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Patient choice modelling: How do patients choose their hospitals?

Patient choice modelling: How do patients choose their hospitals?
Patient choice modelling: How do patients choose their hospitals?
As an aid to predicting future hospital admissions, we compare use of the Multinomial Logit and the Utility Maximising Nested Logit models to describe how patients choose their hospitals. The models are fitted to real data from Derbyshire, United Kingdom, which lists the postcodes of more than 200,000 admissions to six different local hospitals. Both elective and emergency admissions are analysed for this mixed urban/rural area. For characteristics that may affect a patient's choice of hospital, we consider the distance of the patient from the hospital, the number of beds at the hospital and the number of car parking spaces available at the hospital, as well as several statistics publicly available on National Health Service (NHS) websites: an average waiting time, the patient survey score for ward cleanliness, the patient safety score and the inpatient survey score for overall care. The Multinomial Logit model is successfully fitted to the data. Results obtained with the Utility Maximising Nested Logit model show that nesting according to city or town may be invalid for these data; in other words, the choice of hospital does not appear to be preceded by choice of city. In all of the analysis carried out, distance appears to be one of the main influences on a patient's choice of hospital rather than statistics available on the Internet.
1386-9620
259-268
Smith, Honora
1eaef6a6-4b9c-4997-9163-137b956c06b5
Currie, Christine
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Chaiwuttisak, Pornpimol
42a95b49-60be-423f-aae7-dd530e66197a
Kyprianou, Andreas
ec6ff236-44e9-432b-a57c-54235caa8956
Smith, Honora
1eaef6a6-4b9c-4997-9163-137b956c06b5
Currie, Christine
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Chaiwuttisak, Pornpimol
42a95b49-60be-423f-aae7-dd530e66197a
Kyprianou, Andreas
ec6ff236-44e9-432b-a57c-54235caa8956

Smith, Honora, Currie, Christine, Chaiwuttisak, Pornpimol and Kyprianou, Andreas (2018) Patient choice modelling: How do patients choose their hospitals? Health Care Management Science, 21 (2), 259-268. (doi:10.1007/s10729-017-9399-1).

Record type: Article

Abstract

As an aid to predicting future hospital admissions, we compare use of the Multinomial Logit and the Utility Maximising Nested Logit models to describe how patients choose their hospitals. The models are fitted to real data from Derbyshire, United Kingdom, which lists the postcodes of more than 200,000 admissions to six different local hospitals. Both elective and emergency admissions are analysed for this mixed urban/rural area. For characteristics that may affect a patient's choice of hospital, we consider the distance of the patient from the hospital, the number of beds at the hospital and the number of car parking spaces available at the hospital, as well as several statistics publicly available on National Health Service (NHS) websites: an average waiting time, the patient survey score for ward cleanliness, the patient safety score and the inpatient survey score for overall care. The Multinomial Logit model is successfully fitted to the data. Results obtained with the Utility Maximising Nested Logit model show that nesting according to city or town may be invalid for these data; in other words, the choice of hospital does not appear to be preceded by choice of city. In all of the analysis carried out, distance appears to be one of the main influences on a patient's choice of hospital rather than statistics available on the Internet.

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Smith_et_al_2016_submit 051216 - Accepted Manuscript
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Accepted/In Press date: 9 February 2017
e-pub ahead of print date: 11 April 2017
Published date: 4 May 2018
Organisations: Operational Research

Identifiers

Local EPrints ID: 406296
URI: http://eprints.soton.ac.uk/id/eprint/406296
ISSN: 1386-9620
PURE UUID: 16cc9489-44b4-4ace-9a5f-35932e5eba2a
ORCID for Honora Smith: ORCID iD orcid.org/0000-0002-4974-3011
ORCID for Christine Currie: ORCID iD orcid.org/0000-0002-7016-3652

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Date deposited: 10 Mar 2017 10:44
Last modified: 16 Mar 2024 05:04

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Contributors

Author: Honora Smith ORCID iD
Author: Pornpimol Chaiwuttisak
Author: Andreas Kyprianou

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