Epidemiological and other research designs · designs. Research Methods in Palliative Care Oxford: Oxford University Press. 2007;pp85-97 • Bowling A, Iliffe S, Kessel A, Higginson

WHO Collaborating Centre for

Palliative Care & Older People

Epidemiological and

other research designs

Irene J Higginson,

Cicely Saunders Institute, Department of Palliative Care, Policy & Rehabilitation,

King’s College London

www.kcl.ac.uk/palliative

http://www.kingshealthpartners.org/khp/

www. kcl . ac. uk/ pal l i at i ve

Outline

• Epidemiology

• Overview of designs

• Examples to study access and care delivery (effects on older people, culture)

– Cross sectional (especially analysis of large data sets)

– Cohort

– Quasi-experimental

– Randomised trial

• Summary and references


Epidemiological research

• Epidemiology is concerned with patterns,

frequency and cause of illness and

diseases (including symptoms

• Epidemiological information is used to

determine needs and to plan and

evaluate the provision of healthcare

and other services.

• It can assess accessibility, effectiveness,

efficacy, efficiency, acceptability


Types of Study - Main classes

• Observational (Non-experimental) -observe something that naturally occurs and often test for associations between variables (cross sectional, cohort)

• Quasi-experimental – acts as if experiment but not random allocation

• Experimental studies - test the effectiveness or efficacy, of a treatment or intervention

• Clinical audit methods


Cross-sectional studies

• Make measurements at one point in time (or over

a short period)

• Information can be used to study relationships

between variables e.g. age and place of death

• Can collect data (e.g. via a survey) or use

routinely collect data (e.g. death registrations)

• Can be on individual patients, or groups of

patients (ecological study)

• Can never be causal – as the data is collected at

the same time


Cross sectional survey of fear of

dying among ethnically diverse

groups• Interviews with people over 65 years in two

national surveys (n=589, n=400)

• Data-sets merged, regression

• Over 7 in 10 of ethnically diverse sample aged

65+ expressed extreme fears of dying

• Only 4 in 10 of ethnically homogeneous sample

had same fears

• Higher quality of life had protective effect against

fears

Bowling A, Iliffe S, Kessel A, Higginson IJ. Postgrad Med J

2010;86(1014):197-202


Can use cross sectional data to explore different

stage of illness – e.g. psychological concerns

Gao et al, European J Cancer 2010


0

10

20

30

40

50

60

75-79 80-84 85-89 90-94 95-99 100+

age cohorts

perc

en

tag

e d

eath

s

Home

Hospice

Care home

Hospital

Individual cross sectional data on place of death among

oldest people - Percentage of cancer deaths in each place of death by age

cohort (N=307,613) (1995-9, E&W)

Source: Lock and Higginson, BMC Palliative Care 2005, 4:6


Differences for older people in home deaths

London and New York (cross sectional data)

Decker & Higginson Eur J Pub Health 2007; 17:285-290

Figure 1. Proportion of Cancer Deaths at Home, 1995-1998

0

5

10

15

20

25

30

40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94

Age

Per

cen

t

London

New York City


Ecological study: variation in place

of death in small areas

Higginson et al J Pub Health Med 1999

% Home cancer deaths vs. deprivation score

North Thames, 1985-1994


Longitudinal (also called cohort)

studies

• Subjects followed over time with continuous or, usually, repeated monitoring of symptoms.

• Can vary enormously in their size and complexity.

• At one extreme could study a large group (or cohort) of patients, repeatedly, from diagnosis to death.

• At the other extreme, a small number of patients (a small cohort) could be followed for a few days or weeks.


Examples cohort / longitudinal

studies


Retrospective cohort study

• Analysis of administrative data collected on

health service use during care

• Examined relationship between age and

use of palliative care programme (PCP)


QUASI-EXPERIMENTAL STUDIES

• = a study in which an intervention is deliberately introduced to observe its effects (the artificial manipulation of the study factor) without using randomisation to create the comparisons from which the effects are inferred.

• tests the efficacy (or the effectiveness) of an intervention,

• in a quasi-experimental study the intervention can be planned by the investigators (that implement the intervention themselves in a group of subjects or in a specific area), or can be planned by others not directly involved in the study


Types of quasi-experimental studies

One-group posttest only design (weakest)

Intervention Assessment

One-group pretest-posttest design (before and after study)

Assessment Intervention Assessment


Time series (stronger)

A A A A A A A A A

Intervention

Repeated assessments (A) before and after

intervention, so trends can be studies, and separated

from the effect of the intervention


pretest-posttest with external control

group design (stronger)

EXPERIMENTAL GROUP

Assessment

Intervention Assessment

CONTROL GROUP

Pain

assessment

Intervention Pain

assessment


• Evaluation of hospice day care using three groups –

– before day care opened (while it was being built)

– received day care and

– comparison group who did not have day care (by choice or distance)

• Patients entering day care were using higher levels of services and had higher levels of need (as measured by POS)

• Little difference in change in service use, slightly greater reduction in day care group


Experimental designs: RCT


Clinical audit / clinical

databases, descriptive studies

and surveys• Collect data on a more representative

group of patients

• Identify strengths and weaknesses

• Cannot test ‘cause and effect’ but in reality

can often highlight areas where these

should be tested and data can be modelled

to explore ‘ cause’


Example: Interval between first palliative care consult and death

in patients diagnosed with advanced cancer at a comprehensive

cancer centre.

• Determined interval between first palliative care consult (PC1) and death (D) in cancer patients at comprehensive cancer center and whether interval has increased over time.

• 2868 consecutive patients who had their PC1 during a 30-month period. Reviewed the charts for information

• Median PC1-D interval was longer in patients with solid tumors (p < 0.0001), less than 65 years old (p = 0.002), and females (p = 0.004).

• The median PC1-D interval in 5 consecutive half-years was 46, 56, 42, 41, and 34 days, respectively (p = 0.02).

• The first palliative care consultation to death interval has decreased over time

Osta BE, Palmer JL, Paraskevopoulos T, Pei BL, Roberts LE, Poulter VA, Chacko R, Bruera E. J Palliat Med. 2008 Jan-Feb;11(1):51-7.


Summary and references

• Epidemiological methods very useful in helping to determine

access and evaluate services

• Range of methods available

• Observational, quasi-experimental, experimental

• Costantini M, Higginson IJ. Experimental and quasi-experimental

designs. Research Methods in Palliative Care Oxford: Oxford

University Press. 2007;pp85-97

• Bowling A, Iliffe S, Kessel A, Higginson IJ. Fear of dying in an

ethnically diverse society: cross-sectional studies of people aged

65+ in Britain. Postgrad Med J 2010;86(1014):197-202

• Higginson IJ, McCrone P, Hart S, Burman R, Silber E, Edmonds

P. Is Short-Term Palliative Care Cost-Effective in Multiple

Sclerosis? A Randomized Phase II Trial. Journal of Pain &

Symptom Management 2009, 38(6):816-826


Cicely Saunders Institute (London) –

Inst i t ut e of Pal l i at i ve Care

Documents

Epidemiological and other research designs · designs. Research Methods in Palliative Care Oxford: Oxford University Press. 2007;pp85-97 • Bowling A, Iliffe S, Kessel A, Higginson