Literature DB >> 748491

The no-show patient in the model family practice unit.

J V Dervin, D L Stone, C H Beck.   

Abstract

Appointment breaking by patients causes problems for the physician's office. Patients who neither keep nor cancel their appointments are often referred to as "no shows." Twenty variables were identified as potential predictors of no-show behavior. These predictors were applied to 291 Family Practice Center patients during a one-month study in April 1977. A discriminant function and multiple regression procedure were utilized ascertain the predictability of the selected variables. Predictive accuracy of the variables was 67.4 percent compared to the presently utilized constant predictor technique, which is 73 percent accurate. Modification of appointment schedules based upon utilization of the variables studies as predictors of show/no-show behavior does not appear to be an effective strategy in the Family Practice Center of the Community Hospital of Sonoma County, Santa Rosa, due to the high proportion of patients who do, in fact, show. In clinics with lower show rates, the technique may prove to be an effective strategy.

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Year:  1978        PMID: 748491

Source DB:  PubMed          Journal:  J Fam Pract        ISSN: 0094-3509            Impact factor:   0.493


  5 in total

1.  Reducing noncompliance to follow-up appointment keeping at a family practice center.

Authors:  J M Rice; J R Lutzker
Journal:  J Appl Behav Anal       Date:  1984

2.  Dynamic Scheduling for Veterans Health Administration Patients using Geospatial Dynamic Overbooking.

Authors:  Stephen Adams; William T Scherer; K Preston White; Jason Payne; Oved Hernandez; Mathew S Gerber; N Peter Whitehead
Journal:  J Med Syst       Date:  2017-10-12       Impact factor: 4.460

3.  Bed crisis and elective surgery late cancellations: An approach using the theory of constraints.

Authors:  Abderrazak Sahraoui; Mohamed Elarref
Journal:  Qatar Med J       Date:  2014-06-16

Review 4.  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 5.  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
  5 in total

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