in which multiple examples demonstrate how leveraging MPL data has been successful at UMass. One powerful example, excerpted below, shows how medical malpractice data supported a staffing change for ultrasound coverage.
MEDICAL MALPRACTICE DATA PROPELS CLINICAL CHANGE
Today, when a young male arrives at UMass Memorial Health Care's emergency department in Worcester, Massachusetts, complaining of pain in his genitals, ultrasound technicians are readily available, no matter the time or day.
UMass Memorial provides full‐time, in‐house ultrasound services on its University and Memorial campuses to address torsion and many other emergency medical conditions. However, that was not the case until 2015, when hospital leadership replaced its nighttime and weekend on‐call ultrasound service with 24/7 onsite technician coverage.
UMass Memorial's claims and risk management (RM) staff had noticed a cluster of four medical malpractice cases involving teenagers who had lost a functioning testicle from testicular torsion. It appeared that three cases involved patients who had arrived at the ED at a time when ultrasound technicians were not available to provide immediate services. This caused delays in accurate diagnosis and treatment.
A comparative analysis of MPL claims data revealed a disturbing fact: UMass Memorial was an outlier in testicular torsion outcomes, compared to peer academic medical centers across the country. The data were provided by the Comparative Benchmarking System (CBS) through UMass Memorial's long‐standing partnership with CRICO Strategies.
With this evidence in hand, chief medical officer and urologist Stephen Tosi, MD, who chairs the hospital's claim committee, urged the administration to expand its ultrasound technician staffing to full‐time coverage. The strategy worked. UMass Memorial has not experienced a similar case since the improvement was made.
LEARN MORE
This is one of several examples described in this journal article—which was awarded ASHRM’s Writing Excellence Award—and is available open-access through October 31, 2020. The above example and other efforts have helped the organization reduce its risk exposure, improve patient safety, and drive down its volume of claims. We also conducted a webinar with the authors which is available as a recording.
Full-text Article
Siegal D, Swift J, Forget J, Slowick T. Harnessing the power of medical malpractice data to improve patient care. Journal of Healthcare Risk Management. 2020; 39(3): 28-36. https://doi.org/10.1002/jhrm.21393.