Evidence map›Paper›PMID 25234141›Full record

ArticleHuman resources for health2014

Personnel planning in general practices: development and testing of a skill mix analysis method.

Juliane von Eitzen-Strassel, Hubertus J M Vrijhoef, Emmy W C C Derckx, Dinny H de Bakker

Abstract readEvaluation Study
In one paragraph

Article in Human resources for health, 2014. 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
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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

4 authors.

Juliane von Eitzen-Strassel
Hubertus J M Vrijhoef
Emmy W C C Derckx
Dinny H de BakkerNIVEL, Netherlands Institute for Health Services Research, P,O, Box 1568, 3500 BN, Utrecht, The Netherlands. d.debakker@nivel.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGeneral practitioners (GPs) have to match patients' demands with the mix of their practice staff's competencies. However, apart from some general principles, there is little guidance on recruiting new staff. The purpose of this study was to develop and test a method which would allow GPs or practice managers to perform a skill mix analysis which would take into account developments in local demand.

methodsThe method was designed with a stepwise method using different research strategies. Literature review took place to detect available methods that map, predict, or measure patients' demands or needs and to fill the contents of the skill mix analysis. Focus groups and expert interviews were held both during the design process and in the first test stage. Both secondary data analysis as primary data collection took place to fill the contents of the tool. A pilot study in general practices tested the feasibility of the newly-developed method.

resultsThe skill mix analysis contains both a quantitative and a qualitative part which includes the following sections: (i) an analysis of the current and the expected future demand; (ii) an analysis of the need to adjust skill mix; (iii) an overview about the functions of different provider disciplines; and (iv) a system to assess the input, assumed or otherwise, of each function concerning the 'catching up demand', the connection between supply and demand, and the introduction of new opportunities. The skill mix analysis shows an acceptable face and content validity and appears feasible in practice.

conclusionsThe skill mix analysis method can be used as a basis to analyze and match, systematically, the demand for care and the supply of practice staff.

Indexed as

Clinical CompetenceDecision MakingDecision Support TechniquesGeneral PracticeHealth Services Needs and DemandPersonnel SelectionPrimary Health CareHumansPilot ProjectsWorkforce

Identifiers

PMID25234141
PMCPMC4177762

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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.