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Rx for Change

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What is the best way to bring about behaviour change in health care? Does evidence show that some intervention strategies are better than others? Rx for Change is a searchable database containing current research evidence about intervention strategies used to alter behaviours of health technology prescribing, practice, and use. The intent of this database is to help inform the choice and use of practical, evidence-based interventions.

CADTH would like to thank the following contributing partners for their generous support with Rx for Change:

If you are interested in becoming an Rx for Change partner, please email requests@cadth.ca.

About Rx for Change

The database was set up using rigorous methods developed through a multi-organizational collaboration. It is structured by categories based on types of behaviour-change strategies: professional, consumer, organizational, financial, or regulatory, and can be searched by keyword.

Detailed analysis is also provided, including:

  • overall summaries of interventions based on evidence from systematic reviews
  • summaries of related individual reviews
  • quality assessments and summarized reviews that highlight key characteristics and relevant evidence for decision-making
  • links to the individual studies included in each review.

Reviews targeting professional — and financial, structural, and organizational strategies — are defined and organized according to an intervention classification scheme of the Cochrane Effective Practice and Organisation of Care (EPOC) Review Group. Reviews targeting consumer strategies are defined and organized according to a unique scheme developed by the Cochrane Consumers and Communication Review Group. Within the database, intervention categories are listed from top to bottom, based on the amount of information provided.

EPOC Taxonomy

Rx for Change Fact Sheet

Example of Its Use 

An organization or jurisdiction decides to address a specific concern regarding the prescribing of antibiotics. It sets aside funds to send out thousands of flyers to prescribers, to influence prescribing behaviour.

Before earmarking this money for flyers, the Rx for Change database can be used to determine if such a strategy actually affects behaviours. If the organization finds out that it does not — that the evidence shows that it may be ineffective, or that there is not enough evidence to demonstrate that it effectively produces behaviour change — investment in an alternate method to change prescribing behaviour may be a good option.

Online Tutorial 

If you are new to Rx for Change, our online tutorial can help you navigate the database. The tutorial explains how the database is organized and what interventions are available, and it uses real-world case studies. 
Note: The tutorial was developed by CADTH’s former Canadian Optimal Medication Prescribing and Utilization Service (COMPUS) directorate, and uses images from CADTH’s previous website; however, the structure of the database remains fundamentally the same.

Rx for Change Updates 

The database is updated on a periodic basis to ensure the evidence base remains as current as feasible for helping to best inform decisions regarding the selection of change interventions.

2014 April

Professionals section – to December 2013

Consumers section – to December 2013

2013 April

Professionals section —to April 2012
Consumers section — to April 2012

2012 April

Professionals section —to September 2011
Consumers section — to September 2011

2011 August

Professional section — to January 2011 
Consumers section — to September 2010

2010 December

Professionals section — to May 2010 
Consumers section — to December 2009

2010 April

Professionals section — April to September 2009
Consumers section — to January 2009

2009 October

Professionals section — June 2008 to March 2009 
Consumers section — to September 2008

2009 April

Full database — April 2006 to May 2008

2007 March

Database launch — Reviews to March 2006

Methods for Development

The following sections summarize the methods for development.  Additional detail on these methods can be found at the following links:

Searching for Reviews

Detailed electronic and hand searches were performed to identify potentially relevant systematic reviews. Selection criteria used in the identification of key systematic reviews included methodological quality and currency of the research.   

Methods for Data Collection and Quality Assessment of Systematic Reviews

A standardized data extraction form was developed and refined through consultation and piloting. The form summarized evidence, methodological quality, and key characteristics for each review.

AMSTAR, A MeaSurement Tool to Assess Reviews, was used to assess systematic review quality. This tool provides an overall quality rating on a scale of 0 to 11, where 11 represents a review of the highest quality. Categories of quality were determined, as follows: low (score 0 to 3), medium (score 4 to 7), and high (score 8 to 11).

Data collection for interventions targeting Health Care Professionals was performed by two reviewers.  Adjudication of discrepancies was handled by one of two senior reviewers, who also compiled the final dataset. Quality assessment was also performed by two reviewers, with adjudication of discrepancies handled by one of two senior reviewers.

Data collection for interventions targeting Consumers was performed by one reviewer. A second reviewer verified the data abstraction. The quality assessment was performed by one reviewer, with a second reviewer verifying the assessment. Any differences for the data collection or the quality assessment were resolved by discussion.Data Synthesis, Presentation, and Rating

Individual Review Summaries

Results of the included reviews were analyzed, summarized, and reported quantitatively and descriptively. Data were organized by overall results and results related to prescribing. Results were broadly reported as:

  • vote counting plus reporting of absolute effect measures (with or without a measure of variability)

  • vote counting plus reporting of relative effect measures (with or without a measure of variability)

  • vote counting alone, by direction or statistical significance, depending on available information.

To standardize the reporting of prescribing-related outcomes, the following categorizations were developed and used:

  • concordance
  • appropriate use:
    • dosage
    • choice
    • route of administration
  • cost containment
  • other

Standardized statements and decision rules were used for reporting the evidence for the Results, Conclusions, and Effectiveness sections of each review summary.

Reviews listed as ‘summary pending’ will be analyzed, summarized and reported at a later date and the findings will then be incorporated in the overall evidence summaries of the interventions they address.

Summaries of Intervention Classification Categories

To improve the usefulness of this database, overall summaries representing the evidence reported among reviews for a common intervention are provided. Standardized statements and decision rules were used for producing these summaries.

Structure of the Database

Summaries of interventions and individual reviews were produced based on a template. Decisions about the amount and type of information presented were made jointly by the CADTH and EPOC teams.

A list of the individual studies included in each review is provided as a link from the individual review summary page. This list may not be comprehensive for each review. Detailed information on the fields available within each summary, as well as methodology and reasons for missing references, is available in the detailed methodology sections for Professionals and Consumers.

Study Team
Dr. Jeremy Grimshaw, Principal Investigator
Dr. Sophie Hill, Senior Advisor (Consumers)
Dianne Lowe
Alain Mayhew
Michelle Fiander
Misty Pratt
Julia Worswick
Julie Wu
Sharlini Yogasingam
Acknowledgements
Lev Bubis
Dr. Genevieve Cowie
Imran Khan
Caroline Kaufman
Shannon O’Sullivan
Dr. Rebecca Ryan
Nancy Santesso
Andrea Silver
Adrienne Stevens
Katrina Sullivan
Dr. Michael Taylor
S. Carolyn Wayne
Michelle Weir
Doug Salzwedel

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