Literature DB >> 10846145

Defaulters in general practice: who are they and what can be done about them?

J Waller1, P Hodgkin.   

Abstract

BACKGROUND: The study of patients in primary care settings who default on their appointment has been based largely on short-term surveys in individual health centres.
OBJECTIVE: As part of a wider research project into the potential of practice computer appointment systems as a data source, we wanted to explore the aggregate pattern of default.
METHOD: Comprehensive computer appointment data from nine general practices for 1 or 2 years were analysed to explore the pattern of defaulted appointments for doctors and practice nurses.
RESULTS: Around 6.5% of all appointments ended in a default. Default rates were found to be highest amongst young adults and, at a practice level, to be highly correlated with deprivation level. About two-thirds of those who defaulted only did it once during the year. A small core of patients defaulted frequently, but only a quarter of these repeated their behaviour in the following year.
CONCLUSIONS: The discussion suggests that strategies based on educating or punishing defaulters in order to change their behaviour may be of limited effectiveness.

Entities:  

Mesh:

Year:  2000        PMID: 10846145     DOI: 10.1093/fampra/17.3.252

Source DB:  PubMed          Journal:  Fam Pract        ISSN: 0263-2136            Impact factor:   2.267


  18 in total

1.  Non-attendance at general practices and outpatient clinics.

Authors:  D J Sharp; W Hamilton
Journal:  BMJ       Date:  2001-11-10

2.  Missed appointments in general practice: retrospective data analysis from four practices.

Authors:  R D Neal; D A Lawlor; V Allgar; M Colledge; S Ali; A Hassey; C Portz; A Wilson
Journal:  Br J Gen Pract       Date:  2001-10       Impact factor: 5.386

3.  Predicting appointment misses in hospitals using data analytics.

Authors:  Sylvester Rohan Devasahay; Sylvia Karpagam; Nang Laik Ma
Journal:  Mhealth       Date:  2017-04-17

4.  What Study Design Should I Choose?

Authors:  Zailinawati Abu Hassan; Nik Sherina Hanafi; Teng Cheong Lieng
Journal:  Malays Fam Physician       Date:  2006-04-30

5.  Factors associated with non-attendance in a general practice super clinic population in regional Australia: A retrospective cohort study.

Authors:  Susan Nancarrow; Joanne Bradbury; Catherine Avila
Journal:  Australas Med J       Date:  2014-08-31

Review 6.  Mobile phone messaging reminders for attendance at healthcare appointments.

Authors:  Ipek Gurol-Urganci; Thyra de Jongh; Vlasta Vodopivec-Jamsek; Rifat Atun; Josip Car
Journal:  Cochrane Database Syst Rev       Date:  2013-12-05

7.  Factors Associated with Low Socioeconomic Status Predict Poor Postoperative Follow-up after Meningioma Resection.

Authors:  Arash Nayeri; Philip R Brinson; Kyle D Weaver; Reid C Thompson; Lola B Chambless
Journal:  J Neurol Surg B Skull Base       Date:  2015-10-28

8.  The Effectiveness of SMS Reminders on Appointment Attendance: a Meta-Analysis.

Authors:  Nasim Boksmati; Kerryn Butler-Henderson; Kevin Anderson; Tony Sahama
Journal:  J Med Syst       Date:  2016-02-06       Impact factor: 4.460

9.  Characteristics and outcomes of advanced cancer patients who miss outpatient supportive care consult appointments.

Authors:  Marvin Omar Delgado Guay; Marvin Omar Delgado Guay; Silvia Tanzi; Maria Teresa San Miguel Arregui; Maria Teresa San Miguel Arregui; Gary Chisholm; Maxine G De la Cruz; Maxine de la Cruz; Eduardo Bruera
Journal:  Support Care Cancer       Date:  2014-04-26       Impact factor: 3.603

10.  Reduction of missed appointments at an urban primary care clinic: a randomised controlled study.

Authors:  Noelle Junod Perron; Melissa Dominicé Dao; Michel P Kossovsky; Valerie Miserez; Carmen Chuard; Alexandra Calmy; Jean-Michel Gaspoz
Journal:  BMC Fam Pract       Date:  2010-10-25       Impact factor: 2.497

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