Evidence map›Paper›PMID 28413630›Full record

ReviewHealth information science and systems2017

Patient healthcare trajectory. An essential monitoring tool: a systematic review.

Jessica Pinaire, Jérôme Azé, Sandra Bringay, Paul Landais

Abstract readReview
In one paragraph

Review in Health information science and systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Barriers to accessing formal cancer care from the perspective of informal caregivers: a qualitative study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
  4. Article
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  6. Observational
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  9. Observational
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  11. "Frontiers in public health · 2023
    Article
  12. Artificial Intelligence in Biological Sciences.Life (Basel, Switzerland) · 2022
    Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Multi-level medical periodic patterns from human movement behaviors.Health information science and systems · 2019
    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

4 authors.

Jessica PinaireBiostatistics, Epidemiology and Public Health Department, Nîmes University Hospital, Place R Debré, 30 029 Nîmes, France.
Jérôme AzéLIRMM, UMR 5506, Montpellier University, 860 rue de Saint Priest - Bât 5, 34 095 Montpellier Cedex 5, France.
Sandra BringayLIRMM, UMR 5506, Montpellier University, 860 rue de Saint Priest - Bât 5, 34 095 Montpellier Cedex 5, France.
Paul LandaisBiostatistics, Epidemiology and Public Health Department, Nîmes University Hospital, Place R Debré, 30 029 Nîmes, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatient healthcare trajectory is a recent emergent topic in the literature, encompassing broad concepts. However, the rationale for studying patients' trajectories, and how this trajectory concept is defined remains a public health challenge. Our research was focused on patients' trajectories based on disease management and care, while also considering medico-economic aspects of the associated management. We illustrated this concept with an example: a myocardial infarction (MI) occurring in a patient's hospital trajectory of care. The patient follow-up was traced via the prospective payment system. We applied a semi-automatic text mining process to conduct a comprehensive review of patient healthcare trajectory studies. This review investigated how the concept of trajectory is defined, studied and what it achieves.

methodsWe performed a PubMed search to identify reports that had been published in peer-reviewed journals between January 1, 2000 and October 31, 2015. Fourteen search questions were formulated to guide our review. A semi-automatic text mining process based on a semantic approach was performed to conduct a comprehensive review of patient healthcare trajectory studies. Text mining techniques were used to explore the corpus in a semantic perspective in order to answer non-a priori questions. Complementary review methods on a selected subset were used to answer a priori questions.

resultsAmong the 33,514 publications initially selected for analysis, only 70 relevant articles were semi-automatically extracted and thoroughly analysed. Oncology is particularly prevalent due to its already well-established processes of care. For the trajectory thema, 80% of articles were distributed in 11 clusters. These clusters contain distinct semantic information, for example health outcomes (29%), care process (26%) and administrative and financial aspects (16%).

conclusionThis literature review highlights the recent interest in the trajectory concept. The approach is also gradually being used to monitor trajectories of care for chronic diseases such as diabetes, organ failure or coronary artery and MI trajectory of care, to improve care and reduce costs. Patient trajectory is undoubtedly an essential approach to be further explored in order to improve healthcare monitoring.

Indexed as

Healthcare trajectoryPPSSemi-automatedSystematic reviewsText miningWord cloud

Identifiers

PMID28413630
PMCPMC5390363

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.