In the course of my work, I once met a senior enlisted Navy corpsman who provides healthcare HIPAA training throughout the USA. For the sake of privacy, let’s call him Carl Kabacinski. As we discussed healthcare IT problems, he was intrigued to learn more about how I detect clinical data mistakenly entered into the wrong patient records, or as known in clinical informatics,
in the wrong patient records because Carl had his own wild story.
He told me about a call he received during what otherwise was his usual morning routine. He heard an older male voice on the other side of the phone, “Mr. Kabacinski?”
“Yes?”, Carl said.
“We need to talk, sir,” said the older gentleman. “I am also Carl Kabacinski.”
The older Mr. Kabacinski, a retired Navy Petty Officer, told the younger Carl Kabacinski that he had just discovered a big problem with both of their medical records in the Department of Veterans Affairs medical record system.
During a checkup, a nurse asked the elder Mr. Kabacinski if he was still on active duty. Perplexed, Mr. Kabacinski told the nurse he was long retired. The nurse told him his record indicated he was still on active duty. Thus began the discovery of comingling medical records for messieurs Carl the elder and Carl the younger. It turned out that their records were intertwined during the entire time of the younger Carl’s service.
After moments of conversation, they agreed to gather the entirety of their DoD medical records and do a weekly video call to determine which part of their medical records belonged to the other Carl, then request the incorrect portions be assigned to the other’s record. Of notes, some of the injury treatments for the elder Carl that were related to his purple heart were in the younger Carl’s record.
Advanced data validation upon clinical data input can entirely avoid these human-induced errors. Technology exists, such as available from Avant Health Sciences, to do this outside of electronic healthcare record systems. Still, vendors do not offer anything near this level of sophistication today inside of their monolithic software systems. The healthcare IT industry needs to adopt such technology and protocols to avoid these wrong patient errors.