Polypharmacy is a major challenge in healthcare for older people, and is associated with increased risks of adverse outcomes, such as delirium, falls, frailty, cognitive impairment and hospitalization. There is significant public and professional interest in the role of deprescribing in reducing medication-related harms in older people. We aim to provide a narrative review of 1) the safety and efficacy of deprescribing interventions, 2) the challenges and solutions of deprescribing research and implementation in clinical practice, and 3) the benefits of using Computerized Clinical Decision Support Systems (CCDSS) and Quality Indicators (QIs) in deprescribing research and practice. Deprescribing is an established management strategy to minimize polypharmacy and potentially inappropriate medications. There is limited clinical evidence for its efficacy on global and geriatric outcomes. Various challenges at patient, healthcare professional and healthcare system levels may impact on the success of deprescribing interventions in research and practice. Management strategies that target all levels of the healthcare system are required to overcome these challenges. Future studies may consider large multicenter prospective designs to establish the effects and sustainability of deprescribing interventions on clinical outcomes.

ObjectiveAll healthcare systems require valid ways to evaluate service delivery. The objective of this study was to identify existing content validated quality indicators (QIs) for responsible use of medicines (RUM) and classify them using multiple frameworks to identify gaps in current quality measurements.DesignSystematic review without meta-analysis.SettingAll care settings.Search strategyCINAHL, Embase, Global Health, International Pharmaceutical Abstract, MEDLINE, PubMed and Web of Science databases were searched up to April 2018. An internet search was also conducted. Articles were included if they described medication-related QIs developed using consensus methods. Government agency websites listing QIs for RUM were also included.AnalysisSeveral multidimensional frameworks were selected to assess the scope of QI coverage. These included Donabedian’s framework (structure, process and outcome), the Anatomical Therapeutic Chemical (ATC) classification system and a validated classification for causes of drug-related problems (c-DRPs; drug selection, drug form, dose selection, treatment duration, drug use process, logistics, monitoring, adverse drug reactions and others).Results2431 content validated QIs were identified from 131 articles and 5 websites. Using Donabedian’s framework, the majority of QIs were process indicators. Based on the ATC code, the largest number of QIs pertained to medicines for nervous system (ATC code: N), followed by anti-infectives for systemic use (J) and cardiovascular system (C). The most common c-DRPs pertained to ‘drug selection’, followed by ‘monitoring’ and ‘drug use process’.ConclusionsThis study was the first systematic review classifying QIs for RUM using multiple frameworks. The list of the identified QIs can be used as a database for evaluating the achievement of RUM. Although many QIs were identified, this approach allowed for the identification of gaps in quality measurement of RUM. In order to more effectively evaluate the extent to which RUM has been achieved, further development of QIs may be required.

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Objective: Quality indicators (QIs) are an important mechanism by which health services can be evaluated. We aimed to develop a set of QIs for pharmacist home visit services and assess their measurement properties. Methods: A three-step procedure was applied: (1) Selection of existing contentvalidated QIs from the international literature and the development of QIs based on national guidelines and home healthcare professionals' opinions; (2) Expert panel consensus of a preliminary set of QIs using the RAND/UCLA Appropriateness Method; (3) Field testing to evaluate their measurement properties (feasibility, applicability, improvement potential, discriminatory capacity, sensitivity to change, acceptability and implementation issues) followed by exploratory semistructured interviews in Japan. Results: Fifty-two preliminary QIs were prepared and 45 were judged as "appropriate"by the expert panel. Sixty-one community pharmacies were recruited to this study with 41 contributing QI data monthly over the 6-month period. Field testing showed that 20 QIs met six measurement properties (ie, feasibility, applicability, improvement potential, discriminatory capacity, acceptability and implementation issues). Nine of these QIs also had high sensitivity to change. Additionally, interviews identified that the main positive impact on practice of using QIs was the early detection of causes of drug-related problems but a negative impact was decrease of pharmacists' motivation. Auto extraction of QIs was seen as a major facilitator, given the time taken to manually extract QI data. Conclusions: A set of QIs for pharmacist home visit services was rigorously developed and tested. This QI set may be useful in evaluating the quality of such services.

Background Polypharmacy is associated with an increased risk of adverse drug events in older people. Although national guidance on geriatric pharmacotherapy exists in Japan, tools to routinely monitor the quality of care provided by community pharmacists are lacking. Aim To develop a set of quality indicators (QIs) to measure the quality of care provided by community pharmacists in improving geriatric pharmacotherapy in primary care in Japan, using a modified Delphi study. Method The development of QIs for the Japanese community pharmacy context followed a two–step process: national guidance review and consensus testing using a modified Delphi study. The latter involved two rounds of rating with a face–to–face meeting between the rounds. Ten experts in geriatric pharmacotherapy in primary care were recruited for the panel discussion. QIs were mapped to three key taxonomies and frameworks: the Anatomical Therapeutic Chemical (ATC) classification system, problems and causes of drug–related problems (DRPs) taxonomy and Donabedian’s framework. Results A total of 134 QIs for geriatric pharmacotherapy were developed. This QI set included 111 medicine specific indicators, covering medicines in 243 third–level ATC classifications. QIs were classified into the problem of treatment safety (80%) and causes of drug selection (38%) based on validated classification for DRPs. In Donabedian's framework, most QIs (82%) were process indicators. There were no structure indicators. Conclusion A set of 134 QIs for geriatric pharmacotherapy was rigorously developed. Measurement properties of these QIs will be evaluated for feasibility, applicability, room for improvement, sensitivity to change, predictive validity, acceptability and implementation issues in a subsequent study.

Aim In Japan, home pharmaceutical care (HPC) has recently been provided to home‐bound older adults who have difficulties in accessing a community pharmacy, for regular medicine supplies and medication management. Although the number of HPC services provided has increased, HPC is not always carried out by clinically well‐trained pharmacists, causing differences in the quality of HPC provided. The aim of the present study was to establish the quality dimensions of HPC (i.e. components that impact the quality of HPC) from the perspectives of home healthcare professionals. Methods Semistructured interviews and focus groups were carried out with nine home healthcare teams, comprising 61 multidisciplinary professionals including pharmacists, doctors, nurses, care managers, home helpers, medical social workers and other relevant stakeholders involved in home healthcare. Participants’ responses were analyzed using thematic analysis. Identified themes were then categorized using Donabedian's framework (structure, process and outcome). Results Nine themes and 27 subthemes emerged, including: structure (pharmacist factors, pharmacy factors and external factors), process (before HPC, during HPC, after HPC and outside of HPC) and outcome (impact on patients and impact on other healthcare professionals). Conclusion This study has identified quality dimensions of HPC from multidisciplinary home healthcare professionals’ perspectives. These findings might be used to inform aspects of HPC that require improvement. In order to evaluate the quality of HPC, a set of indicators based on the identified quality dimensions could be developed. Geriatr Gerontol Int 2019; 19: 35–43.

The results of the survey show that clinical pharmacy services are established to very different extents among the participating countries. The strong correlation suggests that achieving a successful transition in professional practice needs to address several aspects of education and research to reach progress. The collected data might help to identify potential areas of improvement to foster implementation of clinical pharmacy services.
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Various functions expected by patient expects are needed with progress in the system for separation of dispensing and prescribing functions. In this investigation, the relationship between patient satisfaction and pharmacy function were analyzed quantitatively. A questionnaire survey was conducted in 178 community pharmacies. Questions on pharmacy functions and services totaled 87 items concerning information service, amenities, safety, personnel training, etc. The questionnaires for patients hadˆve-grade scales and composed 11 items (observed variables). Based on the results,`t he percentage of satisˆed patients'' was determined. Multivariate analysis was performed to investigate the relationship between patient satisfaction and pharmacy functions or services provided, to conˆrm patient's evaluation of the pharmacy, and how factors aŠected comprehensive satisfaction. In correlation analysis,``the number of pharmacists'' and``comprehensive satisfaction'' had a negative correlation. Other interesting results were obtained. As a results of factor analysis, three latent factors were obtained: the``human factor,''``patients' convenience,'' and``environmental factor,'' Multiple regression analysis showed that the``human factor'' aŠected``comprehensive satisfaction'' the most. Various pharmacy functions and services in‰uence patient satisfaction, and improvement in their quality increases patient satisfaction. This will result in the practice of patient-centered medicine.