The stories embedded within a medical malpractice claim are rich and diverse. The need for actionable data drives the design, structure, and content of Candello’s clinical coding taxonomy. The taxonomy is a structured set of clinical, behavioral, and systems concepts that allows for the meaningful capture and analysis of malpractice claims. This proprietary product is very carefully curated and governed to address the need for improved analytic insight into medical malpractice cases and uphold patient safety and health care industry standards.

Highly-trained clinical taxonomy specialists apply the taxonomy to each case. These specialists come to us with clinical skills acquired through direct patient care in a variety of settings and specialties, including obstetrics and gynecology, NICU and pediatrics, surgery, emergency medicine, radiology, primary care, oncology, and home care. The specialists read and analyze case files and clinical materials, using well-defined methodology to choose codes to represent the key concepts in a case – who, what, where, and why the event occurred.

All specialists undergo rigorous training on the use of the taxonomy on a regular basis, and a clinical coding manager performs a quarterly audit to evaluate the accuracy and consistency of the coding. Audits routinely show our coders exhibit 95-100 percent accuracy, which is well above industry standards.

A Taxonomy working group also ensures the clinical coding retains quality, accuracy, and usability while the taxonomy continues to evolve. Input streams from multiple stakeholders result in a flexible, responsive taxonomy and highly actionable data.

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We apply the taxonomy to identify both the commonalities among cases and the factors that make them different. Two case stories may appear to have no unifying themes at first glance, but applying the taxonomy reveals the underlying themes of who, what, where, and why.

Take the following two case studies as an example:

  1. A failure to diagnose a pulmonary embolism in the emergency department (ED) results in a patient’s death. This occurred during a COVID-19 surge, which magnified chronic systems issues, such as staffing shortages and lack of available equipment.
  2. A patient with Alzheimer’s disease elopes from a nursing home, falls outside, and suffers a subdural hematoma, ultimately leading to their death. The nursing home was understaffed and had malfunctioning equipment.

The circumstances of these two cases are significantly different, but we can find commonalities when we code the main themes and dig deeper. For example, both cases exhibit a failure to monitor and chronic systems issues, specifically inadequate staffing constraints. If we then want to see how provider burnout may have contributed to these cases, we can use several potential contributors that can affect the clinician related to work environment and time pressure. We then apply an analytic algorithm to see if a combination of these factors are indicators of burnout.

These are just two cases out of hundreds of thousands in the Candello database we can use to gain valuable insights. Breaking down each case to identify every aspect of care that could have contributed to the error allows us to identify the most vulnerable points in the health care delivery system that increase the risk of medical error and malpractice liability.

Our taxonomy will continue to evolve to, first, reflect changes in health care delivery and the corresponding risk, and second, to enable a deeper understanding of the systems that support care as well as the people that operate within those systems. As such, we and our Candello members will be able to tell a powerful story about the risks of patient harm and financial loss that no other data services anywhere can tell.

Written By
Clinical Taxonomy Specialist
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