Assessment of the Use of Patient Vital Sign Data for Preventing Misidentification and Medical Errors
Patient misidentification is a preventable issue that contributes to medical errors. When patients are confused with each other, they can be given the wrong medication or unneeded surgeries. Unconscious, juvenile, and mentally impaired patients represent particular areas of concern, due to their pot...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/10/12/2440 |
| _version_ | 1797457544920170496 |
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| author | Jared Maul Jeremy Straub |
| author_facet | Jared Maul Jeremy Straub |
| author_sort | Jared Maul |
| collection | DOAJ |
| description | Patient misidentification is a preventable issue that contributes to medical errors. When patients are confused with each other, they can be given the wrong medication or unneeded surgeries. Unconscious, juvenile, and mentally impaired patients represent particular areas of concern, due to their potential inability to confirm their identity or the possibility that they may inadvertently respond to an incorrect patient name (in the case of juveniles and the mentally impaired). This paper evaluates the use of patient vital sign data, within an enabling artificial intelligence (AI) framework, for the purposes of patient identification. The AI technique utilized is both explainable (meaning that its decision-making process is human understandable) and defensible (meaning that its decision-making pathways cannot be altered, just optimized). It is used to identify patients based on standard vital sign data. Analysis is presented on the efficacy of doing this, for the purposes of catching misidentification and preventing error. |
| first_indexed | 2024-03-09T16:23:35Z |
| format | Article |
| id | doaj.art-5c99287b2562493c8207a958205dd86a |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-09T16:23:35Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-5c99287b2562493c8207a958205dd86a2023-11-24T15:10:02ZengMDPI AGHealthcare2227-90322022-12-011012244010.3390/healthcare10122440Assessment of the Use of Patient Vital Sign Data for Preventing Misidentification and Medical ErrorsJared Maul0Jeremy Straub1Department of Computer Science, North Dakota State University, Fargo, ND 58102, USADepartment of Computer Science, North Dakota State University, Fargo, ND 58102, USAPatient misidentification is a preventable issue that contributes to medical errors. When patients are confused with each other, they can be given the wrong medication or unneeded surgeries. Unconscious, juvenile, and mentally impaired patients represent particular areas of concern, due to their potential inability to confirm their identity or the possibility that they may inadvertently respond to an incorrect patient name (in the case of juveniles and the mentally impaired). This paper evaluates the use of patient vital sign data, within an enabling artificial intelligence (AI) framework, for the purposes of patient identification. The AI technique utilized is both explainable (meaning that its decision-making process is human understandable) and defensible (meaning that its decision-making pathways cannot be altered, just optimized). It is used to identify patients based on standard vital sign data. Analysis is presented on the efficacy of doing this, for the purposes of catching misidentification and preventing error.https://www.mdpi.com/2227-9032/10/12/2440patient identificationartificial intelligencevital sign datamedical error preventiongradient descent trained expert system |
| spellingShingle | Jared Maul Jeremy Straub Assessment of the Use of Patient Vital Sign Data for Preventing Misidentification and Medical Errors Healthcare patient identification artificial intelligence vital sign data medical error prevention gradient descent trained expert system |
| title | Assessment of the Use of Patient Vital Sign Data for Preventing Misidentification and Medical Errors |
| title_full | Assessment of the Use of Patient Vital Sign Data for Preventing Misidentification and Medical Errors |
| title_fullStr | Assessment of the Use of Patient Vital Sign Data for Preventing Misidentification and Medical Errors |
| title_full_unstemmed | Assessment of the Use of Patient Vital Sign Data for Preventing Misidentification and Medical Errors |
| title_short | Assessment of the Use of Patient Vital Sign Data for Preventing Misidentification and Medical Errors |
| title_sort | assessment of the use of patient vital sign data for preventing misidentification and medical errors |
| topic | patient identification artificial intelligence vital sign data medical error prevention gradient descent trained expert system |
| url | https://www.mdpi.com/2227-9032/10/12/2440 |
| work_keys_str_mv | AT jaredmaul assessmentoftheuseofpatientvitalsigndataforpreventingmisidentificationandmedicalerrors AT jeremystraub assessmentoftheuseofpatientvitalsigndataforpreventingmisidentificationandmedicalerrors |