Planning HPSR studies:

key issues for specific

designs

IHPSR Presentation 7

www.hpsa-africa.org

@hpsa_africa

www.slideshare.net/hpsa_africa

Introduction to Health Policy and

Systems Research

Specific study designs

1. Cross-sectional design

2. Case study

3. Action research

Research questions

Purpose(s) Theory

Methods Sampling

strategy

Researchdesign and strategy

1. Cross-sectional design

• Most frequently reported HPSR study design

• Used to explore, describe or explain a

phenomenon at a particular time

– Does not examine change over time

– Does not assess interventions

• Encompasses a range of disciplinary

perspectives and design approaches

Fixed design Flexible design Mixed method design

Discrete Choice

Experiment studies

e.g. Blaauw et al. (2010)

nurses preferences for

policy interventions to

attract them to work in rural

areas across three

countries

Kurowski et al. (2007)

Building explanatory

frameworks about the

role of trust in the

choice of health care

provider among women

of different socio-

economic status in

Thailand (Riewpaiboon

et al., 2005)

Interpretive analysis of

how policy actors’

understandings

influence

implementation of HIV

clinical guidelines in

India (Sheikh & Porter,

2010)

Constructing a model of

the demand and supply

side dimensions of poor

malaria control in

Vietnam (Morrow et al.,

2009)

Examining the coping

strategies used by

households to manage

the costs of inpatient

care in India (Ranson,

Jayaswal & Mills, 2011)

Always have to think about

• What are phenomena of focus?

• How can key concepts/variables of question be

operationalised?

– to be able to measure, see, interpret, e.g. good quality, trust

in provider, motivation

– what role for theory?

• What data sources (e.g. people, documents, records)

and forms (e.g. numerical, talk, text) are relevant?

• What sampling approach is relevant?

• What are most appropriate data collection tools?

– e.g. structured questionnaire or in-depth interview?

– e.g. record audit or discourse analysis of documents?

• What are most appropriate analysis strategies?

– deductive vs. inductive analysis?

– what role for theory?

• What are relevant analysis steps?

– e.g. DCE steps, statistical modeling, stakeholder analysis,

causal loop diagrams

2. Case study

• Why use a case study design in HPSR?

• What is it?

• Key issues in doing case study work

Why use it?

NB Widely, but weakly used in HPSR

• Use to help explore little understood health policy and

systems (HPS) issues

• Use to investigate HPS complexity:

– Multiple contextual factors

– Actors’ perceptions matter, with multiple

interpretations of same phenomena

• Often can only examine small number of ‘cases’

(statistical inference not possible)

What is it?

Case study is a strategy for doing research

which involves an empirical investigation of:

• a particular contemporary phenomenon

• within its real life context

• using multiple sources of evidence Yin, 2009

When planning a case study you

have to think about more than data

collection procedures!

A case study strategy can be

appropriately used to address any

purpose, and as part of a range of study

types

What’s your purpose?

Exploratory Descriptive Explanatory Emancipatory

Identifying categories,

labelling them &

identifying underlying

principles

Identifying movement

through time

Unravelling complex

causality, esp. relationship

between deliberate

behaviour of several actors

& agencies

Action

research

• Can be cross-sectional, retrospective, prospective

• Can be frame for mixed method studies

• Can be element of evaluation work

Examples

Paper Purpose Question

Mutemwa,

2006

Exploratory/De

scriptive

WHAT information forms

are used in decision-

making?

Rolfe et al.,

2008

Exploratory/De

scriptive

(?Explanatory)

WHAT influences the

development of private

midwifery practices?

Lee et al.,

1998

Explanatory WHY do some countries

have effective family

planning programmes

and others do not?

When to use case study rather

than fixed design?Exploratory & Descriptive

work:

• When do not already

know enough about issue

to be able to develop

structured tool or

approach to

measure/assess

• Mutemwa, 2006

• Rolfe et al., 2008

Explanatory work:

• When complexity of issue

makes

measurement/assessmen

t difficult – and need to

ask how and why

questions

• Russell & Gilson, 2006

Explanatory

• Household case studies, followed over

time

– Revealed the complex and dynamic nature

of economic burdens of illness, and

associated coping strategies

– Allowed a picture of the interconnected

factors mediating the impact of illness on

livelihood outcomes

Case study work should either ‘test’ or

generate ‘theory’

But remember, theory comes in various

forms!

Exploratory & Descriptive

work:

• may involve building

theory: linked to

classification and

identifying underlying

principles

Mutemwa, 2006

Rolfe et al. 2008

Explanatory work:

• use theory to analyse

movement through time

and understand causality

• but be open/flexible even

when have some initial

ideas seek to ‘test’

Rolfe et al. 2008

Lee et al. 1998

Sampling: it is always important to identify

and select cases carefully

Defining feature of

case study work

• Focuses on a single case or small set of

cases

– Robson, 2002:

• use the word ‘site’ as a reminder that every

case is situated in a specific social and physical

setting

• so need to contextualise the case to

understand experience (unlike much fixed

design research)

Many possible cases

Case study types

single multiple

holistic single policy multiple policies

embedded single policy +

multiple districts +

multiple facilities

multiple policies +

multiple districts +

multiple facilities

Case selection

Exploratory Explanatory Single case

• Aim to find as many

different types as

possible, so

describe lots of

cases in limited

detail (to allow

classification,

taxonomy)

• Select to allow

theory testing

through comparison

& contrast, e.g. max

variability/ extremes

• ‘The one next door’

or

extreme/revealing

case

• Use theory to

explain how & why

something happens

by looking in detail

at inter-

relationships and

inner workings of

case

Case selection practicalities

• Think before start – be aware of what you are doing

• When possible, especially for explanatory work:

• develop ideas & ‘theory’ first

• purposively select ‘challenging’ cases to allow ideas & theory to be

tested

• Operationalise key concepts to allow case selection e.g. well/poorly

performing; success/failure

• May need to gather data through e.g. initial rapid appraisal to allow

appropriate case selection

• May choose all cases initially or adapt selection strategy during data

collection to allow theory testing & development (Flexible study design!)

• Test theory/assumptions in analysis AND explore unexpected

Pay particular attention to your analysis

strategy in case study work

In single cases

• Allison, 1971: The 1962 Cuban missile crisis

Three competing but complementary theoretical

explanations considered

– ability of each to explain actual course of events

compared

– explanations drawn out

– lessons intended to be ‘generalisable’ to conduct

of foreign affairs and other complex government

actions

Allison, G (1971). Essence of Decision: Explaining the Cuban

Missile Crisis, Boston, Little Brown.

Analysing multiple cases

• Analyse each case separately (don’t pool data)

• Test assumptions (‘theory’) on case by case basis –

repeating test of theory as you analyse

• Replication in analysis underpins development of

trustworthy ‘generalisable’ claims

NB case selection: apparently similar cases;

theoretically different cases (literal and theoretical

replication), see Rolfe et al., 2008

Develop theory/ideas

Select cases

Design data collection protocol

Conduct 1st case study

Conduct 2nd case study

Conduct remaining case studies

Write individual case report

Modify theory

Develop policy implications

Write individual case report

Write individual case reports

Analyse iteratively across cases

Write cross-case report

Define & design Prepare, collect & analyse

Analyse & conclude

Yin, 2009

Analytic/theoretical

generalisation

• Develop ‘theoretical insights’ (generalisable

claims) by:

• building or testing theory and/or

• comparative analysis across multiple cases

• These insights are universal enough to have

relevance in other settings

3. Participatory Action

Research (PAR)

• Multiple varieties: PRA, action research,

collaborative inquiry, experiential research,

endogenous research, community-driven

development etc etc.

• Emerges from a ‘critical’ social science tradition

“… a good explanation is one that will ultimately

lead to transformation and change in the world”

Babbie & Mouton, 2001

• Key words in PAR: participation, engagement,

collaboration, power

• Emphasis on collaboration between researcher and

subject – the latter becoming involved in the

research process as an equal partner

“People’s role in setting the agendas, participating in

the data gathering and analysis, and controlling the

use of outcomes … shared ownership of the research

enterprise”

Babbie & Mouton, 2001

PAR and theory

• The difference is not method (tools), but the

underlying theory/ethos – of an engaged

researcher with an emphasis on social

relevance, empowerment, and (political)

emancipation

• In PAR, the approach IS the theory

• (Research as action, research as intervention)

PAR and method

• Cycles of observation, critical

reflection and action (but not

always)

• Lots of different ‘tools’ – e.g.

participatory mapping, diagrams,

spidergrams, coffee-corners, etc…

• The theory and the cycle is the keyKemmis & McTaggart, 2005

The real trick:

‘meaningful/genuine’ participation

• Chambers 1994 (classic) … ‘participation’ was hi-jacked

(from its emancipatory roots)

– cosmetic (to make a project appear good … a mask

for top-down)

– co-optation (to mobilise labour and reduce costs …

they participate in our project)

– empowerment process (enables local communities

to do their own analysis, take command … we

participate in their project)

The real trick: ‘meaningful/genuine’ participation (continued)

• Traps and common problems in PAR (Chambers, 1994):

– who participates?

– rushing; self-sustaining myths (ventriloquism)

– routines and ruts (manuals)

– cosmetics (words change not behaviour)

Nature of data?

• Generated ‘from below’

• Context-specific (but generalisable across?)

• Mainly qualitative, but some numbers possible

• The problem when you ‘hand over the stick’

• How do you judge ‘success’ or ‘impact’ of PAR?

Copyright

Funding

You are free:

To Share – to copy, distribute and transmit the work

To Remix – to adapt the work

Under the following conditions:

Attribution You must attribute the work in the manner

specified by the author or licensor (but not in any way that

suggests that they endorse you or your use of the work).

Non-commercial You may not use this work for commercial

purposes.

Share Alike If you alter, transform, or build upon this work,

you may distribute the resulting work but only under the same

or similar license to this one.

Other conditionsFor any reuse or distribution, you must make clear to

others the license terms of this work.

Nothing in this license impairs or restricts the authors’

moral rights.

Nothing in this license impairs or restricts the rights of

authors whose work is referenced in this document.

Cited works used in this document must be cited following

usual academic conventions.

Citation of this work must follow normal academic

conventions. Suggested citation:

Introduction to Health Policy and Systems Research,

course presentation, Presentation 7. Copyright

CHEPSAA (Consortium for Health Policy & Systems

Analysis in Africa) 2014, www.hpsa-africa.org

www.slideshare.net/hpsa_africa

This document is an output from a project funded by the European Commission (EC) FP7-Africa (Grant no.

265482). The views expressed are not necessarily those of the EC.

The CHEPSAA partners

University of Dar Es SalaamInstitute of Development Studies

University of the WitwatersrandCentre for Health Policy

University of GhanaSchool of Public Health, Department of Health Policy, Planning and Management

University of LeedsNuffield Centre for International Health and Development

University of Nigeria Enugu Health Policy Research Group & the Department of Health Administration and Management

London School of Hygiene and Tropical MedicineHealth Economics and Systems Analysis Group, Depart of Global Health & Dev.

Great Lakes University of KisumuTropical Institute of Community Health and Development

Karolinska InstitutetHealth Systems and Policy Group, Department of Public Health Sciences

University of Cape TownHealth Policy and Systems Programme, Health Economics Unit

Swiss Tropical and Public Health InstituteHealth Systems Research Group

University of the Western CapeSchool of Public Health