Evidence map›Paper›PMID 36598880›Full record

ArticleNursing open2023

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

Tanja Liukas, Riitta Rosio, Laura-Maria Peltonen

Open access · goldAbstract read
In one paragraph

Article in Nursing open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.8field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. 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 : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025
    Observational
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Tanja LiukasTurku University hospital/Department of Nursing Science, University of Turku, Turku, Finland.ORCID 0000-0002-4187-3700
Riitta RosioDepartment of Nursing Science, University of Turku, Turku, Finland.
Laura-Maria PeltonenDepartment of Nursing Science, University of Turku, Turku, Finland.
University of Turku · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThe 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.

Indexed as

Breast NeoplasmsElectronic Health RecordsFemaleHumansMastectomyPostoperative PainRetrospective Studiesdecision support systemelectronic health recordpeople with breast cancerpostoperative persistent painpsychosocial factors

Identifiers

PMID36598880
PMCPMC10077400
OpenAlexW4313489136

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.