Development and validation of the 15-STARS - A novel self-report pharmacy-based questionnaire to screen for medication non-adherence.

BACKGROUND: Published scales measuring medication adherence are myriad. There is a need for a tool that guides towards downstream adherence interventions. OBJECTIVE: To develop and validate a self-report questionnaire able to detect modifiable determinants of medication non-adherence. METHODS: Workshops, surveys and meetings were used to identify items. Validation was performed in French and German (Switzerland) between March and April 2022. Face validation, content validation, construct validation, internal consistency and test-retest reliability were assessed. The questionnaire was finalized in August 2022. RESULTS: The first draft in English included 13 items divided into four areas. Following translation, validation was performed with 144 patients (63 German-, 81 French-speaking) who were recruited in 35 community pharmacies. Acceptability was good (<5% missing data). Psychometric properties were acceptable with good content validity and moderate construct validity. Internal consistency was acceptable for the French version (Cronbach's alpha = 0.71 [item 1-5] - 0.61 [item 6-9]) and less acceptable for the German version (Cronbach's alpha = 0.43 [item 1-5] - 0.45 [item 6-9]). Test-retest was given for all items (r = 0.52 to 1.0) except item 10 in French (r = 0.25). The final instrument is a 15-item questionnaire called the 15-STARS (Screening Tool for AdheRence to medicineS) that assesses practical difficulties with medicine use, reasons for non-adherence, doses missed, and need for further help. CONCLUSIONS: Our findings support the validity and clinical utility of the 15-STARS questionnaire. Reliability was inconclusive due to incoherent internal consistency, but explainable by the single-item nature of the scale. This new tool will enable the detection of patients who experience difficulties that negatively influence medication adherence. Pharmacists will be able to propose specific and tailored adherence interventions to the patients. Next steps will focus on evaluating its usefulness for developing targeted interventions that optimize medication adherence in routine care and research settings.

HIOPP-6 - a pilot study on the evaluation of an electronic tool to assess and reduce the complexity of drug treatment considering patients' views.

BACKGROUND: A complex drug treatment might pose a barrier to safe and reliable drug administration for patients. Therefore, a novel tool automatically analyzes structured medication data for factors possibly contributing to complexity and subsequently personalizes the results by evaluating the relevance of each identified factor for the patient by means of key questions. Hence, tailor-made optimization measures can be proposed. METHODS: In this controlled, prospective, exploratory trial the tool was evaluated with nine general practitioners (GP) in three study groups: In the two intervention groups the tool was applied in a version with (GI_with) and a version without (GI_without) integrated key questions for the personalization of the analysis, while the control group (GC) did not use any tools (routine care). Four to eight weeks after application of the tool, the benefits of the optimization measures to reduce or mitigate complexity of drug treatment were evaluated from the patient perspective. RESULTS: A total of 126 patients regularly using more than five drugs could be included for analysis. GP suggested 117 optimization measures in GI_with, 83 in GI_without, and 2 in GC. Patients in GI_with were more likely to rate an optimization measure as helpful than patients in GI_without (IRR: 3.5; 95% CI: 1.2-10.3). Thereby, the number of optimization measures recommended by the GP had no significant influence (P = 0.167). CONCLUSIONS: The study suggests that an automated analysis considering patient perspectives results in more helpful optimization measures than an automated analysis alone - a result which should be further assessed in confirmatory studies. TRIAL REGISTRATION: The trial was registered retrospectively at the German Clinical Trials register under DRKS-ID DRKS00025257 (17/05/2021).

Prevalence and patient-rated relevance of complexity factors in medication regimens of community-dwelling patients with polypharmacy.

PURPOSE: To describe the prevalence of complexity factors in the medication regimens of community-dwelling patients with more than five drugs and to evaluate the relevance of these factors for individual patients. METHODS: Data were derived from the HIOPP-6 trial, a controlled study conducted in 9 general practices which evaluated an electronic tool to detect and reduce complexity of drug treatment. The prevalence of complexity factors was based on the results of the automated analysis of 139 patients' medication data. The relevance assessment was based on the patients' rating of each factor in an interview (48 patients included for analysis). RESULTS: A median of 5 (range 0-21) complexity factors per medication regimen were detected and at least one factor was observed in 131 of 139 patients. Almost half of these patients found no complexity factor in their medication regimen relevant. CONCLUSION: In most medication regimens, complexity factors could be identified automatically, yet less than 15% of factors were indeed relevant for patients as judged by themselves. When assessing complexity of medication regimens, one should especially consider factors that are both particularly frequent and often challenging for patients, such as use of inhalers or tablet splitting. TRIAL REGISTRATION: The HIOPP-6 trial was registered retrospectively on May 17, 2021, in the German Clinical Trials register under DRKS-ID DRKS00025257.

Development and Pilot-Testing of Key Questions to Identify Patients' Difficulties in Medication Administration.

PURPOSE: 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.

Development of an algorithm to detect and reduce complexity of drug treatment and its technical realisation.

BACKGROUND: The increasing complexity of current drug therapies jeopardizes patient adherence. While individual needs to simplify a medication regimen vary from patient to patient, a straightforward approach to integrate the patients' perspective into decision making for complexity reduction is still lacking. We therefore aimed to develop an electronic, algorithm-based tool that analyses complexity of drug treatment and supports the assessment and consideration of patient preferences and needs regarding the reduction of complexity of drug treatment. METHODS: Complexity factors were selected based on literature and expert rating and specified for integration in the automated assessment. Subsequently, distinct key questions were phrased and allocated to each complexity factor to guide conversation with the patient and personalize the results of the automated assessment. Furthermore, each complexity factor was complemented with a potential optimisation measure to facilitate drug treatment (e.g. a patient leaflet). Complexity factors, key questions, and optimisation strategies were technically realized as tablet computer-based application, tested, and adapted iteratively until no further technical or content-related errors occurred. RESULTS: In total, 61 complexity factors referring to the dosage form, the dosage scheme, additional instructions, the patient, the product, and the process were considered relevant for inclusion in the tool; 38 of them allowed for automated detection. In total, 52 complexity factors were complemented with at least one key question for preference assessment and at least one optimisation measure. These measures included 29 recommendations for action for the health care provider (e.g. to suggest a dosage aid), 27 training videos, 44 patient leaflets, and 5 algorithms to select and suggest alternative drugs. CONCLUSIONS: Both the set-up of an algorithm and its technical realisation as computer-based app was successful. The electronic tool covers a wide range of different factors that potentially increase the complexity of drug treatment. For the majority of factors, simple key questions could be phrased to include the patients' perspective, and, even more important, for each complexity factor, specific measures to mitigate or reduce complexity could be defined.

Individual factors increasing complexity of drug treatment-a narrative review.

PURPOSE: Complexity of drug treatment is known to be a risk factor for administration errors and nonadherence promoting higher healthcare costs, hospital admissions and increased mortality. Number of drugs and dose frequency are parameters often used to assess complexity related to the medication regimen. However, factors resulting from complex processes of care or arising from patient characteristics are only sporadically analyzed. Hence, the objective of this review is to give a comprehensive overview of relevant, patient-centered factors influencing complexity of drug treatment. METHODS: A purposeful literature search was performed in MEDLINE to identify potential complexity factors relating to the prescribed drug (i.e. dosage forms or other product characteristics), the specific medication regimen (i.e. dosage schemes or additional instructions), specific patient characteristics and process characteristics. Factors were included if they were associated to administration errors, nonadherence and related adverse drug events detected in community dwelling adult patients. RESULTS: Ninety-one influencing factors were identified: fourteen in "dosage forms", five in "product characteristics", twelve in "dosage schemes", nine in "additional instructions", thirty-one in "patient characteristics" and twenty in "process characteristics". CONCLUSIONS: Although the findings are limited by the non-systematic search process and the heterogeneous results, the search shows the influence of many factors on the complexity of drug treatment. However, to evaluate their relevance for individual patients, prospective studies are necessary.

[Simplifying complex drug therapies : Challenges and solutions]. / Komplexe Arzneimitteltherapien vereinfachen : Herausforderungen und Lösungsansätze.

The difficulties of managing a complex medication regimen are often underestimated in outpatient care. A large number of drugs (polypharmacy) and complicated dosage schemes or dosage forms may overstrain patients. Indeed, wrong drug administration can impair treatment success or cause adverse drug events.Patients are often unaware of the medication administration errors. Furthermore they do not voice administration problems, often because they are not aware of the potential to optimize their drug therapy. Medication regimen complexity can often be reduced by simple measures. However, feasible concepts for reducing medication regimen complexity in a structured way have been lacking in routine care so far.Electronic decision support facilitates systematic and efficient identification of factors that increase the complexity of a medication regimen. Furthermore, electronic decision aids may enable physicians and pharmacists to take appropriate measures in order to reduce medication regimen complexity. Personalizing the analysis and resulting measures to reduce medication regimen complexity might increase readiness of patients to implement changes in treatment and, thus, probably increase adherence. The first results of a prospective trial that is supported by the Federal Joint Committee (G-BA) Innovationsfonds (HIOPP-6, Komplexitätsreduktion in der Polypharmazie unter Beachtung von Patientenpräferenzen) will be available in autumn 2018 and answer these questions.