The University of Southampton
University of Southampton Institutional Repository

How many surgery appointments should be offered to avoid undesirable numbers of 'extras'?

How many surgery appointments should be offered to avoid undesirable numbers of 'extras'?
How many surgery appointments should be offered to avoid undesirable numbers of 'extras'?
BACKGROUND: Patients seen as 'extras' (or 'fit-ins') are usually given less time for their problems than those in pre-booked appointments. Consequently, long queues of 'extras' should be avoided. AIM: To determine whether a predictable relationship exists between the number of available appointments at the start of the day and the number of extra patients who must be fitted in. This might be used to help plan a practice appointment system.
METHOD: Numbers of available appointments at the start of the day and numbers of 'extras' seen were recorded prospectively in 1995 and 1997 in one group general practice. Minimum numbers of available appointments at the start of the day, below which undesirably large numbers of extra patients could be predicted, were determined using logistic regression applied to the 1995 data. Predictive values of the minimum numbers calculated for 1995, in terms of predicting undesirable numbers of 'extras', were then determined when applied to the 1997 data.
RESULTS: Numbers of extra patients seen correlated negatively with available appointments at the start of the day for all days of the week, with coefficients ranging from -0.66 to -0.80. Minimum numbers of available appointments below which undesirably large numbers of extras could be predicted were 26 for Mondays and four for the other week-days. When applied to 1997 data, these minimum numbers gave positive and negative predictive values of 76% and 82% respectively, similar to their values for 1995, despite increases in patient attendance and changes in the day-to-day pattern of surgery provision between the two years.
CONCLUSION: A predictable relationship exists between the number of available appointments at the start of the day and the number of extras who must be fitted in, which may be used to help plan the appointment system for some years ahead, at least in this relatively stable suburban practice.
logistic models, time, Great Britain, general practice, patients, economics, appointments and schedules, medical, organization & administration, data collection, family practice, surgery, practice management, problems, statistics & numerical data, general-practice, methods
0960-1643
273-276
Kendrick, T.
c697a72c-c698-469d-8ac2-f00df40583e5
Kerry, S.
45167362-3df0-427c-88db-045cb9e8c63c
Kendrick, T.
c697a72c-c698-469d-8ac2-f00df40583e5
Kerry, S.
45167362-3df0-427c-88db-045cb9e8c63c

Kendrick, T. and Kerry, S. (1999) How many surgery appointments should be offered to avoid undesirable numbers of 'extras'? British Journal of General Practice, 49 (441), 273-276.

Record type: Article

Abstract

BACKGROUND: Patients seen as 'extras' (or 'fit-ins') are usually given less time for their problems than those in pre-booked appointments. Consequently, long queues of 'extras' should be avoided. AIM: To determine whether a predictable relationship exists between the number of available appointments at the start of the day and the number of extra patients who must be fitted in. This might be used to help plan a practice appointment system.
METHOD: Numbers of available appointments at the start of the day and numbers of 'extras' seen were recorded prospectively in 1995 and 1997 in one group general practice. Minimum numbers of available appointments at the start of the day, below which undesirably large numbers of extra patients could be predicted, were determined using logistic regression applied to the 1995 data. Predictive values of the minimum numbers calculated for 1995, in terms of predicting undesirable numbers of 'extras', were then determined when applied to the 1997 data.
RESULTS: Numbers of extra patients seen correlated negatively with available appointments at the start of the day for all days of the week, with coefficients ranging from -0.66 to -0.80. Minimum numbers of available appointments below which undesirably large numbers of extras could be predicted were 26 for Mondays and four for the other week-days. When applied to 1997 data, these minimum numbers gave positive and negative predictive values of 76% and 82% respectively, similar to their values for 1995, despite increases in patient attendance and changes in the day-to-day pattern of surgery provision between the two years.
CONCLUSION: A predictable relationship exists between the number of available appointments at the start of the day and the number of extras who must be fitted in, which may be used to help plan the appointment system for some years ahead, at least in this relatively stable suburban practice.

This record has no associated files available for download.

More information

Published date: 1999
Keywords: logistic models, time, Great Britain, general practice, patients, economics, appointments and schedules, medical, organization & administration, data collection, family practice, surgery, practice management, problems, statistics & numerical data, general-practice, methods

Identifiers

Local EPrints ID: 61862
URI: http://eprints.soton.ac.uk/id/eprint/61862
ISSN: 0960-1643
PURE UUID: 119ca4c8-bce9-4945-a393-0cfd34139d9d
ORCID for T. Kendrick: ORCID iD orcid.org/0000-0003-1618-9381

Catalogue record

Date deposited: 11 Sep 2008
Last modified: 08 Jan 2022 02:48

Export record

Contributors

Author: T. Kendrick ORCID iD
Author: S. Kerry

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×