access to health services: deprivation and transport measures in urban and rural settings

Access to health services:deprivation and transport measures

in urban and rural settings

Hannah JordanPaul Roderick, David Martin

Health Care Research Unit, Community Clinical Sciences, School of Medicine, Southampton University

&School of Geography, Southampton University

Introduction

• Access: under-reported, under-researched?

• Why measure access?

• Cornwall: a case study of measuring access to hospitals

• Where is the research going next?

Under-researched?

• Access is rarely measured, has many, many meanings and is rarely used to explain differences in health

Under-reported?

• Deprivation measurements are widely used to target resources.

• Could geographical access be used the same way?

Missing information?

• Rural areas have a special interest in access as deprivation is not a good predictor of health in these places

Modelling access

• What is a model?

• What kind of model will be most useful?

Modelling accessGENERAL SPECIFIC

Are there enough doctors to serve this population?

How far is it to the closest GP?

How quickly can people in this area get to hospital?

Can I get to my 10 am appointment by bus?

I’m at the chemists on the high street. It’s 9.30 am. Can I get to Southampton General by 10.15 for my outpatient appointment?

Ratio of population to services

Straight line distance

Drive time

Journey planning software

Transport-specific travel time

Cornwall: a case study

• Wanted to model access to the same thing, but in different ways, so we could compare the results.

• Chose to model access to acute District General Hospitals in Cornwall

• Access by:– Network ‘drive time’ distance– Public transport

Putting the model together

Drive-time

The study area

Derriford hospital, Plymouth

Treliske hospital, Truro

Bodmin Moor

Lands End

The Lizard

Data

• Land surface:– divided up into cells, size 200m2. Land cells assigned

background speed of 10kph, non land cells assigned ‘no data’ values

• Demand points: – 1991 census populations assigned to unit postcode locations

• Supply points: – postcode locations assigned to all DGHs (n=2)

• Population centres:– identified through Surpop database; adjacent populated zones

grouped to identify settlements of over 1000.

• Travel speeds:– Bartholomew road network assigns speeds based on road class

Vector road network

Admin area polygons

Surpop population model

Assign speeds to links

Rasterize land area

Identify settlements over 1000 pop

Rasterize Assign background speed

Assign urban speed

Travel speed model

Hospital point locations

Costsurface to hospitals

Drive time model

Drive times to hospital

The second model

Public transport

Data

• Land surface divided up into cells, size 200m2 – Land cells assigned background speed of 3kph, non

land cells assigned ‘no data’ values

• Demand points: – 1991 census populations assigned to unit postcode

locations

• Supply points: – postcode locations assigned to all DGHs (n=2)

• Travel speeds:– Directly from the bus timetables

Bus travel speeds

• The Cornwall Public Transport Timetable

• All services connecting directly to either hospital or via Truro or Plymouth– Journey duration– Number of services per day– First and last journey times

• Georeferencing of each bus stop using http://www.multimap.com

Cornwall public transport timetable

Bus travel network

Vector bus network

Admin area polygons

Surpop population model

Assign speeds to links

Rasterize land area

Identify settlements over 1000 pop

Rasterize Assign background (walk) speed

Assign urban speed

Bus speed model

Hospital point locations

Costsurface to hospitals

Bus time model

Bus times to hospital

Next steps for the model

• More information from web based timetable systems than transcribing paper timetables

• The South West Public Transport Initiative have granted access to their data – electronic format cuts the data entry time

dramatically – Different models for time of day, weekends– Models for specific questions…

SWPTI dataATCO-CIF0500AIM EMS MIA 4.10.4 20030626093409QLNCOY38619 Rising Sun Car Park, Portmellon 1 QBNCOY38619 201532 43984 GSCOY38619BN QLNCOC31056 CAR PARK, GORRAN HAVEN 1 QBNCOC31056 201083 41531 GSCOC31056BN QLNCOC31053 OPP TRIANGLE, GORRAN HAVEN 1 QBNCOC31053 200720 41547 GSCOC31053HN QLNCOC31050 WANSFORD MEADOWS, BELL HILL, GORRAN HAVEN

0 QBNCOC31050 200562 41697 GSCOC31050HN QLNCOC31048 OPP GORRAN CHURCH, GORRAN 1 QBNCOC31048 199883 42281

Modelling accessGENERAL SPECIFIC

Are there enough doctors to serve this population?

How far is it to the closest GP?

How quickly can people in this area get to hospital?

How quickly can people in this area get to hospital by bus?

I’m at the chemists on the high street. It’s 9.30 am. Can I get to Southampton General by 10.15 for my outpatient appointment?

Ratio of population to services

Straight line distance

Drive time

Journey planning software

Transport-specific travel time

Modelling access

• Extract data from the ATCO files using custom-made VB program (‘ATCO Reader’)

• Re-organise extracted data using a second VB program (‘ATCO Analyst’)

• Output information on ‘valid’ routes– Parameters include day of week, time of arrival, time

of departure, number of changes– Outputs include

• time taken for journey• location of stops and route• a network with speed characteristics (like the road network)

A synthetic test environment

Use in health research

• Add to statistical models to help explain health outcomes

• Test in rural areas where disadvantage to those without their own car is likely to be greatest

• Test in poorer areas where car ownership is lowest

• Target resources at areas in need, identify areas where people may find it difficult or impossible to attend appointments

Next steps for the model

• Combining public and private transport– A single ‘weighted average’

• More or less useful than separate transport-specific models?

– A single accessibility score for an area• time-distance to hospital • characteristics of the local population

References

1. Martin D., Wrigley H., Barnett S., Roderick P. (2002). Increasing the sophistication of access measurement in a rural healthcare study. Health and Place 8, 3-13

2. Jordan H., Roderick P., Martin D. (2004). The Index of Multiple Deprivation 2000 and accessibility effects on health. Journal of Epidemiology and Community Health 58(3): 250-257

3. Jordan H., Roderick P., Martin D., Barnett S. (2004). Distance, rurality and the need for care: access to health services in South West England. International Journal of Health Geographics 3:21 (29 September)

h.c.jordan@sheffield.ac.uk