Diffusion of new drugs in Danish general practice.
OBJECTIVE
There is a large variation in implementing research findings in clinical practice. We examined whether the concept of early or late adopters is universal for the diffusion of all new drugs, and whether it is associated with non-scientific factors in general practice.


METHODS
We identified all prescriptions for five new drugs from the population-based prescription database in North Jutland County, Denmark (490000 inhabitants) from 1993 to 1996, and calculated the period from release of the drugs to the issuing of the first prescription by each GP. Logistic regression was performed to predict early or late prescribing from physician characteristics, practice activity and the number of prescriptions, adjusted for age and sex.


RESULTS
The distributions of the diffusion time of the drugs by 95 solo practitioners were asymmetrical, with a long upper tail representing the late prescribers. The shape and slope of the diffusion curve were highly drug dependent. There was poor agreement of the three adopter categories (early, intermediate and late prescribers) between the five drugs (kappa < 0.35), but being a late prescriber was the most consistent condition. Late prescribing of tramadol, compared with intermediate prescribing, was associated with female physicians (odds ratio (OR) 5.7; 95% CI 1.5-21.3), smaller list size (OR 0.1; 95% CI 0.0-0.8), a strong general restrictive attitude to pharmacotherapy (OR 0.07; 95% CI 0.01-0.68) and a tendency to lower diagnostic activity per patient (OR 0.4; 95% CI 0.1-1.9).


CONCLUSIONS
The slope and shape of the diffusion curve are both dependent on physician and drug characteristics, but late prescribers share some common characteristics.
Steffensen
F H
FH
Danish Epidemiology Science Centre at the Department of Epidemiology and Social Medicine, University of Aarhus.
Sørensen
H T
HT
Olesen
F
F
D017677:Age Distribution; D000368:Aged; D001291:Attitude of Health Personnel; D003718:Denmark; D004059:Diffusion of Innovation; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D004358:Drug Therapy / Q000706:statistics & numerical data* / Q000639:trends; D004363:Drug Utilization; D005194:Family Practice / Q000193:education / Q000706:statistics & numerical data* / Q000639:trends; D005260:Female; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010821:Physicians, Family / Q000193:education / Q000523:psychology; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data / Q000639:trends; D017678:Sex Distribution; D013997:Time Factors