ABSTRACT
Purpose: 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.
ABSTRACT
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).
Subject(s)
General Practitioners , Electronics , Humans , Pharmaceutical Preparations , Pilot Projects , Prospective Studies , Retrospective StudiesABSTRACT
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.
Subject(s)
Independent Living , Polypharmacy , Clinical Protocols , Humans , Prevalence , Retrospective StudiesABSTRACT
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.
Subject(s)
Pharmaceutical Preparations , Polypharmacy , Algorithms , Female , Health Personnel , Humans , Patient PreferenceABSTRACT
4-Hydroxyphenylpyruvate dioxygenase (Hpd, EC 1.13.11.27) catalyzes the conversion of 4-hydroxyphenylpyruvate into homogentisate in the second step of oxidative tyrosine catabolism. This pathway is known from bacteria and eukaryotes, but so far no archaeal Hpd has been described. Here, we report the biochemical characterization of an Hpd from the extremophilic archaeon Picrophilus torridus (Pt_Hpd), together with its three-dimensional structure at a resolution of 2.6 Å. Two pH optima were observed at 50 °C: pH 4.0 (close to native conditions) and pH 7.0. The enzyme showed only moderate thermostability and was inactivated with a half-life of ~1.5 h even under optimal reaction conditions. At the ideal physiological growth conditions of P. torridus, Pt_Hpd was inactive after 1 h, showing that the enzyme is protected in vivo from denaturation and/or is only partially adapted to the harsh environmental conditions in the cytosol of P. torridus. The influence of different additives on the activity was investigated. Pt_Hpd exhibited a turnover number k(cat) of 9.9 ± 0.6 s(-1) and a substrate binding affinity K(m) of 142 ± 23 µM. In addition, substrate inhibition with a binding affinity K(i) of 1.9 ± 0.3 mM was observed. Pt_Hpd is compared with isoenzymes from other species and the putative bacterial origin of the gene is discussed.