Enabling cross-country learning and exchange to support universal health coverage implementation.

Peer-to-peer learning decolonizing global health joint learning knowledge exchange

Journal

Health policy and planning
ISSN: 1460-2237
Titre abrégé: Health Policy Plan
Pays: England
ID NLM: 8610614

Informations de publication

Date de publication:
23 Jan 2024
Historique:
received: 02 03 2023
revised: 29 09 2023
accepted: 24 10 2023
medline: 23 1 2024
pubmed: 23 1 2024
entrez: 22 1 2024
Statut: ppublish

Résumé

As countries transition from external assistance while pursuing ambitious plans to achieve universal health coverage (UHC), there is increasing need to facilitate knowledge sharing and learning among them. Country-led and country-owned knowledge management is foundational to sustainable, more equitable external assistance for health and is a useful complement to more conventional capacity-building modalities provided under external assistance. In the context of external assistance, few initiatives use country-to-country sharing of practitioner experiences, and link learning to receiving guidance on how to adapt, apply and sustain policy changes. Dominant knowledge exchange processes are didactic, implicitly assuming static technical needs, and that practitioners in low- and middle-income countries require problem-specific, time-bound solutions. In reality, the technical challenges of achieving UHC and the group of policymakers involved continuously evolve. This paper aims to explore factors which are supportive of experience-based knowledge exchange between practitioners from diverse settings, drawing from the experience of the Joint Learning Network (JLN) for UHC-a global network of practitioners and policymakers sharing experiences about common challenges to develop and implement knowledge products supporting reforms for UHC-as an illustration of a peer-to-peer learning approach. This paper considers: (1) an analysis of JLN monitoring and evaluation data between 2020 and 2023 and (2) a qualitative inquiry to explore policymakers' engagement with the JLN using semi-structured interviews (n = 14) with stakeholders from 10 countries. The JLN's experience provides insights to factors that contribute to successful peer-to-peer learning approaches. JLN relies on engaging a network of practitioners with diverse experiences who organically identify and pursue a common learning agenda. Meaningful peer-to-peer learning requires dynamic, structured interactions, and alignment with windows of opportunity for implementation that enable rapid response to emerging and timely issues. Peer-to-peer learning can facilitate in-country knowledge sharing, learning and catalyse action at the institutional and health system levels.

Identifiants

pubmed: 38253439
pii: 7578675
doi: 10.1093/heapol/czad097
doi:

Types de publication

Journal Article

Langues

eng

Pagination

i125-i130

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

Auteurs

Lauren Oliveira Hashiguchi (L)

The World Bank, 1818 H Street NW, Washington, DC 20433, USA.

Maeve Conlin (M)

Management Sciences for Health, 4301 Fairfax Drive, Suite 400, Arlington, VA 22203, USA.

Dawn Roberts (D)

Independent Consultant, Portland, ME, USA.

Kathleen McGee (K)

The World Bank, 1818 H Street NW, Washington, DC 20433, USA.

Robert Marten (R)

Alliance for Health Policy and Systems Research, World Health Organization, Avenue Appia 20, Geneva 1211, Switzerland.

Stefan Nachuk (S)

Morris Brothers LLC, Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia.

Ali Ghufron Mukti (AG)

BPJS Kesehatan (Social Insurance Administration Organization), Government of Indonesia, JL Letjen Suprapto Cempaka Putih, Jakarta 10510, Indonesia.

Aditi Nigam (A)

The World Bank, 1818 H Street NW, Washington, DC 20433, USA.

Naina Ahluwalia (N)

The World Bank, 1818 H Street NW, Washington, DC 20433, USA.

Somil Nagpal (S)

The World Bank, 12th Floor, IDX Building, Tower 2, Sudirman CBD, Jakarta, Indonesia.

Classifications MeSH