Medication adherence assessment: high accuracy of the new Ingestible Sensor System in kidney transplants.
Ontology highlight
ABSTRACT:
SUBMITTER: Eisenberger U
PROVIDER: S-EPMC3749815 | biostudies-literature | 2013 Aug
REPOSITORIES: biostudies-literature
Publications
Medication adherence assessment: high accuracy of the new Ingestible Sensor System in kidney transplants.
Eisenberger Ute U Wüthrich Rudolf P RP Bock Andreas A Ambühl Patrice P Steiger Jürg J Intondi Allison A Kuranoff Susan S Maier Thomas T Green Damian D DiCarlo Lorenzo L Feutren Gilles G De Geest Sabina S
Transplantation 20130801 3
<h4>Background</h4>This open-label single-arm exploratory study evaluated the accuracy of the Ingestible Sensor System (ISS), a novel technology for directly assessing the ingestion of oral medications and treatment adherence.<h4>Methods</h4>ISS consists of an ingestible event marker (IEM), a microsensor that becomes activated in gastric fluid, and an adhesive personal monitor (APM) that detects IEM activation. In this study, the IEM was combined to enteric-coated mycophenolate sodium (ECMPS). T ...[more]
Similar Datasets
Project description:BackgroundTimely, accurate adherence data may support oral pre-exposure prophylaxis (PrEP) success and inform prophylaxis choice. We evaluated a Food and Drug Administration (FDA)-approved digital health feedback system (DHFS) with ingestible-sensor-enabled (IS) tenofovir-disoproxil-fumarate plus emtricitabine (Truvada®) in persons starting oral PrEP.MethodsHuman immunodeficiency virus (HIV)-negative adults were prescribed IS-Truvada® with DHFS for 12 weeks to observe medication taking behavior. Baseline demographics, urine toxicology, and self-report questionnaires were obtained. Positive detection accuracy and adverse events were computed as percentages, with Kaplan Meier Estimate for persistence-of-use. In participants persisting ≥28 days, adherence patterns (taking and timing) were analyzed, and mixed-effects logistic regression modeled characteristics associated with treatment adherence.ResultsSeventy-one participants were enrolled, mean age 37.6 years (range 18-69), 90.1% male, 77.5% White, 33.8% Hispanic, 95.8% housed, and 74.6% employed. Sixty-three participants (88.7%) persisted ≥28 days, generating 4987 observation days, average 79.2 (29-105). Total confirmed doses were 86.2% (95% confidence interval [CI] 82.5, 89.4), decreasing over time, odds ratio (OR) 0.899 (95% CI .876, .923) per week, P < .001; 79.4% (95% CI 66.7%, 87.3%) of participants had ≥80% adherence. Pattern analysis showed days without confirmed doses clustered (P = .003); regular dose timing was higher among participants with ≥80% confirmed doses (0.828, 95% CI .796 to .859) than among those with <80% (0.542, 95% CI95 .405 to .679) P < .001. In multi-predictor models, better adherence was associated with older age, OR 1.060 (95% CI 1.033, 1.091) per year, P < .001; negative vs positive methamphetamine screen, OR 5.051 (95% CI 2.252, 11.494), P < .001.ConclusionsDHFS with IS-Truvada® distinguished adherent persons from those potentially at risk of prophylactic failure. Ongoing methamphetamine substance use may impact oral PrEP success.
| S-EPMC10202440 | biostudies-literature
Project description:BackgroundCo-encapsulated antiretrovirals (ARVs) with ingestible sensor (IS) has the capacity to monitor adherence in real-time using a sensor patch, a mobile device, and supporting software. We evaluated the acceptability, effectiveness, and sustainability of the IS system with real-time text reminders.MethodsParticipants were recruited from HIV clinics in Los Angeles and were randomised 1:1 to IS or usual care (UC) group. Adherence to ARVs (primary outcome) was measured by IS system (IS group only), plasma ARV concentration, and self-report. IS-measured adherence was clustered by group-based trajectory model and was validated by ARV concentration summarized by integrated pharmacokinetic adherence measure (IPAM) score. HIV RNA viral load (VL) was compared between IS and UC group.FindingsA total of 112 (IS = 54, UC = 58) participants who completed baseline with at least one follow-up data collection were included in analyses. Overall satisfaction rate for the IS system was >90%. The IPAM score was higher (0.018, 95% CI: -0.098-0.134, p = 0.75) and VL decayed faster (-0.020, 95% CI: -0.042-0.002, p = 0.08) in the IS group compared with the UC group. The ingestible sensor system was well tolerated by study participants.InterpretationThe IS system was well accepted by participants and its use was associated with improved adherence and lower HIV RNA VL. The findings provide a potentially effective strategy for improving adherence.FundingThis work was supported by grant R01-MH110056 from the National Institute of Mental Health (NIMH)/National Institutes of Health (NIH). Y. Wang was in part supported by the NIMH/NIH award T32MH080634. E. Daar was in part supported by the National Center for Advancing Translational Sciences through UCLACTSI Grant UL1TR001881. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
| S-EPMC9782816 | biostudies-literature
Project description:Importance:Inaccurate medication records and poor medication adherence result in incomplete knowledge of therapy for patients. Objective:To study accuracy of medical records and patient adherence by measuring blood concentrations of medications. Design, Setting, and Participants:This cross-sectional study validated a serum-based liquid chromatography-tandem mass spectrometry assay to simultaneously quantify 263 medications used for acute and chronic conditions. The assay panel was applied to 3 clinical patient cohorts: residual serum from 1000 randomly selected samples sent for routine clinical chemistry testing between April 8 and October 6, 2015 (residuals cohort), 50 prospectively enrolled patients in a gastroenterology clinic between March 1 and March 15, 2016, who were prescribed more than 5 medications (gastroenterology care cohort), and a convenience cohort of 296 patients with hypertension who sought care in an emergency department (ED care cohort) between July 1, 2012, and April 25, 2013. Integrated data analysis of the cohorts was performed from August 22 to November 29, 2017. Main Outcomes and Measures:Medication serum concentrations, electronic health record medication lists, and predicted drug interactions. Results:Of the 1346 total samples, 1000 came from the residuals cohort (640 women and 360 men; median age, 60 years [interquartile range (IQR), 44-71 years]), 50 from the gastroenterology care cohort (30 women and 20 men; median age, 66 years [IQR, 62-70 years]), and 296 from the ED care cohort (160 women and 136 men; median age, 59 years [IQR, 52-66 years]). Median medication adherence, defined as the subset of detected medications from the prescription record, was 83% (IQR, 50%-100%) in the residuals cohort, 100% (IQR, 84%-100%) in the gastroenterology care cohort, and 78% (IQR, 57%-100%) in the ED care cohort. Patients adherent to 1 medication were more often adherent to other medications. Among patients prescribed 3 medications or more, there were no significant associations between medication adherence and sex or number of prescribed medications, and there was a modest association between adherence and age. By comparing detected vs prescribed medications, we detected a median of 0 (IQR, 0-2) medications per patient that were not listed in the electronic health record in the residuals cohort, 1 (IQR, 0-2) medication per patient that was not listed in the electronic health record in the gastroenterology care cohort, and 1 (IQR, 0-2) medication per patient that was not listed in the electronic health record in the ED care cohort. A total of 435 patients (43.5%) in the residuals cohort had no discrepancy between the electronic health record and detected medication lists, 22 patients (44.0%) in the gastroenterology care cohort had no discrepancy between the electronic health record and detected medication lists, and 41 patients (13.9%) in the ED care cohort had no discrepancy between the electronic health record and detected medication lists. Half of adverse drug reaction alerts occurred among medications detected without prescription. Conclusions and Relevance:Comprehensive medication monitoring offers promise to improve adherence, the accuracy of medical records, and the safety for patients with polypharmacy.
| S-EPMC6324396 | biostudies-literature
Project description:Before the 2014 implementation of a new kidney allocation system by the United Network for Organ Sharing, white patients were more likely than black or Hispanic patients to receive a kidney transplant. To determine the effect of the new allocation system on these disparities, we examined data for 179,071 transplant waiting list events in the period June 2013-September 2016, and we calculated monthly transplantation rates (34,133 patients actually received transplants). Implementation of the new system was associated with a narrowing of the disparities in the average monthly transplantation rates by 0.29 percentage point for blacks compared to whites and by 0.24 percentage point for Hispanics compared to whites, which resulted in both disparities becoming nonsignificant after implementation of the new system.
| S-EPMC5681858 | biostudies-literature
Project description:Poor adherence to medication regimens and medical record inconsistencies result in incomplete knowledge of medication therapy in polypharmacy patients. By quantitatively identifying medications in the blood of patients and reconciling detected medications with the medical record, we have defined the severity of this knowledge gap and created a path toward optimizing medication therapy.We validated a liquid chromatography-tandem mass spectrometry assay to detect and/or quantify 38 medications across a broad range of chronic diseases to obtain a comprehensive survey of patient adherence, medical record accuracy, and exposure variability in two patient populations. In a retrospectively tested 821-patient cohort representing U.S. adults, we found that 46% of medications assessed were detected in patients as prescribed in the medical record. Of the remaining medications, 23% were detected, but not listed in the medical record while 30% were prescribed to patients, but not detected in blood. To determine how often each detected medication fell within literature-derived reference ranges when taken as prescribed, we prospectively enrolled a cohort of 151 treatment-regimen adherent patients. In this cohort, we found that 53% of medications that were taken as prescribed, as determined using patient self-reporting, were not within the blood reference range. Of the medications not in range, 83% were below and 17% above the lower and upper range limits, respectively. Only 32% of out-of-range medications could be attributed to short oral half-lives, leaving extensive exposure variability to result from patient behavior, undefined drug interactions, genetics, and other characteristics that can affect medication exposure.This is the first study to assess compliance, medical record accuracy, and exposure as determinants of real-world treatment and response. Variation in medication detection and exposure is greater than previously demonstrated, illustrating the scope of current therapy issues and opening avenues that warrant further investigation to optimize medication therapy.
| S-EPMC5619774 | biostudies-literature
Project description:PurposeTo assess the accuracy of 5 subjective self-assessment tools (3 adherence measures and 2 psychometric scales) and pharmacy refill data in predicting objective electronically monitored nonadherence.DesignProspective cohort study.ParticipantsGlaucoma patients (> 40 years old, >1 medication with poor self-reported adherence) were recruited from University of Michigan Kellogg Eye Center for a study assessing the impact of a personalized glaucoma coaching program on medication adherence.MethodsParticipants completed an initial assessment including 5 self-assessment tools and a 3-month period of electronic monitoring of glaucoma medication adherence (AdhereTech); pharmacy refill data were obtained. Electronically monitored adherence was calculated monthly as the percentage of doses taken on time. The median of these adherence rates was designated as baseline adherence. Patients with adherence of ≤80% by electronic monitoring were considered nonadherent. Self-assessment tools were scored, and pharmacy refill data were summarized as the proportion of days covered. Correlation between measures of adherence was estimated with Pearson and Spearman correlation coefficients. Receiver operating characteristic curves, including estimation of area under the curve (AUC), sensitivity, specificity, and accuracy were used to compare measures of adherence with respect to predicting electronically monitored nonadherence.Main outcome measuresAccuracy of self-reported and pharmacy refill data adherence measures in predicting electronically monitored nonadherence.ResultsNinety-five patients completed 3 months of electronic monitoring with a median monthly adherence of 74 (± 21%); 53 patients (56%) were nonadherent. Pharmacy refill data were not correlated significantly with electronically monitored medication adherence (r = 0.12; P = 0.2). Of all the measures, a single-item adherence question ("Over the past month, what percentage of your drops do you think you took correctly?") showed the largest correlation with median electronically monitored adherence (r = 0.47; P < 0.0001), largest AUC for predicting nonadherence (AUC = 0.76 [95% confidence interval [CI], 0.66-0.87]), best accuracy (71% [95% CI, 61%-82%]), and good sensitivity (84% [95% CI, 73%-96%]).ConclusionsThe single-item question was the most accurate in predicting electronically monitored nonadherence among participants with poor self-reported adherence. In clinical practice, where alternatives are too resource intensive, this free single-item screening question can help to identify glaucoma patients at risk of poor medication adherence with reasonable accuracy.
| S-EPMC8814049 | biostudies-literature
Project description:BackgroundThis systematic review examined the reliability and validity of the Morisky Medication Adherence Scale-8 (MMAS-8), which has been widely used to assess patient medication adherence in clinical research and medical practice.MethodsOf 418 studies identified through searching 4 electronic databases, we finally analyzed 28 studies meeting the selection criteria of this study regarding the reliability and validity of MMAS-8 including sensitivity and specificity. Meta-analysis for Cronbach's ?, intraclass correlation coefficient (ICC), sensitivity and specificity to detect a patient with nonadherence to medication were performed. The pooled estimates for Cronbach's ? and ICC were calculated using the random-effects weighted T transformation. A bivariate random-effects model was used to estimate pooled sensitivity and specificity.FindingsThe pooled Cronbach's ? estimate for type 2 diabetes group in 7 studies and osteoporosis group in 3 studies were 0.67 (95% Confidence Interval(CI), 0.65 to 0.69) and 0.77 (95% CI, 0.72 to 0.83), respectively. With regard to test-retest, the pooled ICC for type 2 diabetes group in 3 studies and osteoporosis group in 2 studies were 0.81 (95% CI, 0.75 to 0.85) and 0.80 (95% CI, 0.74 to 0.85). For a cut-off value of 6, the pooled sensitivity and specificity in 12 studies were 0.43 (95% CI, 0.33 to 0.53) and 0.73 (95% CI, 0.68 to 0.78), respectively.ConclusionsThe MMAS-8 had acceptable internal consistency and reproducibility in a few diseases like type 2 diabetes. Using the cut-off value of 6, criterion validity was not enough good to validly screen a patient with nonadherence to medication. However, this study did not calculated a pooled estimate for criterion validity using the higher values than 6 as a cut-off value since most of included individual studies did not report criterion validity based on those values.
| S-EPMC5667769 | biostudies-literature
Project description:ObjectiveDescribe a novel approach to comprehensively summarize medication adherence.Data sources/study settingKaiser Permanente Northern California Diabetes Registry (n approximately 220,000)Study designIn a new prescription cohort design (27,329 subjects prescribed new medications), we used pharmacy utilization data to estimate adherence during 24 months follow-up. Proportion of time without sufficient medications (medication gaps) was estimated using a novel measure (New Prescription Medication Gaps [NPMG]) and compared with a traditional measure of adherence.Data collection/extraction methodsData derived from electronic medical records and survey responses.Principal findingsTwenty-two percent of patients did not become ongoing users (had zero or only one dispensing of the new prescription). The proportion of newly prescribed patients that never became ongoing users was eightfold greater than the proportion who maintained ongoing use, but with inadequate adherence. Four percent of those with at least two dispensings discontinued therapy during the 24 months follow-up. NPMG was significantly associated with high out-of-pocket costs, self-reported adherence, and clinical response to therapy.ConclusionsNPMG is a valid adherence measure. Findings also suggest a larger burden of inadequate adherence than previously thought. Public health efforts have traditionally focused on improving adherence in ongoing users; clearly more attention is needed to address nonpersistence in the very first stages after a new medication is prescribed.
| S-EPMC2754552 | biostudies-literature
Project description:Proteolytic and antiproteolytic enzymes play a critical role in the physiology and pathology of different stages of human life. One of the important members of the proteolytic family is the plasminogen activation system (PAS), which includes several elements crucial for this review: the 50 kDa glycoprotein plasminogen activator inhibitor 1 (PAI-1) that inhibits tissue-type (tPA) and urokinase-type plasminogen activator (uPA). These two convert plasminogen into its active form named plasmin that can lyse a broad spectrum of proteins. Urokinase receptor (uPAR) is the binding site of uPA. This glycoprotein on the cell surface facilitates urokinase activation of plasminogen, creating high proteolytic activity close to the cell surface. PAS activities have been reported to predict the outcome of kidney transplants. However, reports on expression of PAS in kidney transplants seem to be controversial. On the one hand there are reports that impaired proteolytic activity leads to induction of chronic allograft nephropathy, while on the other hand treatment with uPA and tPA can restore function of acute renal transplants. In this comprehensive review we describe the complexity of the PAS as well as biological effects of the PAS on renal allografts, and provide a possible explanation of the reported controversy.
| S-EPMC6102612 | biostudies-literature
Project description:BackgroundAccurate measurement and monitoring of patient medication adherence is a global challenge because of the absence of gold standard methods for adherence measurement. Recent attention has been directed toward the adoption of technologies for medication adherence monitoring, as they provide the opportunity for continuous tracking of individual medication adherence behavior. However, current medication adherence monitoring technologies vary according to their technical features and data capture methods, leading to differences in their respective advantages and limitations. Overall, appropriate criteria to guide the assessment of medication adherence monitoring technologies for optimal adoption and use are lacking.ObjectiveThis study aims to provide a narrative review of current medication adherence monitoring technologies and propose a set of technology assessment criteria to support technology development and adoption.MethodsA literature search was conducted on PubMed, Scopus, CINAHL, and ProQuest Technology Collection (2010-present) using the combination of keywords medication adherence, measurement technology, and monitoring technology. The selection focused on studies related to medication adherence monitoring technology and its development and use. The technological features, data capture methods, and potential advantages and limitations of the identified technology applications were extracted. Methods for using data for adherence monitoring were also identified. Common recurring elements were synthesized as potential technology assessment criteria.ResultsOf the 3865 articles retrieved, 98 (2.54%) were included in the final review, which reported a variety of technology applications for monitoring medication adherence, including electronic pill bottles or boxes, ingestible sensors, electronic medication management systems, blister pack technology, patient self-report technology, video-based technology, and motion sensor technology. Technical features varied by technology type, with common expectations for using these technologies to accurately monitor medication adherence and increase adoption in patients' daily lives owing to their unobtrusiveness and convenience of use. Most technologies were able to provide real-time monitoring of medication-taking behaviors but relied on proxy measures of medication adherence. Successful implementation of these technologies in clinical settings has rarely been reported. In all, 28 technology assessment criteria were identified and organized into the following five categories: development information, technology features, adherence to data collection and management, feasibility and implementation, and acceptability and usability.ConclusionsThis narrative review summarizes the technical features, data capture methods, and various advantages and limitations of medication adherence monitoring technology reported in the literature and the proposed criteria for assessing medication adherence monitoring technologies. This collection of assessment criteria can be a useful tool to guide the development and selection of relevant technologies, facilitating the optimal adoption and effective use of technology to improve medication adherence outcomes. Future studies are needed to further validate the medication adherence monitoring technology assessment criteria and construct an appropriate technology assessment framework.
| S-EPMC8949687 | biostudies-literature