Evidence map›Paper›PMID 39469491›Full record

ReviewPortuguese journal of public health2024

People with Multiple Long-Term Health Problems: Personalized Care Planning.

Edgar Canais, Lucília Nunes

Abstract readReview
In one paragraph

Review in Portuguese journal of public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Edgar CanaisDepartment of Nursing, Higher School of Health, Instituto Politécnico de Setúbal, Setúbal, Portugal.
Lucília NunesDepartment of Nursing, Higher School of Health, Instituto Politécnico de Setúbal, Setúbal, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The personalized care planning is a collaborative process used in managing long-term health conditions when the person and health professionals identify and discuss problems caused by or related to the health condition and develop a plan to address them. Objective: The aim of the study was to map the evidence on the impact of personalized care planning management on health outcomes in persons with multiple long-term health problems in the community. Methods: Scoping review was based on the Joanna Briggs Institute protocol; the search strategy was carried out in platforms and databases online; the participants are adults, with chronic disease or long-term health conditions, in the period from 2016 to 2021, in English, Spanish, and Portuguese; the exclusion criteria included studies of adults with dementia and intellectual disability; 22 studies were obtained. We applied critical appraisal, and two independent reviewers performed data extraction; data synthesis was performed in narrative form. Results: Nursing interventions, the strategies used by nurses, and the production of health gains (maintaining the level of health and well-being) promoted by nurses through the proper management of personalized care planning were identified. Conclusions: Nurses develop a wide range of interventions, using various strategies that promote health gains through the proper management of personalized care planning. Contributions to the Practice: Personalized care planning focuses on people with multimorbidity, and the health gains reduce, also, the nurses' workload.

Indexed as

Chronic diseasesCuidados de longa duraçãoCuidados de saúde primáriosDoenças crónicasLong-term careNursing care planPatient care planningPlano de cuidados de enfermagemPlano individual de cuidadosPrimary health care

Identifiers

PMID39469491
PMCPMC11499663

What OpenQuestion holds

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Registered trials

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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.