Dissemin is shutting down on January 1st, 2025

Published in

Wiley, Academic Emergency Medicine: A Global Journal of Emergency Care, 8(18), p. 890-897, 2011

DOI: 10.1111/j.1553-2712.2011.01132.x

Links

Tools

Export citation

Search in Google Scholar

Pan-Asian Resuscitation Outcomes Study (PAROS): Rationale, Methodology, and Implementation

This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Disease-based registries can form the basis of comparative research to improve and inform policy for optimizing outcomes, for example, in out-of-hospital cardiac arrest (OHCA). Such registries are often lacking in resource-limited countries and settings. Anecdotally, survival rates for OHCA in Asia are low compared to those in North America or Europe, and a regional registry is needed. The Pan-Asian Resuscitation Outcomes Study (PAROS) network of hospitals was established in 2009 as an international, multicenter, prospective registry of OHCA across the Asia-Pacific region, to date representing a population base of 89 million in nine countries. The network's goal is to provide benchmarking against established registries and to generate best practice protocols for Asian emergency medical services (EMS) systems, to impact community awareness of prehospital emergency care, and ultimately to improve OHCA survival. Data are collected from emergency dispatch, ambulance providers, emergency departments, and in-hospital collaborators using standard protocols. To date (March 2011), there are a total of 9,302 patients in the database. The authors expect to achieve a sample size of 13,500 cases over the next 2 years of data collection. The PAROS network is an example of a low-cost, self-funded model of an Asia-Pacific collaborative research network with potential for international comparisons to inform OHCA policies and practices. The model can be applied across similar resource-limited settings.