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Pierre Barker MD

Senior Vice President IHI

Improving Quality: Theories of Change

Basic

science

Proof of

concept

Large

scale

efficacy

Study

What are we trying to solve?

The “What”

Reliable

“real-life”

implement-

ation

Scale-up to

populations

The “How”

Guidelines, Training & Resources,

Adaptive Designs that are context

sensitive

Designs that can be scaled-

up with the resources at

hand

Quality Improvement: Bringing Together

Two Types of Knowledge – (Deming)

Implementation

Knowledge Common view of the System

Motivation/Leadership

Accurate Reflective Data

“Learning by Doing”

Evidence

Based Subject

Matter

Knowledge Protocols/Guidelines,

Physical resources,

Clinical Training

the “what”

the “how”

Implementation

Knowledge

Evidence-based Subject

Matter Knowledge

Improvement

Improvement: Bringing Together Two

Types of Knowledge

Dr. Joseph M. Juran’s “Quality Trilogy” 5

QUALITY PLANNING

QUALITY IMPROVEMENT

QUALITY CONTROL

Juran Trilogy: All three elements are

needed

6

PERFORMANCE SHIFT

Chronic waste (opportunity for improvement)

Sporadic spike

Source: Juran J, Godfrey AB, eds. Juran’s Quality

Handbook: Fifth Edition. New York: McGraw-Hill, 1999.

Juran Trilogy: All three elements are

needed

7

PERFORMANCE SHIFT

Chronic waste (opportunity for improvement)

Sporadic spike

Source: Juran J, Godfrey AB, eds. Juran’s Quality

Handbook: Fifth Edition. New York: McGraw-Hill, 1999.

Juran Trilogy: All three elements are

needed

8

PERFORMANCE SHIFT

Chronic waste (opportunity for improvement)

Sporadic spike

Source: Juran J, Godfrey AB, eds. Juran’s Quality

Handbook: Fifth Edition. New York: McGraw-Hill, 1999.

Juran Trilogy: All three elements are

needed

9

PERFORMANCE SHIFT

Chronic waste (opportunity for improvement)

Sporadic spike

Source: Juran J, Godfrey AB, eds. Juran’s Quality

Handbook: Fifth Edition. New York: McGraw-Hill, 1999.

Policy, resources, coordination, accountability, mandates, etc.

Quality Planning

Components of quality: structure,

quality control and quality improvement

10

Quality

Improvement Rapid cycle

improvement

Motivation

Building knowledge

Continuous data

Standards/ Guidelines/

protocols

Professional oversight

Accreditation

Checklists

Quality Control

(Assurance)

IMPROVED

OUTCOMES

Quality Planning

11

Quality

Improvement Aims

Measures

Changes

Quality Control

IMPROVED

OUTCOMES

QA and “QI” confusion: both can/should

use Model for Improvement

Aims

Measures

Changes

QA Approach

IMPLEMENT STANDARDS

PROBLEM

SOLUTION (DEVELOP

STANDARDS)

Review (Succeed/Fail)

SYSTEM BARRIERS

Context & Local Knowledge

QI Approach

GREAT IDEAS

SYSTEM ANALYSIS

IMPLEMENT

SUCCEED/ FAIL

PROBLEM

Context & Local Knowledge

Rapid Test System

Where do approaches fit on the QA/QI

Spectrum

QA QI Accreditation

COPE

SBM-R

IHI Breakthrough Series

Standards based approaches

Preterm mortality ~60/1000 births

Theory of Change: Drivers of Maternal

and Newborn Survival

Decrease Maternal and

newborn mortality by

50%

Motivation for change

Knowledgeable health workers ready to use their

skills

Immediate access to essential commodities

Data systems in real time

A Learning System Cross-professional teams meet regularly, review data, test changes, report progress

Progress celebrated, challenges supported

Informed/activated patients & communities

Drills, mentoring

Decision support, checklists

Key suppliers part of QI team

Data for improvement vs data for reporting

Data “owned” at every level

Multi-level leaders promote change

Supportive Supervision

Essential QI methods

Data-driven process

improvement

SCREEN TREAT RELIABLE

MEASURES

AVAILABLE DRUGS & SUPPLIES

Systems approach The Gap

% m

oth

ers

rece

ivin

g A

CS

Rapid cycle testing of local ideas

% eligible women received at least one

dose of corticosteroids

2

1

Sustainability

February 2014

June 2014

December 2014

% eligible women received at least one

dose of corticosteroids

Zone of control/assurance QI

Essential QI methods

Phased Scale up

methods

Local leadership

Context-sensitive learning systems

Summary

1. What is the problem we are trying to solve? Context-sensitive implementation and scale up, using

adaptive designs

2. How do you change system performance? Deming – the “what” and the “how” (common systems,

psychology/motivation, reflective data, learning while

doing)

3. A balanced view of quality Juran Trilogy (planning, assurance/control, improvement)

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