Evidence map›Paper›PMID 36043026›Full record

ArticleInternational journal of integrated care

Identifying Individuals for Integrated Multidisciplinary Care: Lessons from Finland.

Juha Koivisto, Hanna Tiirinki, Eeva Liukko

Abstract read
In one paragraph

Article in International journal of integrated care. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Juha KoivistoFinnish Institute for Health and Welfare, FI.ORCID https://orcid.org/0000-0002-8442-6820
Hanna TiirinkiFinnish Institute for Health and Welfare, FI.ORCID https://orcid.org/0000-0002-8529-3206
Eeva LiukkoFinnish Institute for Health and Welfare, FI.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This paper analyses and discusses the models and tools in the Finnish health and social care system to identify the individuals who might benefit from integrated multidisciplinary care. Description: The analysis and discussion of the paper is based on a study which mapped and studied the models and tools in practice or under development for identification in the Finnish health and social care organizations. The study used electric survey and structured interviews as research methods. Discussion: There are several different established models of identification in Finland and the experiences of using them are mainly positive. However, only every third of health and social care organizations in Finland have defined a common model or tool. The identification practices and criteria vary by region, municipality and/or organization. The identification is in general unsystematic and insufficient in practice that may inhibit the individuals to access the integrated care they might benefit from. Conclusions: Models and tools are needed for founding and identifying individuals who are outside the service system, those whose client-ship has just begun, and those who already access services. The identification of individuals for integrated multidisciplinary care and the assimilation and understanding of different identification models and tools requires the development of basic and further competence in the different fields of health and social care. Multidisciplinary collaboration requires shared concepts and positive attitudes on the development of integrated professional environments, identification models and services. It is therefore also a question of shared working culture.

Indexed as

health and social careintegrated caremultidisciplinaryservices

Identifiers

PMID36043026
PMCPMC9374024

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.