Building capacity for evidence-informed public health decision making

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Building capacity for

evidence-informed public

health decision making

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Participant Side

Panel in WebEx

Building capacity for

evidence-informed public

health decision making

Partnerships for health

system improvement

The Health Evidence Team

Maureen Dobbins

Scientific Director

Heather Husson

Manager

Lori Greco

Knowledge Broker Robyn Traynor

Research Coordinator

Research Assistants

Stephanie Workentine

Arnav Agarwal

Linda Chan

Tiffany Oei

Students

Reza Yousefi Nooraie

(PhD candidate)

Yaso Gowrinathan

Research Assistant/

Coordinator

Jennifer Yost

Assistant Professor

What is www.healthevidence.org?

Evidence

Decision

Making

inform

A Model for Evidence-Informed

Decision Making

National Collaborating Centre for Methods and Tools. (revised 2012).

A Model for Evidence-Informed Decision-Making in Public Health (Fact

Sheet). [http://www.nccmt.ca/pubs/FactSheet_EIDM_EN_WEB.pdf]

Stages in the process of

Evidence-Informed Public Health

National Collaborating Centre for Methods and Tools. Evidence-

Informed Public Health. [http://www.nccmt.ca/eiph/index-eng.html]

Funding for today’s webinar

Partnerships for

Health System Improvement

(FRN 101867)

Dissemination Event

(FRN 126353)

PHSI Study

• CIHR ‘Partnerships for Health System

Improvement’ grant

– Integrated KT program

– Collaborative, applied research

– Researcher/knowledge user partnerships

• Case study design

– Three Ontario health departments (“cases”)

– Tailored KTE intervention, delivered by KBs

We asked…

What is the impact of a

tailored KTE strategy on knowledge,

capacity & behaviour for EIDM?

What contextual factors facilitate

and/or impede impact?

Case A

Large, diverse

MOH/AMOH vision

EIDM strategic priority

Resources committed

Case B

Large, urban centre

MOH commitment

Manager ‘champion’

EIDM strategic priority

Case C

Mid-size, urban/rural mix

MOH commitment

Exec commitment

Tailored Interventions

Case A Case B Case C

Conte

xt

Inte

rvention

• Large, diverse

• MOH/AMOH vision

• EIDM strategic priority

• Resources committed

• Sept 2010 – Jun 2012

• KB on site, 2 d/wk

Mentored staff teams

Provided training

Participated in EIDM-

related events

One-on-one consulting

• Large, urban centre

• MOH commitment

• Manager ‘champion’

• EIDM strategic priority

• Apr 2011 – Feb 2013

• KB on/off-site: 2 d/wk


Provided training

Meetings /

presentations

Advised Senior

Management Team

• Mid-size, urban / rural

mix

• MOH commitment

• Exec commitment

• Apr 2011 – Dec 2012

• KB off-site*: 2 d/wk

(on-site 2 d/mon)


Advised RKEC on

Policy & Procedure

Provided training

Meetings /

presentations

Total Activities


• 5 questions/reviews

• Additional divisional

training delivered

(e.g. half-day

workshops)

• Presentations to

Senior Management

• Abstracts submitted

to present research

• 18 Rapid Reviews

• Large-scale training

sessions provided

• KB facilitated /

contributed to

Critical Appraisal

Club

• Presentations of

research to staff

colleagues & Senior

Management

• 5 questions/reviews

• EIDM Policy &

Procedure developed

& approved

• RKEC presentations

• All-staff training

delivered

Data Collection Baseline

Inte

rim

Follow

-Up

Online Survey*

EIDM Skills Tool

*Demographics, EBP Scale, SNA

Online Survey*

Online Survey*

EIDM Skills Tool

CHSRF Self-

Assessment

Interviews

Interviews

KB Journal

Meeting Minutes

Communications

Document Collection

Response Rate

Demographics

Gender Public Health

Experience

Highest Degree

Earned

● Diploma

● Bachelors

Masters

● Doctorate

20

15

10

5

0

We asked…


tailored KTE strategy on knowledge,




EIDM Knowledge & Skills

Baseline Follow-up

Case A 11.8 (6.1) 16.3 (5.9)***

Case B 10.1 (3.5) 10.9 (4.4)

Case C 9.3 (2.5) 12.9 (4.4)**

Pooled analysis† 10.5 (1.0) 13.4 (1.0)***

**p<0.01, ***p<0.001

† marginal means from a mixed effects regression model

EIDM Knowledge & Skills

• Increase in EIDM knowledge and skills in

those who worked intensively with KB (2.8

points, (2.0 to 3.6), p<0.001)

EIDM Behaviours

Baseline Interim Follow Up

Not involved 9.2 (0.8) 8.8 (0.9) 8.9 (0.8)

Large-group

training 9.3 (1.0) 10 (1.1) 10.4 (1.0)

Intensively

involved 10.4 (1.3) 12.8 (1.4)* 13.2 (1.3)*

*p<0.05

EIDM Behaviours


Baseline Interim Follow Up Baseline Interim Follow Up Baseline Interim Follow Up

Not

involved 7(9) 7(8) 7(10) 9.5(8.5) 6(9) 7(8) 3(6) 5(7) 4(7)

Large-

group

training

6.5(8) 8(8) 7.5(9) 10(7) 7.5(10) 8(7) 7(7) 8(6) 6(9)

Intensively

involved 12(9) 14(9) 15(13)* 7(4)

10.5

(6)* 10.5(8) 7.5(9) 11(9)*

8.5

(15.5)

All time points were compared to baseline using Wilcoxon Signed rank test.

*difference from baseline, p < 0.05

EIDM Behaviours

• Significant increase in EIDM behaviours in

those who worked intensively with KB, vs.

only attended large group sessions or not

involved at all.

• Based on SNA, of those who did not work

intensively with KB, staff who contacted an

expert in the department had significantly

improved EIDM behaviours.

EIDM Behaviours

• “Centrality” as a predictor of improvement:

significant increase in EIDM behaviours of

staff with many connections (i.e. staff come

to them for guidance) at baseline.

• Staff learned EIDM knowledge and skills, but

may not yet be putting these new learnings

into practice (i.e. changing behaviour).

We asked…


tailored KT strategy on knowledge,




Qualitative Analysis

• Data collected:

– 37 interviews

– 170+ KB reflective journal entries

– Case study notes

• Analyzed using NVivo9; coding

framework developed, constant

comparative process

Value of EIDM

• EIDM is foundational

“Critical, responsible”

• Research evidence is

only one aspect

• Pre-existing interest,

self-starters

Identified Supports

• Knowledge Broker skills and

support; neutral, expert mentor

• Easy access to resources and

tools; template and “process”

• Champions; peer support and

mentoring

• EIDM valued, embedded

Potential Challenges

• Time, competing priorities

• Limited engagement, slow progress

• Anxiety, uncertainty

• Communication

Potential Challenges

EIDM

EIDM

EIDM

• Definition of EIDM

• Not a “novel” concept

Overall Conclusions

• Public health practitioners who worked

most closely with KBs demonstrated

improvement in EIDM-related

behaviours, knowledge, skills.

• Those not intensively involved did not

change, with the exception of those

who interacted with someone identified

as an expert. Centrality in networks may

predict improvement.

• An improved understanding of EIDM

was transmitted among individuals and

diffused throughout health department.

• Improvement in EIDM behaviours cannot

be sustained unless organizational

structures are in place; process is

embedded, made routine practice.

• Understanding context is critical to

sustaining EIDM.

Publications • Traynor R, DeCorby K, Dobbins M. Knowledge brokering in public health: A

tale of two studies. Public Health 2014, doi: 10.1016/j.puhe.2014.01.015.

• Yousefi Nooraie R, Dobbins M, Marin A. Social and organizational factors

affecting implementation of evidence-informed practice in a public health

department in Ontario: a network modelling approach. Implementation

Science 2014, 9(1):29.

• Traynor R, Dobbins M, DeCorby K. Challenges of partnership research:

Insights from a collaborative partnership in evidence-informed public health

decision making. Evidence & Policy (accepted June 2014).

• Yost J, Dobbins M, Traynor R, DeCorby K, Workentine S, Greco L. Tools to

support evidence-informed public health decision making. BMC Public Health

(resubmitted June 2014).

• Greco L, DeCorby K, Traynor R, Dobbins M, Yost J, Workentine S.

Implementing tailored, knowledge translation and exchange interventions in

public health: a Partnerships for Health System Improvement study.

Canadian Journal of Public Health (submitted January 2014).

Thank you!

Contact us:

[email protected]

Building capacity for evidence-informed public health decision making

Healthcare

Transcript of Building capacity for evidence-informed public health decision making