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How do GP practices and patient characteristics influence the prescription of antidepressants? A cross-sectional study.

Mercier A, Benichou J, Auger-Aubin I, Lebeau JP, Houivet E, Van Royen P, Peremans L - Ann Gen Psychiatry (2015)

Bottom Line: GPs' workload (e.g., volume of prescribed drug reimbursement and number of consultations) had no influence on the AD prescription ratio.Our study described a profile of the typical higher AD prescriber that did not include heavy workload.In future work, a more detailed assessment of all biopsychosocial components of the consultation and other influences on GP behavior such as prior training would be useful to explain AD prescription in GP's practice.

View Article: PubMed Central - PubMed

Affiliation: Department of General Practice, Rouen University, CIC Inserm 0204, 1 rue de Germont, 76031 Rouen Cedex, France ; Department of General Practice, University Paris 13, Sorbonne Paris Cité, Bobigny, France ; Department of Family practice, Faculty of Medicine, Rouen University, 20 Bd Gambetta, 76000 Rouen, France.

ABSTRACT

Background: Under-prescription of antidepressants (ADs) among people meeting the criteria for major depressive episodes and excessive prescription in less symptomatic patients have been reported. The reasons influencing general practitioners' (GPs) prescription of ADs remain little explored. This study aimed at assessing the influence of GP and patient characteristics on AD prescription.

Methods: This cross-sectional study was based on a sample of 816 GPs working within the main health care insurance system in the Seine-Maritime district of France during 2010. Only GPs meeting the criteria for full-time GP practice were included. The ratio of AD prescription to overall prescription volume, a relative measure of AD prescription level, was calculated for each GP, using the defined daily dose (DDD) concept. Associations of this AD prescription ratio with GPs' age, gender, practice location, number of years of practice, number of days of sickness certificates prescribed, number of home visits and consultations, number and mean age of registered patients, mean patient income, and number of patients with a chronic condition were assessed using univariate and multivariate analysis.

Results: The high prescribers were middle-aged (40-59) urban GPs, with a moderate number of consultations and fewer low-income and chronic patients. GPs' workload (e.g., volume of prescribed drug reimbursement and number of consultations) had no influence on the AD prescription ratio. GPs with more patients with risk factors for depression prescribed fewer ADs, however, which could suggest the medications were under-prescribed among the at-risk population.

Conclusions: Our study described a profile of the typical higher AD prescriber that did not include heavy workload. In future work, a more detailed assessment of all biopsychosocial components of the consultation and other influences on GP behavior such as prior training would be useful to explain AD prescription in GP's practice.

No MeSH data available.


Related in: MedlinePlus

Flow chart of data extraction. Among the physicians recorded as GPs, 17 were recorded with an exclusive particular mode of practice (e.g. acupuncture), 13 did not prescribe any sick leave, 24 had no chronic patients, 42 had no low-income patients, 4 had no conventional agreement with the health care system, 156 performed less than one consultation per day, and 16 had less than two registered patients.
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Fig1: Flow chart of data extraction. Among the physicians recorded as GPs, 17 were recorded with an exclusive particular mode of practice (e.g. acupuncture), 13 did not prescribe any sick leave, 24 had no chronic patients, 42 had no low-income patients, 4 had no conventional agreement with the health care system, 156 performed less than one consultation per day, and 16 had less than two registered patients.

Mentions: Among the 1,046 registered GPs, data from 36 GPs were missing, thus leaving data for 1,004 registered GPs for further selection. As our aim was to analyze data coming from full-time standard primary GP practice, the following exclusion criteria were applied to the initial data sample of physicians registered as GPs. “Specialized” physicians with a predominant particular mode of practice (PMP) such as osteopathy or acupuncture, as well as those practicing homeopathy or nutrition exclusively, were excluded. Other exclusion criteria were prescription of no or only a few medications, no sickness certificates prescribed, performing no home visits, and having only a part-time GP activity (e.g., a GP practice combined with hospital or emergency department practices). GPs performing less than one reimbursed consultation per day, and having no contractual agreement with the French national health insurance system, were also excluded. GPs were also excluded when they did not treat chronic patients (i.e., no patients with any of the 30 chronic diseases allowing patients to be treated free of charge in France) or any very low-income patients (i.e., no patients who can see a GP free of charge based on their very low-income level as defined by French law). After applying these criteria, the data for 816 GPs were retained and constituted the analysis sample. The different steps of data selection are presented in Figure 1.Figure 1


How do GP practices and patient characteristics influence the prescription of antidepressants? A cross-sectional study.

Mercier A, Benichou J, Auger-Aubin I, Lebeau JP, Houivet E, Van Royen P, Peremans L - Ann Gen Psychiatry (2015)

Flow chart of data extraction. Among the physicians recorded as GPs, 17 were recorded with an exclusive particular mode of practice (e.g. acupuncture), 13 did not prescribe any sick leave, 24 had no chronic patients, 42 had no low-income patients, 4 had no conventional agreement with the health care system, 156 performed less than one consultation per day, and 16 had less than two registered patients.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4308843&req=5

Fig1: Flow chart of data extraction. Among the physicians recorded as GPs, 17 were recorded with an exclusive particular mode of practice (e.g. acupuncture), 13 did not prescribe any sick leave, 24 had no chronic patients, 42 had no low-income patients, 4 had no conventional agreement with the health care system, 156 performed less than one consultation per day, and 16 had less than two registered patients.
Mentions: Among the 1,046 registered GPs, data from 36 GPs were missing, thus leaving data for 1,004 registered GPs for further selection. As our aim was to analyze data coming from full-time standard primary GP practice, the following exclusion criteria were applied to the initial data sample of physicians registered as GPs. “Specialized” physicians with a predominant particular mode of practice (PMP) such as osteopathy or acupuncture, as well as those practicing homeopathy or nutrition exclusively, were excluded. Other exclusion criteria were prescription of no or only a few medications, no sickness certificates prescribed, performing no home visits, and having only a part-time GP activity (e.g., a GP practice combined with hospital or emergency department practices). GPs performing less than one reimbursed consultation per day, and having no contractual agreement with the French national health insurance system, were also excluded. GPs were also excluded when they did not treat chronic patients (i.e., no patients with any of the 30 chronic diseases allowing patients to be treated free of charge in France) or any very low-income patients (i.e., no patients who can see a GP free of charge based on their very low-income level as defined by French law). After applying these criteria, the data for 816 GPs were retained and constituted the analysis sample. The different steps of data selection are presented in Figure 1.Figure 1

Bottom Line: GPs' workload (e.g., volume of prescribed drug reimbursement and number of consultations) had no influence on the AD prescription ratio.Our study described a profile of the typical higher AD prescriber that did not include heavy workload.In future work, a more detailed assessment of all biopsychosocial components of the consultation and other influences on GP behavior such as prior training would be useful to explain AD prescription in GP's practice.

View Article: PubMed Central - PubMed

Affiliation: Department of General Practice, Rouen University, CIC Inserm 0204, 1 rue de Germont, 76031 Rouen Cedex, France ; Department of General Practice, University Paris 13, Sorbonne Paris Cité, Bobigny, France ; Department of Family practice, Faculty of Medicine, Rouen University, 20 Bd Gambetta, 76000 Rouen, France.

ABSTRACT

Background: Under-prescription of antidepressants (ADs) among people meeting the criteria for major depressive episodes and excessive prescription in less symptomatic patients have been reported. The reasons influencing general practitioners' (GPs) prescription of ADs remain little explored. This study aimed at assessing the influence of GP and patient characteristics on AD prescription.

Methods: This cross-sectional study was based on a sample of 816 GPs working within the main health care insurance system in the Seine-Maritime district of France during 2010. Only GPs meeting the criteria for full-time GP practice were included. The ratio of AD prescription to overall prescription volume, a relative measure of AD prescription level, was calculated for each GP, using the defined daily dose (DDD) concept. Associations of this AD prescription ratio with GPs' age, gender, practice location, number of years of practice, number of days of sickness certificates prescribed, number of home visits and consultations, number and mean age of registered patients, mean patient income, and number of patients with a chronic condition were assessed using univariate and multivariate analysis.

Results: The high prescribers were middle-aged (40-59) urban GPs, with a moderate number of consultations and fewer low-income and chronic patients. GPs' workload (e.g., volume of prescribed drug reimbursement and number of consultations) had no influence on the AD prescription ratio. GPs with more patients with risk factors for depression prescribed fewer ADs, however, which could suggest the medications were under-prescribed among the at-risk population.

Conclusions: Our study described a profile of the typical higher AD prescriber that did not include heavy workload. In future work, a more detailed assessment of all biopsychosocial components of the consultation and other influences on GP behavior such as prior training would be useful to explain AD prescription in GP's practice.

No MeSH data available.


Related in: MedlinePlus