Literature DB >> 10142384

Predicting appointment breaking.

A G Bean1, J Talaga.   

Abstract

The goal of physician referral services is to schedule appointments, but if too many patients fail to show up, the value of the service will be compromised. The authors found that appointment breaking can be predicted by the number of days to the scheduled appointment, the doctor's specialty, and the patient's age and gender. They also offer specific suggestions for modifying the marketing mix to reduce the incidence of no-shows.

Entities:  

Mesh:

Year:  1995        PMID: 10142384

Source DB:  PubMed          Journal:  J Health Care Mark        ISSN: 0737-3252


  10 in total

1.  Using electronic data sources to understand the determinants of psychiatric visit non-adherence.

Authors:  Patricia E Alafaireet; Howard L Houghton; Grant T Savage; Yang Gong
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

2.  A probabilistic model for predicting the probability of no-show in hospital appointments.

Authors:  Adel Alaeddini; Kai Yang; Chandan Reddy; Susan Yu
Journal:  Health Care Manag Sci       Date:  2011-02-01

3.  Patient no-show predictive model development using multiple data sources for an effective overbooking approach.

Authors:  Y Huang; D A Hanauer
Journal:  Appl Clin Inform       Date:  2014-09-24       Impact factor: 2.342

4.  The productivity and cost-efficiency of models for involving nurse practitioners in primary care: a perspective from queueing analysis.

Authors:  Nan Liu; Thomas D'Aunno
Journal:  Health Serv Res       Date:  2011-11-08       Impact factor: 3.402

5.  Barriers to obtaining diagnostic testing for coronary artery disease among veterans.

Authors:  Laura A Siminoff; Leslie R M Hausmann; Said Ibrahim
Journal:  Am J Public Health       Date:  2008-04-01       Impact factor: 9.308

6.  Preventing Endoscopy Clinic No-Shows: Prospective Validation of a Predictive Overbooking Model.

Authors:  Mark W Reid; Folasade P May; Bibiana Martinez; Samuel Cohen; Hank Wang; Demetrius L Williams; Brennan M R Spiegel
Journal:  Am J Gastroenterol       Date:  2016-07-05       Impact factor: 10.864

7.  Large-Scale No-Show Patterns and Distributions for Clinic Operational Research.

Authors:  Michael L Davies; Rachel M Goffman; Jerrold H May; Robert J Monte; Keri L Rodriguez; Youxu C Tjader; Dominic L Vargas
Journal:  Healthcare (Basel)       Date:  2016-02-16

Review 8.  Patient No-Show Prediction: A Systematic Literature Review.

Authors:  Danae Carreras-García; David Delgado-Gómez; Fernando Llorente-Fernández; Ana Arribas-Gil
Journal:  Entropy (Basel)       Date:  2020-06-17       Impact factor: 2.524

Review 9.  Effects of clinical characteristics on successful open access scheduling.

Authors:  Renata Kopach; Po-Ching DeLaurentis; Mark Lawley; Kumar Muthuraman; Leyla Ozsen; Ron Rardin; Hong Wan; Paul Intrevado; Xiuli Qu; Deanna Willis
Journal:  Health Care Manag Sci       Date:  2007-06

10.  Factors associated with nonattendance at clinical medicine scheduled outpatient appointments in a university general hospital.

Authors:  Diego Giunta; Agustina Briatore; Analía Baum; Daniel Luna; Gabriel Waisman; Fernán Gonzalez Bernaldo de Quiros
Journal:  Patient Prefer Adherence       Date:  2013-11-08       Impact factor: 2.711

  10 in total

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