Towards automated risk prediction of persistent pain: Exploring psychosocial factors from electronic health records after breast cancer surgery

Author:

Liukas Tanja12ORCID,Rosio Riitta2,Peltonen Laura‐Maria2

Affiliation:

1. Turku University hospital/Department of Nursing Science University of Turku Turku Finland

2. Department of Nursing Science University of Turku Turku Finland

Abstract

AbstractAimThe 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.DesignA qualitative descriptive study.MethodsA 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.ResultsA 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.ConclusionsThe 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.

Publisher

Wiley

Subject

General Nursing

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimizing pain management in breast cancer care: Utilizing ‘All of Us’ data and deep learning to identify patients at elevated risk for chronic pain;Journal of Nursing Scholarship;2024-07-26

2. Natural Language Processing in Electronic Health Record Mining for Clinical Decision Support;2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI);2023-12-29

3. Postmastectomy Pain Syndrome: A Narrative Review;Cureus;2023-10-20

4. Security and Privacy Aspects of Electronic Health Records: A Review;2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT);2023-05-05

5. Therapeutic Approaches to Post-Mastectomy Pain Syndrome;Journal of Biosciences and Medicines;2023

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