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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.
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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
OBJECTIVES: In 2017, an in-house best-practice process for medication documentation was developed and implemented to meet the new German legal requirements concerning the management of patient discharge from the hospital. Because this law regulates the common steps of good discharge practices (eg, specification of discharge mediation documentation), we used its implementation to assess the impact of such a measure on the quality of medication documentation and related workflows in clinical routine. METHODS: By observing workflows and interviewing the affected employees, we analysed the medication workflow processes from admission to discharge of seven representative departments of a large university hospital before and early after implementation of a newly defined best-practice process. To investigate the implementation impact, following measures were determined overall and for five key process steps: quality of medication documentation as measured by predefined criteria, the adherence to the best-practice process (range 0%-100%), workload and potential shifts in responsibilities. RESULTS: Already early after implementation, all departments met the legal requirements and the quality of the medication documentation increased from low to high quality in most departments. Mean adherence to the best-practice process was 77% (range 60%-100%) with strictest adherence of 100% in one department. Thereby, the number of process steps and hence, likely also the workload increased in all departments. New tasks were mainly performed by physicians and in one department by pharmacists. CONCLUSIONS: The new lawful best-practice process led to a higher quality in medication documentation at the cost of a higher workload for physicians, potentially limiting time for other care tasks. Therefore, it could be important to define areas of the medication documentation process in which physicians could be supported by other professions or new tools facilitating accurate medication documentation as the basis of continuity of care.
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Patient Discharge , Physicians , Documentation , Humans , Pharmacists , WorkflowABSTRACT
BACKGROUND: Through targeted medication alerts, clinical decision support systems (CDSS) help users to identify medication errors such as disregarded drug-drug interactions (DDIs). Override rates of such alerts are high; however, they can be mitigated by alert tailoring or workflow-interrupting display of severe alerts that need active user acceptance or overriding. Yet, the extent to which the displayed alert interferes with the prescribers' workflow showed inconclusive impact on alert acceptance. OBJECTIVES: We aimed to assess whether and how often prescriptions were changed as a potential result of interruptive alerts on different (contraindicated) prescription constellations with particularly high risks for adverse drug events (ADEs). METHODS: We retrospectively collected data of all interruptive alerts issued between March 2016 and August 2020 in the local CDSS (AiDKlinik) at Heidelberg University Hospital. The alert battery consisted of 31 distinct alerts for contraindicated DDI with simvastatin, potentially inappropriate medication for patients > 65 years (PIM, N = 14 drugs and 36 drug combinations), and contraindicated drugs in hyperkalemia (N = 5) that could be accepted or overridden giving a reason in free-text form. RESULTS: In 935 prescribing sessions of 500 274 total sessions, at least one interruptive alert was fired. Of all interruptive alerts, about half of the sessions were evaluable whereof in total 57.5% (269 of 468 sessions) were accepted while 42.5% were overridden. The acceptance rate of interruptive alerts differed significantly depending on the alert type (p <0.0001), reaching 85.7% for DDI alerts (N = 185), 65.3% for contraindicated drugs in hyperkalemia (N = 98), and 25.1% for PIM alerts (N = 185). CONCLUSION: A total of 57.5% of the interruptive medication alerts with particularly high risks for ADE in our setting were accepted while the acceptance rate differed according to the alert type with contraindicated simvastatin DDI alerts being accepted most frequently.
Subject(s)
Decision Support Systems, Clinical , Medical Order Entry Systems , Drug Interactions , Electronics , Humans , Medication Errors/prevention & control , 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.
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Pharmaceutical Preparations , Polypharmacy , Algorithms , Female , Health Personnel , Humans , Patient PreferenceABSTRACT
INTRODUCTION: Breast cancer-related extremity lymphedema is a potentially devastating condition. Vascularized lymph node transfer (VLNT) has shown benefit in lymphedema treatment. Due to concerns over potential iatrogenic complications, various donor sites have been described. The current study aims at defining the deep inferior epigastric lymph node basin as a novel donor site for VLNT. METHODS: A retrospective study was performed on patients undergoing routine abdominal-based breast reconstruction. Resection of all perivascular adipose and lymphatic tissue surrounding the proximal deep inferior epigastric pedicle was performed at the time of pedicle dissection and submitted for Pathologic evaluation. Patient demographics and pertinent medical/surgical history was obtained from medical records. RESULTS: Specimens were obtained from 10 consecutive patients. Seven patients underwent bilateral reconstruction for a total of 17 specimens obtained. Mean patient age and BMI were 48 years ± 9.4 and 27 ± 4.2, respectively. Fourteen out of 17 (82%) specimens contained viable lymph nodes displaying a thin fibrous connective tissue capsule overlying an unremarkable subcapsular sinus with a cortex and paracortex containing germinal centers composed of B lymphocytes, tangible body macrophages, and T-cells. The medullary sinus space displayed a fatty unremarkable hilum. The mean number and size of lymph nodes were 2.6 ±1.2 nodes/specimen and 3.67 mm ± 2.3, respectively. All patients experienced an uneventful postoperative course without evidence any of compromised flap viability. CONCLUSION: Lacking previous description, the deep inferior epigastric lymph node basin is a readily accessible donor site with significant anatomic advantages for potential VLNT during autologous breast reconstruction.
Subject(s)
Breast Cancer Lymphedema/surgery , Epigastric Arteries , Lymph Nodes/pathology , Lymph Nodes/transplantation , Mammaplasty , Microsurgery/methods , Transplant Donor Site/anatomy & histology , Vascularized Composite Allotransplantation/methods , Abdomen/surgery , Adult , Female , Humans , Inguinal Canal , Lymph Node Excision , Lymph Nodes/blood supply , Middle Aged , Perforator Flap/blood supply , Perforator Flap/transplantation , Postoperative Complications , Quality of Life , Retrospective Studies , Transplant Donor Site/blood supply , Treatment OutcomeABSTRACT
PURPOSE: Electronic clinical decision support systems (CDSS) require drug information that can be processed by computers. The goal of this project was to determine and evaluate a compilation of variables that comprehensively capture the information contained in the summary of product characteristic (SmPC) and unequivocally describe the drug, its dosage options, and clinical pharmacokinetics. METHODS: An expert panel defined and structured a set of variables and drafted a guideline to extract and enter information on dosage and clinical pharmacokinetics from textual SmPCs as published by the European Medicines Agency (EMA). The set of variables was iteratively revised and evaluated by data extraction and variable allocation of roughly 7% of all centrally approved drugs. RESULTS: The information contained in the SmPC was allocated to three information clusters consisting of 260 variables. The cluster "drug characterization" specifies the nature of the drug. The cluster "dosage" provides information on approved drug dosages and defines corresponding specific conditions. The cluster "clinical pharmacokinetics" includes pharmacokinetic parameters of relevance for dosing in clinical practice. A first evaluation demonstrated that, despite the complexity of the current free text SmPCs, dosage and pharmacokinetic information can be reliably extracted from the SmPCs and comprehensively described by a limited set of variables. CONCLUSION: By proposing a compilation of variables well describing drug dosage and clinical pharmacokinetics, the project represents a step forward towards the development of a comprehensive database system serving as information source for sophisticated CDSS.
Subject(s)
Medical Order Entry Systems , Pharmacokinetics , Dose-Response Relationship, DrugABSTRACT
Glioblastoma multiforme (GBM) is one of the most aggressive brain tumors. GBM cell lines used in laboratory studies are frequently passaged in various culture media at high proliferation rates, resulting in significant genetic and molecular alterations. Thus, data obtained in cell lines are often inapplicable to patient tumors. Furthermore, recent studies suggest that there is a stem cell-like hierarchy among GBM cell populations and a crucial role for tumor vasculature in stem cells, as well as tumor growth, which cannot be reproduced in cell line cultures. Our laboratory has developed a novel three-dimensional (3D) organotypic "explant" system of surgical GBM specimens that preserves tumor cells in their original milieu, as well as the cytoarchitecture of the tumor stroma. Our previous study on the role of Notch inhibition has demonstrated a definitive effect on the tumor endothelium that could only be highlighted by this system. In this unit, we describe a detailed protocol for preparing GBM explants, and discuss strengths, as well as limitations of the explant system as an in vitro 3D model of GBM.