Literature DB >> 34872725

Supporting evidence-informed policy making in rehabilitation: A logic framework for continuous improvement of rehabilitation programs.

Carla Sabariego1, Jerome Bickenbach1, Gerold Stucki2.   

Abstract

Because of important health and population trends, rehabilitation is a key health strategy of the 21st century, and efforts are being made towards a broader integration of rehabilitation into health systems worldwide. In the scope of the call for action Rehabilitation 2030, WHO recommends a logic model approach for monitoring and evaluating national efforts at the systems level. In this paper we argue that as strengthening rehabilitation in health systems will require countries to implement a range of new programs, sound logic models designed to monitor and evaluate rehabilitation programs at service level are needed as well. We therefore propose in this paper an overarching logic model for monitoring and evaluating rehabilitation programs, including feasible indicators, options for their operationalization and considerations about data analyses. Our overarching logic model for monitoring and evaluation at service level is suitable to structure national clinical quality management for continuous improvement, to inform policy making and programming at the national level, and to serve as a reference framework for research. The model will serve as a starting point for developing other logic models that fit specific features of rehabilitation programs in diverse settings and countries.
Copyright © 2021. Published by Elsevier B.V.

Entities:  

Keywords:  Evidence-Based Practice; Healthcare Quality Assurance; Learning Health System; Logic model; Rehabilitation

Mesh:

Year:  2021        PMID: 34872725     DOI: 10.1016/j.healthpol.2021.11.007

Source DB:  PubMed          Journal:  Health Policy        ISSN: 0168-8510            Impact factor:   2.980


  1 in total

1.  Editorial: Strengthening Rehabilitation in Europe.

Authors:  J Bickenbach; G Stucki; E van Ginneken; R Busse
Journal:  Health Policy       Date:  2022-03       Impact factor: 2.980

  1 in total

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