Epidemiological and Other Research Designs

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 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

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

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

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

www.kcl . ac. uk/ pal l i at i ve Cross sectional survey of fear of dying among ethnically diverse •groupsInterviews 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 www.kcl . ac. uk/ pal l i at i ve Can use cross sectional data to explore different stage of illness – e.g. psychological concerns

Gao et al, European J Cancer 2010 www.kcl . ac. uk/ pal l i at i ve 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)

40 Home Hospice 30 Care home Hospital

20 percentage deaths percentage

0 75-79 80-84 85-89 90-94 95-99 100+ age cohorts

Source: Lock and Higginson, BMC Palliative Care 2005, 4:6 www.kcl . ac. uk/ pal l i at i ve Differences for older people in home deaths London and New York (cross sectional data)

Figure 1. Proportion of Cancer Deaths at Home, 1995-1998 30

25 London

Percent New York City

40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 Age Decker & Higginson Eur J Pub Health 2007; 17:285-290

www.kcl . ac. uk/ pal l i at i ve Ecological study: variation in place of death in small areas

% Home cancer deaths vs. deprivation score North Thames, 1985-1994

Higginson et al J Pub Health Med 1999

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

www.kcl . ac. uk/ pal l i at i ve Examples cohort / longitudinal studies

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

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

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

www.kcl . ac. uk/ pal l i at i ve Time series (stronger)

Repeated assessments (A) before and after intervention, so trends can be studies, and separated from the effect of the intervention

A A A A A A A A A

Intervention

www.kcl . ac. uk/ pal l i at i ve pretest-posttest with external control group design (stronger)

EXPERIMENTAL GROUP Intervention Assessment Assessment

CONTROL GROUP

Intervention Pain Pain assessment assessment

www.kcl . ac. uk/ pal l i at i ve • 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 www.kcl . ac. uk/ pal l i at i ve Experimental designs: RCT

www.kcl . ac. uk/ pal l i at i ve 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’

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

www.kcl . ac. uk/ pal l i at i ve Cicely Saunders Institute (London) – Inst i t ute of alP l i at i ve Care