Implementation of a clinical decision support system to improve the medical data quality for hypertensive patients
The digitalization of healthcare relies heavily on data analytics from medical information systems. Such systems aggregate information from heterogeneous sources, including electronic medical records. Improving the quality of data from electronic medical records is a modern challenge for developers...
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| Published in: | Nauchno-tekhnicheskiĭ vestnik informat͡s︡ionnykh tekhnologiĭ, mekhaniki i optiki Vol. 22; no. 1; pp. 217 - 222 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
ITMO University
01.12.2024
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| Subjects: | |
| ISSN: | 2226-1494, 2500-0373 |
| Online Access: | Get full text |
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| Summary: | The digitalization of healthcare relies heavily on data analytics from medical information systems. Such systems aggregate information from heterogeneous sources, including electronic medical records. Improving the quality of data from electronic medical records is a modern challenge for developers of medical information systems. The authors have designed a decision support system with an expanded set of auxiliary functions to solve the problems of human-computer interaction, increasing the completeness and reliability of medical information. In this paper, the applicability of the existing decision-making system is investigated on the example of medical data of patients with arterial hypertension. The testing of the decision support system among medical specialists was carried out. The impact of the implementation of the system on the number of errors when filling out an electronic medical record was assessed. A software module was created integrated into the working version of the medical information system in the Almazov National Medical Research Centre. Test implementation of the system made it possible to reduce the number of errors and increase satisfaction with the information presented in patients with arterial hypertension. |
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| ISSN: | 2226-1494 2500-0373 |
| DOI: | 10.17586/2226-1494-2022-22-1-217-222 |