Evidence map›Paper›PMID 37198637›Full record

ArticleBMC health services research2023

Effects of care of multimorbid patients in general practices by advanced practice nurses (FAMOUS): study protocol for a nonrandomized controlled trial.

Renate Stemmer, Britta Büchler, Matthias Büttner, Christina Dera-Ströhm, Joachim Klein, Emilio Gianicolo

Abstract readClinical Trial Protocol
In one paragraph

Article in BMC health services research, 2023. 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. [Focusing on intersectorality-strategies and current research projects for the care of geriatric people].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024
    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

6 authors.

Renate StemmerFaculty of Health Care and Nursing, Catholic University of Applied Sciences Mainz, Mainz, Germany. stemmer@kh-mz.de.
Britta BüchlerInstitute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Matthias BüttnerInstitute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Christina Dera-StröhmFaculty of Health Care and Nursing, Catholic University of Applied Sciences Mainz, Mainz, Germany.
Joachim KleinFaculty of Health Care and Nursing, Catholic University of Applied Sciences Mainz, Mainz, Germany.
Emilio GianicoloInstitute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Funding

German Innovation Fund of the Federal Joint Committee 01NVF19012
6 · The paper itself

Abstract

backgroundMultimorbidity is a common phenomenon among patients treated in general practices. Key challenges within this group include functional difficulties, polypharmacy, treatment burden, fragmentation of care, reduced quality of life and increased health care utilization. These problems cannot be solved in the short consultation time of a general practitioner (GP) since there is an increasing shortage of GPs. In many countries, advanced practice nurses (APNs) are successfully integrated into primary health care for multimorbid patients. The objective of this study is to examine whether the integration of APNs in the primary care of multimorbid patients in Germany leads to optimized care of the target group and to a reduction in the workload of the GPs.

methodsThe intervention includes the integration of APNs into the care for multimorbid patients in general practice for twelve months. Qualifications for APNs include a master's level academic degree and 500 hours of project-specific training. Their tasks include in-depth assessment, preparation, implementation, monitoring and evaluation of a person-centred and evidence-based care plan. In this nonrandomized controlled trial, a prospective multicentre mixed methods study will be performed. The main inclusion criterion was the cooccurrence of three chronic diseases. For data collection in the intervention group (n = 817), routine data from health insurance companies and association of statutory health insurance physicians (ASHIP) will be used, as well as qualitative interviews. In addition, the intervention will be assessed through documentation of the care process and standardized questionnaires using a longitudinal design. The control group (n = 1634) will receive standard care. For the evaluation, routine data from health insurance companies are matched at a ratio of 1:2. Outcomes will be measured using emergency contacts and GP visits, treatment costs, health status of the patients and the satisfaction of parties involved. The statistical analyses will include Poisson regression to compare outcomes between the intervention and control groups. Descriptive and analytical statistical methods will be used in the longitudinal analysis of the intervention group data. Cost analysis will compare total costs and subgroup costs between the intervention and control groups. Qualitative data will be analysed using content analysis. DISCUSSION: Challenges to this protocol could include the political and strategic environment as well as the planned number of participants.

trial registrationDRKS00026172 on DRKS.

Indexed as

General PracticeQuality of LifeControlled Clinical Trials as TopicHealth Care CostsHumansMultimorbidityProspective StudiesSurveys and QuestionnairesAdvanced practice nursesEvidence-based nursingMultimorbidityNonrandomized controlled trialPerson-centred carePrimary health care

Identifiers

PMID37198637
PMCPMC10189994

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.