Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgery
Abstract Aim The aim of this study was to describe what psychosocial factors associated with postoperative persistent pain can be found in electronic health records of patients with breast cancer, and which of these factors that may be used in the development of a decision‐support system algorithm t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-05-01
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| Series: | Nursing Open |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/nop2.1594 |
| _version_ | 1797851148747538432 |
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| author | Tanja Liukas Riitta Rosio Laura‐Maria Peltonen |
| author_facet | Tanja Liukas Riitta Rosio Laura‐Maria Peltonen |
| author_sort | Tanja Liukas |
| collection | DOAJ |
| description | Abstract Aim The aim of this study was to describe what psychosocial factors associated with postoperative persistent pain can be found in electronic health records of patients with breast cancer, and which of these factors that may be used in the development of a decision‐support system algorithm to better support health professionals in their clinical work. Design A qualitative descriptive study. Methods A retrospective electronic health record review was done using manual semantic annotation. A set of 101 records of patients with breast cancer were selected by computerized random sampling. The data were analysed with deductive content analysis. Results A total of 337 different expressions describing psychosocial factors associated with postoperative persistent pain were identified from the documentation done in the electronic health records. These regarded psychological strength and resilience, social factors, emotional factors, anxiety, sleep‐related factors and depression. No records were found dealing with pain catastrophizing. Although psychosocial factors associated with postoperative persistent pain were documented in the electronic health records, documentation about such factors was not found in all patient's records, nor was the documentation done in a systematic manner. Conclusions The findings show that there is potential to use electronic health records as information source in the development of decision‐support system algorithms to better support nurses in the identification of patients at risk of developing postoperative persistent pain. However, the documentation quality needs to be acknowledged in the application of decision support systems, which are built on information extracted from electronic health records. Future work is needed to standardize documentation practices and assess the comprehensiveness of the documentation. |
| first_indexed | 2024-04-09T19:13:11Z |
| format | Article |
| id | doaj.art-12821969de6c4e39ae2b6094a6e81b53 |
| institution | Directory Open Access Journal |
| issn | 2054-1058 |
| language | English |
| last_indexed | 2024-04-09T19:13:11Z |
| publishDate | 2023-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Nursing Open |
| spelling | doaj.art-12821969de6c4e39ae2b6094a6e81b532023-04-06T09:45:47ZengWileyNursing Open2054-10582023-05-011053399340510.1002/nop2.1594Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgeryTanja Liukas0Riitta Rosio1Laura‐Maria Peltonen2Turku University hospital/Department of Nursing Science University of Turku Turku FinlandDepartment of Nursing Science University of Turku Turku FinlandDepartment of Nursing Science University of Turku Turku FinlandAbstract Aim The aim of this study was to describe what psychosocial factors associated with postoperative persistent pain can be found in electronic health records of patients with breast cancer, and which of these factors that may be used in the development of a decision‐support system algorithm to better support health professionals in their clinical work. Design A qualitative descriptive study. Methods A retrospective electronic health record review was done using manual semantic annotation. A set of 101 records of patients with breast cancer were selected by computerized random sampling. The data were analysed with deductive content analysis. Results A total of 337 different expressions describing psychosocial factors associated with postoperative persistent pain were identified from the documentation done in the electronic health records. These regarded psychological strength and resilience, social factors, emotional factors, anxiety, sleep‐related factors and depression. No records were found dealing with pain catastrophizing. Although psychosocial factors associated with postoperative persistent pain were documented in the electronic health records, documentation about such factors was not found in all patient's records, nor was the documentation done in a systematic manner. Conclusions The findings show that there is potential to use electronic health records as information source in the development of decision‐support system algorithms to better support nurses in the identification of patients at risk of developing postoperative persistent pain. However, the documentation quality needs to be acknowledged in the application of decision support systems, which are built on information extracted from electronic health records. Future work is needed to standardize documentation practices and assess the comprehensiveness of the documentation.https://doi.org/10.1002/nop2.1594decision support systemelectronic health recordpeople with breast cancerpostoperative persistent painpsychosocial factors |
| spellingShingle | Tanja Liukas Riitta Rosio Laura‐Maria Peltonen Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgery Nursing Open decision support system electronic health record people with breast cancer postoperative persistent pain psychosocial factors |
| title | Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgery |
| title_full | Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgery |
| title_fullStr | Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgery |
| title_full_unstemmed | Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgery |
| title_short | Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgery |
| title_sort | towards automated risk prediction of persistent pain exploring psychosocial factors from electronic health records after breast cancer surgery |
| topic | decision support system electronic health record people with breast cancer postoperative persistent pain psychosocial factors |
| url | https://doi.org/10.1002/nop2.1594 |
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