Background: Databases of prescription drug purchases are now widely used in pharmacoepidemiologic studies. Several methods have been used to generate drug use periods from drug purchases to investigate various aspects; e.g., to study associations between exposure and outcome. Typically, such methods have been fairly simplistic, with fixed assumptions of drug use pattern and or dose (for example, the assumed usage of 1 tablet per day). This paper describes a novel PRE2DUP method that constructs drug use periods from purchase histories, and verified by a validation based on an expert evaluation of the drug use periods generated by the method. Methods: The PRE2DUP method is a novel approach based on mathematical modelling of personal drug purchasing behaviors. The method uses a decision procedure that includes each person's purchase history for each ATC code, processed in a chronological order. The method constructs exposure time periods and estimates the dose used during the period by considering the purchased amount in Defined Daily Doses (DDDs), which is recorded in the prescription register database. This method takes account of stockpiling of drugs, personal purchasing pattern; i.e., regularity of the purchases, and periods of hospital or nursing home care where drug use is not recorded in the prescription register. The method can be applied to a variety of drug classes with different doses and use patterns by controlling restriction parameters for each ATC class, or even each drug package. In the presented example, the PRE2DUP method was applied to a register-based MEDALZ-2005 study cohort. All drug purchases (3,793,085) recorded in the Finnish prescription register between 2002 and 2009 for persons with Alzheimer's disease (28,093) were included. Results: Results of the expert-opinion based validation indicate that PRE2DUP method creates drug use periods with a relatively high correctness. Drugs with varying patterns of use and drugs used on a short-term basis only require more precise parameters. Conclusions: PRE2DUP method gives highly accurate drug use periods for most drug classes, especially those meant for long-term use.

BackgroundEvidence is lacking about outcomes associated with the cumulative use of anticholinergic and sedative drugs in people with Alzheimer’s disease (AD). This retrospective cohort study investigated the relationship between cumulative exposure to anticholinergic and sedative drugs and hospitalization and mortality in people with and without AD in Finland.MethodsCommunity-dwelling people aged 65 years and over, with AD on December 31st 2005 (n = 16,603) and individually matched (n = 16,603) comparison persons (age, sex, region of residence) were identified by the Social Insurance Institution of Finland. Drug utilization data were extracted from the Finnish National Prescription Register. Exposure to anticholinergic and sedative drugs was defined using the Drug Burden Index (DBI). Hospitalization and mortality data were extracted from national registers. Cox and zero-inflated negative binomial analyses were used to investigate the relationship between DBI and hospitalization and mortality over a one-year follow-up.ResultsIn total, 5.8% of people with AD and 3.7% without AD died during 2006. For every unit increase in DBI, the adjusted hazard ratio for mortality was 1.21 (95% confidence intervals [CI]: 1.09–1.33) among people with AD, and 1.37 (95%CI: 1.20–1.56) among people without AD. Overall, 44.3% of people with AD and 33.4% without AD were hospitalized. When using no DBI exposure as the reference group, the adjusted incidence rate ratio for length of hospital stay among high DBI group (≥1) in people with AD was 1.15 (95%CI: 1.05–1.26) and 1.63 (95%CI: 1.41–1.88) in people without AD.ConclusionThere is a dose-response relationship between cumulative anticholinergic and sedative drug use and hospitalization and mortality in people with and without AD.

BackgroundPRE2DUP is a modeling method that generates drug use periods (ie, when drug use started and ended) from drug purchases recorded in dispensing-based register data. It is based on the evaluation of personal drug purchasing patterns and considers hospital stays, possible stockpiling of drugs, and package information.ObjectiveThe objective of this study was to investigate person-level agreement between self-reported drug use in the interview and drug use modeled from dispensing data with PRE2DUP method for various drug classes used by older persons.MethodsSelf-reported drug use was assessed from the GeMS Study including a random sample of persons aged ≥75 years from the city of Kuopio, Finland, in 2006. Drug purchases recorded in the Prescription register data of these persons were modeled to determine drug use periods with PRE2DUP modeling method. Agreement between self-reported drug use on the interview date and drug use calculated from register-based data was compared in order to find the frequently used drugs and drug classes, which was evaluated by Cohen’s kappa. Kappa values 0.61–0.80 were considered to represent good and 0.81–1.00 as very good agreement.ResultsAmong 569 participants with mean age of 82 years, the agreement between interview and register data was very good for 75% and very good or good for 93% of the studied drugs or drug classes. Good or very good agreement was observed for drugs that are typically used on regular bases, whereas “as needed” drugs represented poorer results.ConclusionPRE2DUP modeling method validly describes regular drug use among older persons. For most of drug classes investigated, PRE2DUP-modeled register data described drug use as well as interview-based data which are more time-consuming to collect. Further studies should be conducted by comparing it with other methods and in different drug user populations.

Pain is a frequent cause of discomfort and distress in residents in residential aged care facilities (RACFs). Despite the benefits of adequate pain management, there is inconsistency in the literature regarding analgesic use and pain in residents with dementia. The aim of this systematic review was to determine the prevalence of analgesic drug use among residents with and without dementia or cognitive impairment in RACFs. A systematic search of MEDLINE and EMBASE (inception to January 2014) was conducted using Medical Subject Headings and Emtree terms, respectively. Studies were included if they reported prevalence of analgesic use for residents both with and without dementia within the same study. Data extraction and quality assessment was performed independently by two investigators. Data on the prevalence of analgesic use, pain and painful conditions were extracted. Meta-analyses were performed using random effect models. The 7 included studies were of high quality (≥ 5 out of 7 on the adapted Newcastle-Ottawa Scale). Analgesic use in residents with and without dementia or cognitive impairment ranged from 20.2% to 61.2% and 38.8% to 79.6%, respectively. Paracetamol was the most prevalent analgesic in people with and without dementia. Residents with dementia or cognitive impairment had a significantly lower prevalence of analgesic use (odds ratio [OR] 0.576, 95% confidence interval [CI] = 0.406-0.816) and of self-reported and clinician-observed pain (OR 0.355, 95% CI = 0.278-0.454) than residents without cognitive impairment, despite a comparable prevalence of painful conditions. These findings may indicate under-reporting and under-detection of pain in persons with dementia, and subsequent suboptimal treatment.

Psychotropic drugs are used for treatment of behavioral and psychological symptoms of dementia (BPSD) although they are associated with serious adverse drug events. Objective of our study was to investigate prevalence of psychotropic drug use one year after diagnoses of Alzheimer's disease (AD), to compare prevalence to persons without AD and to assess changes in prevalence over time. Data from the MEDALZ (Medication use and Alzheimer's disease) cohort was utilized in the study including all 69,080 community-dwelling persons with new diagnosis of AD during years 2005-2011 in Finland. Four age-, gender- and region of residence-matched persons without AD were identified for each case. Register-based data included prescription drug purchases and comorbidities from Special Reimbursement Register. Annual prevalence of psychotropic drug use one year after diagnosis was determined for each person. Psychotropic drugs were used by 53% of persons with AD compared with 33% of persons without AD during one year after diagnoses. Persons with AD were six times more likely to use antipsychotics and three times more likely to use antidepressants whereas benzodiazepine and related drug (BZDR) use was comparable between persons with and without AD. According to year of AD diagnoses during 2005-2011, antipsychotic use increased from 18% to 20% (p<0.0001) and BZDR use declined from 31% to 26% (p<0.0001) among persons with AD. Widespread utilization of psychotropic drugs was observed among persons with AD. Despite safety warnings of antipsychotic use for BPSD, antipsychotic use increased from 2005 to 2011 among newly diagnosed persons with AD in Finland.