Predictability of persistent frequent attendance: a historic 3-year cohort study.
BACKGROUND
Few patients who attend GP consultations frequently continue to do so long term. While transient frequent attendance may be readily explicable, persistent frequent attendance often is not. It increases GPs' workload while reducing work satisfaction. It is neither reasonable, nor efficient to target diagnostic assessment and intervention at transient frequent attenders.


OBJECTIVE
To develop a prediction rule for selecting persistent frequent attenders, using readily available information from GPs' electronic medical records.


METHODS
A historic 3-year cohort study.


METHODS
Data of 28 860 adult patients from 2003 to 2005 were examined. Frequent attenders were patients whose attendance rate ranked in the (age- and sex-adjusted) top 10% during 1 year (1-year frequent attenders) or 3 years (persistent frequent attenders). Bootstrapped multivariable logistic regression analysis was used to determine which predictors contained information on persistent frequent attendance.


RESULTS
Of 3045 1-year frequent attenders, 470 (15.4%) became persistent frequent attenders. The prediction rule could update this prior probability to 3.3% (lowest value) or 43.3% (highest value). However, the 10th and 90th centiles of the posterior probability distribution were 7.4% and 26.3% respectively, indicating that the model performs modestly. The area under the receiver operating characteristic curve was 0.67 (95% confidence limits 0.64 and 0.69).


CONCLUSIONS
Among 1-year frequent attenders, six out of seven are transient frequent attenders. With the present indicators, the rule developed performs modestly in selecting those more likely to become persistent frequent attenders.
Smits
Frans ThM
FT
Network of General Practitioners of the Academic Medical Centre/University of Amsterdam, The Netherlands.
Brouwer
Henk J
HJ
van Weert
Henk C P
HC
Schene
Aart H
AH
ter Riet
Gerben
G
D000293:Adolescent; D000328:Adult; D000368:Aged; D001071:Appointments and Schedules; D004812:Epidemiologic Methods; D005194:Family Practice / Q000706:statistics & numerical data*; D005260:Female; D006300:Health Services Misuse / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009426:Netherlands / Q000453:epidemiology; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data*; D016526:Workload; D055815:Young Adult