5 Common Causes of Patient Misidentification
Patient identification is considered as the backbone of a healthcare system. It’s the way a pharmacist knows whether he/she is handing over the right prescription to the patient or not. It’s the way a physiotherapist identifies what happened during a patient’s knee surgery a few months back. It’s how hospital staff ensure that they’re mailing to the right address for patients’ bills. It’s the only way you can appropriately recognize who your patients are.
What harms can patient misidentification do?
Patient misidentification is directly linked to many far-reaching negative impacts. It can cause lousy patient experience and patient safety issues. It also can lead to an operational nightmare; hospitals can face severe damage in reputation for giving the wrong treatment to the patient. Incorrect patient records can cause a patient to get wrong drugs, delayed treatment, or missing a follow-up. Clinicians can end up making medical decisions without having an all-around view of the patient in front of them. In addition to that, medical identity theft originating from data breaches can put providers in the threat of financial and legal challenges.
It doesn't have a good history
Things can go even more complicated when hospitals don’t have organized data for recognizing the scale of the problem. Healthcare IT did a survey in 2018 on Chief Information Officers of healthcare systems. Among them, 66% rated patient matching as the highest priority for their leadership team. Although, only 18% had actual data in hand regarding mismatch and duplicated records within their systems.
This does not even include the errors done while passing data between different healthcare providers. Research indicates that half of the time, patients’ individual information- like name, address, or insurance numbers- is put incorrectly.
A study by the Phenomenon Institute found the principles of patient misidentification. The study had a sample of 500 nurses, clinicians, IT staff, and finance leads within the United States:
Most of the time, misidentification starts with the wrong registration of the patient. Frontline staff can mess up patient information while interacting with patients for the registration process.
Multiple records, or no record at all!
This is quite scary. Results may come up with multiple records for the same patient as a result of the wrong registration process. This can lead to delay of treatment, as the hospital staff has to go through files in detail to figure out the actual record.
Waste of time
When the hospital staff goes through multiple records for one patient, they don’t only delay patients’ treatment, but also lose valuable time of their work schedule. This is not efficient for any work or activity.
Lack of training
Many healthcare systems or hospitals don’t provide or bother to provide proper training to the staff regarding patient data protocol. Patient misidentification is an unexpected event- the team is not supposed to know how to find the right identity if they don’t get a proper guideline or training for this situation. It will put patients into trouble and make them unsatisfied with the overall service of the hospital.
Lack of interoperability
Although it’s necessary for the betterment of patients and doctors, hospitals still deny engaging a proper information-sharing system between departments or workflows. This can lead to duplicate records and misidentification of the patient's emotion.
How can we solve it?
Patient experience is adversely affected by patient identification errors and generates longer patient waiting times. Biometric patient identification platform can eliminate these problems. Using patients’ biometric data, such as fingerprints or irises, it can create a closed-loop patient data record. Once patients’ enrollment is complete, they only have to scan their biometrics, and RightPatient will identify medical records within seconds. Several decision-makers and health systems such as Community Medical Centers and Catholic Health Services are using it and getting satisfactory responses.