Evidence map›Paper›PMID 29464528›Full record

ReviewHealth economics review2018

The shaded side of the UHC cube: a systematic review of human resources for health management and administration in social health protection schemes.

Konrad Obermann, Tata Chanturidze, Bernd Glazinski, Karin Dobberschuetz, Heiko Steinhauer, Jean-Olivier Schmidt

Abstract readReview
In one paragraph

Review in Health economics review, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Konrad ObermannMannheim Institute of Public Health (MIPH), Heidelberg University, Ludolf-Krehl-Str. 7-11, Mannheim, 68167, Germany. konrad.obermann@medma.uni-heidelberg.de.ORCID http://orcid.org/0000-0002-0687-5014
Tata ChanturidzeOxford Policy Management, Oxford, UK.
Bernd GlazinskiRheinische Fachhochschule, Cologne, Germany.
Karin DobberschuetzAOK International Consulting by KomPart, Berlin, Germany.
Heiko SteinhauerMannheim Institute of Public Health (MIPH), Heidelberg University, Ludolf-Krehl-Str. 7-11, Mannheim, 68167, Germany.
Jean-Olivier SchmidtGIZ Deutsche Gesellschaft für Internationale Zusammenarbeit, Eschborn, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Managers and administrators in charge of social protection and health financing, service purchasing and provision play a crucial role in harnessing the potential advantage of prudent organization, management and purchasing of health services, thereby supporting the attainment of Universal Health Coverage. However, very little is known about the needed quantity and quality of such staff, in particular when it comes to those institutions managing mandatory health insurance schemes and purchasing services. As many health care systems in low- and middle-income countries move towards independent institutions (both purchasers and providers) there is a clear need to have good data on staff and administrative cost in different social health protection schemes as a basis for investing in the development of a cadre of health managers and administrators for such schemes. We report on a systematic literature review of human resources in health management and administration in social protection schemes and suggest some aspects in moving research, practical applications and the policy debate forward.

Indexed as

Health administrationHealth care purchasingHealth financingHuman resourcesManagementUHC

Identifiers

PMID29464528
PMCPMC5820241

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.