Evidence map›Paper›PMID 31856192›Full record

ArticlePloS one2019

Caring for the elderly: A person-centered segmentation approach for exploring the association between health care needs, mental health care use, and costs in Germany.

Beate Wild, Dirk Heider, Dieter Schellberg, Friederike Böhlen, Ben Schöttker, Dana Clarissa Muhlack, Hans-Helmut König, Joris Slaets

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

  1. Unlocking the WHO's Age-Friendly Healthcare Principles: Portugal's Quest and Recommendations.International journal of environmental research and public health · 2023
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  4. Inequalities in Psychiatric Morbidity in Hong Kong and Strategies for Mitigation.International journal of environmental research and public health · 2022
    Article
  5. Article
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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

8 authors at 3 institutions in 1 country.

Beate WildDepartment of General Internal Medicine and Psychosomatics, Medical University Hospital, Heidelberg, Germany.ORCID 0000-0002-2279-8135
Dirk HeiderDepartment of Health Economics and Health Services Research, University Medical Center Hamburg-Eppendorf, Germany.
Dieter SchellbergDepartment of General Internal Medicine and Psychosomatics, Medical University Hospital, Heidelberg, Germany.
Friederike BöhlenDepartment of General Internal Medicine and Psychosomatics, Medical University Hospital, Heidelberg, Germany.ORCID 0000-0003-1502-4470
Ben SchöttkerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany.
Dana Clarissa MuhlackDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany.ORCID 0000-0002-7806-4480
Hans-Helmut KönigDepartment of Health Economics and Health Services Research, University Medical Center Hamburg-Eppendorf, Germany.
Joris SlaetsDepartments of Internal Medicine and Geriatrics, University Hospital, Groningen, Netherlands.
Heidelberg University · DEGerman Cancer Research Center · DEUniversität Hamburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPerson-centered care demands the evaluation of needs and preferences of the patients. In this study, we conducted a segmentation analysis of a large sample of older people based on their bio-psycho-social-needs and functioning. The aim of this study was to clarify differences in health care use and costs of the elderly in Germany.

methodsData was derived from the 8-year follow-up of the ESTHER study-a German epidemiological study of the elderly population. Trained medical doctors visited n = 3124 participants aged 57 to 84 years in their home. Bio-psycho-social health care needs were assessed using the INTERMED for the Elderly (IM-E) interview. Further information was measured using questionnaires or assessment scales (Barthel index, Patients Health Questionnaire (PHQ) etc.). The segmentation analysis applied a factor mixture model (FMM) that combined both a confirmatory factor analysis and a latent class analysis.

resultsIn total, n = 3017 persons were included in the study. Results of the latent class analysis indicated that a five-cluster-model best fit the data. The largest cluster (48%) can be described as healthy, one cluster (13.9%) shows minor physical complaints and higher social support, while the third cluster (24.3%) includes persons with only a few physical and psychological difficulties ("minor physical and psychological complaints"). One of the profiles (10.5%) showed high and complex bio-psycho-social health care needs ("complex needs") while another profile (2.5%) can be labelled as "frail". Mean values of all psychosomatic variables-including the variable health care costs-gradually increased over the five clusters. Use of mental health care was comparatively low in the more burdened clusters. In the profiles "minor physical and psychological complaints" and "complex needs", only half of the persons suffering from a mental disorder were treated by a mental health professional; in the frail cluster, only a third of those with a depression or anxiety disorder received mental health care.

conclusionsThe segmentation of the older people of this study sample led to five different clusters that vary profoundly regarding their bio-psycho-social needs. Results indicate that elderly persons with complex bio-psycho-social needs do not receive appropriate mental health care.

Indexed as

Costs and Cost AnalysisNeeds AssessmentAgedAged, 80 and overDelivery of Health CareFemaleGermanyHumansMaleMental HealthMiddle Aged

Identifiers

PMID31856192
PMCPMC6922348
OpenAlexW2994962494

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.