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Annette Eidam,1 Anja Roth,1 Eduard Frick,2 Michael Metzner,2 Anette Lampert,2,3 Hanna M Seidling,2,3 Walter E Haefeli,2,3 Jürgen M Bauer1,4 1Center for Geriatric Medicine, Heidelberg University, AGAPLESION Bethanien Hospital Heidelberg, Heidelberg, Germany; 2Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University, Heidelberg, Germany; 3Cooperation Unit Clinical Pharmacy, Heidelberg University, Heidelberg, Germany; 4Network Aging Research (NAR), Heidelberg University, Heidelberg, GermanyCorrespondence: Annette Eidam, Center for Geriatric Medicine, Heidelberg University, AGAPLESION Bethanien Hospital Heidelberg, Heidelberg, Germany, Tel +49 6221-319-1795, Fax +49 6221-319-1505, Email Annette.Eidam@agaplesion.dePurpose: Medical decision-making in older adults with multiple chronic conditions and polypharmacy should include the individual patient’s treatment preferences. We developed and pilot-tested an electronic instrument (PolyPref) to elicit patient preferences in geriatric polypharmacy.Patients and Methods: PolyPref follows a two-stage direct approach to preference assessment. Stage 1 generates an individual preselection of relevant health outcomes and medication regimen characteristics, followed by stage 2, in which their importance is assessed using the Q-sort methodology. The feasibility of the instrument was tested in adults aged ≥ 70 years with ≥ 2 chronic conditions and regular intake of ≥ 5 medicines. After the assessment with PolyPref, the patients rated the tool with regard to its comprehensibility and usability and assessed the accuracy of the personal result. Evaluators rated the patients’ understanding of the task.Results: Eighteen short-term health outcomes, 3 long-term health outcomes, and 8 medication regimen characteristics were included in the instrument. The final population for the pilot study comprised 15 inpatients at a clinic for geriatric rehabilitation with a mean age of 80.6 (± 6.0) years, a median score of 28 (range 25– 30) points on the Mini-Mental State Examination, and a mean of 11.6 (± 3.6) regularly taken medicines. Feedback by the patients and the evaluators revealed ratings in favor of understanding and comprehensibility of 86.7% to 100%. The majority of the patients stated that their final result summarized the most important aspects of their pharmacotherapy (93.3%) and that its ranking order reflected their personal opinion (100%). Preference assessment took an average of 35 (± 8.5) min, with the instrument being handled by the evaluator in 14 of the 15 participants.Conclusion: Preference assessment with PolyPref was feasible in older adults with multiple chronic conditions and polypharmacy, offering a new strategy for the standardized evaluation of patient priorities in geriatric pharmacotherapy.Keywords: geriatric pharmacotherapy, medication priorities, multimorbidity, multiple chronic conditions, patient-centered, preference assessment

Viktoria S Wurmbach,1,2 Steffen J Schmidt,3 Anette Lampert,1,2 Simone Bernard,3 Christine K Faller,1,2 Petra A Thürmann,3,4 Walter E Haefeli,1,2 Hanna M Seidling1,2 On behalf of HIOPP-6 Consortium1Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Heidelberg, Germany; 2Cooperation Unit Clinical Pharmacy, Heidelberg University Hospital, Heidelberg, Germany; 3Department of Clinical Pharmacology, School of Medicine, Faculty of Health, Witten/Herdecke University, Witten, Germany; 4Philipp Klee-Institute for Clinical Pharmacology, HELIOS University Clinic Wuppertal, Wuppertal, GermanyCorrespondence: Hanna M SeidlingHeidelberg University Hospital, Department of Clinical Pharmacology and Pharmacoepidemiology, Im Neuenheimer Feld 410, Heidelberg, 69120, GermanyTel +49 6221/56-38736Email hanna.seidling@med.uni-heidelberg.dePurpose: The development and testing of key questions suitable to identify patients’ difficulties with medication administration.Materials and Methods: We used a consecutive five-step process to draft key questions regarding 43 aspects of medication administration that can be difficult for patients who manage a complex drug treatment: Step 1) Identification of potentially error-prone characteristics of drug treatment (such as certain dosage forms) and initial draft of key questions. Step 2) Assessment of how comprehensible the questions are for patients. Step 3) Pre-testing of exemplary key questions with patients and monitoring of patient’s actual medication administration behavior. Step 4) Evaluation by general practitioners of how well the questions may be integrated into actual patient visits. Step 5) Final approval of the questions in an expert panel. Thereafter, we pilot-tested exemplary questions with 36 patients (43 tests). In the course of this pilot-testing, the patients’ answers to the key questions were tested against both their actual behavior during medication administration and against their answers to more general questions regarding potential difficulties with medication administration.Results: More than half of the key questions (N = 24/43) were revised at least once during the development process. During the pilot-testing, 55.8% of the pilot-tests (N = 24/43) revealed medication administration difficulties. It was observed that the key questions identified significantly more difficulties (N = 17) than the general questions (N = 8; P = 0.021, positive predictive value = 94.4% vs 88.9%). In one case, both a key question and a general question identified difficulties, which, however, was not confirmed during the drug administration demonstration, indicating a false positive rate of 5.3% in both cases.Conclusion: We developed key questions aimed at detecting administration errors with a high specificity and a significantly higher sensitivity than general questions, suggesting that the resource-intensive demonstration of medication administration can be reserved for the detection of rarer and uncommon administration errors.Keywords: medication adherence, medication errors, quality of health care, patient preference

Andreas D Meid,1 Carmen Ruff,1 Lucas Wirbka,1 Felicitas Stoll,1 Hanna M Seidling,1,2 Andreas Groll,3 Walter E Haefeli1,2 1Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Heidelberg 69120, Germany; 2Cooperation Unit Clinical Pharmacy, University of Heidelberg, Heidelberg 69120, Germany; 3Department of Statistics, TU Dortmund University, Dortmund 44227, GermanyCorrespondence: Andreas D MeidDepartment of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Im Neuenheimer Feld 410, Heidelberg 69120, GermanyTel +49 6221 56 37113Fax +49 6221 56 4642Email Andreas.Meid@med.uni-heidelberg.deAbstract: When healthcare professionals have the choice between several drug treatments for their patients, they often experience considerable decision uncertainty because many decisions simply have no single “best” choice. The challenges are manifold and include that guideline recommendations focus on randomized controlled trials whose populations do not necessarily correspond to specific patients in everyday treatment. Further reasons may be insufficient evidence on outcomes, lack of direct comparison of distinct options, and the need to individually balance benefits and risks. All these situations will occur in routine care, its outcomes will be mirrored in routine data, and could thus be used to guide decisions. We propose a concept to facilitate decision-making by exploiting this wealth of information. Our working example for illustration assumes that the response to a particular (drug) treatment can substantially differ between individual patients depending on their characteristics (heterogeneous treatment effects, HTE), and that decisions will be more precise if they are based on real-world evidence of HTE considering this information. However, such methods must account for confounding by indication and effect measure modification, eg, by adequately using machine learning methods or parametric regressions to estimate individual responses to pharmacological treatments. The better a model assesses the underlying HTE, the more accurate are predicted probabilities of treatment response. After probabilities for treatment-related benefit and harm have been calculated, decision rules can be applied and patient preferences can be considered to provide individual recommendations. Emulated trials in observational data are a straightforward technique to predict the effects of such decision rules when applied in routine care. Prediction-based decision rules from routine data have the potential to efficiently supplement clinical guidelines and support healthcare professionals in creating personalized treatment plans using decision support tools.Keywords: claims data, decision-making, heterogeneous treatment effects, effect modification, confounding by indication, prediction-based decision rules

Annette Eidam, 1 Anja Roth, 1 André Lacroix, 1 Sabine Goisser, 1, 2 Hanna M Seidling, 3, 4 Walter E Haefeli, 3, 4 Jürgen M Bauer 1, 2 1Center of Geriatric Medicine, Heidelberg University, AGAPLESION Bethanien Hospital Heidelberg, Heidelberg 69126, Germany; 2Network Aging Research (NAR), Heidelberg University, Heidelberg 69115, Germany; 3Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University, Heidelberg 69120, Germany; 4Cooperation Unit Clinical Pharmacy, Heidelberg University, Heidelberg 69120, GermanyCorrespondence: Annette EidamCenter of Geriatric Medicine, Heidelberg University, AGAPLESION Bethanien Hospital Heidelberg, Rohrbacher Straße 149, Heidelberg 69126, GermanyTel +49 6221-319-1795Fax +49 6221-319-1505Email Annette.Eidam@bethanien-heidelberg.dePurpose: The aim of this systematic review was to identify methods used to assess medication preferences in older adults and evaluate their advantages and disadvantages with respect to their applicability to the context of multimorbidity and polypharmacy.Material and Methods: Three electronic databases (PubMed, Web of Science, PsycINFO) were searched. Eligible studies elicited individual treatment or outcome preferences in a context that involved long-term pharmacological treatment options. We included studies with a study population aged ≥ 65 years and/or with a mean or median age of ≥ 75 years. Qualitative studies, studies assessing preferences for only two different treatments, and studies targeting preferences for life-sustaining treatments were excluded. The identified preference measurement methods were evaluated based on four criteria (time budget, cognitive demand, variety of pharmacological aspects, and link with treatment strategies) judged to be relevant for the elicitation of patient preferences in polypharmacy.Results: Sixty articles met the eligibility criteria and were included in the narrative synthesis. Fifty-five different instruments to assess patient preferences, based on 24 different elicitation methods, were identified. The most commonly applied preference measurement techniques were “medication willingness” (description of a specific medication with inquiry of the participant’s willingness to take it), discrete choice experiments, Likert scale-based questionnaires, and rank prioritization. The majority of the instruments were created for disease-specific or context-specific settings. Only three instruments (Outcome Prioritization Tool, a complex intervention, “MediMol” questionnaire) dealt with the broader issue of geriatric multimorbidity. Only seven of the identified tools showed somewhat favorable characteristics for a potential use of the respective method in the context of polypharmacy.Conclusion: Up to now, few instruments have been specifically designed for the assessment of medication preferences in older patients with multimorbidity. To facilitate valid preference elicitation in the context of geriatric polypharmacy, future research should focus on suitable characteristics of existing techniques to develop new measurement approaches for this increasingly relevant population.Keywords: polypharmacy, outcome priorities, multimorbidity, older adults, multiple chronic conditions, patient-centered

Background: Information technology in health care has a clear potential to improve the quality and efficiency of health care, especially in the area of medication processes. On the other hand, existing studies show possible adverse effects on patient safety when IT for medication-related processes is developed, introduced or used inappropriately. Objectives: To summarize definitions and observations on IT usage in pharmacotherapy and to derive recommendations and future research priorities for decision makers and domain experts. Methods: This memorandum was developed in a consensus-based iterative process that included workshops and e-mail discussions among 21 experts coordinated by the Drug Information Systems Working Group of the German Society for Medical Informatics, Biometry and Epidemiology (GMDS). Results: The recommendations address, among other things, a stepwise and comprehensive strategy for IT usage in medication processes, the integration of contextual information for alert generation, the involvement of patients, the semantic integration of information resources, usability and adaptability of IT solutions, and the need for their continuous evaluation. Conclusion: Information technology can help to improve medication safety. However, challenges remain regarding access to information, quality of information, and measurable benefits. [ABSTRACT FROM AUTHOR]

Marcel KP Kusch,1,2 Walter E Haefeli,1,2 Hanna M Seidling1,2 1Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, 69120 Heidelberg, Baden-Wurttemberg, Germany; 2Cooperation Unit Clinical Pharmacy, University of Heidelberg, 69120 Heidelberg, Baden-Wurttemberg, Germany Purpose: The aim of this study was to 1) describe drug information desired by patients and 2) analyze how such information could be customized to be presented to patients according to their individual information needs.Materials and methods: We performed a scoping literature search and identified relevant drug information topics by assessing and clustering 1) studies analyzing patients’ enquiries to drug information hotlines and services, and 2) qualitative studies evaluating patient drug information needs. For the two most frequently mentioned topics, we further analyzed which components (ie, information domains) the topics contained and examined patients’ and health care professionals’ (HCPs) views on these components.Results: Of 27 identified drug information topics in the literature search, patients most frequently requested information on adverse drug reactions (ADRs) and drug–drug interactions (DDIs). Hypothetically, those topics are composed of seven distinct information domains each (eg, ADR and DDI classification by frequency, severity, or onset; information on management strategies, monitoring, and prevention strategies). Patients’ and HCPs’ appraisal concerning the information content of these domains varies greatly and is even lacking sometimes.Conclusion: Patients particularly request information on ADRs and DDIs. Approaches to customize such information are sparse. The identified information domains of each topic could be used to structure corresponding drug information and to thus facilitate customization to individual information needs. Keywords: medication information, information needs, customization, adverse drug reactions, side effects, drug–drug interactions

The article focuses on the development of a clinical decision support (CDS) systems drug application database model that is based on ontology. It states that the model is composed of a schema that includes significant drug application attributes and an ontology that offers a structured vocabulary of terms that describes the values of the schema's features. Results show that the model allows characterization of drug application which closes a gap in current CDS systems used in pharmacotherapy.

Gerda Längst,1 Hanna Marita Seidling,2,3 Marion Stützle,2,3 Dominik Ose,1 Ines Baudendistel,1 Joachim Szecsenyi,1 Michel Wensing,1,4 Cornelia Mahler1 1Department of General Practice and Health Services Research, University Hospital of Heidelberg, Heidelberg, Germany; 2Cooperation Unit Clinical Pharmacy, University of Heidelberg, Heidelberg, Germany; 3Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Heidelberg, Germany; 4Radboud University Nijmegen Medical Centre, Scientific Institute for Quality of Healthcare, Nijmegen, the Netherlands Purpose: This qualitative study in patients with type 2 diabetes and health care professionals (HCPs) aimed to investigate which factors they perceive to enhance or impede medication information provision in primary care. Similarities and differences in perspectives were explored.Methods: Eight semistructured focus groups were conducted, four with type 2 diabetes patients (n=25) and four with both general practitioners (n=13) and health care assistants (n=10). Sessions were audio and video recorded, transcribed verbatim, and subjected to computer-aided qualitative content analysis.Results: Diabetes patients and HCPs broadly highlighted similar factors as enablers for satisfactory medication information delivery. Perceptions substantially differed regarding impeding factors. Both patients and HCPs perceived it to be essential to deliver tailored information, to have a trustful and continuous patient–provider relationship, to regularly reconcile medications, and to provide tools for medication management. However, substantial differences in perceptions related to impeding factors included the causes of inadequate information, the detail required for risk-related information, and barriers to medication reconciliation. Medication self-management was a prevalent topic among patients, whereas HCPs’ focus was on fulfilling therapy and medication management responsibilities.Conclusion: The findings suggest a noteworthy gap in perceptions between information provision and patients’ needs regarding medication-related communication. Medication safety and adherence may be improved if HCPs collaborate more closely with diabetes patients in managing their medication, in particular by incorporating the patients’ perspective. Health care systems need to be structured in a way that supports this process. Keywords: medication information, patient–provider communication, type 2 diabetes, focus groups, primary care

Diana Witticke,1,2 Hanna Marita Seidling,1,2 Hans-Dieter Klimm,3 Walter Emil Haefeli1,21Department of Clinical Pharmacology and Pharmacoepidemiology, 2Cooperation Unit Clinical Pharmacy, 3Department of General Practice and Health Service Research, University of Heidelberg, Heidelberg, GermanyBackground: The aim of this pilot study was to evaluate patients' self-reported attitudes towards medication-related factors known to impair adherence and to assess their prevalence in ambulatory care as an essential prerequisite to improve patient adherence.Methods: We conducted a face-to-face interview with 110 primary care patients maintained on at least one drug. For each drug, the patient was asked to specify medication-related factors of interest, ie, dosage form, dosage interval, required relationship with food intake, and the planned time of day for intake, and to rate the individual relevance of each prevalent parameter on a three-point Likert scale (discriminating between prefer, neutral, and dislike).Results: Tablets with a once-daily dosage frequency were the most preferred dosage form, with a high prevalence in the ambulatory setting. Drug intake in the morning and evening were most preferred, and drug intake at noon was least preferred, but also had a low prevalence in contrast with drug intake independent of meals that was most preferred. Interestingly, only one quarter (26.4%) of all the patients were able to indicate clear preferences or dislikes.Conclusion: When patients are asked to specify their preferences for relevant medication regimen characteristics, they clearly indicated regimens that have been associated with better adherence in earlier studies. Therefore, our results suggest that adaptation of drug regimens to individual preferences might be a promising strategy to improve adherence. Because the German health care system may differ from other systems in relevant aspects, our findings should be confirmed by evaluation of patient preferences in other health care systems. Once generalizability of the study results is shown, these findings could be a promising basis upon which to promote patient adherence right from the beginning of drug therapy.Keywords: patient perception, medication regimen complexity, adherence

Polypharmacy (≥5 drugs) increases the risk of discrepancies between patient- and general practitioner (GP)-reported drugs, leading to adverse outcomes. This explorative analysis assesses the agreement between patient- and GP-reported drugs under the influence of a paper-based patient portfolio in a pilot cluster randomized controlled trial (cRCT). Complete data were available for 68 patients aged 65 or older (26 were female), with multimorbidity, polypharmacy, and at least one hospitalization in the past year. Agreement was assessed for drug name and strength level. Differences between the intervention and control group (IG/CG) and comparisons between two time points (six-month interval) stratified according to gender were analyzed using Wilcoxon and Mann-Whitney U tests (α = 5%). To evaluate the reasons for discrepancies, the agreement of active pharmaceutical ingredients (APIs) and anatomical therapeutic chemical (ATC) groups was analyzed. At baseline, the agreement was 72.1% for the IG and 73.9% for the CG. Inclusion of the reported drug strength reduced the agreement in both groups (IG 66.7%, CG 60.0%). Agreement for the IG decreased statistically significantly after six months (-5.4%). ATC groups B, C, and H had the highest agreement, while N, R, and Z had the lowest. Large discrepancies in the drugs reported, due to the APIs and the corresponding ATC group, were observed.

Background: The transition of patients between inpatient and outpatient care can lead to adverse events and medication-related problems due to medication and communication errors, such as medication discontinuation, the frequency of (re-)hospitalizations, and increased morbidity and mortality. Older patients with multimorbidity and polypharmacy are particularly at high risk during transitions of care. Previous research highlighted the need for interventions to improve transitions of care in order to support information continuity, coordination, and communication. The HYPERION-TransCare project aims to improve the continuity of medication management for older patients during transitions of care., Methods and Findings: Using a qualitative design, 32 expert interviews were conducted to explore the perspectives of key stakeholders, which included healthcare professionals, patients and one informal caregiver, on transitions of care. Interviews were conducted between October 2020 and January 2021, transcribed verbatim and analyzed using content analysis. We narratively summarized four main topics (stakeholders' tasks, challenges, ideas for solutions and best practice examples, and patient-related factors) and mapped them in a patient journey map. Lacking or incomplete information on patients' medication and health conditions, inappropriate communication and collaboration between healthcare providers within and across settings, and insufficient digital support limit the continuity of medication management., Conclusions: The study confirms that medication management during transitions of care is a complex process that can be compromised by a variety of factors. Legal requirements and standardized processes are urgently needed to ensure adequate exchange of information and organization of medication management before, during and after hospital admissions. Despite the numerous barriers identified, the findings indicate that involved healthcare professionals from both the inpatient and outpatient care settings have a common understanding., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Dinh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: Approximately one fifth of the German population suffers from chronic pain, which is often associated with limitations in coping with everyday life, social isolation and psychological comorbidities such as anxiety and depression. The importance of a treatment approach that considers biological, psychological, and social factors (bio-psycho-social model) as well as non-drug interventions is emphasized in current guidelines, but presents challenges for primary care practices. To support the implementation of evidence-based best practice recommendations, the RELIEF project (Resource-oriented case management to implement recommendations for patients with chronic pain and frequent use of analgesics in general practices) aims to develop a case management program for the primary care of patients with chronic non-tumor pain., Methods: Prior to intervention development, a rapid review was conducted to identify best practice recommendations for the care of patients with chronic non-tumor pain, barriers and strategies to their implementation, and gaps in care in current guidelines and literature. Selective searches of guidelines, PubMed, the Cochrane Library, bibliographies of relevant publications, and the gray literature focused on assessment and monitoring, education, promotion of self-care, and rational pharmacotherapy., Results: Numerous recommendations on assessment and monitoring were identified, but only a few studies examined their feasibility in primary care practices. Guidelines contained few specific recommendations on content and format of patient education on chronic pain. Recommendations for non-drug self-care measures were mainly related to physical activity, relaxation techniques, behavioral therapy techniques and external applications. Especially for the area of physical activity, numerous barriers but also strategies for a successful implementation could be identified., Discussion: In a potential primary care model for patients with chronic non-tumor pain, pain assessment should aim to identify patients who need support in implementing medication and non-medication interventions in the primary care setting and/or could benefit from specialized care. To implement recommendations for pain education, primary care physicians need educational materials in a variety of formats and levels of detail that ideally could be processed by patients at home and then get addressed in practices using simple key questions. Non-drug measures should be an explicit part of the treatment plan., Conclusion: Many of the identified recommendations for the treatment of patients with chronic non-tumor pain can also be considered relevant for the primary care setting. Specific guidelines and concepts for primary care physicians that include setting-specific characteristics at the physician, patient, and system levels would be desirable for a successful implementation of these recommendations., (Copyright © 2024. Published by Elsevier GmbH.)

Introduction: We investigated the effectiveness of a multidomain intervention to preserve cognitive function in older adults at risk for dementia in Germany in a cluster-randomized trial., Methods: Individuals with a Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) risk score ≥ 9 aged 60 to 77 years were recruited. After randomization of their general practitioner (GP), patients received a multidomain intervention (including optimization of nutrition and medication, and physical, social, and cognitive activity) or general health advice and GP treatment as usual over 24 months. Primary outcome was global cognitive performance (composite z score, based on domain-specific neuropsychological tests)., Results: Of 1030 participants at baseline, n = 819 completed the 24-month follow-up assessment. No differences regarding global cognitive performance (average marginal effect = 0.010, 95% confidence interval: -0.113, 0.133) were found between groups at follow-up. Perceived restrictions in intervention conduct by the COVID-19 pandemic did not impact intervention effectiveness., Discussion: The intervention did not improve global cognitive performance., Highlights: Overall, no intervention effects on global cognitive performance were detected. The multidomain intervention improved health-related quality of life in the total sample. In women, the multidomain intervention reduced depressive symptoms. The intervention was completed during the COVID-19 pandemic., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Prescription forms enable the communication between physicians and pharmacists. Hence, incorrectly issued prescriptions may result in delay of health-care delivery, additional workload, and potentially adverse patient outcomes. We aimed to evaluate the formal prescription quality in our outpatient clinics (OC) before and after performing teaching sessions and using an electronic prescription system to replace handwritten prescriptions., Methods: All OCs of a university hospital were offered a short teaching session on how to issue prescriptions correctly and how to use the electronic prescription system. During four weeks before and after the teaching, we anonymously collected all prescriptions of the OCs in 20 surrounding community pharmacies and assessed whether they were error-free, required an intervention by the pharmacist, additional clarification by the OC, or had to be reissued., Results: After the intervention, the absolute fraction of formally error-free prescriptions increased by 12.9% from 52.9% (516/976) to 65.8% (713/1084, p < 0.001; d = 12,9% 95% confidence interval [8,7%; 17,1%]). Largest improvements were seen in prescriptions requiring clarification by the OC (224/976 prescriptions at baseline versus 93/1084 post-intervention, p < 0.001). The fraction of electronic prescriptions increased from 34.9% (341/976) to 46.9% (509/1084, p < 0.001, d = 12,0% 95% confidence interval [7,8%; 16,2%]) with electronic prescriptions consistently being of higher formal quality than handwritten prescriptions., Conclusion: After increased use of electronic prescribing and teaching courses, formal prescription quality was significantly improved., (© Georg Thieme Verlag KG Stuttgart · New York.)