Clinical pharmacy as an area of practice, education and research started developing around the 1960s when pharmacists across the globe gradually identified the need to focus more on ensuring the appropriate use of medicines to improve patient outcomes rather than being engaged in manufacturing and supply. Since that time numerous studies have shown the positive impact of clinical pharmacy services (CPS). The need for wider adoption of CPS worldwide becomes urgent, as the global population ages, and the prevalence of polypharmacy as well as shortage of healthcare professionals is rising. At the same time, there is great pressure to provide both high-quality and cost-effective health services. All these challenges urgently require the adoption of a new paradigm of healthcare system architecture. One of the most appropriate answers to these challenges is to increase the utilization of the potential of highly educated and skilled professionals widely available in these countries, i.e., pharmacists, who are well positioned to prevent and manage drug-related problems together with ensuring safe and effective use of medications with further care relating to medication adherence. Unfortunately, CPS are still underdeveloped and underutilized in some parts of Europe, namely, in most of the Central and Eastern European (CEE) countries. This paper reviews current situation of CPS development in CEE countries and the prospects for the future of CPS in that region.

• Keywords
• clinical pharmacy, cost-effective treatment, drug safety, drug utilization, health policy, medication adherence, medication errors, polypharmacy,
• Publication type
• Journal Article MeSH

Background: Drug-related problems (DRPs) which arise from potentially inappropriate medications (PIMs) are a common problem in older people with multi-morbidity and polypharmacy. Aim: To develop an integrated PIM clinical decision support tool for identification of DRPs in geriatric multi-morbid polypharmacy patients, using the EU(7)-PIM and EURO-FORTA lists, with a focus on high-risk medications. Methods: The integrated PIM tool used the information on PIMs in both databases-the EU(7)-PIM and EURO-FORTA. PIMs were classified into four color groups based on risk profile: high-risk PIMs (should be avoided in older patients) as red, moderate-risk PIMs (require dose and/or treatment duration adjustment) as yellow, low-risk PIMs (low DRP risk) as green, and questionable PIMs (incomplete/missing information) as grey. Results: The summarized list of the high-risk (red and some grey) PIMs contained 81 active substances and medication classes. According to the ATC classification, most of the high-risk PIMs (n = 60, 74.1%) belong to the A, C, and N medication groups and 50.6% (n = 41) of the high-risk PIMs have currently marketing authorization in Estonia. The preliminary list of the moderate- and low-risk (yellow, green, and other grey) PIMs contained 240 active substances and medication classes, but sub-classification of this category into one or another group depends mainly on an individual patient´s clinical characteristics in a concrete analyzed study sample and needs further research. Conclusion: The integrated clinical decision support tool based on the EU(7)-PIM and EURO-FORTA criteria addresses the need for more efficient identification of DRPs. It can be applied to identify PIMs and geriatric prescribing problems in different health care settings, and also in a context of little clinical information available.

• Keywords
• Estonia, clinical decision support tool, drug related problems, multi-morbidity, older adults, polypharmacy, potentially inappropriate medications,
• Publication type
• Journal Article MeSH

PURPOSE: The aim of this study was to explore patterns and long-term development in prescribing potentially inappropriate medication (PIM) according to the EU(7)-PIM list to elderly patients in Germany. METHODS: We analysed anonymized German claims data. The study population comprised 6.0 million insured individuals at least 65 years old, including all their prescriptions reimbursed in 2019. For the analysis of long-term development, we used data for the years 2009-2019. Factors associated with PIM prescribing were considered from two perspectives: patient-oriented analysis was performed with logistic regression and prescriber-oriented analysis was performed with multiple linear regression. RESULTS: EU(7)-PIM prevalence was reduced from 56.9% in 2009 to 45.1% in 2019. Average annual volume (DDDs/insured) decreased from 145 in 2009 to 121 in 2019. These figures are substantially greater than those for the older PRISCUS list. The majority of investigated ATC level 2 groups with the highest EU(7)-PIM DDD volume exhibited substantial decreases; moderate increases were found for antihypertensive and urological drugs. Antithrombotics increased strongly with the introduction of direct oral anticoagulants. The most prevalent EU(7)-PIM medication was diclofenac; however, in the age group 85+ years, apixaban was twice as prevalent as diclofenac. Polypharmacy, female sex, age < 90 years, need for nursing care and living in Eastern regions were identified as risk factors. Prescriber specialty was the most marked factor in the prescriber-oriented analysis. CONCLUSION: Although the use of EU(7)-PIMs has been declining, regional differences indicate considerable room for improvement. The comparison with PRISCUS highlights the necessity of regular updates of PIM lists.

• Keywords
• Claims data, EU(7)-PIM list, Elderly, PRISCUS list, Potentially inappropriate medication,
• MeSH
• Residence Characteristics MeSH
• Humans MeSH
• Insurance Claim Review statistics & numerical data   MeSH
• Polypharmacy MeSH
• Cross-Sectional Studies MeSH
• Retrospective Studies MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Sex Factors MeSH
• Potentially Inappropriate Medication List statistics & numerical data   trends   MeSH
• Age Factors MeSH
• Check Tag
• Humans MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH
• Observational Study MeSH
• Geographicals
• Germany epidemiology   MeSH