Evidence map›Paper›PMID 28202047›Full record

ArticleHuman resources for health2017

Health workforce metrics pre- and post-2015: a stimulus to public policy and planning.

Francisco Pozo-Martin, Andrea Nove, Sofia Castro Lopes, James Campbell, James Buchan, Gilles Dussault, Teena Kunjumen, Giorgio Cometto, Amani Siyam

Abstract read
In one paragraph

Article in Human resources for health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. 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

9 authors.

Francisco Pozo-MartinInstituto de Cooperación Social Integrare, calle Balmes 30, 3-1, 08007, Barcelona, Spain.
Andrea NoveInstituto de Cooperación Social Integrare, calle Balmes 30, 3-1, 08007, Barcelona, Spain. andrea.nove@icsintegrare.org.
Sofia Castro LopesInstituto de Cooperación Social Integrare, calle Balmes 30, 3-1, 08007, Barcelona, Spain.
James CampbellHealth Systems and Innovations, WHO Headquarters, Geneva, Switzerland.
James BuchanSchool of Nursing Midwifery and Health, University of Technology Sydney, Sydney, Australia.
Gilles DussaultGlobal Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal.
Teena KunjumenHealth Systems and Innovations, WHO Headquarters, Geneva, Switzerland.
Giorgio ComettoGlobal Health Workforce Network, WHO Headquarters, Geneva, Switzerland.
Amani SiyamHealth Systems and Innovations, WHO Headquarters, Geneva, Switzerland.

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundEvidence-based health workforce policies are essential to ensure the provision of high-quality health services and to support the attainment of universal health coverage (UHC). This paper describes the main characteristics of available health workforce data for 74 of the 75 countries identified under the 'Countdown to 2015' initiative as accounting for more than 95% of the world's maternal, newborn and child deaths. It also discusses best practices in the development of health workforce metrics post-2015.

methodsUsing available health workforce data from the Global Health Workforce Statistics database from the Global Health Observatory, we generated descriptive statistics to explore the current status, recent trends in the number of skilled health professionals (SHPs: physicians, nurses, midwives) per 10 000 population, and future requirements to achieve adequate levels of health care in the 74 countries. A rapid literature review was conducted to obtain an overview of the types of methods and the types of data sources used in human resources for health (HRH) studies.

resultsThere are large intercountry and interregional differences in the density of SHPs to progress towards UHC in Countdown countries: a median of 10.2 per 10 000 population with range 1.6 to 142 per 10 000. Substantial efforts have been made in some countries to increase the availability of SHPs as shown by a positive average exponential growth rate (AEGR) in SHPs in 51% of Countdown countries for which there are data. Many of these countries will require large investments to achieve levels of workforce availability commensurate with UHC and the health-related sustainable development goals (SDGs). The availability, quality and comparability of global health workforce metrics remain limited. Most published workforce studies are descriptive, but more sophisticated needs-based workforce planning methods are being developed.

conclusionsThere is a need for high-quality, comprehensive, interoperable sources of HRH data to support all policies towards UHC and the health-related SDGs. The recent WHO-led initiative of supporting countries in the development of National Health Workforce Accounts is a very promising move towards purposive health workforce metrics post-2015. Such data will allow more countries to apply the latest methods for health workforce planning.

Indexed as

Developing CountriesHealth PlanningHealth PolicyHealth Services AccessibilityData CollectionFemaleGlobal HealthHealth PersonnelHealth Services Needs and DemandHumansInfantInfant MortalityInfant, NewbornMaternal MortalityMidwiferyNursesCountdownDataDensitiesHealth systemsHealth workforceLow- and middle-income countriesMetricsSustainable development goalsUniversal health coverage

Identifiers

PMID28202047
PMCPMC5312527

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.