View clinical trials related to Medication Non-adherence.
Filter by:Successful medication management is an essential instrumental activity of daily living (IADL) for older adults with polypharmacy; however, between 40%-70% of older adults fail to take their medications as prescribed. Providing interventions to address medication management and restore performance for this IADL is within the scope of practice for occupational therapy (OT), however, there is paucity of evidence for OT interventions to improve medication management in community-dwelling older adults. We have developed a tailored medication management intervention (TIMM) for community-dwelling older adults which recognizes the unique context in which medication management occurs (the home) and addresses the personal and environmental barriers experienced by older adults. TIMM is delivered in the home, by an OT, and in collaboration with a pharmacist to reduce inappropriate polypharmacy.
This study investigated the feasibility and acceptability of a phone-delivered mindfulness intervention to improve medication adherence among outpatients with heart failure.
This is a prospective study using customized adherence enhancement (CAE) and long-acting injectable (LAI) antipsychotic in 30 individuals with bipolar disorder (BD) at risk for treatment non-adherence. The CAE approach is expected to improve treatment adherence, as well as improve BD symptoms, functioning and treatment attitudes among subjects with bipolar disorder.
Uncontrolled hypertension is a major cause of morbidity and mortality and many patients fail to take their antihypertensive medication as prescribed. The investigators propose to use artificial intelligence (AI) to allow short message service (SMS or text messages) interventions to adapt to patients' adherence needs and substantially improve medication taking. The aims of the study are to: (1) develop AI methods for adaptive decision-making in human-centered environments and demonstrate the feasibility of the resulting AI-enhanced SMS medication adherence intervention, (2) demonstrate that the intervention can "learn" by adapting the SMS message stream according to patients' medication taking over time, and (3) examine potential intervention impact as measured by improvements in medication adherence and systolic blood pressures. The investigators will recruit 100 patients with uncontrolled hypertension and antihypertensive medication non-adherence. Adherence and other covariates will be measured via surveys at baseline, 3- and 6 months; blood pressures will be measured at baseline and 6 months. Participants will be given an electronic pill-bottle adherence monitor. Participants will receive SMS messages designed to motivate antihypertensive medication adherence. Message content and frequency will adapt automatically using AI algorithms designed to automatically optimize expected pill bottle opening. For Aim 1, the first 25 patients will be enrolled to develop and test alternative RL algorithms and fine-tune the system parameters. For Aim 2, the investigators will examine changes in the probability distribution over message-types and compare that distribution with patients' reasons for non-adherence reported at baseline. For Aim 3, the investigators will examine changes in self-reported medication non-adherence and blood pressure and automatically-reported pill bottle openings. This pilot study will establish the feasibility and potential impact of this novel approach to mobile health messaging for self-management support. The results will be used to support an R01 application for a larger and more definitive trial of intervention impacts.
This study uses an artificial intelligence platform to automatically confirm medication ingestion. The Health Insurance Portability and Accountability Act (HIPAA)-compliant platform can be downloaded as an 'app' onto any smartphone to automate directly observed therapy (Automated DOT®). Real-time patient adherence data are encrypted and automatically sent to a centralized web-based dashboard for use by healthcare professionals or research staff. Unlike Facetime® or Skype®, the system relies on computer vision algorithms to confirm the process of medication administration; no human review is necessary. The purpose of this study is to evaluate the feasibility and acceptability, and measure the accuracy, of the AiCure platform ("platform") in patients being treated for opioid dependence with Zubsolv® over the course of 12 weeks. The following aims will be tested: 1) to assess the feasibility and acceptability to both participants and study staff in using AiCure to monitor medication adherence; 2) to evaluate the acceptability of using AiCure to optimize care pathways; and 3) to measure the reliability and validity of AiCure in detecting interruptions in treatment. To assess feasibility and acceptability of the platform, we will measure rates of physician satisfaction and user acceptance. Optimization of care pathways will be measured by assessing the sustainability of AiCure use over 12 weeks (retention rates) and measuring illicit opioid use (urine drug screens) compared to historical data. Reliability and validity of AiCure will be measured by comparing AiCure adherence against pharmacokinetic data. All participants will be requested to take each of their prescribed doses using the app. Participants will be able to download the app onto their own smartphone or will be provisioned a device at the start of the study. The data captured during the medication ingestion process will be automatically encrypted and stored on the participant smartphone and uploaded wirelessly to a cloud-based dashboard. If a participant is non-adherent (missed dose, incorrect dosage) or if suspicious behavior is detected, an automated alert will be sent to study staff via email or SMS to prompt immediate intervention. In addition, all participants will receive treatment as usual.
This is a prospective study using a concierge model of customized adherence enhancement and long-acting injectable antipsychotic (CAL-Concierge) in 30 individuals with schizophrenia or schizoaffective disorder at risk for treatment non-adherence and for homelessness. Like the CAE-L approach, CAL-Concierge is expected to improve health outcomes among the most vulnerable of populations with schizophrenia but even more importantly, will demonstrate that it can be used to improve the efficiency and quality of care in typical practice settings.
The main objectives of this research are: 1. To identify factors that influence medication adherence rates in Emergency Department (ED) patients. 2. To measure the effects of alternative information prescriptions on medication adherence rates of ED patients. 3. To measure the effects of alternative information prescriptions (IRxs) on health and service utilization.
Despite extensive reports of the benefits of statins in reducing serious cardiovascular events such as stroke and heart disease in patients with elevated LDL-cholesterol, patients do not take their medicines regularly as prescribed. Reasons include forgetfulness, lack of understanding of the seriousness of the disease, and fear of side effects. An intervention strategy comprising 3-5 minutes of counseling, emotional support and cost-sharing may be motivational and improve adherence to treatment.
The purpose of this observational research study is to determine when and why patients discontinue, interrupt, or disrupt the regimen of anti-platelet medications prescribed following stent implantation, and to examine the relationship between specific patterns of non-adherence and patient outcomes.