In total, 25 primary care physicians in Germany participated in this prospective, multicentre observational study. All of them were members of the EvaMed Network, which aims to evaluate CAM remedies in usual care with regard to prescribing patterns, efficacy, and safety [29–31]. Physicians were recruited through the German National Association of Anthroposophic Physicians (Gesellschaft Antroposophischer Ärzte in Deutschland; GAÄD). A total of 362 physicians were contacted and informed about the EvaMed Network by standard mail and, in the event of non-response, four weeks later by telephone. For a physician to be eligible to participate in the study, his or her medical practice had to meet a number of technical requirements, including the presence of a special computerized patient documentation system (DocExpert, DocConcept, TurboMed, Duria, AdamedPlus, Medistar), a local area network (LAN) connection, and Microsoft Windows and Internet Explorer (i.e. as client software). A total of 38 physicians (10.5%) fulfilled the technical requirements, gave informed consent, and agreed to participate in the EvaMed network. Of these physicians, 13 specialized in paediatrics and dermatology were excluded from the study. Each of the remaining 25 physicians had practised for at least five years in primary care in addition to completing training in anthroposophic medicine.
The present study is based on secondary data provided by physicians. As such, the recommendations for good practice in secondary data analysis (e.g. anonymization of data on prescriptions and diagnoses) developed by the German Working Group on the Collection and Use of Secondary Data  were applied in full. In addition, the study was approved by the responsible data security official.
Data were included in the study if patients were at least 16 years old, had been diagnosed with hypertension, and had received pharmacological treatment for hypertension at least once during the study period (January-December 2005).
During the study, physicians continued to follow their routine documentation procedures, recording diagnoses and all prescriptions for each consecutive patient using their existing, computerized patient documentation system. These data were exported to the QuaDoSta postgreSQL database hosted in each practice . Physicians used a browser-based interface to match individual diagnoses with the corresponding drugs or remedies that had been prescribed. Diagnoses were coded according to the 10th revision of the International Classification of Diseases (ICD-10). Prescribed drugs were documented using the German National Drug Code.
Study investigators identified all drugs and remedies prescribed for hypertension (i.e. ICD-10: I10 - I15). Each substance was classified using the Anatomical Therapeutic Chemical Index, and hypertensive drugs were clustered into classic antihypertensives (i.e. calcium channel blockers (CCBs), diuretics, beta-blockers, angiotensin converting enzyme (ACE) inhibitors, angiotensin II receptor antagonists, alpha-1 blockers, and antiadrenergic agents), and combination treatments (e.g. diuretics and beta-blockers, either as fixed-dose coformulations or as separate agents).
All statistical analyses were performed using SPSS 16.0 for Windows. Mean and standard deviations (SD) were calculated for continuous, normally distributed data. In cases where data were not normally distributed, medians and interquartile ranges (IQR) were reported. Subgroup analyses of prescribing rates were performed for patient age (under 40 years, 40-59 years, 60-79 years, 80 years and older), gender, and co-morbidities (e.g. diabetes mellitus, renal insufficiency, hypercholesterolaemia, coronary heart disease (CHD), post myocardial infarction, heart failure, stroke, obesity, asthma/chronic obstructive pulmonary disease (COPD)). The two-tailed Chi square test was used to analyse differences in prescription rates, and the Cochran-Armitage test was used as a measure of trend. A P value of less than 0.05 was regarded as indicating a statistically significant difference. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were calculated using multiple logistic regression to determine factors associated with different hypertensive medications (CCBs, diuretics, beta-blockers, ACE inhibitors, angiotensin II antagonists, or CAM remedies).