The prescription of analgesics and anti-inflammatory drugs (analgesics) was studied using computerized patient records from a Finnish health centre with a population base of some 27,000 inhabitants. A random sample of every fifth patient visiting the health centre in 1986 was chosen. This study sample consisted of 4,577 patients with 17,021 physician contacts and altogether 14,035 prescriptions during the 1-year follow-up: of these analgesics comprised 14.8%. The proportion of the study population who received at least one analgesic prescription was 23 +/- 1.2% (95% CI). The use of physician contacts as a base revealed 10.7 +/- 0.5% (95% CI) of the contacts with an analgesic prescription. The exposure to analgesics among males increased with age from 17% for those aged 15-34 years to 34% for those aged 75 years or more. Among women, exposure to analgesics increased from 17% (15-34 years) to 41% (75 years or more). Most of patients who received analgesic prescriptions were incidental users (one or two analgesic prescriptions per year). Only 4% of women and 3% of men were categorized as heavy users of analgesics (seven or more analgesic prescriptions per year). The proportion of heavy users increased with age and was highest in the oldest age-group (75 years or more). In order to make informed policy judgements about drug use in society, we need routine sales statistics and patient-specific drug-use data such as those presented in this paper.
Drug dependency may develop during long-term benzodiazepine use, indicated, for example, by dose escalation. The first benzodiazepine chosen may affect the risk of dose escalation.
To detect possible differences in benzodiazepine use between new users of diazepam and oxazepam over time.
This 5-year prescription database study included 19 747 new benzodiazepine users, inhabitants of Norway, aged 30-60 years, with first redemption for diazepam or oxazepam.
Individuals starting on diazepam versus oxazepam were analysed by logistic regression with sex, age, other drug redemptions, prescriber's specialty, household income, education level, type of work, and vocational rehabilitation support as background variables. Time to reach a daily average intake of =1 defined daily doses (DDD) over a 3-month period was analysed using a Cox proportional hazard regression model.
New users of oxazepam had a higher risk for dose escalation compared with new users of diazepam. This was true even when accounting for differences in sociodemographic status and previous drug use (hazard ratio [HR] 1.33, 95% confidence interval = 1.17 to 1.51).
Most doctors prescribed, according to recommendations, oxazepam to individuals they may have regarded as prone to and at risk of dependency. However, these individuals were at higher risk for dose escalation even when accounting for differences in sociodemographic status and previous drug use. Differences between the two user groups could be explained by different preferences for starting drug, DDD for oxazepam being possibly too low, and some unaccounted differences in illness.
A 75 year-old man with a well known opioid abuse is described. Within the last 10 years the patient had 161 acute admissions to hospital--in total 942 in-hospital days. The diagnoses were either angina pectoris, low back pain or migraine. With time, the patient had become very skilled in mimicking these three diseases, knowing all subjective and objective signs even better than most of his doctors. In connection with all admissions he received the opioids he wanted. Nevertheless, he was astonished that it was so easy to fool the doctors. It is recommended that the patients' own doctor should be the coordinator and the only person responsible for prescription of opioids to these patients. In case of admissions to hospital, this should only be possible to a few selected departments who know the patient.
British Columbia's central prescription database, PharmaNet, is often used for both clinical and research applications. However, PharmaNet details prescription transactions, not actual medication consumption, resulting in many potential sources of inaccuracy when the information is assumed to reflect population or individual drug utilization.
To assess the accuracy of PharmaNet for adherence assessment in patients with heart failure who are taking beta-blockers.
A 6-month prospective, longitudinal assessment of adherence to the prescribed beta-blocker regimen was carried out using both PharmaNet data and the Medication Event Monitoring System (MEMS) for each patient enrolled. The limit of agreement between the 2 adherence assessment methods was assessed using the Bland-Altman approach.
Fifteen of 58 patients initially enrolled in the study were excluded, most due to misuse of MEMS or failure to return the MEMS vial despite thorough follow-up. For the 43 patients included in the final analysis, mean +/- SD adherence was 97.8 +/- 11.8% when assessed by PharmaNet and 97.1 +/- 7.3% when MEMS was used. However, the limit of agreement, reported as the mean of the differences +/- 2SD, was 6.8 +/- 18.5%, indicating a moderate-to-high level of agreement between the 2 methods when the confidence interval is taken into consideration.
These results suggest that PharmaNet data accurately reflect medication adherence for most patients. The MEMS system proved unreliable in several cases, illustrating the difficulty of identifying a gold standard for adherence assessment.