Analysis of adherence to peak flow monitoring when recording of data is electronic.
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ABSTRACT:
SUBMITTER: Reddel HK
PROVIDER: S-EPMC64515 | biostudies-literature | 2002 Jan
REPOSITORIES: biostudies-literature
Publications
Analysis of adherence to peak flow monitoring when recording of data is electronic.
Reddel Helen K HK Toelle Brett G BG Marks Guy B GB Ware Sandra I SI Jenkins Christine R CR Woolcock Ann J AJ
BMJ (Clinical research ed.) 20020101 7330
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Project description:Maintaining high medication adherence is essential for achieving desired efficacy in clinical trials, especially prevention trials. However, adherence is traditionally measured by self-reports that are subject to reporting biases and measurement error. Recently, electronic medication dispenser devices have been adopted in several HIV pre-exposure prophylaxis prevention studies. These devices are capable of collecting objective, frequent, and timely drug adherence data. The device opening signals generated by such devices are often represented as regularly or irregularly spaced discrete functional data, which are challenging for statistical analysis. In this paper we focus on clustering the adherence monitoring data from such devices. We first pre-process the raw discrete functional data into smoothed functional data. Parametric mixture models with change-points, as well as several non-parametric and semi-parametric functional clustering approaches are adapted and applied to the smoothed adherence data. Simulation studies were conducted to evaluate finite sample performances, on the choices of tuning parameters in the pre-processing step as well as the relative performance of different clustering algorithms. We applied these methods to the HIV Prevention Trials Network(HPTN) 069 study for identifying subgroups with distinct adherence behavior over the study period.
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Project description:IntroductionElectronic adherence monitoring (EAM) is increasingly used to improve adherence. However, there is limited evidence on the effect of EAM in across chronic conditions and on patient acceptability. We aimed to assess the effect of EAM on adherence and clinical outcomes, across all ages and all chronic conditions, and examine acceptability in this systematic review and meta-analysis.MethodsA systematic search of Ovid MEDLINE, EMBASE, Social Work Abstracts, PsycINFO, International Pharmaceutical Abstracts and CINAHL databases was performed from database inception to December 31, 2020. Randomised controlled trials (RCTs) that evaluated the effect of EAM on medication adherence as part of an adherence intervention in chronic conditions were included. Study characteristics, differences in adherence and clinical outcomes between intervention and control were extracted from each study. Estimates were pooled using random-effects meta-analysis, and presented as mean differences, standardised mean differences (SMD) or risk ratios depending on the data. Differences by study-level characteristics were estimated using subgroup meta-analysis to identify intervention characteristics associated with improved adherence. Effects on adherence and clinical outcomes which could not be meta-analysed, and patient acceptability, were synthesised narratively. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline was followed, and Risk of bias (RoB) assessed using the Cochrane Collaboration's RoB tool for RCTs. The review is registered with PROSPERO CRD42017084231.FindingsOur search identified 365 studies, of which 47 studies involving 6194 patients were included. Data from 27 studies (n = 2584) were extracted for the adherence outcome. The intervention group (n = 1267) had significantly better adherence compared to control (n = 1317), (SMD = 0.93, CI:0.69 to 1.17, p<0.0001) with high heterogeneity across studies (I2 = 86%). There was a significant difference in effect according to intervention complexity (p = 0.01); EAM only improved adherence when used with a reminder and/or health provider support. Clinical outcomes were measured in 38/47 (81%) of studies; of these data from 14 studies were included in a meta-analysis of clinical outcomes for HIV, hypertension and asthma. In total, 13/47 (28%) studies assessed acceptability; patient perceptions were mixed.InterpretationPatients receiving an EAM intervention had significantly better adherence than those who did not, but improved adherence did not consistently translate into clinical benefits. Acceptability data were mixed. Further research measuring effects on clinical outcomes and patient acceptability are needed.
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2021-07-26 | PXD026875 | Pride
Project description:BackgroundMedication adherence is essential to optimizing blood pressure (BP) control. Prior research has demonstrated differences in pharmacy refill patterns according to antihypertensive drug class. No prior study has assessed the association between drug class and day-to-day adherence.MethodsBetween 2011 and 2014, we enrolled a convenience sample of 149 patients with persistently uncontrolled hypertension from two inner-city clinics and concurrently measured adherence of up to four antihypertensive medications using electronic pillboxes during the interval between two primary care visits. The main outcome was mean percent of days adherent to each drug. Mixed effects regression analyses were used to assess the association between drug class and adherence adjusting for age, gender, race, ethnicity, education, health insurance, coronary artery disease, heart failure, chronic kidney disease, diabetes, number of medications, days monitored, and dosing frequency.ResultsThe mean age was 64 years; 72% women, 75% Hispanic, 88% prescribed ≥ 1 BP medication. In unadjusted analyses, adherence was lower for beta-blockers (70.9%) compared to angiotensin receptor blocking agents (75.0%, P = 0.11), diuretics (75.9%, P < 0.001), calcium channel blockers (77.6%, P < 0.001) and angiotensin-converting enzyme inhibitors (78.0%, P < 0.0001). In the adjusted analysis, only dosing frequency (P = 0.0001) but not drug class (P = 0.71) was associated with medication adherence.ConclusionsAntihypertensive drug class was not associated with electronically measured adherence after accounting for dosing frequency amongst patients with uncontrolled hypertension. Low adherence to beta-blockers may have been due to the common practice of prescribing multiple daily dosing. Providers may consider using once daily formulations to optimize adherence and should assess adherence among all treated patients with uncontrolled hypertension.
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Project description:Glaucoma, the leading cause of irreversible blindness, affects >70 million people worldwide. Lowering intraocular pressure via topical administration of eye drops is the most common first-line therapy for glaucoma. This treatment paradigm has notoriously high non-adherence rates: ranging from 30% to 80%. The advent of smart phone enabled technologies creates promise for improving eyedrop adherence. However, previous eyedrop electronic monitoring solutions had awkward medication bottle adjuncts and crude software for monitoring the administration of a drop that adversely affected their ability to foster sustainable improvements in adherence. The current work begins to address this unmet need for wireless technology by creating a "smart drop" bottle. This medication bottle is instrumented with sensing electronics that enable detection of each eyedrop administered while maintaining the shape and size of the bottle. This is achieved by a thin electronic force sensor wrapped around the bottle and underneath the label, interfaced with a thin electronic circuit underneath the bottle that allows for detection and wireless transmission to a smart-phone application. We demonstrate 100% success rate of wireless communication over 75 feet with <1% false positive and false negative rates of single drop deliveries, thus providing a viable solution for eyedrop monitoring for glaucoma patients.
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Project description:ObjectiveTo determine whether peak flow monitoring has value above and beyond symptom monitoring when used as part of an asthma management plan.MethodsFrom a large managed-care organization, 296 adults, aged 50-92 yr, were recruited and randomly assigned in equal numbers to either use of symptoms or peak flow rate (twice daily or "as needed") for asthma monitoring, and monitored every 6 mo for 2 yr. Interventions were delivered in four 90-min small-group classes and included a personalized action plan and coaching in proper use of asthma inhalers.ResultsWe found no significant differences between peak flow rate and symptom monitoring, or between twice-daily and as-needed peak flow monitoring in the primary or secondary study outcomes: health care utilization (acute, nonacute, or total asthma visits), Asthma Quality-of-Life Questionnaire (AQLQ) scores, and lung function. AQLQ scores and prebronchodilator FEV1 increased significantly for both groups between baseline and 6 mo (AQLQ: mean, 0.4 units; 95% confidence interval, 0.3, 0.5; p < 0.0001; FEV1% predicted: mean, 4%). Inhaler technique improved substantially in both groups.ConclusionsPeak flow monitoring has no advantage over symptom monitoring as an asthma management strategy for older adults with moderate-severe asthma when used in a comprehensive asthma management program. Improved outcomes in both groups suggest that understanding proper medication use, regular monitoring of asthma status, and understanding how to respond to changes are of primary importance.
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