Purpose
Despite the current legislative indications toward the digitization of patient health records, 80% of health data are unstructured and in a format that cannot be used in electronic archives or in registries of diseases. An innovative automated system is here proposed to efficiently retrieve and digitize clinical information from original unstructured ear, nose, and throat (ENT) medical records, in order to reduce the manual workload in the retrieval and digitization process.
Method
The system, based on an eHealth technology named
cognitive computing
, interprets medical reports to transform unstructured clinical data (e.g., narrative text) into a structured digital format. The system has been tailored to handle the reports of aged cochlear implant (CI) patients by digitizing the information typically requested in electronic CI registries and by the current ENT/audiology guidelines. Results were obtained from the reports generated by an outpatient ENT care service from 52 older adult CI patients.
Results
The system allowed a quick and automated interpretation and retrieval of all the information required, such as the patient's medical history, risk factors, examination outcomes, communicative performances before and after CI implantation, and CI settings. The accuracy of the system in correctly interpreting and retrieving the above information from the original unstructured medical reports was very good (recall = 0.78; precision = 0.95). The system allowed to reduce the time needed to manually digitize the information from 20–30 min/report to only 20 s/report.
Conclusion
The proposed system is a viable solution for the automated digitization of unstructured health data as recommended by the ENT/audiology clinical best practices.
Managing Free Text for Secondary Use of Health Data
