Evidence map›Paper›PMID 23962231›Full record

ArticleInternational journal for equity in health2013

Targeting patients for multimorbid care management interventions: the case for equity in high-risk patient identification.

Efrat Shadmi, Tobias Freund

Abstract readEditorial
In one paragraph

Article in International journal for equity in health, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
  2. Trial
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  8. Review
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  13. Multimorbidity and equity in health.International journal for equity in health · 2013
    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

2 authors.

Efrat ShadmiFaculty of Social Welfare and Health Sciences, University of Haifa, Mount Carmel 31905, Israel. eshadmi@univ.haifa.ac.il.
Tobias Freund

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Targeting patients for multimorbid care management interventions requires accurate and comprehensive assessment of patients' need in order to direct resources to those who need and can benefit from them the most. Multimorbid patient selection is complicated due to the lack of clear criteria--unlike disease management programs for which patients with a specific condition are identified. This ambiguity can potentially result in inequitable selection, as biases in selection may differentially affect patients from disadvantaged population groups. Patient selection could in principal be performed in three ways: physician referral, patient screening surveys, or by statistical prediction algorithms. This paper discusses equity issues related to each method. We conclude that each method may result in inequitable selection and bias, such as physicians' attentiveness or familiarity, or prediction models' reliance on prior resource use, potentially affected by socio-cultural and economic barriers. These biases should be acknowledged and dealt with. We recommend combining patient selection approaches to achieve high care sensitivity, efficiency and equity.

Indexed as

ComorbidityHealthcare DisparitiesPatient SelectionCase ManagementDelivery of Health CareHumansNeeds Assessment

Identifiers

PMID23962231
PMCPMC3847614

What OpenQuestion holds

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LicenceCC BY
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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.